Documents published in 2022 : Scipedia

Investigation of higher harmonic Lamb waves for facilitating delamination characterization
A. Gangwar, D. Joglekar

eccomas2022.

Abstract
We advance this field by systematically exploring nonlinear interactions of A0 Lamb mode signals with delamination defects of various sizes and interlaminar locations, to facilitate the characterization of delaminations. The interrogation signal, in this regard, is a modulated sinusoid whose frequency varies in steps of 20 kHz between 40 kHz and 100 kHz. Commercial FEM software is used for modelling the contact at delamination interfaces and for simulating the Lamb wave propagation through the waveguide with delamination defect. It is demonstrated that the intermittently acting contact pressure between the two surfaces of delamination acts as a source of nonlinearity, resulting in generation of higher order harmonics of interrogation frequency. A metric for measuring nonlinearity, the nonlinearity index (NI), is used to quantify the strength of wave-damage interactions over a range of interrogation frequencies. The NI index is observed to vary with both the interlaminar location as well as the width of the delamination. The maximum value of NI is further influenced by the frequency of excitation signal. To infer the effect of delamination parameters on the NI, a concept of a concept of contact energy intensity is introduced, which is largely dependent on the size and the interlaminar position of the delamination. The nonlinearity index patterns are explained by combining the intensity of the contact energy with the phase difference between waves traveling through the sub-laminations and the flexural rigidity of the two sub-laminates at the delamination location. The inferences provided can potentially be used for determining the interlaminar location and width of delamination employing higher harmonic Lamb wave signals generated by the breathing delamination.
Abstract
We advance this field by systematically exploring nonlinear interactions of A0 Lamb mode signals with delamination defects of various sizes and interlaminar locations, to [...]
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Forming effects on high-cycle fatigue in an aluminum sheet structure using the Ottosen-Stenström-Ristinmaa model
S. Tveit, A. Reyes, E. Erduran

eccomas2022.

Abstract
In this paper a multi-stage numerical analysis is presented with the aim to investigate effects of forming on the high-cycle fatigue performance of a deep-drawn aluminum sheet structure for use in a floating photovoltaic system. Forming simulations of a subsection of the full geometry are performed in a realistic two-step drawing-springback cycle. A simplified global analysis of service load response is performed to obtain displacements at the submodel boundary, that are used to generate boundary conditions for a local service load analysis. The local analysis is then performed on three different models of the subsection: (I) excluding forming effects, (II) including effects of thinning, and (III) including effects of thinning and residual stresses. The critical location with respect to the fatigue limit criterion in the Ottosen-Stenström-Ristinmaa high-cycle fatigue model was identified for case (I), and this location was used to compare the different models to assess effects of forming on high-cycle fatigue performance. Furthermore, the dynamic friction coefficient , and the isotropickinematic mixing coefficient were varied in order to investigate their respective effects.
Abstract
In this paper a multi-stage numerical analysis is presented with the aim to investigate effects of forming on the high-cycle fatigue performance of a deep-drawn aluminum sheet [...]
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Using artificial intelligence techniques for the accurate estimation of the ultimate pure bending of steel circular tubes
M. Ben Seghier, V. Plevris, G. Solorzano

eccomas2022.

Abstract
In this paper, the potential of building more accurate and robust models for the prediction of the ultimate pure bending capacity of steel circular tubes using artificial intelligence techniques is investigated. Therefore, a database consisting of 104 tests for fabricated and cold-formed steel circular tubes are collected from the open literature and used to train and validate the proposed data-driven approaches which include the Random Forest methodology in two variants: the original version in which the control parameters are manually updated, and an enhanced RF-PSO variant, where Particle Swarm Optimization is used for optimizing these parameters. The data set has four input parameters, namely the tube thickness, tube diameter, yield strength of steel and steel elasticity modulus, while the ultimate pure bending capacity is considered as the target output variable. The obtained results are compared to the real test values through various statistical indicators such as the root mean square error and the coefficient of determination. The results indicate that the proposed enhanced model can provide an accurate solution for modelling the complex behavior of steel circular tubes under pure bending conditions.
Abstract
In this paper, the potential of building more accurate and robust models for the prediction of the ultimate pure bending capacity of steel circular tubes using artificial [...]
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Multi-physical modelling and analysis of lubricated transmissions using a coupled finite element approach
S. Neeckx, B. Blockmans, W. Rottiers, W. Desmet

eccomas2022.

Abstract
Lubrication is vital to improve performance, efficiency and durability in transmissions; it serves to minimize wear, noise, vibration and friction. The proper functioning of lubricated transmissions relies on interactions amongst a wide range of physical phenomena (contact dynamics, fluid-structure interaction and heat transfer) operating at different spatial and temporal scales. A lubricated transmission model is proposed in this work to obtain accurate information regarding all physical domains and the coupling thereof to quantify performance, efficiency and durability. The model consists of a thermo-elastically coupled flexible multibody model for the gear pair and a Thermo-Elasto-Hydrodynamic Lubrication (TEHL) model for the lubricant, both based on first principle modelling to ensure high fidelity.
Abstract
Lubrication is vital to improve performance, efficiency and durability in transmissions; it serves to minimize wear, noise, vibration and friction. The proper functioning [...]
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Advanced deep learning comparisons for non-invasive tunnel lining assessment from ground penetrating radar profiles
M. Rosso, G. Marasco, L. Tanzi, S. Aiello, A. Aloisio, R. Cucuzza, B. Chiaia, G. Cirrincione, G. Marano

eccomas2022.

Abstract
Innovative, automated, and non-invasive techniques have been developed by scientific community to indirectly assess structural conditions and support the decision-making process for a worthwhile maintenance schedule. Nowadays, machine learning tools are in the spotlight because of their outstanding capabilities to deal with data coming from even heterogeneous sources and their ability to extract information from the structural systems, providing highly effective, reliable, and efficient damage classification tools. In the current study, a supervised multi-level damage classification strategy has been developed regarding Ground Penetrating Radar (GPR) profiles for the assessment of tunnel lining conditions. In previous research, the authors firstly considered a convolutional neural network (CNN), adopting the quite popular ResNet-50, initialized through transfer learning. In the present work, further enhancements have been attempted by adopting two configurations of the newest state-of-art advanced neural architectures: the neural transformers. The foremost is the original Vision Transformer (ViT), whose core is an encoder entirely based on the innovative self-attention mechanism and does not rely on convolution at all. The second is an improvement of ViT which merges convolution and self-attention, the Compact Convolution Transformer (CCT). In conclusion, a critical discussion of the different pros and cons of adopting the above-mentioned different architectures is finally provided, highlighting the actual powerfulness of these technologies in the future civil engineering paradigm nevertheless.
Abstract
Innovative, automated, and non-invasive techniques have been developed by scientific community to indirectly assess structural conditions and support the decision-making process [...]
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Thermal and structural modelling of thermoset composite repairs towards optimization of the cure cycle for minimum distortion
T. Koenis, N. van Hoorn, M. Moghadasi

eccomas2022.

Abstract
During manufacturing of composite materials residual stresses can result in distortion of the final part. This distortion is even more critical when building on existing parts, such as for a repair, as the added material has to conform to the original structure. To predict this distortion due to curing of thermoset carbon-matrix composite repairs, a numerical modelling method is employed. The temperature cycle applied for the cure of thermoset composites can significantly influence the amount of residual stress and resulting deformation after manufacturing. Therefore, a method is devised to parametrise and subsequently tune this temperature cycle for minimum distortion after manufacturing. Numerical tests with the optimised temperature cycle resulted in a 36% reduction in process induced strain for a repair of a flat laminate plate. The same methodology is applied to a wing box consisting of two composite skins connected by two C-spars where a scarf repair is applied in the skin. The repair patch is locally heated by a heating blanket to cure the repair patch. A subsequent thermalmechanical model is used to investigate the amount of residual stress and strain after cure and the influence of underlying structural elements on the repair. The developed framework can support the patch fabrication with accurate design and analysis for repairs with minimum distortion. Which in turn will result in development of cost-effective composite repairs.
Abstract
During manufacturing of composite materials residual stresses can result in distortion of the final part. This distortion is even more critical when building on existing parts, [...]
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A machine learning based approach to predict the stress intensity factors in 2D linear elastic fracture mechanics
P. Zhang

eccomas2022.

Abstract
Within the framework of linear elastic fracture mechanics, the stress intensity factors (SIFs) are the mostly applied crack-tip characterizing parameters. To obtain the SIFs, approximate formulae are widely used because exact analytical solutions are available only for very simple geometrical and loading configurations [1]. However, even approximate solutions for SIFs are also rather limited to very simple geometrical and loading conditions. In this work, an accurate and efficient SIF prediction model based on Physics-informed neural network (PINN) [4] is developed, where we incorporate the equilibrium equations and constitutive relations into the PINN. In order to capture the singular behavior of the stress and displacement fields around the crack tip, we extend the standard PINN structure by adding two more trainable parameters
Abstract
Within the framework of linear elastic fracture mechanics, the stress intensity factors (SIFs) are the mostly applied crack-tip characterizing parameters. To obtain the SIFs, [...]
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Dynamic characterization of offshore wind turbines supported on a jacket using Artificial Neural Networks
R. Quevedo-Reina, G. Álamo, L. Padrón, J. Aznárez

eccomas2022.

Abstract
The dynamic characterization of an offshore wind turbine (OWT) and its foundation is an important task within the design stage of the support structure. The system fundamental frequency should not coincide with that of the loads that affect it, otherwise resonance phenomena can conclude with the collapse of the structure or its deterioration due to fatigue. Assuming a linear behaviour, the system fundamental frequency can be computed by solving the eingenvalue problem after defining the stiffness and mass global matrices. This procedure can become computationally expensive if soil-structure interaction (SSI) phenomena is taken into account. For this reason, a surrogate model based on Artificial Neural Networks (ANN) is proposed for estimating the fundamental frequency of the wind turbine assembly, jacket support structure and pile foundation considering SSI effects. A dataset is generated to train the ANN. This synthetic data collects the characteristics of the OWT-jacket-foundation and its fundamental frequency, which is obtained by a finite element substructuring model. The SSI is reproduced through impedance functions computed through a previously developed continuum model. Comparing the predictions of the ANN with the results obtained by the structural model, it is observed that this type of regression allows to reproduce in a sufficiently precise way the dependence of the fundamental frequency with respect to the variables that define the system. Thus the use of Machine Learning techniques, such as ANNs, makes it possible to take into account the system behaviour obtained by rigorous models in large-scale calculations that it would be unfeasible otherwise.
Abstract
The dynamic characterization of an offshore wind turbine (OWT) and its foundation is an important task within the design stage of the support structure. The system fundamental [...]
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Postbuckling failure mechanism of square aluminum plates under shear loading
C. Kalfountzos, G. Bikakis, E. Theotokoglou

eccomas2022.

Abstract
Buckling is very important for structural design, especially when the structure is thin-walled. Slender plates are widely used as structural members in civil, naval and aerospace engineering and they are able to carry considerable additional loads in the postbuckling range. Engineers take advantage of this postbuckling reserve and design structures that are allowed to buckle and operate below their ultimate loads for further weight and cost reduction. Consequently, both buckling and postbuckling behavior of slender plates are of critical importance during the design of lightweight thin-walled engineering structures.
Abstract
Buckling is very important for structural design, especially when the structure is thin-walled. Slender plates are widely used as structural members in civil, naval and aerospace [...]
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New predictive models for ballistic limit of spacecraft honeycomb-core sandwich panels subjected to hypervelocity impact
R. Carriere, A. Cherniaev

eccomas2022.

Abstract
Parameters of the honeycomb core (such as cell size and foil thickness), as well as the material of the core, influence the ballistic performance of honeycomb-core sandwich panels in cases of hypervelocity impact (HVI) by orbital debris. Two predictive models capable of accounting for this influence have been developed in this study: one utilized a conventional approach based on a dedicated ballistic limit equation, while the other employed an artificial neural network trained to predict the outcomes of HVI on HCSP. BLE fitting and ANN training were conducted using a database composed of 46 numerical experiments, performed with a validated numerical model and ten physical tests derived from the literature. The new ballistic limit equation is based on the Whipple shield BLE, in which the standoff distance between the facesheets was replaced by a function of the honeycomb cell size, foil thickness, and yield strength of the HC material. The corresponding fit factors were determined by minimizing the sum of squared errors between the BLE predictions and the results of HVI tests listed in the database. The BLE was then tested against a new set of simulation data and demonstrated an excellent predictive accuracy, with the discrepancy ranging from 1.13% to 5.58% only. The artificial neural network was developed using MATLAB's Deep Learning Toolbox framework and was trained utilizing the same HCSP HVI database as was employed for the BLE fitting. The ANN demonstrated a very good predictive accuracy, when tested against a set of simulation data not previously used in the training of the network, with the discrepancy ranging from 0.67% to 7.27%. Both of the developed predictive models (the BLE and the ANN) are recommended for use in the design of orbital debris shielding for spacecraft, involving honeycomb-core sandwich panels.
Abstract
Parameters of the honeycomb core (such as cell size and foil thickness), as well as the material of the core, influence the ballistic performance of honeycomb-core sandwich [...]
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Distinct element modelling of the seismic response of historical masonry constructions: insight on the out-of-plane collapse of façades
P. Meriggi, S. De Santis, R. Fugger, R. Yanez Chura, G. de Felice

eccomas2022.

Abstract
Façades belonging to historical masonry constructions typically fail by out-of-plane mechanisms. The estimate of their out-of-plane capacity is not a trivial task, due to the different possible collapse modes (overturning, bending, disaggregation, leaf separation, sliding) and to the discontinuous nature of masonry, influencing the non-linear seismic behaviour of walls. Simplified approaches, proposed by building codes, mainly based on the mechanics of the rigid block, may not always be suitable for the purpose. Indeed, they disregard the real morphology of masonry, which instead influences weaker failure mechanisms (such as disaggregation and leaf separation). Furthermore, they neglect the interaction of the façade with the rest of the building and its interlocking with transversal walls. These shortcomings can be overcome resorting to distinct element method (DEM), in which masonry is modelled as an aggregation of discrete units and no-thickness interfaces and the actual morphology of constructions is considered. In this paper, DEM is adopted to investigate the out-of-plane seismic behaviour of façades through non-linear analyses, by focusing on vertical bending and overturning failure mechanisms. The former is studied by comparing results of shake table tests on both single-leaf and double-leaf masonry walls to dynamic simulations in which real accelerograms are applied. The latter is analysed by performing non-linear static analyses on the Romanesque church of St. Maria Maggiore in Tuscania, Italy, by focusing on its façade. Distinct element method provided a realistic description of the behaviour of façades under earthquake loadings, in terms of both seismic capacity, crack pattern and failure mode.
Abstract
Façades belonging to historical masonry constructions typically fail by out-of-plane mechanisms. The estimate of their out-of-plane capacity is not a trivial task, [...]
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Limit analysis of non-periodic masonry by means of Discontinuity Layout Optimization
M. Schiantella, M. Gilbert, C. Smith, L. He, F. Cluni, V. Gusella

eccomas2022.

