Documents published in 2024 : Scipedia

A Solar Irradiance Prediction Model with Recurrent Neural Networks and Computer Graphics Methods
W. Shin, N. Baek

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (4), 52

Abstract
This paper presents a computer simulation model for predicting solar irradiance in a three-dimensional (3D) environment. Solar irradiance prediction is critical for solar energy systems and related fields. Machine learning techniques, such as recurrent neural networks (RNNs), are employed for more accurate predictions. Integrating a 3D environmental simulation with the RNN models achieves accurate predictions with reasonable resolutions. The training model uses selected astronomical and atmospheric factors to train the RNN models. The proposed method allows the user to obtain the corresponding solar irradiance prediction values for arbitrary periods. Astronomical and atmospheric factors affect solar irradiance; hence, data from the Korea Meteorological Administration are used for training. The RNNs, including the long short-term memory (LSTM) and gated recurrent unit methods, are employed for the prediction. The LSTM layers outperformed other configurations, accurately predicting zero irradiation values. A set of solar irradiance models is presented using RNNs by configuring their layers, and the layout consisting of four LSTM layers performed best. This layout achieved reasonable error bounds, with relatively good root mean squared error and mean absolute error values. A computer graphics-based solar irradiance prediction model is proposed based on this prediction model, incorporating simulations of the surrounding environment. A case study is presented with surrounding buildings to analyze the solar irradiance over the year with a one-hour forecasting horizon to demonstrate its feasibility. Moreover, we plan to improve the results with other neural network models, such as the fuzzyembedded RNN.OPEN ACCESS Received: 19/09/2024 Accepted: 13/12/2024
Abstract
This paper presents a computer simulation model for predicting solar irradiance in a three-dimensional (3D) environment. Solar irradiance prediction is critical for solar [...]
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Binary and Multi-Classification Models for Breast Cancer Diagnosis Using Automated Deep Learning and Mammography Images with Different Augmentation Cases
N. Charim, N. Ruza, M. Arzmi, S. Hussain

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (4), 53

Abstract
Mammography is a very efficient medical imaging procedure that is used to detect and diagnose breast cancer. However, the use of mammography for the early detection and identification of cancer is very complicated and represents a considerable workload for radiologists. Machine learning (ML) can help address these challenges by providing accurate, automated diagnosis, but traditional ML methods are complex and resourceintensive. Google AutoML Vision offers a simplified approach, enabling healthcare professionals with minimal programming skills to develop effective diagnostic models. The aim of this study was to evaluate the ability of automated deep learning using mammography images using Google AutoML with different augmentation cases. In this work, two models were created: one for binary classification and another for multiclassification. The binary classification model includes two scenarios: noncancerous and malignant, while the multi-classification approach includes three scenarios: normal, benign and malignant. The average accuracy of the two classifications was evaluated and compared. The average accuracy of the binary and multi-classification models was 77.98% and 79.29%, respectively. These results suggest that Google AutoML can simplify the use of ML models in the clinical setting and provide a reliable diagnostic tool that can reduce the workload of radiologists. This study shows that AutoML has the potential to streamline diagnostic workflows in healthcare and make machine learning more accessible and effective in medical practise.OPEN ACCESS Received: 01/08/2024 Accepted: 29/11/2024
Abstract
Mammography is a very efficient medical imaging procedure that is used to detect and diagnose breast cancer. However, the use of mammography for the early detection and identification [...]
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A Dynamically Consistent Numerical Approach for the Ebola Virus Transmission Model with Fuzzy Parameters and Time Delay
M. Tashfeen, F. Dayan, M. Rehman, T. Abdeljawad, B. Abdalla

