JOURNALS

Documents published in Scipedia

• Fast prediction of rain erosion in wind turbine blades using a data-based computational tool

  J. Gimenez, S. Idelsohn, E. Oñate

  Journal of Hydrodynamics (2024). Vol. 36, pp. 504–518

  
  

  Abstract

  Wind turbines (WTs) face a high risk of failure due to environmental factors like erosion, particularly in high-precipitation areas and offshore scenarios. In this paper we introduce a novel computational tool for the fast prediction of rain erosion damage on WT blades that is useful in operation and maintenance decision making tasks. The approach is as follows: Pseudo-Direct Numerical Simulation (P-DNS) simulations of the droplet-laden flow around the blade section profile are employed to build a high-fidelity data set of impact statistics for potential operating conditions. Using this database as training data, a machine learning-based surrogate model provides the feature of the impact pattern over the 2-D section for given wind and rain conditions. With this information, a fatigue-based model estimates the remaining lifetime and erosion damage for both homogeneous and coating-substrate blade materials. This prediction is done by quantifying the accumulated droplet impact energy and evaluating operative conditions over time periods for which the weather at the installation site is known. In this work, we describe the modules that compose the prediction method, namely the database creation, the training of the surrogate model and their coupling to build the prediction tool. Then, the method is applied to predict the remaining lifetime and erosion damage to the blade sections of a reference WT. To evaluate the reliability of the tool, several site locations (offshore, coastal, and inland), the coating material and the coating thickness of the blade are investigated. In few minutes we are able to estimate erosion after many years of operation. The results are in good agreement with field observations, showing the promise of the new rain erosion prediction approach.

  Abstract
  Wind turbines (WTs) face a high risk of failure due to environmental factors like erosion, particularly in high-precipitation areas and offshore scenarios. In this paper we [...]

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• Multi-scale methods: applications to fluid mechanics problems

  S. Idelsohn, J. Gimenez, A. Larreteguy, N. Nigro, F. Sivori, E. Oñate

  Mecánica Computacional (2023). Vol. 40 (1), pp. 9-9

  
  

  Abstract

  Multi-scale methods have emerged to facilitate its numerical solution when several simulta- neous scales exist in the same problem, and where all of them exert a significant influence on the solution. The difference in scales may be in the physical properties of the materials, for example density, modulus of elasticity, viscosity or diffusion coefficients, etc. or there may also be a difference in scales in the solution to the problem itself, such as a great difference in the magnitude of the waves or the instabilities involved. Multi-scale methods emerged primarily for the study of composite solids, but have later been generalized to very different applications. In this talk we will apply them to fluid mechanics problems. We will develop two very different types of applications. On the one hand, turbulence problems, where the multi-scale exists due to the great difference in the magnitude of the instabilities existing within a turbulent fluid. In a second application, we will see the problem of fluids that contain particles within them, where their homogeneous study is essential due to the large number of particles that have to be studied.

  Abstract
  Multi-scale methods have emerged to facilitate its numerical solution when several simulta- neous scales exist in the same problem, and where all of them exert a significant [...]

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• Virtual reality for the creation of stories and scenarios for construction safety: social distancing in the COVID-19 pandemic context

  F. Rivera, J. Mora, E. Oñate

  International Journal of Computational Methods and Experimental Measurements (2023). Vol. 11 (2), pp. 105-114

  
  

  Abstract

  The construction site is a complex and dynamic place. Workers are susceptible to certain risks due to the variability of their worksites, the tasks they perform, and the equipment they use. These aspects make the architecture, engineering, construction, and operation industry (AECO) have high accident rates. These typical processes are added to the growing use of new technologies in the workplace (e.g., drones, robots) that must coexist with human workers, not altering their routines and preserving a safe environment. A key aspect of occupational risk prevention (ORP) is worker training. Traditional training methods are not satisfactory. Given these deficiencies, virtual reality has shown advantages and benefits for training, allowing the development of immersive training experiences that promise to generate more meaningful learning for students. The construction sector needs to reactivate their construction sites after periods of confinement due to the direct implications on the progress of projects and, indeed, the industry's productivity (with the repercussions on costs, time and legal aspects). In this respect, training workers in covid protection measures and designing and analysing changing construction site scenarios to reduce the spread of viruses is crucial to ensure workers' health. This research shows the application and agile development of a training experience for social distancing at construction sites to prevent COVID-19 transmission, based on virtual reality and building information modelling and using serious games as a teaching strategy. Analyses are shown to exemplify the application and potential of the tools.