Abstract
Masonry structures forming part of our historical heritage were often constructed using nonperiodic textures. In this case, unlike the situation for masonry with periodic textures, few methods are available to estimate wall strength and, moreover, available methods are often difficult to apply. In this work, Discontinuity Layout Optimization (DLO) is proposed as a method of estimating the failure load and associated mechanism of masonry walls constructed with non-periodic textures. In the first part three different textures are considered (periodic, quasi-periodic and chaotic) with a simplified scheme and a parametric analysis is undertaken, considering the variation of the height of the panel. A further classification for quasi-periodic textures is then provided and a DLO rigid block analysis is carried for square panels to show the influence of such textures. The results highlight the importance of the parameters considered in the analysis, and that DLO is a suitable method to investigate their influence.
Abstract
Masonry structures forming part of our historical heritage were often constructed using nonperiodic textures. In this case, unlike the situation for masonry with periodic [...]
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Nonlinear macroelement based on Bouc-Wen formulation with degradation for the equivalent frame modelling of masonry walls
D. Liberatore, D. Addessi, A. Paoloni

eccomas2022.

Abstract
The equivalent frame model takes into account the shear and bending mechanisms that take place in piers and spandrels through plastic hinges. It represents a good compromise between accuracy and computational burden in the analysis of complex masonry walls. For the purposes of dynamic analysis, in addition to the hysteretic behaviour of the plastic hinges, it is also necessary to introduce their degradation of strength and stiffness. This study presents a macroelement model for piers and spandrels in which the bending mechanism is described by two hinges at the ends of the macroelement, and the shear mechanism by a shear link. They are characterized by a hysteretic behaviour with progressive plasticity, described by the Bouc-Wen model, and by degradation of strength and stiffness. Degradation is described through a damage parameter, which governs both strength and stiffness decay, and a flexibility increase parameter, which only governs stiffness reduction. In this way it is possible to independently control both strength and stiffness degradation. The model is applied to simulate experimental tests on panels, highlighting a good agreement with the experimental results.
Abstract
The equivalent frame model takes into account the shear and bending mechanisms that take place in piers and spandrels through plastic hinges. It represents a good compromise [...]
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Mesh adaptation of ablating hypersonic vehicles
J. Breil, C. Roche, M. Olazabal

eccomas2022.

Abstract
The ablation of a vehicle during atmospheric reentry leads to a degradation of its surface state. Ablated wall interacts with the boundary layer that develops around the object. The deformation can be seen as a ripple or a roughness pattern with different characteristic amplitudes and wavelengths. The effect on the flow is taken into account either by means of modelizations or by direct simulation by applying the deformation to the mesh. Mesh regularization techniques can be used in order to take into account wall deformations during a simulation. In this work we apply our regularization directly to a mesh which has been already deformed. The meshes will be adapted for use in a parallel CFD Navier-Stokes code. A refinement of the mesh close to the wall is required to correctly capture the boundary layer, but also to accuratly represent the geometry of the wall deformation. For the numerical methods used, a constraint of orthogonality is added to the mesh impining on the wall.
Abstract
The ablation of a vehicle during atmospheric reentry leads to a degradation of its surface state. Ablated wall interacts with the boundary layer that develops around the object. [...]
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Rocking Analysis for the bell tower of Sant’anna in Cervino
A. Gesualdo, M. Guadagnuolo

eccomas2022.

Abstract
In seismic prone areas ecclesiastical masonry complexes have shown a very high vulnerability, as detected after the last Italian earthquakes, such as those occurred in L'Aquila (2009), Emilia-Romagna (2012), Central Italy (2016), and Ischia (2017). These are particular types of aggregate buildings subjected often to partial collapses, due to the presence of highly vulnerable elements, like the bell towers. Preliminary analyses should including straightforward and quick methods are necessary. In this paper the bell tower vulnerability is analyzed taking into account the rocking behaviour of the tower only and considering the contribute of the entire ecclesiastical complex as a rigid body sliding with a fixed friction coefficient with respect to the foundations. It is shown that suitable values of maximum oscillations and horizontal displacements are obtained. The case study is the ecclesiastical complex of S. Anna in Cervino (Caserta, Italy).
Abstract
In seismic prone areas ecclesiastical masonry complexes have shown a very high vulnerability, as detected after the last Italian earthquakes, such as those occurred in [...]
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Data-led Mechanical and Thermal Analysis of Layered Structures Based on Parametric Finite Element Analysis and Neural Network
J. Ren

eccomas2022.

Abstract
The mechanical and thermal behaviours of layered structures is of great importance for many advanced material systems and loading conditions. The responses of layered structures are controlled by the constitutive properties of each layer as well as the thicknesses. A comprehensive data-based approach is essential for both material analysis and design in direct or inverse problems. In this work parametric numerical modelling and Artificial Neural Network (ANN) are jointly used to develop data for layered structures. Mechanical and thermal finite element (FE) models are used to produce data for different material property and thickness domains. The use of ANN program is established and evaluated for different loading conditions. Using indentation as a typical case for mechanical loading and localized heating as typical example for thermal loading, ANN program was used to predict the behaviour of layered structures with different properties and layer thicknesses. Use of the data system in establishing dominating factors, synergetic effect on mechanical-thermal performance in advanced materials design is discussed.
Abstract
The mechanical and thermal behaviours of layered structures is of great importance for many advanced material systems and loading conditions. The responses of layered structures [...]
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Explorative In-situ Analysis of Turbulent Flow Data Based on a Data-Driven Approach
C. Gscheidle, J. Garcke

eccomas2022.

Abstract
The Proper Orthogonal Decomposition (POD) has been used for several years in the post-processing of highly-resolved Computational Fluid Dynamics (CFD) simulations. While the POD can provide valuable insights into the spatial-temporal behaviour of single transient flows, it can be challenging to evaluate and compare results when applied to multiple simulations. Therefore, we propose a workflow based on data-driven techniques, namely dimensionality reduction and clustering to extract knowledge from large simulation bundles from transient CFD simulations. We apply this workflow to investigate the flow around two cylinders that contain complex modal structures in the wake region. A special emphasis lies on the formulation of in-situ algorithms to compute the data-driven representations during run-time of the simulation. This can reduce the amount of data inand output and enables a simulation monitoring to reduce computational efforts. Finally, a classifier is trained to predict characteristic physical behaviour in the flow only based on the input parameters.
Abstract
The Proper Orthogonal Decomposition (POD) has been used for several years in the post-processing of highly-resolved Computational Fluid Dynamics (CFD) simulations. While the [...]
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Fluid-Structure Interaction Analyses of Amniotic Fluid with a Comprehensive Fetus Model Exposed to External Loading
G. Kurgansky, J. Arias, E. Frankini, S. Echeverri, R. Chan-Akeley, M. Toma

eccomas2022.

Abstract
A history of trauma during gestation is a risk factor for poor pregnancy outcomes. A multidisciplinary approach is vital to protect the mother's and the fetus' safety. Even though pregnancy-related trauma is uncommon, it is one of the leading causes of morbidity and mortality in pregnant women and fetuses. Hence, it is axiomatic to study the mechanism of the traumatic injuries to the fetus. The development of next-generation protective devices depends on our understanding of these mechanisms. Computational fluid-structure interaction simulations are used to study the effect of external loading on the fetus submerged in the amniotic fluid inside the uterus. A multitude of resulting variables is utilized to understand the cushioning function of the amniotic fluid on the fetus.
Abstract
A history of trauma during gestation is a risk factor for poor pregnancy outcomes. A multidisciplinary approach is vital to protect the mother's and the fetus' safety. [...]
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Single-edge notched tension testing for assessing hydrogen embrittlement: a numerical study of test parameter influences
R. Depraetere, M. Cauwels, W. De Waele, T. Depover, K. Verbeken, S. Hertelé

eccomas2022.

Abstract
To evaluate the feasibility of the safe use of existing gas grids for the transport and storage of hydrogen gas, the phenomenon of hydrogen assisted degradation of steel used in the pipeline grid has to be examined. A finite element based framework developed for describing this phenomenon at the continuum scale is used to assist in the design and analysis of experimental characterisation of the tearing resistance. The framework is based on the complete Gurson model for ductile damage and takes into account damage acceleration due to the local hydrogen concentration, and the diffusion of hydrogen. Simulations representing single edge notched tension (SENT) fracture toughness tests of an API 5L X70 grade steel are performed and results are discussed in terms of crack growth resistance curves. Side grooves are included in the geometry of the SENT model to promote uniform crack growth. Different boundary conditions are employed, simulating ex-situ and in-situ hydrogen charging of specimens. Moreover, the effect of the applied deformation rate on the dynamics of hydrogen diffusion and the resulting toughness values is investigated. Accordingly, guidance regarding experimental SENT testing for the hydrogen assisted tearing resistance degradation is provided, in terms of test conditions (in-situ/ex-situ) and deformation rate.
Abstract
To evaluate the feasibility of the safe use of existing gas grids for the transport and storage of hydrogen gas, the phenomenon of hydrogen assisted degradation of steel used [...]
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Design of integrated fluidic actuators for muti-axial loaded structural elements
M. Bosch, M. Nitzlader, T. Burghardt, M. Bachmann, H. Binz, L. Blandini, M. Kreimeyer

eccomas2022.

Abstract
The construction sector is responsible for high grey energy consumption and high greenhouse gas emissions. Adaptive structures can be a suitable solution to counteract this. Actuation of a beam to reduce the mass by counteracting the deflection with integrated fluidic actuators has been proven in previous studies. New challenges are brought about with the actuation of slabs due to the multi-axial load transfer. Many actuator principles are conceivable for this application. A combination of uniaxially acting actuators and complex designs that generate forces in different spatial directions in a targeted manner are possible. This paper presents various principles for the development of actuators integrated into the cross-section of a slab. These are able to manipulate the multi-axial load transfer behaviour directly. For this purpose, the actuator principles are classified according to various aspects. In a second step, numerical investigations are used to prove the effectiveness of the actuator principles.
Abstract
The construction sector is responsible for high grey energy consumption and high greenhouse gas emissions. Adaptive structures can be a suitable solution to counteract this. [...]
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ARCHITECTURAL AND ENVIRONMENTAL IMPACT OF RETROFITTING TECHNIQUES TO PREVENT IN-PLANE ≪DOMINO≫ FAILURE MODES OF UNREINFORCED MASONRY BUILDINGS
R. Liberotti, F. Cluni, F. Faralli, V. Gusella

eccomas2022.

Abstract
The preservation of heritage buildings is not just about the structural safety, but it is necessarily related to the central themes of restoration, fruition and reuse of ancient buildings. Such topic requires an interdisciplinary design approach that involves, among the others, structural engineering, numerical modelling and architecture to address the challenges of contemporaneity in heritage management also in terms of interests of the stakeholders. In this regard, the opportunities offered by natural F.R.C.M. (Fibre Reinforced Cementitious Matrix) composites, made of basaltic fibres and lime mortar, are analysed.
Abstract
The preservation of heritage buildings is not just about the structural safety, but it is necessarily related to the central themes of restoration, fruition and reuse of ancient [...]
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Effects of uncertainties of image-based material properties of great vessels on vascular deformation
B. Fanni, M. Antonuccio, G. Santoro, A. Mariotti, M. Salvetti, S. Celi

eccomas2022.

Abstract
Patient-specific computational models represent a powerful tool for the planning of cardiovascular interventions. In this context, the patient-specific material properties are considered as one of the biggest source of uncertainty. In this work, we investigated the effect of the uncertainty of the elastic module (E), as computed from a recent image-based methodology, on a fluid-structure interaction (FSI) model of a patientspecific aorta. The Uncertainty Quantification (UQ) was carried out using the generalized Polynomial Chaos (gPC) method. Four deterministic simulations were run based on the four quadrature points, computed considering a deviation of ±20% on the estimation of the E value of the vessel wall from patient's imaging. The UQ of the E parameter was evaluated on the area and flow variations among cardiac cycle extracted from five cross-sections of the aortic FSI model. Results from gPC analysis showed a not significant variation of the area and flow quantities during the whole cardiac period, thus demonstrating the effectiveness of the used image-based methodology in the inferring of the E parameter, despite its intrinsic errors due to model definition. This study highlights the importance of imaging to retrieve useful data in an indirect and noninvasive way, to enhance the reliability of in-silico models in the clinical practice.
Abstract
Patient-specific computational models represent a powerful tool for the planning of cardiovascular interventions. In this context, the patient-specific material properties [...]
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Quantification of time-averaging uncertainties in turbulence simulations
D. Xavier, S. Rezaeiravesh, R. Vinuesa, P. Schlatter

eccomas2022.

Abstract
An automatic method is proposed for the removal of the initialization bias that is intrinsic to the output of any statistically stationary simulation. The general techniques based on optimization approaches such as Beyhaghi et al. [1] following the Marginal Standard Error Rules (MSER) method of White et al. [16] were observed to be highly sensitive to the fluctuations in a time series and resulted in frequent overprediction of the length of the initial truncation. As fluctuations are an innate part of turbulence data, these techniques performed poorly on turbulence quantities, meaning that the local minima was often wrongly interpreted as the minimum variance in the time series and resulted in different transient point predictions for any increments to the sample size. This limitation was overcome by considering the finite difference of the slope of the variance computed in the optimization algorithm. The start of the zero slope region was considered as the initial transient truncation point. This modification to the standard approach eliminated the sensitivity of the scheme, and led to consistent estimates of the transient truncation point, provided that the finite difference time interval was chosen large enough to cover the fluctuations in the time series. Therefore, the step size for the finite difference slope was computed using both visual inspection of the time series and trial and error. We propose the Augmented DickeyFuller test as an automatic and reliable method to determine the truncation point, from which the time series is considered stationary and without an initialization bias.
Abstract
An automatic method is proposed for the removal of the initialization bias that is intrinsic to the output of any statistically stationary simulation. The general techniques [...]
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Classification of compromised DOFS data with LSTM neural networks
V. Usenco, K. Lasn

eccomas2022.

Abstract
Distributed optical fiber sensors (DOFS) are gaining momentum for in-situ condition monitoring and damage detection purposes. Although DOFS are a versatile sensing method enabling high-resolution strain and temperature mapping, they are also sensitive to mechanical vibrations. Vibrations are typically created by the ambient environment (e.g acoustic background, rotating equipment) which can produce high levels of measurement noise. With physical access to DOFS installations, the principle of acoustic or mechanical vibrations can also be utilized for malicious sensor tampering. The current lack of anomaly-detection systems suggests that practical DOFS applications would benefit from an automated analysis to detect and classify compromised measurements. Noise classification makes it possible to identify its source and potentially remove its effects from the measurement in the future. This would expand the commercial applications of DOFS systems significantly. Neural networks have been used for error detection in cyber-physical applications in numerous studies with high-accuracy results. Specifically, long short-term memory (LSTM) neural network models have become popular in recent years to classify anomalies in sequential e.g time-series data. Our investigation conducted a series of physical experiments using magnitude-controlled mechanical disturbances on bare free-hanging DOFS. Both random low-frequency vibrations at large displacement amplitudes and a constant high-frequency acoustic source at a low amplitude were employed. Experiments revealed that strain patterns are visually different with varying types and levels of disturbances. For the numerical analysis, statistics and machine learningbased approaches were applied for DOFS vibration noise classification, and their accuracy is discussed in detail. Results from the post-processing of compromised DOFS data suggest that it is possible to develop a vibration detection or classification system based on off-the-shelf DOFS interrogation equipment coupled with LSTM numerical tools.
Abstract
Distributed optical fiber sensors (DOFS) are gaining momentum for in-situ condition monitoring and damage detection purposes. Although DOFS are a versatile sensing method [...]
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Multiscale finite element modeling linking shell elements to 3D continuum
D. Addessi, P. Di Re, C. Gatta, E. Sacco

eccomas2022.