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (4), 51

Abstract
The Ebola virus disease (EVD) is a major threat to human health, especially in Central West Africa. In this study, the transmission dynamics of EVD infection are studied using the Susceptible, Infected, Recovered, Deceased, and Pathogen (SIRDP) epidemic framework that prioritizes identifying and quantifying the sources of uncertainty in parameters. Conventional quantitative methods may believe that all measurements are exact, but in reality, data can often be imprecise or hard to measure. To overcome this challenge, fuzzy theory has been integrated into the model due to its flexibility in managing uncertainty. Additionally, this study considers the temporal dynamics of EVD transmission by integrating time delays, which makes the model fit the real-world simulation of disease progression. A sensitivity analysis of the reproductive number was also conducted to assess the impact of key parameters on the transmission dynamics. The behavior of the model has been numerically explored using various algorithms, such as the forward Euler method and the NonStandard Finite Difference (NSFD) scheme. Some significant numerical characteristics like positivity, convergence, and consistency have been assessed, which indicates that the NSFD method can capture the trends of EVD with fuzzy parameters. The proposed scheme maintains important characteristics of the traditional epidemic models and provides a stable approach for assessing EVD patterns in conditions of risks and unknown variables. The computational experiment confirms the theoretical conclusions and depicts the deficiencies of the normal finite difference approximations, notably for large step sizes, and supports the advantages of the NSFD approach in maintaining the structure of the model.OPEN ACCESS Received: 01/08/2024 Accepted: 16/10/2024
Abstract
The Ebola virus disease (EVD) is a major threat to human health, especially in Central West Africa. In this study, the transmission dynamics of EVD infection are studied using [...]
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Eddy Current Modeling and Simulations for the Characterization of Low Thickness Multilayer Materials
S. Bennoud, E. Sari

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (4), 48

Abstract
Measuring and determining the parameters and characteristics of multilayer structures have become an important subject for several recent studies. This importance is due to industry needs and structural health requirements. The eddy current inspection is considered an important practical tool that ensures the safety and efficiency of multilayer structures and responds to the above necessities. The diversity of multilayer structure characteristics is one of the principal problems that must be solved. These physical and electromagnetic parameters are not always available or provided by the suppliers. Another problem that arises in the development of different models related to these structures is the difficulty of obtaining a satisfactory diagnosis. This difficulty returns to the complexity of geometry, the presence of small dimensions and sizes, and the existence of various parameters. In this context, it is necessary to achieve a strategy for the development of software and hardware tools concerning the characterization of multilayer structures. These tools must be applied to surmount the above problems and improve the technical advantages of the eddy current inspection. The principal objective of this work is to investigate the efficacy of the eddy current method applied to aeronautical materials, particularly low thickness multilayer structures. The modeling was performed using the finite element method. A software program was developed to investigate changes in the coil impedance. Results are initially validated and compared against the analytical and computational results given for simple cases. They are very similar, and they present a good agreement for both situations. The error is 5% for the calculus of the induction magnetic B. It also varies from 0.17% to 5.32% for impedance responses that enable the application of the developed code to carry out simulations for complex geometries. For various values of parameters and a wide range of applications, the parameters and properties of the problem can easily be introduced into the code. This permits the analysis and calculation of changes in impedance versus the effect of any variation in parameters. The developed approach is sufficiently general. It can simulate various potential cases of defects in low thickness multilayer structures due to its adequate design. It can generate interpretable results for different. OPEN ACCESS Received: 14/07/2024 Accepted: 02/10/2024
Abstract
Measuring and determining the parameters and characteristics of multilayer structures have become an important subject for several recent studies. This importance is due to [...]
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A New Dynamical Analysis of COVID-19 Epidemic Model Using Two Fractional Operators
A. Hagag, Z. Alqahtani, A. Arafa

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (4), 49

Abstract
Fractional calculus has emerged as a powerful tool for modeling complex systems with memory and hereditary properties, particularly in biological and epidemiological contexts. Despite its potential, accurately capturing the dynamics of diseases like COVID-19 remains challenging due to the need for models that balance accuracy with computational efficiency. This study presents a new dynamic analysis of the fractional-order coronavirus (2019-nCOV) pandemic model. The model incorporates two fractional derivatives, the Caputo and Atangana-Baleanu in Caputo sense (ABC) derivatives. By applying the Fractional Temimi-Ansari Method (FTAM), we derive a power series solution, demonstrating the existence, uniqueness, and convergence of the solutions. Our findings indicate that the fractional derivatives, particularly the ABC derivative, offer a more comprehensive description of memory effects in biological systems, which is crucial for accurately modeling the dynamics of COVID-19. The results show a high degree of accuracy and efficiency in capturing the behavior of the system, with convergence analyses confirming the robustness of the model. Graphical representations further illustrate the system’s behavior under different parameter settings. The proposed model also effectively simulates the spread of the virus in Ghana, offering valuable insights for implementing non-pharmaceutical interventions. These findings demonstrate the potential of fractional calculus in improving epidemic models, especially in capturing the long-term effects and memory characteristics of pandemics.OPEN ACCESS Received: 31/08/2024 Accepted: 01/11/2024
Abstract
Fractional calculus has emerged as a powerful tool for modeling complex systems with memory and hereditary properties, particularly in biological and epidemiological contexts. [...]
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Free Vibration Analysis of Non-Uniform Timoshenko Beams Using Haar Wavelets
T. Baran