  Abstract
  The construction site is a complex and dynamic place. Workers are susceptible to certain risks due to the variability of their worksites, the tasks they perform, and the equipment [...]

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• Development of an individual 3D particle reconstruction method for discrete mechanical modeling: Interpolation by Fourier composition

  J. Pena, M. Castro, M. Farías, E. Oñate, L. Moreno, C. Recarey

  Computer Methods in Applied Mechanics and Engineering (2024). Vol. 420, Art. Num.116705

  
  

  Abstract

  Reconstruction methods for granular materials are an essential step in achieving an accurate geometrical basis in the use of particle methods such as the well-known discrete element method. In this study, a novel continuous analytical method will be proposed to achieve individual 3D reconstructions of granular materials. For this purpose, the 2D Fourier Descriptor theory is used and a generalization of it to the 3D case is obtained, which is quite different from the spherical harmonics theory. Some limitations existing in the original model will be addressed by developing and calibrating a generalized approach that results in a total of four main models. Particles from a study sample are reconstructed, and the models are evaluated based on four generalized error metrics, as well as the presence of some specific limitations detected in the models. Finally, the models are compared using a decision-making method in different decisional scenarios.

  Abstract
  Reconstruction methods for granular materials are an essential step in achieving an accurate geometrical basis in the use of particle methods such as the well-known discrete [...]

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• Interaction of particulate fluids and structures. Modelling and computational challenges

  E. Oñate

  complas2023.

  
  

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• A numerical framework for modelling tire mechanics accounting for composite materials, large strains and frictional contact

  A. Cornejo Velázquez, V. Mataix, P. Wriggers, L. Barbu, E. Oñate

  Computational Mechanics  (2024). Vol. 73(1), pp. 1-25

  
  

  Abstract

  We present a general framework for the analysis and modelling of frictional contact involving composite materials. The study has focused on composite materials formed by a matrix of rubber and synthetic or metallic fibres, which is the case of standard tires. We detail the numerical treatment of incompressibility at large deformations that rubber can experience, as well as the stiffening effect that properly oriented fibres will induce within the rubber. To solve the frictional contact between solids, a Dual Augmented Lagrangian Multiplier Method is used together with the Mortar method. This ensures a variationally consistent estimation of the contact forces. A modified Serial-Parallel Rule of Mixtures is employed to model the behaviour of composite materials. This is a simple and novel methodology that allows the blending of constitutive behaviours as diverse as rubber (very low stiffness and incompressible behaviour) and steel (high stiffness and compressible behaviour) taking into account the orientation of the fibres within the material. The locking due to the incompressibility constraint in the rubber material has been overcome by using Total Lagrangian mixed displacement-pressure elements. A collection of numerical examples is provided to show the accuracy and consistency of the methodology presented when solving frictional contact, incompressibility and composite materials under finite strains.

  Abstract
  We present a general framework for the analysis and modelling of frictional contact involving composite materials. The study has focused on composite materials formed by a [...]