Abstract
The present paper investigates the response of masonry structural elements with periodic texture adopting an advanced multiscale finite element model, coupling different formulations at the two selected scales of analysis. At the macroscopic structural level, a homogeneous thick shell is considered and its constitutive response is derived by the detailed analysis of the masonry repetitive Unit Cell (UC), analyzed at the microlevel in the framework of the threedimensional (3D) Cauchy continuum. The UC is formed by the assembly of elastic bricks and nonlinear mortar joints, modeled as zero-thickness interfaces. The Transformation Field Analysis procedure is invoked to address the nonlinear homogenization problem of the regular masonry. The performance of the model in reproducing various masonry textures is explored by referring to an experimentally tested pointed vault under different profiles of prescribed differential settlements. The structural behavior of the vault is studied in terms of global load-displacement curves and damaging patterns and the numerical results are compared with those recovered by detailed micromechanical analyses and experimental evidences.
Abstract
The present paper investigates the response of masonry structural elements with periodic texture adopting an advanced multiscale finite element model, coupling different formulations [...]
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Validation of the temperature history during extrusion based additive manufacturing
R. Hein, F. Winkelmann

eccomas2022.

Abstract
Additive manufacturing (AM) is considered as a key technology for the efficient production of individualized components. The technique enables the tool-less production of complex geometries and designs that could not be realized cost-effectively with conventional manufacturing methods. The focus of this work is on the Fused Filament Fabrication (FFF), where a thermoplastic filament is extruded trough a nozzle. The material is deposited layer by layer until the final part is build. Thereby, high temperature gradients occur within the part when the hot material is deposited on the lower layers. During the printing process the lower layers are reheated several times so that the material properties are influenced even after the deposition has been made. The thermal history has major effects on crucial material properties such as the degree of crystallization or thermal and mechanical properties. An inadequate degree of crystallization influences both the structural properties such as the stiffness or the degree of bonding and the dimensional accuracy due to subsequent shrinkage effects. Additionally, the temperature gradients cause residual stresses which are partly relaxed to varying part deformations. The remaining stresses can lead to premature failures. To achieve a high and repeatable part quality as well as a low scatter in the final part dimension an in-depth process understanding is required considering the underlying material-process-partinteractions. In order to analyse these complex multiphysical processes, manufacturing process simulations are a suitable method. A main requirement for the numerical analysis of AM processes is the calculation of the thermal history as accurately as possible. The objective of this work is, therefore, to evaluate the prediction accuracy of currently available AM process simulation tools. For this purpose, a gcode-based AM process simulation of a cuboid is performed in order to calculate the transient temperature fields using the Abaqus AM plug-in from Dassault Syst`emes. The cuboid made of PETG is printed with a Prusa i3 MK3.
Abstract
Additive manufacturing (AM) is considered as a key technology for the efficient production of individualized components. The technique enables the tool-less production of [...]
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Voxel-based density registration of trabecular bone: a longitudinal HR-pQCT study of postmenopausal women
J. Du, M. Huang, S. Li, V. Silberschmidt

eccomas2022.

Abstract
Bone mineral density (BMD) is one of the important parameters used to characterise bone quality. Clinically, the only recommended method - dual X-ray absorptiometry - can only evaluate a two-dimensional areal BMD. Currently, three-dimensional localised BMD information is absent. HR-pQCT enables the assessments of 3D microstructure down to trabecular bone. Therefore, in this study, a voxel-based density registration (VDR) method is proposed to analyse the longitudinal changes of trabecular-bone density distribution. The VDR techniques were evaluated based on a six-month longitudinal study of five postmenopausal women. The time effect on localised changes of trabecular-bone mineral density was visualized and variations between different anatomical regions were quantified for the first time. Different distributions between anatomical regions were found in bone mineral density of trabecular bone (vBMDtrab), with a change of vBMDtrab at medial region (-0.56%) significantly higher than anterior (-1.58%) (p = 0.032). This study indicates that localised density changes might be used as a prior indicator for the effect of aging or other interventions.
Abstract
Bone mineral density (BMD) is one of the important parameters used to characterise bone quality. Clinically, the only recommended method - dual X-ray absorptiometry - can [...]
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Tangential differential calculus for curved, linear Kirchhoff beams with systematic convergence studies
M. Kaiser, T. Fries

eccomas2022.

Abstract
We propose a reformulation of linear Kirchhoff beams in two dimensions based on the tangential differential calculus (TDC). The rotation-free formulation of the Kirchhoff beam is classically based on curvilinear coordinates. However, for general applications in engineering and sciences that take place on curved geometries embedded in a higher-dimensional space, the tangential differential calculus enables a formulation independent of curvilinear coordinates and, hence, is suitable also for implicitly defined geometries. The geometry and differential operators are formulated in global Cartesian coordinates related to the embedding space.
Abstract
We propose a reformulation of linear Kirchhoff beams in two dimensions based on the tangential differential calculus (TDC). The rotation-free formulation of the Kirchhoff [...]
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Photoelasticity of YVO4 through first-principle calculation
A. mirzai

eccomas2022.

Abstract
The laser host materials undergo relatively small changes in their intrinsic properties due to various sources during an experiment. These sources are often related to temperature change and vibrations due to crystal mounting, which may cause stress-induced birefringence in laser host materials[1]. Birefringence is a phenomenon that causes optical anisotropy due to external load or residual stress. As a result, the final outcome of the experiments can be affected. One way to reduce probable noises is to predict the change in optical properties with respect to load. In the case of laser host materials, refractive index is one of the most prominent properties that undergoes change. The change in refractive index due to external load in the linear response regime is known as photoelasticity. Therefore, to predict the change pattern of refractive index in a crystal, one needs to know the elastic and photoelastic constants of the material.
Abstract
The laser host materials undergo relatively small changes in their intrinsic properties due to various sources during an experiment. These sources are often related to temperature [...]
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Effect of graphite-particle morphology on thermomechanical performance of compacted graphite iron: Numerical modelling
M. Cao, E. Palkanoglou, K. Baxevanakis, V. Silberschmidt

eccomas2022.

Abstract
Compacted graphite iron (CGI) is used in numerous applications, e.g., in the automotive industry, in tools and pipes, thanks to its excellent thermomechanical properties. Despite its extensive industrial use, its fracture at the microscale was not thoroughly investigated. Interfacial debonding is the main mechanism of fracture of CGI at the microscale and is based on the deformational incompatibility between graphite and the surrounding matrix. To study this decohesion, a two-dimensional micromechanical model of elliptical inclusions embedded in a metallic matrix is generated. An elastoplastic response is assumed for both constituents, and cohesive finite elements are applied to the graphite-matrix interface to simulate decohesion. A parametric analysis of interfacial features such as thickness and stiffness is performed to identify the effect of these parameters on debonding. The obtained results provide insights into the thermomechanical behaviour of CGI at the microscale and enable more effective modelling of this engineering alloy.
Abstract
Compacted graphite iron (CGI) is used in numerous applications, e.g., in the automotive industry, in tools and pipes, thanks to its excellent thermomechanical properties. [...]
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An efficient strategy of parcel modeling for polydispersed multiphase turbulent flows
L. Bahramian, J. Muela, C. Oliet, C. Pérez-Segarra, F. Trias

eccomas2022.

Abstract
A three-dimensional particle-laden two-phase turbulent flow by employing the Eulerian-Lagrangian method using multiphase Particle-In-Cell model is implemented to analyze the effects of parcel modeling. In order to achieve an optimal trade-off between accuracy and computational cost, a hybrid approach is proposed. This approach is a combination of two typical models: the volume fixed model, in which each parcel has the same volume, and the number fixed model, in which each parcel has the same number of particles. This approach is studied for the particle-laden turbulent flow benchmark case of Boreé et al. [1], with a mass loading of 22%, by using large eddy simulation through a two-way coupling between continuous and polydispersed phases.
Abstract
A three-dimensional particle-laden two-phase turbulent flow by employing the Eulerian-Lagrangian method using multiphase Particle-In-Cell model is implemented to analyze the [...]
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A numerical analysis of CO2 storage by adsorption using ZIF-8
G. Fonseca da Silva, L. Rodrigues Capello Silva, M. Oliveira Pelic, B. Galelli Chieregatti, J. de Sá Brasil Lima

eccomas2022.

Abstract
In 21st century, the reduction of CO2 concentration in the atmosphere is one of the most challenges of the humanity, specifically in the engineering. To start a possibility solution proposal, this work consisted in an analysis of carbon dioxide storage, using adsorption by ZIF8, a material that belongs to a class called Zeolitic Imidazolate Frameworks, which have high porosity, high thermal resistance and chemical stability. The main contribution of this work is to verify which parameters are relevant in the CO2 storage capacity by adsorption. To archive this goal, the study was made through computational simulations using the open source FreeFem++ software, inputting a specified quantity of pure CO2, entering in an 1,82 liter tank filled by the adsorbent until its internal pressure reached 1,0 MPa. First, the isothermal curve was validated with the literature, and after adjusting the parameters of adsorption model, called Dubinin Astakov (D-A). The simulations were performed, varying CO2 inlet flow, the tank’s aspect ratio with the values of 1; 1,9; 3; 5 and 7, and the external wall’s heat transfer coefficient with values of 5, 700 and 1000 W/m²K. Each simulation generated at each step the tank’s average and maximum temperatures, internal pressure, and the carbon dioxide adsorption density. All the simulations started with a standard temperature of 300 K and pressure of 100 kPa. Temperature and adsorption density distributions were generated to analyze in which part of the tank the adsorption is higher. The results showed that the regions where the temperatures are higher, the adsorption is lower, and in the end of the simulation, the simulations with the lower average temperatures had the higher adsorption density. The highest values of adsorption density were obtained with higher surface areas under the influence of forced convection, rather than natural convection, and with lower CO2 inlet flow. The highest adsorption density reached was 15,67 %, in a simulation with 50% of the tank’s volume per minute as CO2 inlet flow rate, aspect ratio of 7,0; and 700 W/m²K heat transfer coefficient. The average temperature obtained in the end of this simulation was 326,20 K and it took 3644 seconds for the tank to achieve the internal pressure of 1,0 MPa.
Abstract
In 21st century, the reduction of CO2 concentration in the atmosphere is one of the most challenges of the humanity, specifically in the engineering. To start a possibility [...]
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A multigrid immersed boundary method for the CFD solver Horses3D
S. Colombo, E. Ferrer, E. Valero

eccomas2022.

Abstract
This work describes the implementation of the Immersed Boundary Method (IBM) in a high order discontinuous Galerkin framework for the CFD solver Horses3D [1]. High order schemes are very attractive due to their low numerical dissipation, their capability of providing high-accurate solutions and higher efficiency for a given level of accuracy with respect to low order schemes. However, the generation of high order meshes needed by these schemes is still a bottleneck since it requires a large amount of time. IBM tries to tackle the problem by preserving the high order beneficial properties while avoiding the generation of complex meshes.
Abstract
This work describes the implementation of the Immersed Boundary Method (IBM) in a high order discontinuous Galerkin framework for the CFD solver Horses3D [1]. High order schemes [...]
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On highly scalable 2-level-parallel unstructured CFD
J. Jaegerskuepper, D. Vollmer

eccomas2022.

Abstract
Exascale HPC systems are just about to become available. Such enormous simulation capabilities from the hardware perspective, however, require software that can effectively make efficient use of this massively parallel hardware. For the domain-decomposition based algorithms generally used for CFD, it has become apparent that running one MPI process, i.e. one domain, per CPU core is no longer apt when there are hundreds of cores available per cluster node. There are just too many processes per node that need to communicate with other remote processes. Message aggregation is thus a key aspect of highly scalable parallel codes. A 2-level parallelization featuring a shared-memory level in addition to the MPI process level seems a promising solution. The CODA (CFD for ONERA, DLR, Airbus) software for high-fidelity compressible-flow simulations of industrial configurations implements such a 2-level domaindecomposition hybrid-parallel approach. The processing of unstructured meshes is particularly challenging with respect to load balancing and non-linear data access. For maximum parallel scalability, CODA's parallelization not only features overlapping communication with computation on the process level, but also a dedicated Single Program (on) Multiple Data (SPMD) programming model for the shared-memory level. Here, the design principles of this parallelization concept are outlined, followed by details concerning its implementation in the Flucs infrastructure (FLIS), which has become part of CODA. Moreover, results of scalability studies with CODA are presented, which impressively demonstrate the extreme scalability realized with this parallelization approach. The studies were performed on two distinct HPC clusters, one based on Intel's Xeon Scalable Processor, the other one based on AMD's EPYC.
Abstract
Exascale HPC systems are just about to become available. Such enormous simulation capabilities from the hardware perspective, however, require software that can effectively [...]
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EXPLICIT AND IMPLICIT LARGE EDDY SIMULATION FOR A NACA0012 USING A HIGH ORDER DISCONTINUOUS GALERKIN SOLVER
O. Marino, E. Ferrer, E. Valero, J. Errasti

eccomas2022.

Abstract
We perform Large Eddy Simulation on a 3D NACA0012 airfoil using a high order discontiuous Galerkin spectral element solver at moderate Reynolds numbers, Re = 1.0 · 105. The aim is to compare the results of classic explicit Sub Grid Scale models, e.g. the WALE and VREMAN models, with the ones get by using implicit LES, where no explicit SGS is used, but we use stabilising split-form energy-stable formulations, with two-point Pirozzoli and KennedyGruber fluxes. We compare general qualitative variables such as the Q-criteria as well as local quantitative variables, as boundary layer velocity profiles. We show that both methods achive similar predictions for the integrated global variables, but differences can be appreciated in the local velocity profiles.
Abstract
We perform Large Eddy Simulation on a 3D NACA0012 airfoil using a high order discontiuous Galerkin spectral element solver at moderate Reynolds numbers, Re = 1.0 · [...]
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Free response of a gravitational liquid sheet by means of three-dimensional Volume-of-Fluid simulations
A. Della Pia, L. Grande, A. Colanera, M. Chiatto, L. Luca

eccomas2022.

Abstract
The volume-of-fluid (VOF) method is employed to simulate the dynamics of gravitational liquid sheets (curtains) issuing into an initially quiescent gaseous environment.
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A level-set model for two-phase flow with variable surface tension: Thermocapillary and surfactants
N. Balcazar-Arciniega, J. Rigola, A. Oliva

eccomas2022.