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (4), 46

Abstract
In this paper, we present a method using Haar wavelets for solving axially functionally graded (FG) Timoshenko beam equations with non-uniform cross-sections. We compare two different approaches to the solution. The first approach involves approximating the resulting function (i.e., rotation) of the differential equation with a polynomial function using Haar wavelets, which is a classical application in the Haar wavelet method. The second method employs an auxiliary function that uses Haar wavelets, but the rotation or deflection do not directly equal the sought function. The rotation and deflection are derived from this auxiliary function. In both methods, the coupled governing equations are transformed into a single governing equation. Using the Haar wavelet method, this single differential equation transforms into a system of linear algebraic equations. For different boundary conditions, the roots of the characteristic polynomial equation obtained from the system of linear algebraic equations are solved to determine the lowest to highest-order natural frequencies. Our results show that the use of auxiliary function is faster and more consistent with the results available in the literature. We presented several natural frequency predictions of Timoshenko beams with different taper ratios and support conditions that have not been detailed in the literature before.OPEN ACCESS Received: 04/09/2024 Accepted: 07/11/2024
Abstract
In this paper, we present a method using Haar wavelets for solving axially functionally graded (FG) Timoshenko beam equations with non-uniform cross-sections. We compare two [...]
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Finite Element Discretization of the Thermo-Diffusive-Mechanical Problem with Large Deformations
A. Ortiz-Toranzo, I. Romero

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (4), 47

Abstract
In certain relevant engineering problems, the mechanical field is strongly coupled with the temperature and mass transport fields. The solution to these problems is complex, especially when deformations are large. Therefore, numerical approximations are often used to find all the fields involved in the coupled problem, their effects, and their interactions. This article describes a finite element method discretization of the coupled problem of diffusion, temperature, and deformation, including the nonlinear range of deformations. The formulation takes into account all possible couplings between the three fields of study, and all the necessary details for its complete implementation are provided, filling a gap in the literature of these methods. Additionally, the article describes the thermodynamic foundation of coupled thermo-diffusive-mechanical problems, emphasizing the derivation of balance equations and constraints that follow from these condlaw of thermodynamics. The results of the article will be of interest tore searchers who need to implement the equations of coupled problems infinite element codes, particularly for applications in battery modeling, the behavior of metals under the effects of hydrogen, gels, etc.
Abstract
In certain relevant engineering problems, the mechanical field is strongly coupled with the temperature and mass transport fields. The solution to these problems is [...]
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A Fractional Semi-Analytical Iterative Method for the Approximate Treatment of Fisher’s Equations
A. Almuneef, A. Hagag

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (4), 50

Abstract
This study presents a novel fractional semi-analytical iterative approach for solving nonlinear fractional Fisher’s equations using the Caputo fractional operator. The primary objective is to provide a method that yields exact solutions to nonlinear fractional equations without requiring assumptions about nonlinear terms. By applying the Temimi-Ansari Method (TAM) with fractional calculus, this approach offers a robust solution to the time-fractional nonlinear Fisher’s equation, a model relevant in fields such as population dynamics, tumor growth, and gene propagation. In this work, tables and graphical illustrations show that the proposed method minimizes computational complexity and delivers significant accuracy across multiple cases of Fisher’s equations. The findings indicate that TAM with fractional order derivatives provides accurate, efficient approximations with reduced computational workload, showcasing the technique’s potential for addressing a wide range of nonlinear fractional differential equations.OPEN ACCESS Received: 19/07/2024 Accepted: 01/11/2024
Abstract
This study presents a novel fractional semi-analytical iterative approach for solving nonlinear fractional Fisher’s equations using the Caputo fractional operator. The [...]
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Analysis of Airflow Uniformity in Pig Nurseries Using Duct Ventilation in Northeast China_prova_latex_2
Z. Wu, K. Xu, Y. Chen, Y. Liu, M. Liu, J. Sánchez Pinedo