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• Dataset of the temperature rise during granular flows in a rotating drum

  R. Rangel, F. Kisuka, C. Hare, V. Vivacqua, A. Franci, E. Oñate, C. Wu

  Data in Brief (2023). Vol. 48, Art. 109282

  
  

  Abstract

  This paper provides experimental data on the temperature rise during granular flows in a small-scale rotating drum due to heat generation. All heat is believed to be generated by conversion of some mechanical energy, through mechanisms such as friction and collisions between particles and between particles and walls. Particles of different material types were used, while multiple rotation speeds were considered, and the drum was filled with different amounts of particles. The temperature of the granular materials inside the rotating drum was monitored using a thermal camera. The temperature increases at specific times of each experiment are presented in form of tables, along with the average and standard deviation of the repetitions of each setup configuration. The data can be used as a reference to set the operating conditions of rotating drums, in addition to calibrating numerical models and validating computer simulations.

  Abstract
  This paper provides experimental data on the temperature rise during granular flows in a small-scale rotating drum due to heat generation. All heat is believed to be generated [...]

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• Experimental investigation of heat generation during granular flow in a rotating drum using infrared thermography

  R. Rangel, F. Kisuka, C. Hare, V. Vivacqua, A. Franci, E. Oñate, C. Wu

  Powder Technology (2023). Vol. 426, Art. 118619

  
  

  Abstract

  Granular flow is common in many industrial applications, and involves heat generation from frictional contacts and inelastic collisions between particles. The self-heating process is still poorly understood despite being intrinsic to many processes. This work, for the first time, explores this problem experimentally by quantifying the temperature rise of granular flows in a rotating drum with a robust methodology based on infrared thermography. Particles of four different materials (lead, steel, plastic and glass) are used in the experiments, at various rotation speeds and drum fill ratios. To assess the mechanical behaviour, the flow regime of every experiment was determined. It was inferred that particles with higher density tend to generate more heat. It was also revealed that increasing the rotation speed favours the temperature rise. At the same time, the fill ratio had the least influence on the thermal response of the particulate systems considered.

  Abstract
  Granular flow is common in many industrial applications, and involves heat generation from frictional contacts and inelastic collisions between particles. The self-heating [...]

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• Enhanced semi-explicit particle finite element method via a modified Strang splitting operator for incompressible flows

  J. Marti, E. Oñate

  Computational Particle Mechanics (2023). Vol. 10, pp. 1463–1475

  
  

  Abstract

  This work presents an enhanced version of the semi-explicit particle finite element method for incompressible flow problems. This goal is achieved by improving the methodology that results from applying the Strang splitting operator by adding an acceleration term. The advective step is evaluated on the mesh considering the new term leading to a more efficient algorithm. Two test cases are solved for validating the methodology and estimating its accuracy. The numerical results demonstrate that the proposed scheme improves the accuracy and the computational efficiency of the semi-explicit PFEM scheme.

  Abstract
  This work presents an enhanced version of the semi-explicit particle finite element method for incompressible flow problems. This goal is achieved by improving the methodology [...]

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• A prototype of a micro-scale model for the distribution of NO2 in urban areas

  I. Pouplana, S. Latorre, M. Maso, C. Alonso, E. Pérez, X. Guinart, I. Hernández, X. Baulies, E. Oñate

  Atmospheric Pollution Research (2023). Vol. 14 (2), 101668

  
  

  Abstract

  We present a new 2.5D model for predicting the concentration of nitrogen dioxide (NO2) at street level in an urban area. This work develops the first prototype of a tool that should provide fast quantitative answers to help decision-making on the suitability of implementing traffic restrictions during air pollution episodes. The model first solves the wind flow over the city streets ignoring vorticity and turbulence. The obtained velocity field is used to transport the pollutant via a semi-Lagrangian model, combining the particle finite element method of second generation (PFEM2) with the finite element method. A variable absorption term is used to account for the part of the contaminant entering and leaving the calculation plane. The NO2 emissions are estimated from the historical traffic data. The model has been tested during four air pollution episodes in the city of Barcelona (Spain), two in summer and two in winter. A comparison against experimental measurements has been performed at seven different locations throughout the city with promising results.

  Abstract
  We present a new 2.5D model for predicting the concentration of nitrogen dioxide (NO2) at street level in an urban area. This work develops the first prototype of a tool that [...]

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