Abstract
An unstructured conservative level-set method for two-phase flow with variable surface tension is introduced. Surface tension is a function of temperature or surfactant concentration on the interface. Consequently, the called Marangoni stresses induced by temperature gradients or surfactant concentration gradients on the interface lead to a coupling of momentum transport equation with thermal energy transport equation or interface surfactant transport equation. The finite-volume method discretizes transport equations on 3D collocated unstructured meshes. The unstructured conservative level-set method is employed for interface capturing, whereas the multiple marker approach avoids the numerical coalescence of fluid particles. The fractional-step projection method solves the pressure-velocity coupling. Unstructured flux-limiters are proposed to discretize the convective term of transport equations. A central difference scheme discretizes diffusive terms. Gradients are evaluated by the weighted least-squares method. Verifications and validations are reported.
Abstract
An unstructured conservative level-set method for two-phase flow with variable surface tension is introduced. Surface tension is a function of temperature or surfactant concentration [...]
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Comparison of different entropy stabilization techniques for discontinuous Galerkin spectral element methods
J. Markert, G. Gassner

eccomas2022.

Abstract
We review and compare two techniques to get entropy stability for nodal Discontinuous Galerkin Spectral Element Methods (DG) in compressible flows. One technique is based on entropy split-forms, e.g., [8, 15, 5] and one is based on a direct algebraic correction [1]. We have implemented the Flux Differencing methodology for both, Legendre-Gauss-Lobatto (Lobatto) and Legendre-Gauss (Gauss) based spectral element basis functions. While the Lobatto operators belong to the class of diagonal norm summation-by-parts (SBP) operators, the Gauss operators belong to the generalized class of SBP operators, where it is not necessary that the boundary nodes are included. To reach entropy stability, respectively guaranteed entropy dissipation, a key ingredient is an entropy conserving numerical flux function. With this ingredient, only the volume integral term of the DG method has to be modified accordingly. We have also implemented an alternative technique, which is in general applicable for a wide range of discretizations. Abgrall [R. Abgrall, A general framework to construct schemes satisfying additional conservation relations. Application to entropy conservative and entropy dissipative schemes. Journal of Computational Physics, vol 372, 2018] introduced an algebraic correction term that retains conservation of the primary quantities and is furthermore constructed such, that an entropy (in-) equality can be shown. The second technique is at first sight a simpler alternative to the split-form based approach. Hence, questions regarding its advantages and disadvantages naturally come up.
Abstract
We review and compare two techniques to get entropy stability for nodal Discontinuous Galerkin Spectral Element Methods (DG) in compressible flows. One technique is based [...]
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A Machine Learning based Expert System for Optimizing CFD Solver Parameters
L. El Zaatari, T. Leicht, S. Langer, P. Bekemeyer, S. Görtz

eccomas2022.

Abstract
Computational Fluid Dynamics is a viable tool in the field of aerodynamics enabling to reduce time, effort and budget required for experimental testing. Although powerful and established for various years, it remains a complex tool calling for experienced users to ensure consistent high-quality results. This complexity primarily stems from the underlying model, namely the Navier-Stokes equations typically combined with a set of equations resolving the effects of turbulence. Additionally, to obtain accurate high-fidelity result appropriate meshes are required. As a consequence, a substantial number of parameters needs to be selected carefully and the quality of a result often highly depends on individual knowledge and experience of a user. Hence, a strong desire exists to reduce the number of input parameters without causing a loss of accuracy and efficiency. Such reduction of parameters might be viewed as a prerequisite to CFD as a tool in process chains for multidisciplinary applications where typically no user interaction is possible. In this article we propose a machine-learned Expert System for CFD to provide guidance for users in selecting optimal or at least near optimal parameter combinations. The proposed Expert System is divided into two macro steps, the surrogate model and a genetic algorithm to determine from the surrogate model the parameters. Numerical examples are presented to demonstrate the approach.
Abstract
Computational Fluid Dynamics is a viable tool in the field of aerodynamics enabling to reduce time, effort and budget required for experimental testing. Although powerful [...]
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A new projection method for Navier-stokes equations by using Raviart-thomas finite element
G. Barbi, A. Chierici, A. Cervone, V. Giovacchini, S. Manservisi, L. Sirotti, R. Scardovelli

eccomas2022.

Abstract
Computational Fluid Dynamics codes usually adopt velocity-pressure splitting to reduce the computational effort in the solution of the Navier-Stokes equations. In standard projection methods, the finite element approximations show difficulties to find a solution with discrete free-divergence velocity field in all space points. In this work, a new velocity-pressure method for Navier-Stokes equations that projects the velocity field inside the discrete free-divergence velocity space is presented. This algorithm computes the velocity field on the discrete free-divergence space by using Raviart-Thomas finite elements. The projection is obtained by the minimization of the distance, over the discrete free-divergence space, between the auxiliary field and the desired Raviart-Thomas interpolation space. The Raviart-Thomas discretization is based on the quadrilateral and hexahedral finite element space and therefore the divergence mimetic computational approach is used to avoid the well-known degradation of the divergence term convergence. The auxiliary velocity field is obtained by solving the velocity-pressure split system used in the classical ChorinTemam algorithm. The pressure is recovered by the orthogonal space to the projection on the Raviart-Thomas interpolation space. The method is investigated with an explicit and semi-implicit treatment of the pressure terms. The issues on boundary conditions and the errors in the reproducibility of the tangential components are investigated. Several numerical examples are reported to support this new projection method.
Abstract
Computational Fluid Dynamics codes usually adopt velocity-pressure splitting to reduce the computational effort in the solution of the Navier-Stokes equations. In standard [...]
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Algorithmic Differentiation for an effcient CFD solver
B. Maugars, S. Bourasseau, C. Content, B. Michel, B. Berthoul, J. Nunez Ramirez, I. Salah el Din, P. Raud, L. Hascoët

eccomas2022.

Abstract
We illustrate the benefits of Algorithmic Differentiation (AD) for the development of aerodynamic flow simulation software. In refining the architecture of the elsA CFD solver, developed jointly by ONERA and Safran, we consider AD as a key technology to cut development costs of some derivatives of interest, namely the tangent, adjoint, and Jacobian. We first recall the mathematical background of CFD applications which involve these derivatives. Then, we briefly present the software architecture of elsA (Cambier et al. [12]) and the design choices which give it its HPC capability while highlighting how these choices strongly constrain the applicability of AD. To meet our efficiency requirements, we select the Source-Transformation approach to AD through the Tapenade tool which is justified by a series of experiments and benchmarks. Finally, we present results on large scale configurations.
Abstract
We illustrate the benefits of Algorithmic Differentiation (AD) for the development of aerodynamic flow simulation software. In refining the architecture of the elsA CFD solver, [...]
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A runtime-based dynamic mesh partitioning approach
G. Baldan, R. Borrell, J. Jägersküpper

eccomas2022.

Abstract
Large-scale parallel numerical simulations are fundamental for the understanding of a wide variety of aeronautical problems. Mesh decomposition is applied to make use of parallel hardware. In particular, when using a massively parallel architecture, not only the final quality of the mesh subdivision is relevant. Also the partitioning algorithm itself needs to be robust as well as efficient. A strategy for dynamic mesh partitioning based on runtime measurements is presented. We integrate the 'Geometric Mesh Partitioner' (GeMPa), which is a partitioning library based on Hilbert Space-Filling Curve (HSFC), in the FlowSimulator (FS) software. FS is a platform designed to run multi-disciplinary simulations on massively parallel cluster architectures. The algorithm performance is evaluated on an unstructured mesh representing the ONERA M6 wing. In particular, the load imbalance among processes is evaluated and compared with a well-known graph-based partitioning approach. Finally, we analyze how the number of processes influences the load imbalance.
Abstract
Large-scale parallel numerical simulations are fundamental for the understanding of a wide variety of aeronautical problems. Mesh decomposition is applied to make use of parallel [...]
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Numerical simulation of multiphase flows with incompressible viscoelastic flows and elastic solids
A. Caboussat

eccomas2022.

Abstract
A numerical model for the simulation of multiphase flows with free surfaces is presented. The model allows to incorporate in a unified manner several phases ranging from incompressible Newtonian flows, Oldroyd-B viscoelastic flows and neo-Hookean elastic solids deformations. We advocate a Eulerian modeling of the multiphase flows, relying on the volume fraction of liquid, describing multiple phases with those different rheologies.One advantage of the Eulerian approach is to allow for large deformations of elastic solids, and changes of topologies. The numerical framework relies on an operator splitting strategy and a two-grid method. The numerical model is validated with a numerical experiment based on the collision between two elastic bodies with free surfaces.
Abstract
A numerical model for the simulation of multiphase flows with free surfaces is presented. The model allows to incorporate in a unified manner several phases ranging from incompressible [...]
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D2Q9 model of upwind lattice Boltzmann scheme for hyperbolic scalar conservation laws
M. Anandan, R. Suswaram

eccomas2022.

Abstract
D2Q9 model of upwind lattice Boltzmann scheme for hyperbolic scalar conservation laws.
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A practical algorithm to build geometric models of cardiac muscle tissue
M. Potse, L. Cirrottola, A. Froehly

eccomas2022.

Abstract
Cardiac muscle tissue has a unique, network-like structure. Three-dimensional models of this structure are needed for simulations of cardiac electrophysiology and mechanics. We developed an algorithm to produce such models artificially, using an implicit surface expressed on a tailored unstructured multi-domain mesh to define the cell membranes. The algorithm first creates a random network of cell centers, observing angle and distance criteria inferred from real tissue. The space around the network edges is assigned to the cellular domains based on the nearest half-edge. The network is then immersed in a regular tetrahedral mesh which is refined to fit the domain boundaries and to offer sufficient density around the cell membrane. The refinements are alternated with mesh improvement operations to maintain an acceptable mesh quality. On the refined mesh a level-set function is expressed that defines the cell membrane. The remeshing code Mmg3d is then used to discretize the level set while retaining the domains, and to improve the quality of the final mesh. A serial implementation of the algorithm was able to produce meshes of a few hundreds of cardiac cells in 15 minutes, but we are still facing difficulties in the remesher, likely resulting from the unusual complexity of these meshes. It was still possible, however, to correctly mesh a small network of cells that was designed to be replicated by successive mirroring. This allowed us to build models of upto 1 cm3of tissue (10 million cells and 370 billion tetrahedra) that now serve in performance tests of a large-scale simulation code.
Abstract
Cardiac muscle tissue has a unique, network-like structure. Three-dimensional models of this structure are needed for simulations of cardiac electrophysiology and mechanics. [...]
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Efficient implementation of a high-order compressible Navier-Stokes equations solver running on Graphics Processing Units
F. Gisbert, A. Sotillo, J. Pueblas

eccomas2022.

Abstract
This paper presents the implementation of a compressible Navier-Stokes equations solver that runs on multiple GPUs.
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FEATURE DETECTION ALGORITHMS AND MODAL DECOMPOSITION METHODS
B. Begiashvili, J. Garicano Mena, S. Le Clainche, E. Valero Sánchez

eccomas2022.

Abstract
Various modal decomposition techniques have been developed in the last decade [111]. We focus on data-driven approches, and since data flow volume is increasing day by day, it is important to study the performance of order reduction and feature detection algorithms. In this work we compare the performance and feature detection behaviour of energy and frequency based algorithms (Proper Orthogonal Decomposition [13] and Dynamic Mode Decomposition [46, 811]) on two data set testcases taken from fluid dynamics.
Abstract
Various modal decomposition techniques have been developed in the last decade [111]. We focus on data-driven approches, and since data flow volume is increasing day by [...]
- 3
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Lattice-Boltzmann simulations of traffic-related atmospheric pollutant dispersion in urban areas
M. Pasquier, S. Jay, P. Sagaut

eccomas2022.

Abstract
The developing field of urban physics includes computational fluid dynamics (CFD) as a tool to model wind comfort, heat management and pollutant dispersion in cities. In particular, road traffic emissions significantly contribute to air pollution and should be considered in atmospheric dispersion simulations. To this end, the lattice-Boltzmann method (LBM) offers a promising alternative to traditional finite-volume CFD solvers in terms of computational cost and accuracy. At IFP Energies Nouvelles (IFPEN), a recent emission model relying on real-life driving data recorded with a mobile application was used to construct urban emission maps. However, it has not been coupled yet with a precise unsteady CFD solver, which could provide local unsteady and accurate information about local concentration fields. We propose to combine the LBM open-source code OpenLB with the emission model designed at IFPEN to simulate traffic-induced pollutant dispersion in an urban-like environment. The LBM code is used to solve the Navier-Stokes equations as well as the passive scalar transport with a double distribution function (DDF) approach. The solver is successfully validated on the well-known CODASC test case and a first evaluation of the impact of a representative urban setting on pollutant dispersion with non-uniform sources is proposed.
Abstract
The developing field of urban physics includes computational fluid dynamics (CFD) as a tool to model wind comfort, heat management and pollutant dispersion in cities. In particular, [...]
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An Immersed Boundary Method for the CFD Solver Airbus-CODA
V. Llorente, D. Lodares, E. Ferrer, E. Valero

eccomas2022.

Abstract
This work implements and analyses an Immersed Boundary Method based on Volume Pezalization for the flow simulator Airbus-CODA (CFD for ONERA, DLR, and AIRBUS). The Immersed Boundary Volume Penalization has unique advantages, e.g. easy to implement, straightforward formulation for moving geometries, and numerical errors can be controlled apriori [1, 2], showing the potential for aeronautical applications. Numerical experiments will assess the accuracy of the Immersed Boundary Volume Penalization in CODA.
Abstract
This work implements and analyses an Immersed Boundary Method based on Volume Pezalization for the flow simulator Airbus-CODA (CFD for ONERA, DLR, and AIRBUS). The Immersed [...]
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Momentum-conserving ROMs for the incompressible Navier-Stokes equations
H. Rosenberger, B. Sanderse

eccomas2022.

Abstract
Projection-based model order reduction of an ordinary differential equation (ODE) results in a projected ODE. Based on this ODE, an existing reduced-order model (ROM) for finite volume discretizations satisfies the underlying conservation law over arbitrarily chosen subdomains. However, this ROM does not satisfy the projected ODE exactly but introduces an additional perturbation term. In this work, we propose a novel ROM with the same subdomain conservation properties which also satisfies the perturbed ODE exactly. We apply this ROM to the incompressible Navier-Stokes equations and show with regard to the mass equation how the novel ROM can be constructed to satisfy algebraic constraints. Furthermore, we show that the resulting mass-conserving ROM allows us to derive kinetic energy conservation and consequently nonlinear stability, which was not possible for the existing ROM due to the presence of the perturbation term.
Abstract
Projection-based model order reduction of an ordinary differential equation (ODE) results in a projected ODE. Based on this ODE, an existing reduced-order model (ROM) for [...]
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Numerical simulation of the micro-extrusion process of printable biomaterials
A. Amani, D. Kizildag, J. Castro, L. del Mazo, M. Pegueroles, M. Ginebra

eccomas2022.