Colección de pruebas Jesús Sánchez (2024). 4

Abstract
The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the airflow field and airflow uneven coefficients of pig nurseries with duct ventilation were simulated and calculated using computational fluid dynamics, and compared with pig nurseries with different duct diameters, inlet and outlet air velocities and air supply angles. The average relative error between the simulated and measured values was 12 %. Comparison of simulation results and airflow uneven coefficients showed that the airflow uneven coefficients of the fences were reduced, and the airflow field was uniformly distributed with a duct diameter of 0.3 m , inlet and outlet air velocities of 1.5 and 2.0 \mathrm{~m} / \mathrm{s}, respectively, and an air supply angle of 45^{\circ }. These improvements resulted in a more homogeneous ventilation, which led to more uniform ventilation and contributed to discharging dirty air outdoors. Then the test pig nursery was modified based on the simulation and analysis results. Difference analyses were carried out between the control and the test pig nurseries. Comparative analyses showed the differences between the test data and the monitoring data were smaller, and the duct ventilation was more uniform, which was suitable for the healthy growth of piglets.
Abstract
The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the [...]
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Analysis of Airflow Uniformity in Pig Nurseries Using Duct Ventilation in Northeast China_prova_latex
Z. Wu, K. Xu, Y. Chen, Y. Liu, M. Liu, J. Sánchez Pinedo

Colección de pruebas Jesús Sánchez (2024). 2

Abstract
The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the airflow field and airflow uneven coefficients of pig nurseries with duct ventilation were simulated and calculated using computational fluid dynamics, and compared with pig nurseries with different duct diameters, inlet and outlet air velocities and air supply angles. The average relative error between the simulated and measured values was 12 %. Comparison of simulation results and airflow uneven coefficients showed that the airflow uneven coefficients of the fences were reduced, and the airflow field was uniformly distributed with a duct diameter of 0.3 m , inlet and outlet air velocities of 1.5 and 2.0 \mathrm{~m} / \mathrm{s}, respectively, and an air supply angle of 45^{\circ }. These improvements resulted in a more homogeneous ventilation, which led to more uniform ventilation and contributed to discharging dirty air outdoors. Then the test pig nursery was modified based on the simulation and analysis results. Difference analyses were carried out between the control and the test pig nurseries. Comparative analyses showed the differences between the test data and the monitoring data were smaller, and the duct ventilation was more uniform, which was suitable for the healthy growth of piglets.
Abstract
The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the [...]
- 0
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Analysis of Airflow Uniformity in Pig Nurseries Using Duct Ventilation in Northeast China_prova_word
Z. Wu, K. Xu, Y. Chen, J. Sánchez Pinedo

Colección de pruebas Jesús Sánchez (2024). 3

Abstract
The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the airflow field and airflow uneven coefficients of pig nurseries with duct ventilation were simulated and calculated using computational fluid dynamics, and compared with pig nurseries with different duct diameters, inlet and outlet air velocities and air supply angles. The average relative error between the simulated and measured values was {| class="formulaSCP" style="width: 100%; text-align: center;" |- | 12\% |} . Comparison of simulation results and airflow uneven coefficients showed that the airflow uneven coefficients of the fences were reduced, and the airflow field was uniformly distributed with a duct diameter of 0.3 m , inlet and outlet air velocities of 1.5 and {| class="formulaSCP" style="width: 100%; text-align: center;" |- | 2.0\, m/s |} , respectively, and an air supply angle of {| class="formulaSCP" style="width: 100%; text-align: center;" |- | {45}^{\circ } |} . These improvements resulted in a more homogeneous ventilation, which led to more uniform ventilation and contributed to discharging dirty air outdoors. Then the test pig nursery was modified based on the simulation and analysis results. Difference analyses were carried out between the control and the test pig nurseries. Comparative analyses showed the differences between the test data and the monitoring data were smaller, and the duct ventilation was more uniform, which was suitable for the healthy growth of piglets.
Abstract
The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the [...]
- 5
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Analysis of Airflow Uniformity in Pig Nurseries Using Duct Ventilation in Northeast China
Z. Wu, K. Xu, Y. Chen, Y. Liu, M. Liu

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 39

Abstract
The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the airflow field and airflow uneven coefficients of pig nurseries with duct ventilation were simulated and calculated using computational fluid dynamics, and compared with pig nurseries with different duct diameters, inlet and outlet air velocities and air supply angles. The average relative error between the simulated and measured values was 12%. Comparison of simulation results and airflow uneven coefficients showed that the airflow uneven coefficients of the fences were reduced, and the airflow field was uniformly distributed with a duct diameter of 0.3 m, inlet and outlet air velocities of 1.5 and 2.0 m/s, respectively, and an air supply angle of 45°. These improvements resulted in a more homogeneous ventilation, which led to more uniform ventilation and contributed to discharging dirty air outdoors. Then the test pig nursery was modified based on the simulation and analysis results. Difference analyses were carried out between the control and the test pig nurseries. Comparative analyses showed the differences between the test data and the monitoring data were smaller, and the duct ventilation was more uniform, which was suitable for the healthy growth of piglets.OPEN ACCESS Received: 19/07/2024 Accepted: 10/10/2024
Abstract
The problem of uneven ventilation in pig houses must be solved to effectively improve the winter environmental quality of pig nurseries in cold regions. In this study, the [...]
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Word de prueba
J. Sánchez Pinedo