Abstract
This work aims to gain a better understanding of how the rheological properties of printable materials affect their processability, as well as the quality of the final product, which at the end can lead to reducing time and costs of the process and increase product development. As the first step, the proper rheological non-Newtonian models are extracted from experimental studies. Later, three-dimensional numerical simulation of extrusion process is performed in the context of Direct Numerical Simulation (DNS) of governing equations, where the whole physics of fluid motion is taken into account. A finite-volume fractional step approach is used to solve the Navier-Stocks equations on collocated arbitrary meshes. Geometrical volume-of-fluid (GVOF) interface capturing approach is used to resolve the topological changes of the moving interface. The governing equations are solved using High-Performance Computing (HPC) parallel approaches. Besides the contribution of this work to the advancement of numerical techniques applied to multiphase complex flows, obtained results will shed light on the nature of non-Newtonian extrusion process with vast applications in the 3D printer industrial sectors.
Abstract
This work aims to gain a better understanding of how the rheological properties of printable materials affect their processability, as well as the quality of the final product, [...]
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The X-Mesh method applied to Multiphase Flows
Q. Antoine, J. Remacle, J. Lambrechts, N. Moes

eccomas2022.

Abstract
The accurate modeling of moving boundaries and interfaces is a difficulty present in many situations in computational mechanics. In this paper we use a new approach, X-Mesh, to simulate with the finite element method the interaction between two immiscible fluids while keeping an accurate description of the interface without mesh regeneration. The method is validated with complex problems such as Rayleigh-Taylor instabilities, sloshing and dambreak. The quality of the results and the efficiency of the method show the potential of this approach to simulate such physical phenomena.
Abstract
The accurate modeling of moving boundaries and interfaces is a difficulty present in many situations in computational mechanics. In this paper we use a new approach, X-Mesh, [...]
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DNS and LES on unstructured grids: playing with matrices to preserve symmetries using a minimal set of algebraic kernels
F. Trias, X. Álvarez-Farré, À. Alsalti-Baldellou, A. Gorobets, A. Oliva

eccomas2022.

Abstract
The essence of turbulence are the smallest scales of motion. They result from a subtle balance between two differential operators differing in symmetry: the convective operator is skew-symmetric, whereas the diffusive is symmetric and negative-definite. On the other hand, accuracy and stability need to be reconciled for numerical simulations of turbulent flows in complex configurations. With this in mind, a fully-conservative discretization method for collocated unstructured grids was proposed [Trias et al., J.Comp.Phys. 258, 246-267, 2014]: it preserves the symmetries of the differential operators and it has shown to be a very suitable approach for DNS and LES. On the other hand, an efficient cross-platform portability is nowadays one of the greatest challenges for CFD codes. In this regard, our leitmotiv reads: relying on a minimal set of (algebraic) kernels is crucial for code portability and maintenance! In this context, this work focuses on the computation of eigenbounds for the above-mentioned convection and diffusion matrices which are needed to determine the time-step `a la CFL. A new inexpensive method that allows this, without explicitly constructing these time-dependent matrices is proposed and tested. It only requires a sparse-matrix vector product where only the vector changes on time. Hence, apart from being significantly more efficient than the standard CFL condition, cross-platform portability is straightforward.
Abstract
The essence of turbulence are the smallest scales of motion. They result from a subtle balance between two differential operators differing in symmetry: the convective operator [...]
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The interaction between an isolated roughness element and free-stream turbulence
M. Gholamisheeri, K. Durovic, S. Mamidala, J. Fransson, A. Hanifi, D. Henningson

eccomas2022.

Abstract
Control and delay of the laminar-turbulent transition is a key parameter in reducing skin friction and drag. The flow characteristics, surface roughness, and environmental noise can affect the onset of transition. The present work investigates, numerically and experimentally, the interaction of the free-stream turbulence (FST) and an isolated cylindrical roughness element, and the resulting impact on the transition onset in a flat-plate boundary layer. High-fidelity direct numerical simulations (DNS) are performed for a roughness element immersed in the boundary layer over a flat plate with an asymmetrical leading edge, with and without FST. The numerical results are compared to hot-wire anemometry measurements performed in the Minimum Turbulence Level wind tunnel at KTH. The initial numerical and experimental results show that in the absence of FST, for the chosen flow parameters, highand low-speed streaks are generated downstream of the roughness element while the flow remains laminar and globally stable. When FST is added, the spanwise spacing of the streaky structures changes and the transition location of the boundary layer moves upstream. It was found that the aspect ratio of the streaky structures does not vary significantly.
Abstract
Control and delay of the laminar-turbulent transition is a key parameter in reducing skin friction and drag. The flow characteristics, surface roughness, and environmental [...]
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Non-newtonian viscous elongation and shear fluid model based on optimal triple tensor decomposition
M. Rütten, T. Schomberg

eccomas2022.

Abstract
The modeling of the distinct non-Newtonian fluid properties is an essential prerequisite for the computational simulation of associated flow fields. In particular, some non-Newtonian fluids reveal strong diverse viscosity response behaviours to pure elongational and simple shearing flows. Therefore, it is necessary to be able to distinguish between these flow types even in complex flow configuration. Unfortunately flow types are naturally mixed and this distinction becomes quite difficult. Only in a Lagrangian framework the tracking of the Lagrangian fluid element deformation allows an accurate strain related deformation type assignment. However, most CFD approaches prefer the Eulerian framework accepting the loss of the natural flow path alignment of the moving fluid particles. Consequently shear and elongation rates are barely separable without particular assignment methods. In this work a tensor decomposition method from vortex dynamics is discussed which allows to distinguish between these flow types. In vortex dynamics the problem occurred to separate shearing from purely rotational flows because different hydro- and aerodynamic flow phenomena are caused by shear and vortex related flow types. Thereto, various methods were proposed, among others the optimal triple tensor decomposition method which is able to separate vortical from shearing flows but also, after some modification, elongational from shearing flows. This tensor decomposition is now used to calculate elongation and shearing rates as input variables into non-Newtonian fluid models for the calculation of the local elongational and shear viscosity. The application case is a cross slot channel flow often used as reference. In this numerical simulation study the impact of the elongation rate modeling on the contraction flow topology is shown and discussed. It is shown that the modeling of different viscous elongational and shear-thinning affects the resulting flow significantly
Abstract
The modeling of the distinct non-Newtonian fluid properties is an essential prerequisite for the computational simulation of associated flow fields. In particular, some non-Newtonian [...]
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Neural network prediction of the flow field in a periodic domain with hyper-neural network parametrization
O. Bublík, V. Heidler, A. Pecka, J. Vimmr

eccomas2022.

Abstract
This paper is concerned with fast flow field prediction in a blade cascade for variable blade shapes as well as variable Reynolds number using the machine-learning architecture called convolutional neural network. To generate flow field for a specific Reynolds number, an encoder-decoder convolutional neural network, also called U-Net, is used. The values 500, 1000 and 1500 of the Reynolds number are chosen as the training set. Three U-Nets were trained on CFD results for 100 blade profiles, each U-Net for a different Reynolds number. In order to get a prediction for variable Reynolds number, a so-called hypernetwork in employed. The hypernetwork essentially interpolates between the two trained U-Nets. The architecture of the hypernetwork is fully-connected feedforward neural network with one input neuron corresponding to the Reynolds number, one hidden layer and the output layer corresponds to the weights for the interpolated U-Net. The concept of the hypernetwork-based parametrization is tested on a problem of compressible fluid flow through a blade cascade with three unseen blade profiles and unseen Reynolds number.
Abstract
This paper is concerned with fast flow field prediction in a blade cascade for variable blade shapes as well as variable Reynolds number using the machine-learning architecture [...]
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Symmetry-preserving discretisation methods for magnetohydrodynamics
J. Hopman, X. Trias, J. Rigola

eccomas2022.

Abstract
In this work, the symmetry-preserving method [1, 2, 3] is extended to include magnetohydrodynamic effects, using the collocated grid arrangement of Ni et al. [4, 5]. The electromagnetic part is solved explicitly using the induction-less approximation and an electric potential Poisson equation. The proposed solver is implemented in OpenFOAM and tested for accuracy and stability, and compared to the method of Ni et al. [4, 5]. A new benchmark case using a Taylor-Green vortex in a transverse magnetic field is used, for which kinetic energy budget terms are compared to the analytical solutions. Finally, Hunt's case is used to compare flow profiles to the analytical solutions. Influence of the spatial discretisation on accuracy and stability is also examined by solving both cases on meshes with variable degrees of distortion. The symmetry-preserving method showed accuracy on Cartesian meshes and stability even on extremely distorted meshes, whereas the method of Ni et al. [4, 5] showed less accurate conservation of current density and was not able to produce stable solutions on the extremely distorted meshes.
Abstract
In this work, the symmetry-preserving method [1, 2, 3] is extended to include magnetohydrodynamic effects, using the collocated grid arrangement of Ni et al. [4, 5]. The electromagnetic [...]
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Fluidization by gas pore pressure of dense granular flows: numerical simulations versus experiments
A. Aravena, L. Chupin, T. Dubois, O. Roche

eccomas2022.

Abstract
A model accounting for fluidisation by pore gas pressure in dense granular flows is presented. A viscoplastic rheology, based on the Drucker-Prager criterium, is used to describe the granular medium which is a mixture of air and glass beads. The pore gas pressure, which satisfies an advection-diffusion equation, reduces the friction between the particles and thus the value of the apparent viscosity. As a consequence, dense fluidised granular flows can travel longer distances. In laboratory experiments, the run-out distance reached by dense granular columns when collapsing is almost doubled when fluidisation is applied. This fundamental result, in the context of pyroclastic density currents, is reproduced by numerical simulations performed with the fluidised model.
Abstract
A model accounting for fluidisation by pore gas pressure in dense granular flows is presented. A viscoplastic rheology, based on the Drucker-Prager criterium, is used to describe [...]
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Computational modelling and characterization of non-Newtonian visco-plastic cementitious building materials
M. Thiedeitz, J. Timothy, T. Kränkel

eccomas2022.

Abstract
Cementitious building materials like Ultra High Performance Concrete (UHPC), Self-Compacting Concrete (SCC) or concrete with low clinker content possess complex rheological properties. Due to high packing densities and the use of various additives and chemical admixtures, a huge range of non-Newtonian flow characteristics from shear-thinning to shear-thickening, visco-elastic material behaviour and structural build-up can appear. For these concretes, transient computational modelling using Computational Fluid Dynamics (CFD) requires a meaningful choice of rheological parameters and the associated boundary conditions. The authors present the rheological analysis of five cementitious pastes with low ( = 0.45) to high ( = 0.58) solid volume fraction . Rheological parameters from rheometric flow protocols are compared with empirical stoppage test results for short and steady (slump flow) and transient flow (L-Box) conditions. Following, numerical simulation with the measured rheological parameters as input parameters is compared to the experimental flow results. CFD analysis using OpenFOAM is performed for the flow in empirical stoppage tests. We found that with increasing non-Newtonian behaviour, deviations between real and simulated flow appear due to insufficient transient flow descriptions and unknown secondary effects. The results provide new insight into computational modelling of complex cementitious building materials and serve as basis for further advanced CFD based modelling and characterization of time-dependent non-Newtonian concrete flow.
Abstract
Cementitious building materials like Ultra High Performance Concrete (UHPC), Self-Compacting Concrete (SCC) or concrete with low clinker content possess complex rheological [...]
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Preparing a Fortran legacy code for the upcoming exascale architectures
J. Legaux, G. Staffelbach

eccomas2022.

Abstract
Preparing legacy codes for the upcoming exascale systems is a timely topic since the unveiling of the Frontier system in June 2022. In this work we describe the steps taken to prepare the AVBP code for this new step in computing ressources. AVBP [6] is a parallel CFD code that solves the three-dimensional compressible Navier-Stokes equations on unstructured and hybrid grids. AVBP is a cutting-edge software when it comes to distributed memory CPUs, scaling efficiently up to 200.000's of cores on Bluegene or AMD Epyc2 systems. However, other types of architectures such as ARM processors and accelerators are gaining popularity and play a significant role in the exascale era. We first explore the usage of ARM processors, then GPU accelerators through OpenACC[2] directives. This work highlights the difficulties of porting a legacy code to those architectures and solutions implememented so far for performance.
Abstract
Preparing legacy codes for the upcoming exascale systems is a timely topic since the unveiling of the Frontier system in June 2022. In this work we describe the steps taken [...]
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On the algebraic modifications of traditional turbulence models to predict by-pass and separation induced transition
A. Colombo, A. Crivellini, A. Ghidoni, A. Nigro, G. Noventa

eccomas2022.

Abstract
Many reliable and robust turbulence models are nowadays available for the ReynoldsAveraged Navier-Stokes (RANS) equations to accurately simulate a wide range of engineering flows. However, turbulence models are not able to correctly predict flow phenomena with low to moderate Reynolds numbers, which are characterized by strong transitions. Laminar to turbulent transition is common in aerospace, turbomachinery, maritime, and automotive. Therefore, numerical models able to accurately predict transitional flows are mandatory to overcome the limits of turbulence models for the efficient design of many industrial applications. A modified version of the k-~ and Spalart-Allmaras turbulence models is proposed in order to predict transition due to the bypass and separation-induced modes. The modifications here proposed are based on the kand the SA-BCM transition models. Both the models are correlation-based algebraic transition models that relies on local flow information and include an intermittency function instead of an intermittency equation. The basic idea behind the models is that, instead of writing a transport equation for intermittency, an intermittency function multiplies the production terms of the turbulent working variables of the formulation of the turbulence models. In particular, the turbulence production is damped until it satisfies some transition onset requirements. The proposed models are implemented in a high-order discontinuous Galerkin (dG) solver and validated on different transitional benchmark cases from the ERCOFTAC T3 suite, with bypass (T3A, T3Aand T3B) and separation-induced (T3L1 and T3L3) transition.
Abstract
Many reliable and robust turbulence models are nowadays available for the ReynoldsAveraged Navier-Stokes (RANS) equations to accurately simulate a wide range of engineering [...]
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Fully integrated mesh generation in fluid-structure interaction
T. Fries, D. Bošnjak, R. Schussnig

eccomas2022.

Abstract
In fluid-structure interaction (FSI), the fluid and solid domains are permantently changing, coupled along a time-dependent, moving fluid-structure interface. The update of the fluid domain, i.e., in the numerical context, the mesh update is critical for robust and efficient simulations. Herein, we propose to inherently embed the mesh generation into the simulation.The FSI domain is defined based on structured building blocks that imply all the relevant information needed for the automatic mesh generation: Topology, geometry, and grading information. Transfinite maps play a crucial role for the definition of sub-meshes with any desired order and resolution in each building block. In every time step, a new mesh is generated, taking into account the deforming FSI interface. This generation is fast compared to the overall work load in each time step which is still dominated by the (iterative) solutions of the systems of equations. It is also very robust and removes any mesh entanglement by construction provided that suitable building blocks are selected once initially. Numerical results confirm the success of the proposed FSI strategy with integrated mesh generation.
Abstract
In fluid-structure interaction (FSI), the fluid and solid domains are permantently changing, coupled along a time-dependent, moving fluid-structure interface. The update of [...]
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Reynolds stress correction by machine learning methods with physical constraints
T. Philibert, A. Ferrero, A. Iollo, F. Larocca

eccomas2022.

Abstract
For the past three decade, Reynolds Average Navier-Stokes models have been widely used in the industry to simulate complex flows. However, these models suffer from limitations. Indeed there are still large discrepancies in the Reynolds stresses between the RANS model and high-fidelity data provided by DNS or experiments. This paper presents a strategy to correct the Menter SST model using an explicit algebraic model and two different neural networks: an multilayer perceptron (MLP) and a generative adversarial network (GAN). Moreover, in order to preserve the physical properties of the Reynolds stress tensor, we introduce a penalisation term in the loss of the GAN.
Abstract
For the past three decade, Reynolds Average Navier-Stokes models have been widely used in the industry to simulate complex flows. However, these models suffer from limitations. [...]
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Comparison of uncertainty quantification methods for mathematical problems in intermediate dimensions
J. Peter, Q. Bennehard

eccomas2022.

Abstract
The efficiency of multidimensional quadrature methods is compared for seven test functions in intermediate dimensions. Following this goal, the numerical evaluations of the mean and variance of the test functions, for two probability density functions, are assessed with respect to (wrt) their known exact values. The retained dimensions (3 to 6) correspond to the number of operational and geometrical uncertain parameters we plan to consider in a near future for realistic sensitivity analysis or robust designs. Most of the numerical quadrature methods rely on a generalized Polynomial Chaos (gPC) defined either by quadrature or by collocation. Two of the gPC collocation techniques, Basis Poursuit Denoise (BPdn) and Least Angle Regression (LAR), search for a sparse gPC while satisfying the collocation equations. Finally, the efficiency of the quadrature methods is discussed in relation with the regularity, the input dimension and the ANOVA decomposition of the test functions.
Abstract
The efficiency of multidimensional quadrature methods is compared for seven test functions in intermediate dimensions. Following this goal, the numerical evaluations of the [...]
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Cell-centered Lagrangian scheme for multi-material flows with equal pressure assumption
R. Chauvin, G. Sébastien, M. Bastien, L. Antoine

eccomas2022.

Abstract
The present document is motivated by the development and the study of diffuse interface strategies which does not require the use of geometric interface reconstructions. A simple diffuse interface strategy is proposed for the multimaterial diffusion equation. While it is possible to consider only one average temperature per mixed cell, it is known [7] that standard harmonic or arithmetic homogeneous methods are not accurate on the simple 'sandwich' problem when working with coarse meshes. This has direct consequences for radiation-hydrodynamics applications. The numerical strategy presented here may be seen as a natural extension of standard homogeneous model and understood as if the diffusion operator is integrated on the global cell (not the materials) taking into account several temperature (one per material). Obviously, the accuracy of the presented method, compared to exact geometric reconstruction based ones, is expected to be lower in the general case. However, we believe that the simplicity of the methodology introduced in the present document, its robustness and practicality for real physical applications makes it interesting for a large audience.
Abstract
The present document is motivated by the development and the study of diffuse interface strategies which does not require the use of geometric interface reconstructions. A [...]
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The effect of the tracer staggering on sea ice deformation fields
C. Mehlmann

eccomas2022.

Abstract
Sea ice models can simulate linear deformation characteristics (linear kinematic features) that are observed from satellite imagery. A recent study based on the viscous-plastic sea ice model highlights the role of the velocity placement on the simulation of linear kinematic features (LKFs) and concluded that the tracer staggering has a minor influence on the amount simulated LKFs. In this work we consider the same finite element discretization and show that on triangular meshes the placement of the sea ice tracers and the associated degrees of freedom (DoFs) have a strong influence on the amount of simulated LKFs. This behaivor can be explained by the change of the total number of DoFs associated with the tracer field. We analyze the effect on a benchmark problem and compare P1-P1, P0-P1, CR-P0 and CR-P1 finite element discretizations for the velocity and the tracers, respectively. The influence of the tracer placement is less strong on quadrilateral meshes as a change of the tracer staggering does not modify the total number of DoFs. Among the low order finite element approximations compared in this study, the CR-P0 finite element discretization resolves the deformation structure in the best way. The CR finite element for velocity in combination with the P0 discretization for tracer produces more LKFs than the P1-P1 finite element pair even on grids with fewer DoFs. This can not be achieved with the CR-P1 setup and therefore highlights the importance of the tracer discretization for the simulation of LKFs on triangular meshes.
Abstract
Sea ice models can simulate linear deformation characteristics (linear kinematic features) that are observed from satellite imagery. A recent study based on the viscous-plastic [...]
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Parameterising ocean-induced melt of an idealised Antarctic ice shelf using deep learning
B. Bouissou, C. Burgard, N. Jourdain

eccomas2022.

Abstract
The largest uncertainty when projecting the Antarctic contribution to sea-level rise comes from the ocean-induced melt at the base of Antarctic ice shelves. Current parameterisations used to link the hydrographic properties in front of ice shelves to the melt at their base struggle to accurately simulate basal melt patterns. We suggest that deep learning can be used to tackle this issue. We train a deep feed-forward neural network to emulate basal melt rates simulated by highly-resolved ocean simulations in an idealised geometry. We explore the advantages and limitations of this new approach through sensitivity studies varying hyperparameters, input variables and training choices. We show that large neural networks perform better, that the input format of the temperature and salinity matters most, and that the neural network can be applied to conditions outside of its training range if trained appropriately. The results are promising and we make recommendations for further work with this approach.
Abstract
The largest uncertainty when projecting the Antarctic contribution to sea-level rise comes from the ocean-induced melt at the base of Antarctic ice shelves. Current parameterisations [...]
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Data-Driven Reduced Order Modeling for Aerodynamic Flow Predictions
D. Hines Chaves, P. Bekemeyer

eccomas2022.

Abstract
During each aircraft program a vast amount of aerodynamics data has to be generated to judge performance, structural loads as well as handling qualities. Within the past years the usage of computational fluid dynamics has significantly increased providing accurate insights into aircraft behaviour at early design stages and therefore at least partially enabled the mitigation of costly design changes. However, fully relying on high fidelity aerodynamic data is still computational prohibitive. Hence, data-driven models have gained an increasing attention in recent years. These methods not only provide continuous models but also enable the inclusion of highly accurate aerodynamic results in time-critical environments. This paper aims at applying deep learning techniques to derive such models and compare them to state of the art reduced order modeling techniques. In particular, three deep learning methods, a Multilayer perceptron for distribution predictions, a Multi-layer perceptron for pointwise predictions and an Autoencoder coupled with an interpolation technique are compared to Proper Orthogonal Decomposition and Isomap with latent space interpolation. For all methods an efficient methodology to determine hyperparameters is outlined and applied. Results are presented for an Airbus provided XRF1 dataset which includes surface pressure distributions at various Mach numbers and angles of attack.
Abstract
During each aircraft program a vast amount of aerodynamics data has to be generated to judge performance, structural loads as well as handling qualities. Within the past years [...]
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Transition of separated flow over a bump under unsteady inflow conditions
H. Marbona, A. Martínez-Cava, D. Rodríguez, E. Valero

eccomas2022.

Abstract
Laminar flow separation has detrimental effects on the aerodynamics and performance of low pressure turbines (LPT). Flow separation is caused by the presence of adverse pressure gradient condition on the upper side of the blade past the suction peak, and is followed by laminar-to-turbulent transition and the subsequent turbulent mean reattachment due to the enhanced mixing. These phenomena characterise the size and dynamics of the separated flow, which are primarily dominated by the laminar-turbulent process. This study examines the influence of periodically-varying inflow conditions on the separated flow over a bump geometry at low Reynolds numbers. The geometry and flow conditions represent the upper surface of small LPT during high-altitude of flight. Direct numerical simulations are performed, in which a harmonic variation of the inlet total pressure is imposed, as a rough approximation of the passage of the upstream blade's wake. Three different frequencies with identical amplitude of the total pressure are simulated. The dynamics of the separated shear layer and the transition process are studied by separating the flow components correlated and un-correlated to the inflow frequency. Even moderate frequencies are found to have a strong effect in reducing the averaged size of the separated flow region, thus reducing the losses.
Abstract
Laminar flow separation has detrimental effects on the aerodynamics and performance of low pressure turbines (LPT). Flow separation is caused by the presence of adverse pressure [...]
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A comparison of machine learning methods for pressure coefficient prediction of an aeronautical configuration
A. Gorgues, R. Castellanos, J. Bowen, E. Andrés

eccomas2022.

Abstract
Machine learning entails powerful information processing algorithms that are relevant for modelling, optimization, and control of fluids. Currently, machine-learning capabilities are advancing at an incredible rate, and fluid mechanics is beginning to tap into the full potential of these powerful methods. Many tasks in fluid mechanics, such as reduced-order modelling, shape optimization and uncertainty quantification, may be posed as optimization and regression tasks. Machine learning can dramatically improve optimization performance and reduce convergence time. In this paper, the potential of tree-based machine learning techniques for the aerodynamic prediction of pressure coefficients of an AIRBUS XRF1 aircraft wing-body configuration has been assessed. For this purpose, a dataset including computational fluid dynamics (CFD) simulations has been employed to train the different models, with and without the use of proper orthogonal decomposition (POD) and having their hyperparameters values optimized to obtain the optimal subspace. A deep comparison of decision tree regressors and random forest algorithms has been performed, showing that the random forest regressor model performs better on all configurations.
Abstract
Machine learning entails powerful information processing algorithms that are relevant for modelling, optimization, and control of fluids. Currently, machine-learning capabilities [...]
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Developing a DEM-Coupled OpenFOAM solver for multiphysics simulation of additive manufacturing process
N. Aminnia, A. Estupinan Donoso, B. Peters

eccomas2022.

Abstract
Powder-based additive manufacturing technologies, specifically selective laser melting, are challenging to model due to the complex, interrelated physical phenomena that are present on multiple spatial scales, during the process. A key element of such models will be the detailed simulation of flow and heat transfer throughout the melt pool that is formed when the powder particles melt. Due to the high-temperature gradients that are generated inside the melt pool, the Marangoni force plays a key role in governing the flows inside the melt pool and deciding its shape and dimensions. On the other hand, the mass and heat transfer between the melt and the powder also has a significant role in shaping the melt pool at the edges. In this study, we modified an OpenFOAM solver (icoReactingMultiphaseInterFoam) coupled with an in-house developed DEM code known as eXtended Discrete Element Method or XDEM which models the dynamics and thermodynamics of the particles. By adding the Marangoni force to the momentum equation and also defining a laser model as a boundary condition for liquid-gas interface, the solver is capable of modeling the selective laser melting process from the moment of particle melting to the completion of the solidified track. The coupled solver was validated with an ice packed bed melting case and was used to simulate a multi-track selective laser melting process.
Abstract
Powder-based additive manufacturing technologies, specifically selective laser melting, are challenging to model due to the complex, interrelated physical phenomena that are [...]
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OpenFOAM model of fluid-structure interaction in dry wire drawing
M. Vervaecke, D. Fauconnier, J. Degroote

eccomas2022.

Abstract
A fluid-structure interaction model is employed to numerically investigate the interaction between the pressurized thin lubricant film and the radial, plastically deformed steel wire in a dry wire drawing process. A transient simulation is presented, with the implementation of a sliding fluid-structure interaction interface. Moreover, the fluid film has been calculated by the Navier-Stokes equations and the coupling with the wire model is performed by the IQN-ILS technique. This results on the one hand in the monitoring of the stresses and displacements of the structure and on the other hand in an observation of the hydrodynamic pressure build-up and wall shear stresses in the lubricant. Additionally, the evolution of the thickness of the fluid film is presented.
Abstract
A fluid-structure interaction model is employed to numerically investigate the interaction between the pressurized thin lubricant film and the radial, plastically deformed [...]
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Investigation of the PANS Method for the Prediction of Aerodynamic Noise Around a Circular Cylinder
A. Moosavifard, E. Kolb, M. Schäfer, S. Jakirlic

eccomas2022.

Abstract
Aeroacoustics is the field of studying flow-induced sound, which results from the interaction of unsteady flow with solid structures, such as aircraft and automobiles. Different methods are available to achieve this, including theoretical, experimental, and computational methods. Due to the high costs of experiments, the concentration on computational methods has increased. Computational aeroacoustics (CAA), based on computational fluid dynamics (CFD), has received special attention from researchers because of its outstanding capability to get acceptable results with reasonable computational costs. The partially-Averaged Navier Stokes (PANS) method is a hybrid LES/RANS method based on dynamic resolution parameters. The SSVPANS method is a k---f based PANS method with an additional modeled equation for the resolved kinetic energy. This method has been implemented in FASTEST, an in-house finitevolume solver to compute the flows in complex applications. This study aims to investigate the aeroacoustic performance of the SSV-PANS method compared to a reference Large-eddy Simulation [1] regarding the computational accuracy and costs. To do this, hybrid method based on decomposing the fluid variables into incompressible hydrodynamics and compressible perturbation equations is used to study the aerodynamic noise. The aeroacoustic sources are computed from the incompressible flow field using the SSV-PANS method. In addition, the Kirchhoff wave extrapolation method is used to have an efficient evaluation of the far-field noise.
Abstract
Aeroacoustics is the field of studying flow-induced sound, which results from the interaction of unsteady flow with solid structures, such as aircraft and automobiles. Different [...]
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Development of a Framework for Internal Combustion Engine Simulations in OpenFOAM
C. Gößnitzer, S. Posch, G. Pirker

eccomas2022.

Abstract
High-accuracy simulations of internal combustion engines (ICE) allow deep insight into the physical processes of the different phases of the engine cycle: gas exchange, mixture formation, compression, combustion and emission formation. The commercial solvers for ICE simulations provide a full package which covers these areas. However, the user of such software is unable to look into the source code, making it impossible to implement new models or investigate possible implementation errors in the code, and costs arise due to licensing requirements for commercial solvers. Although the open source framework OpenFOAM already includes multiple classes and two solvers dedicated to internal combustion engine simulations, there is no way to move engine valves and piston simultaneously with its standard tools. Thus, this paper presents a new engine library for ICE simulations written for OpenFOAM. The new framework is capable of simulating a complete fired engine cycle. The piston and the valves are moved simultaneously. To address large deformations in the mesh, a methodology to avoid insufficient mesh quality was developed. Ignition and combustion is modeled with standard tools from OpenFOAM. To validate the method, the simulation results for the averaged in-cylinder quantities pressure, temperature and mass are compared with experimental data.
Abstract
High-accuracy simulations of internal combustion engines (ICE) allow deep insight into the physical processes of the different phases of the engine cycle: gas exchange, mixture [...]
- 2
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An energy-preserving unconditionally stable fractional step method on collocated grids
D. Santos Serrano, F. Trias Miquel, G. Colomer Rey, C. Pérez Segarra

eccomas2022.

Abstract
Preservation of energy is fundamental in order to avoid the introduction of unphysical energy that can lead to unstable simulations. In this work, an energy-preserving unconditionally stable fractional step method on collocated grids is presented as a method which guarantees both preservation of energy and stability of our simulation. Using an algebraic (matrix-vector) representation of the classical incompressible Navier-Stokes equations mimicking the continuous properties of the differential operators, conservation of energy is formally proven. Furthermore, the appearence of unphysical velocities in highly distorted meshes is also adressed. This problem comes from the interpolation of the pressure gradient from faces to cells in the velocity correction equation, and can be corrected by using a proper interpolation.
Abstract
Preservation of energy is fundamental in order to avoid the introduction of unphysical energy that can lead to unstable simulations. In this work, an energy-preserving unconditionally [...]
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On the conservation of primary and secondary properties in the simulation of multiphase flows
N. Valle, F. Trias, R. Verstappen

eccomas2022.

Abstract
The formulation of multiphase flows emanates from basic conservation laws: mass, momentum and energy. While these are embedded in the celebrated Navier-Stokes equations, none of these properties do necessarily hold when constructing a computational model, unless special care is taken in discretizing the different terms of the governing equations. The conservation of both primary (mass, momentum) and secondary (energy) quantities is not only relevant to mimic the dynamics of the system, but also computationally beneficial. Conservation of such quantities produce an enhanced physical reliability, removing most of the need for stabilization artifacts. In addition, discrete conservation implies numerical stability as well, producing inherently stable problems. Focusing on the capillary force, which is one of the most distinguishable features of multiphase flows, we present here our most recent developments in the quest for conservation. Departing from an inherently mass conservative method, in this work we sketch our previous developments to obtain an energy conservation and next we present our attempt at momentum. By carefully assessing the continuum formulation, we delve into the mathematical properties responsible for the conservation of linear momentum, which we then mimic in the regularized and discrete formulations.
Abstract
The formulation of multiphase flows emanates from basic conservation laws: mass, momentum and energy. While these are embedded in the celebrated Navier-Stokes equations, none [...]
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An assessment of various discretizations of the energy equation in compressible flows
C. De Michele, G. Coppola

eccomas2022.

Abstract
Nonlinear instabilities are one of the major problems in turbulence simulations. One reason behind this problem is the accumulation of aliasing errors produced by the discrete evaluation of the convective term. This can be improved by preserving the quadratic invariants in a discrete sense. However, another source of instabilities is the error due to an incorrect evolution of thermodynamic variables, such as entropy. An appropriate discretization of the energy equation is needed to address this issue. An analysis of the preservation properties of various discretizations of the compressible Euler equations is reported, which includes some of the most common approaches used in the literature, together with some new formulations. Two main factors have been identified and studied: one is the choice of the energy equation to be directly discretized; the other is the particular splitting of the convective terms, chosen among the Kinetic Energy Preserving (KEP) forms. The energy equations analyzed in this paper are total and internal energy, entropy, and speed of sound. All the cases examined are locally conservative and KEP, since this is considered an essential condition for a robust simulation. The differences among the formulations have been theoretically investigated through the study of the discrete evolution equations induced by the chosen energy variable, showing which quantities may be preserved. Both one-dimensional and two-dimensional tests have been performed to assess the advantages and disadvantages of the various options in different cases.
Abstract
Nonlinear instabilities are one of the major problems in turbulence simulations. One reason behind this problem is the accumulation of aliasing errors produced by the discrete [...]
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Development of a discontinuous Galerkin solver for the simulation of turbine stages
A. Colombo, A. Ghidoni, E. Mantecca, G. Noventa, S. Rebay, D. Pasquale

eccomas2022.

Abstract
A high-order Discontinuous Galerkin (DG) solver is assessed in the computation of the flow through an Organic Rankine Cycle turbine nozzle and stage. The flow features are predicted with a RANS (Reynolds averaged NavierStoke) approach and the k-log() turbulence model in a multi reference frame, where interfaces between fixed and rotating zones are treated with a mixing plane approach, and non reflecting boundary conditions are used. Primitive variables based on pressure and temperature logarithms are adopted to ensure non-negative thermodynamic variables at a discrete level. The fluid can be modeled with the polytropic ideal gas law and the Peng-Robinson equation of state.
Abstract
A high-order Discontinuous Galerkin (DG) solver is assessed in the computation of the flow through an Organic Rankine Cycle turbine nozzle and stage. The flow features are [...]
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Modal analysis of a 3D gravitational liquid sheet
A. Colanera, A. Della Pia, M. Acquaviva, M. Chiatto, L. de Luca

eccomas2022.

Abstract
Modal analysis of three-dimensional gravitational thin liquid sheet flows, interacting with unconfined gaseous environments located on both sides of the liquid phase, is performed in the present work. Numerical data of this relevant two-phase flow configuration are obtained through the single-phase formulation and the Volume-of-Fluid (VOF) technique implemented in the flow solver Basilisk. This class of flows exhibits a variety of spatial and temporal relevant structures, both in free and forced configurations, that are investigated through the Spectral Proper Orthogonal Decomposition (SPOD). By means of such methodology, we explore the effect of two main governing parameters on the flow dynamics, namely the liquid sheet aspect ratio, AR = W/H, where H and W are the sheet inlet thickness and width, and the Weber number, We = lU2H/(2), in which U is the inlet liquid velocity, lthe liquid density, and the surface tension coefficient. Finally, for the highest aspect ratio value considered (AR = 40), we investigate the forced dynamics of the system excited by a harmonic perturbation in transverse velocity component applied at the inlet section, comparing results with ones arising from a purely two-dimensional analysis of the flow. The obtained results highlight the low rank behavior exhibited by the flow, suggesting that reduced order modeling could be particularly appealing to reduce complexity and computational effort in numerical simulation of this class of flows.
Abstract
Modal analysis of three-dimensional gravitational thin liquid sheet flows, interacting with unconfined gaseous environments located on both sides of the liquid phase, is performed [...]
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A fully-discrete entropy conserving/stable discretization for inviscid unsteady flows
A. Colombo, A. Crivellini, A. Nigro

eccomas2022.

Abstract
The aim of this work is to contribute to the development of a high-order accurate discretization that is entropy conserving and entropy stable both in space and in time. To do this, the general framework is based on a high-order accurate discontinuous Galerkin (dG) method in space with entropy working variables, several entropy conservative and stable numerical fluxes and an entropy conserving modified Crank-Nicolson method. We present the first results, obtained with the discretizations here proposed, for two bi-dimensional unsteady viscous test-case: the Taylor-Green vortex and the double shear layer.
Abstract
The aim of this work is to contribute to the development of a high-order accurate discretization that is entropy conserving and entropy stable both in space and in time. To [...]
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Influence of the turbulent wake downstream offshore wind turbines on larval dispersal: development of a new Lagrangian-Eulerian model
S. Ajmi, M. Boutet, A. Bennis, J. Dauvin

eccomas2022.

Abstract
In the context of future offshore wind farms along the French coasts of the English Channel, the impacts of foundations on larval dispersal from bentho-pelagic species colonizing the hard substratum of artificial structures are studied in order to assess how the species connectivity could be modified by the farms. In particular, the effects of turbulent wake and horseshoe vortices are investigated. To this end, a new numerical approach is developed that combines the Eulerian model, OpenFoam, solving the 3D Navier-Stokes equations to compute the hydrodynamics, and the Lagrangian model, Ichthyop, based on an advection-diffusion equation to compute the larval trajectories. Firstly, some simple test cases are performed to validate the numerical coupling between OpenFoam and Ichthyop, such as the dispersion of larvae downstream a 2D cylinder in water. Secondly, the ability of OpenFoam turbulence models to simulate turbulent structures around monopile and gravity type foundations is evaluated. The RANS (Reynolds Averaged Navier-Stokes) k-omega SST turbulence model is chosen for the realistic application because it can reproduce the horseshoe vortices and turbulent wake with less computing time than the Smagorinsky LES (Large Eddy Simulation) model. Lastly, larval dispersal simulations for four benthic species and for a set of monopile and gravity foundations are performed.
Abstract
In the context of future offshore wind farms along the French coasts of the English Channel, the impacts of foundations on larval dispersal from bentho-pelagic species colonizing [...]
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Surrogate modeling of unsteady aerodynamic loads acting on a plunging airfoil
R. Sundar, V. KUMAR, D. Majumdar, C. Shah, S. Sarkar

eccomas2022.

Abstract
Cost-effective parameteric surrogate models of unsteady aerodynamic loads acting on a flapping wing are highly desirable. They would enable real time aerodynamic load prediction, multiobjective optimisation and optimal control of intelligent flapping wing flight devices. In the present work, a parametric surrogate modeling framework for unsteady aerodynamic loads based on a non-intrusive reduced order modeling approach is presented. The unsteady flow past a plunging 2D flat plate is considered where the aerodynamic load time histories are obtained for different plunging frequencies and amplitudes using a potential flow solver. The parametric non-intrusive reduced order model (p-NIROM) for the obtained loads is constructed using a combination of snapshot proper orthogonal decomposition (POD) for dimensionality reduction and a fully connected feed forward neural network (FCNN) for modeling the input parametric dependency. Both, linear and non-linear FCNN based p-NIROM are explored and compared on the basis of load time history reconstruction accuracy. The non-linear FCNN regression for the p-NIROM is observed to generalise well for unseen parametric instances as compared to the linear approach when a systematic data sampling strategy is adopted.
Abstract
Cost-effective parameteric surrogate models of unsteady aerodynamic loads acting on a flapping wing are highly desirable. They would enable real time aerodynamic load prediction, [...]
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Linear and quadratic invariants preserving discretization of Euler equations
G. Coppola, A. Veldman

eccomas2022.

Abstract
In the context of the numerical treatment of convective terms in compressible transport equations, general criteria for linear and quadratic invariants preservation, valid on uniform and non-uniform (Cartesian) meshes, have been recently derived by using a matrix-vector approach, for both finite-difference and finite-volume methods ([1, 2]). In this work, which constitutes a follow-up investigation of the analysis presented in [1, 2], this theory is applied to the spatial discretization of convective terms for the system of Euler equations. A classical formulation already presented in the literature is investigated and reformulated within the matrix-vector approach. The relations among the discrete versions of the various terms in the Euler equations are analyzed and the additional degrees of freedom identified by the proposed theory are investigated. Numerical simulations on a classical test case are used to validate the theory and to assess the effectiveness of the various formulations.
Abstract
In the context of the numerical treatment of convective terms in compressible transport equations, general criteria for linear and quadratic invariants preservation, valid [...]
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Validation on a new anisotropic four-parameter turbulence model for low Prandtl number fluids
L. Sirotti, G. Barbi, A. Chierici, V. Giovacchini, S. Manservisi

eccomas2022.

Abstract
This work aims to validate a new anisotropic four-parameter turbulence model for low-Prandtl number fluids in forced and mixed convection. Traditional models based on the gradient-diffusion hypothesis and Reynolds analogy are inadequate to simulate the turbulent heat transfer in low-Prandtl number fluids. Additional transport equations for thermal variables are required to predict the characteristic thermal time scale. In a four-parameter turbulence model, two additional transport equations are solved for the temperature variance and its dissipation rate. Thus, it is possible to formulate appropriate characteristic time scales to predict the near-wall and bulk behaviour of mean and turbulent variables. The isotropic version of the four-parameter model has been widely studied and validated in forced and mixed convection. We aim to extend the model validity by proposing explicit algebraic models for the closure of Reynolds stress tensor and turbulent heat flux. For the validation of the anisotropic four-parameter turbulence model, low-Prandtl number fluids are simulated in several flow configurations considering buoyancy effects and numerical results are compared with DNS data.
Abstract
This work aims to validate a new anisotropic four-parameter turbulence model for low-Prandtl number fluids in forced and mixed convection. Traditional models based on the [...]
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Numerical Testcases to Study Proudman Resonance Using Shallow Water Models
N. Beisiegel, J. Behrens

eccomas2022.

Abstract
Proudman resonance is the dominant mechanism behind meteotsunamis. We develop a comprehensive set of testcases to validate numerical methods focusing on the performance with respect to represent mentioned resonance. With the test cases we assess the wave amplification in dependence of characteristics of the pressure perturbation, model parameters, model resolution, and bathymetry characteristics. We use the compilation of tests to validate an adaptive discontinuous Galerkin (DG) model for the two-dimensional non-linear shallow water equations. As the tests are highly sensitive to model resolution, we use the adaptive mesh capabilities of the model to locally refine the disturbance and thus gain considerable efficiency.
Abstract
Proudman resonance is the dominant mechanism behind meteotsunamis. We develop a comprehensive set of testcases to validate numerical methods focusing on the performance with [...]
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Correcting the discretization error of coarse grid CFD simulations with machine learning
A. Kiener, S. Langer, P. Bekemeyer

eccomas2022.

Abstract
Computational fluid dynamics is a cornerstone for the modern aerospace industry, providing important insights on aerodynamic analysis while reducing the need of expensive experiments and tests. Nevertheless, simulations of complex geometries are often performed on a discrete spatial domain too coarse to capture all relevant physical phenomena for the sake of lowering the computational cost. A consistent spatial discretization on so-called grids approximates the analytical solution of the partial differential equation with increasing number of discrete points. Such a grid refinement study is an expensive method to assess the general grid quality. This work shows that machine learning as a post-processing tool is capable of improving coarse grid simulations, even if not converged. The results show that three machine learning models varying in their complexity, namely the random forest, the neural network, and the graph neural network, are capable of finding patterns in coarse grid simulations. These patterns are used to predict the discretization error to approximate the field variables of interest of the corresponding fine grid simulation mapped onto the coarse grid. Initial training and testing is performed on the RAE2822 airfoil leading to corrected flow fields, improved surface integrals and coefficients, even when shocks are present. Additional tests are performed on the RAE5212 airfoil, showing the generalization limits of the trained models. The proposed method promises to reduce computational expenses while increasing the accuracy of the coarse grid results which works locally, e.g. it corrects the error for each cell individually and is therefore not restricted by the number of grid points. The presented results obtained by the machine learning models during post-processing are a promising baseline for more integrated developments, where the models will interact in a dynamic fashion with the flow solver to further improve coarse grid simulations.
Abstract
Computational fluid dynamics is a cornerstone for the modern aerospace industry, providing important insights on aerodynamic analysis while reducing the need of expensive [...]
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SPDE-ConvNet: Predict stabilization parameter for Singularly Perturbed Partial Differential Equation
S. Yadav, S. Ganesan

eccomas2022.

Abstract
Singularly Perturbed Partial Differential Equations are challenging to solve with conventional numerical techniques such as Finite Element Methods due to the presence of boundary and interior layers. Often the standard numerical solution has spurious oscillations in the vicinity of these layers. Stabilization techniques are employed to eliminate these spurious oscillations in the numerical solution. The accuracy of the stabilization technique depends on a user-chosen stabilization parameter, where an optimal value is challenging to find. In this work, we focus on predicting an optimal value of the stabilization parameter for a stabilization technique called the Streamline Upwind Petrov Galerkin technique for solving singularly perturbed partial differential equations. This paper proposes SPDE-ConvNet, a convolutional neural network for predicting stabilization parameters by minimizing a loss based on the cross-wind derivative term. The proposed technique is compared with the state-of-the-art variational form-based neural network schemes.
Abstract
Singularly Perturbed Partial Differential Equations are challenging to solve with conventional numerical techniques such as Finite Element Methods due to the presence of boundary [...]
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Simulation of massively separated flows and rotating machine flows using hybrid models
F. Miralles, B. Sauvage, A. Duben, V. Bobkov, T. Kozubskaya, S. Wornom, B. Koobus, A. Dervieux

eccomas2022.

Abstract
RANS, DES, hybrid RANS/DVMS and DDES/DVMS models are introduced in low dissipation schemes. They are compared for the simulation of vortex shedding flows around a NACA0021 at high angle of attack and a Caradonna-Tung helix.
Abstract
RANS, DES, hybrid RANS/DVMS and DDES/DVMS models are introduced in low dissipation schemes. They are compared for the simulation of vortex shedding flows around a NACA0021 [...]
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Matrix properties associated with discrete conservation in flow simulations
A. Veldman, G. Coppola

eccomas2022.

Abstract
Supraconservative discretization methods are studied which conserve primary (mass, momentum and internal energy) as well as secondary (total energy) invariants. In particular, the coefficient matrices which are related to such conservation properties are analyzed. This analysis holds for any discretization method with a volume-consistent scaling.
Abstract
Supraconservative discretization methods are studied which conserve primary (mass, momentum and internal energy) as well as secondary (total energy) invariants. In particular, [...]
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Energy-preserving stable computations of high-pressure supercritical fluids turbulence
M. Bernades, F. Capuano, F. Trias, L. Jofre

eccomas2022.

Abstract
High-fidelity computations of turbulent flows at high-pressure supercritical fluid conditions present significant challenges. Besides the inherent broadband nature of the flow, the rapid variation of thermophysical properties across the pseudo-boiling region can result in additional complexities in terms of strong localized density gradients, spurious pressure oscillations, non-linear behaviour of fluids, and amplification of aliasing errors. Different research groups have utilized distinct approaches to achieve numerical stability, mostly resorting to upwindbiased schemes, artificial dissipation and/or high-order filtering. However, in these strategies, stability is achieved at the expense of artificially suppressing part of the turbulent energy spectrum. In this regard, this work aims to explore the suitability, in terms of stability and accuracy, of recently proposed energy-preserving schemes for scale-resolving simulations of supercritical turbulence. For ideal gases, such type of methods have been demonstrated to provide stable and accurate computations of turbulence by preserving kinetic energy and/or other quantities of physical relevance. However, their extension to real-gas thermodynamic frameworks is still in its infancy, and consequently requires to be carefully investigated. To this objective, this work analyzes the performance of different classical and energy-preserving discretizations under ideal-gas conditions, and carries out an initial assessment of their performance at high-pressure supercritical fluid regimes. The results obtained indicate that their extension to real-gas thermodynamics is not straightforward, and consequently motivate the necessity to develop new solutions able to satisfy the desired stability and accuracy requirements.
Abstract
High-fidelity computations of turbulent flows at high-pressure supercritical fluid conditions present significant challenges. Besides the inherent broadband nature of the [...]
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A three-dimensional FVC scheme on non-uniform tetrahedron meshes: application to the 3D Euler equation
M. Ziggaf, I. Kissami, M. Boubekeur, F. Benkhaldoun, I. El mahi

eccomas2022.

Abstract
This study is about the construction of a numerical scheme of the predictor-corrector type in conservative form for solving general systems of conservation laws in multiple space dimensions on unstructured meshes. The work is a generalization of the one-dimensional finite volume characteristics (FVC) scheme and is related to the work of Fayssal Benkhaldoun and Mohammed Sead. The construction of the intermediate state is based on the method of characteristics, while the corrective stage recovers the conservation equations. The scheme is accurate to first order, monotonic and entropic; it avoids Riemann solvers at each interface; it also allows for improved accuracy order in time and space on unstructured three-dimensional meshes in the framework of the finite volume method. The scheme's performance is evaluated through a series of test benchmarks for the three-dimensional version of the Euler equations..
Abstract
This study is about the construction of a numerical scheme of the predictor-corrector type in conservative form for solving general systems of conservation laws in multiple [...]
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CFD validation of a controllable pitch marine propeller using a truly autonomous mesh generation with adaptive mesh refinement
M. Vångö, P. Scienza

eccomas2022.

Abstract
The design of propellers for maritime propulsion systems has a long history of using Computational Fluid Dynamics (CFD) as result of the constant desire to improve efficiency. The complex physics in addition to the motion of the propellers pose several challenges to CFD investigations, in particular with regards to mesh generation. In view of addressing these challenges, the present work proposes an alternative approach, which employs an autonomous mesh generation based on a modified Cartesian cut-cell methodology with Adaptive Mesh Refinement (AMR). In this work, this approach is validated against the extensive open measurement data of the Potsdam Propeller Test Case (PPTC) from SVA Potsdam, which contains both open water tests as well as detailed transient velocity field measurements. Additionally, benefits of both steady-state and fully-moving transient approaches for propeller numerical analyses are discussed, together with a future outlook on cavitation phenomena within the presented framework.
Abstract
The design of propellers for maritime propulsion systems has a long history of using Computational Fluid Dynamics (CFD) as result of the constant desire to improve efficiency. [...]
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Large Eddy Simulation of Primary Breakup Processes in Dual Fuel Internal Combustion Engines Using a Fully Compressible Multicomponent Approach
Y. Jiao, S. Schmidt, N. Adams

eccomas2022.

Abstract
Direct numerical simulations of fully compressible multiphase flows in realistic dual fuel internal combustion engine (DFICE) components under realistic operating conditions requireenormous computational resources beyond the scope of current investigations. In order toreduce the computational complexity and computational costs, we come up with a simplifiedatomizing liquid sheet benchmark case. Our set-up is based on properties of the “SprayA-210675 model” with D=89.4μm of a DFICE. The reduced computational nozzle domainis 5D*0.5D*0.5D and the chamber domain is 15D*2.5D*0.5D in x, y, z direction. At the inlet ofthe reduced domain, liquid n-Dodecane and a mixture of Nitrogen and Methane formashearlayer, while the environment is initially filled with a gas mixture. Periodic boundaryconditions in spanwise directions and a symmetry boundary condition at the bottomsurfaceare prescribed. A viscous wall separates the two flows similar to the “SprayAnozzle”geometry and the corner between viscous wall and gas inlet is similar to the “SprayAnozzle”exit. The initial chamber and ambient pressure is 6MPa. Three computational grids (2.50million, 34.56 million, 67.50 million) are used to simulate the shear layer and toanalysethe predicted mixing processes depending on the grid resolution. The mesh resolutionisvaried between 1.788μm and 0.596μm. Velocity differences between the liquid n-Dodecaneand the gas mixture are 400m/s, 200m/s and 50m/s. We employ a numerical algorithm capable of handling fuel primary break-upandcompressibility of all involved phases. An Implicit Large Eddy Simulation approachforcompact stencils proposed by Egerer et al. [1] based on [2, 3] is used to model sub-gridstructures if the resolution is insufficient for DNS. A diffuse interface method is used, together with a barotropic
Abstract
Direct numerical simulations of fully compressible multiphase flows in realistic dual fuel internal combustion engine (DFICE) components under realistic operating conditions [...]
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Effect of hydrogen addition to methane-air jet flame based on Sandia flame D
J. Liu, C. Pérez-Segarra, J. Rigola, F. Trias

eccomas2022.

Abstract
The present study investigates the effect of hydrogen addition to methane-air jet flame based on Sandia flame D.
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A mixed midelity conceptual design process for Boundary Layer Ingestion concepts
O. Atinault, M. Méheut, S. Defoort

eccomas2022.

Abstract
Boundary Layer Ingestion (BLI) is a promising concept that helps improving aircraft aeropropulsive performance. However, it remains difficult to bring together OAD (Overall Aircraft Design) process and high-fidelity tools due to the time of response of complex disciplinary tools. ONERA has thus developed a mixed fidelity approach inside its in-house OAD platform. The purpose is to mix conventional and robust OAD methods with high levels of fidelity from disciplinary tools such as CFD (Computational Fluid Dynamics), FEM (Finite Element Model) or CAA (Computational Aero Acoustics). This paper focuses on the integration of rapid CFD tools inside the OAD process, in order to assess BLI benefits. The resulting process is validated against reference and experimental cases when available, or high-fidelity RANS data elsewhere. The paper intends to present the tools and their validation process. These modules are applied to the common inlet concept, which aims at ingesting00% of the fuselage boundary layer. The results demonstrate the potential gain on the Power Saving Coefficient (up to 3% obtained with the L2 BLI module without resizing loop) but with non-negligible fan losses (up to 1.5%).
Abstract
Boundary Layer Ingestion (BLI) is a promising concept that helps improving aircraft aeropropulsive performance. However, it remains difficult to bring together OAD (Overall [...]
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Shape Optimisation of Turbomachinery Components
B. Semlitsch, A. Huscava

eccomas2022.

Abstract
Low-order models are the first choice to find the initial design of turbomachinery components screening many configurations. The final optimisation of the three-dimensional geometry is crucial for the best performance. Because of the ability to accurately predict the performance of turbomachinery, fluid dynamic simulations became a powerful tool [10]. However, parameter studies for shape optimisation relying on fluid dynamic simulations are computationally expensive and might fail to reveal the optimal geometry. Gradient-based optimisation approaches allow a significant reduction of simulations and hence, determine the optimum efficiency. The adjoint method finds the optimisation gradient by calculating the derivatives of the state variables with respect to the design objective without the need for finite differences [6]. Thus, the adjoint optimisation is especially efficient for problems with many degrees of freedom and few design objectives, e.g. increasing efficiency. The application of the adjoint method for shape optimisation is demonstrated on the example of a centrifugal compressor impeller. The shape of the rotor blades is optimised, and the impact of different objection functions, i.e. reducing the required moment or increasing the achieved pressure ratio, and optimisation constraints, i.e. retaining the operating point or keeping an area ratio, is analysed. The results demonstrate that the compressor performance can be significantly improved using the adjoint method. However, the challenge is to obtain not only an optimised shape for operating points but also for the entire operating map. The final shapes, obtained for different operating points, are compared.
Abstract
Low-order models are the first choice to find the initial design of turbomachinery components screening many configurations. The final optimisation of the three-dimensional [...]
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Hemodynamics in healthy and pathological thoracic aorta: integration of in-vivo data in CFD simulations and in in-vitro experiments
A. Mariotti, E. Vignali, E. Gasparotti, P. Marchese, M. Morello, M. Salvetti, S. Celi

eccomas2022.

Abstract
A comparison between the results of the CFD simulations and the in-vitro experiments carried out on a circulatory mock loop is presented. Both approaches integrate in-vivo measurements obtained from a patient-specific clinical data set. Three thoracic-aorta geometries are analyzed: a healthy aorta, an aneurysmatic aorta, and a coarctated aorta. The healthy geometry is obtained from Magnetic Resonance Imaging (MRI) acquisitions, together with the patient-specific flow-rate waveform, whereas the diseased ones are derived from the former geometry by locally morphing the vessel's wall. The open-source code Simvascular is used for simulations. The in-vitro results are measured in a fully controlled and sensorized circulatory mock loop for 3D-printed aortic models. Differently from in-vivo acquisitions, the experimental set-up eliminates some of the uncontrollable uncertainties that characterize MRI data. Indeed, perfect control of the flow rate and full knowledge of the wall model characteristics (rigid walls in the present case) is allowed in experiments and, thus, clear indications can be obtained to validate and improve the accuracy of numerical models. The numerical and experimental results are in good agreements for the three analyzed geometries and the flow-rate conditions. In-vivo data from the healthy case are in a satisfactory agreement with numerical/in-vitro results, and they can be ascribed to possible differences between MRI and numerical/in-vitro set-ups. The velocity fields obtained through CFD are consistent with the echographic results in in-vitro experiments, showing the same flow patterns in healthy and pathological cases.
Abstract
A comparison between the results of the CFD simulations and the in-vitro experiments carried out on a circulatory mock loop is presented. Both approaches integrate in-vivo [...]
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Effect of Laser Beam Scattering in SPH-Simulation of Deep Penetration Laser Beam Welding
D. Sollich, F. Fetzer, P. Eberhard

eccomas2022.

Abstract
The effect of laser beam scattering on capillary stability and melt dynamics is investigated simulatively for deep penetration laser beam welding. The mesh-free Lagrangian Smoothed Particle Hydrodynamics (SPH) method is coupled with a ray-tracing scheme. The SPH model covers fluid and thermodynamics, including temperature-dependent surface tension, recoil pressure, heat conduction, and phase transitions. The ray tracer models the laser-material interaction by tracking the propagation of light rays within the capillary according to the laws of geometrical optics, and taking into account multiple reflections and scattering. Surface scattering due to surface roughness, and volume scattering due to condensed droplets or local changes of the complex refractive index in the vapor plume are evaluated separately. For surface scattering, the reflections at the material surface are divided into a specular part and a diffuse part with randomly reflected rays. For volume scattering, the Henyey-Greenstein model is used to specify the angular distribution of the scattered light ray. The effect of scattering is examined for laser beam welding of aluminum and titanium. The results show that volume scattering has a stabilizing effect on the capillary for the highly reflective material aluminum, while the effect of surface scattering is small for both materials.
Abstract
The effect of laser beam scattering on capillary stability and melt dynamics is investigated simulatively for deep penetration laser beam welding. The mesh-free Lagrangian [...]
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Dirichlet boundary control of a steady multiscale fluid-structure interaction system
G. Barbi, A. Chierici, V. Giovacchini, L. Manes, S. Manservisi, L. Sirotti

eccomas2022.

Abstract
This work aims to extend the techniques used for the optimal control of the NavierStokes systems to control a steady multi-scale FSI system. In particular, we consider a multiscale fluid-structure interaction problem where the structure obeys a membrane model derived from the Koiter shell equations. With this approach, the thickness of the solid wall can be neglected, with a meaningful reduction of the computational cost of the numerical problem. The fluid-structure simulation is then reduced to the fluid equations on a moving mesh together with a Robin boundary condition imposed on the moving solid surface. The inverse problem is formulated to control the velocity on a boundary to obtain a desired displacement of the solid membrane. For this purpose, we use an optimization method that relies on the Lagrange multiplier formalism to obtain the first-order necessary conditions for optimality. The arising optimality system is discretized in a finite element framework and solved with an iterative steepest descent algorithm, used to reduce the computational cost of the numerical simulations.
Abstract
This work aims to extend the techniques used for the optimal control of the NavierStokes systems to control a steady multi-scale FSI system. In particular, we consider a multiscale [...]
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A posteriori MOOD limiting approach for multicomponent flows on unstructured meshes
P. Tsoutsanis, P. Farmakis

eccomas2022.

Abstract
A relaxed, high-order, Multidimensional Optimal Order Detection (MOOD) framework is extended to the simulation of compressible multicomponent flows on unstructured meshes in the open-source unstructured compressible flow solver UCNS3D. The class of diffuse interface methods (DIM) is employed with a five-equation model. The high-order CWENO spatial discretisation is selected due to its low computational cost and improved non-oscillatory behaviour compared to the original WENO variants. The relaxed MOOD enhancement of the CWENO method has been necessary to further improve the robustness of the CWENO method. A series of challenging compressible multicomponent flow problems have been implemented in UCNS3D, including shock wave interaction with a water droplet and shock-induced collapse of bubbles arrays. Such problems are generally very stiff due to the strong gradients present, and it has been possible to tackle them using the extended MOOD-CWENO numerical framework.
Abstract
A relaxed, high-order, Multidimensional Optimal Order Detection (MOOD) framework is extended to the simulation of compressible multicomponent flows on unstructured meshes [...]
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