Colección de pruebas Jesús Sánchez (2024). 1
- 0
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LA REVOLUCION DE LA MODA A TRAVÉS DEL ECODISEÑO
C. ACTUAL, M. PÉREZ-HICKMAN

MARÍA PÉREZ-HICKMAN's personal collection (2024). 1
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Numerical Turing Patterns Formation on 3D Surfaces with a Linear Finite Element Method
D. Gonzalez, L. Valencia, D. González Mena

SMCCA (2024). 6

Abstract
The purpose of this article is the numerical generation of Turing like patterns on 3D bounded surfaces, based on the analysis of Turing instability in certain types of reaction-diffusion systems in planar regions. We first include a well known 2D-study and analysis of these systems that yield the mathematical conditions under which spatial patterns arise, and which is based on temporal solutions where the classical Laplace diffusion operator is considered. Then, we extend the numerical study to 3D surfaces, employing the Laplace-Beltrami operator to simulate diffusion while keeping the same reaction terms, thus generating similar Turing patterns. The solutions to the involved systems will be calculated numerically using a semi-implicit time discretization in combination with a linear finite element method for spatial discretization using triangular meshes. Details about the numerical implementation are provided for clearness to a broader audience.
Abstract
The purpose of this article is the numerical generation of Turing like patterns on 3D bounded surfaces, based on the analysis of Turing instability in certain types of reaction-diffusion [...]
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Design Thinking in Film and Television Ideation: Enhancing Concept Development
A. Surname, . Name, S. Ntsanwisi

International Journal of Multidisciplinary Educational Research and Innovation (2024). 2

Abstract
This article explores the integration of design thinking into the ideation phase of film and television production through the Media Innovate project at the Durban University of Technology. By employing design thinking methodologies, the project aims to enhance students' creative processes and bridge the gap between academic training and industry practice. Through user-centered problem-solving, students develop feature and short film scripts that address real-world challenges while cultivating entrepreneurial skills. The study follows an exploratory, qualitative methodology, utilising observation of students enrolled in the project to assess the impact of design thinking on their approach to media innovation. The observation focuses on how students apply design thinking principles such as empathy, ideation, and prototyping to their creative work, enabling a deeper understanding of stakeholder needs and fostering self-sustainability. Findings suggest that incorporating design thinking not only enhances creative outcomes but also prepares students for economic growth opportunities in the media industry. This research contributes to the broader discourse on the relevance of design thinking in the creative industries and it’s potential to transform educational practices in film and television production, equipping students for real-world success.
Abstract
This article explores the integration of design thinking into the ideation phase of film and television production through the Media Innovate project at the Durban University [...]
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Research on the Effects of Pit Excavation on Adjacent Existing Subway Tunnel Structures Based on the FEM-DEM Coupling Method
D. Meng, W. Lei, J. Han, H. Li, Y. Huang

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 43

Abstract
With the swift advancement of underground space development, large deep excavation projects above subway stations are becoming more common. This study employs the Finite element method-Discrete element method (FEM-DEM) coupling method to examine the effects of excavation on the structure of nearby subway tunnels. First, the f lexible triaxial compression test was conducted using the FEM-DEM coupling method to acquire the macroscopic mechanical characteristics of various soil layers. Based on this, the ground particle model was developed using the particle size scaling method, the underground continuous wall support was constructed via the FEM-DEM coupling method, and the tunnel model was established using particles arranged circularly. The study shows that with the excavation, the particles at the bottom of the foundation start to heave upward, with the maximum uplift displacement being approximately 10 mm. Throughout the excavation process, substantial changes occur in the contact force chain within the pit, with notable stress release at the pit bottom. Moreover, the porosity at the pit bottom gradually increases, and the vertical stress decreases; the stress decreased by 75% compared to before excavation, primarily due to stress release during excavation. Lastly, a focused analysis was conducted on the tunnel deformation during excavation. Throughout the foundation pit excavation, the tunnel’s displacement mainly took place within the excavation area, and its vertical displacement increased as the excavation depth increased, with a maximum displacement of approximately 0.5 mm. Analysis of particle displacement at various locations in the tunnel revealed that particles closest to the foundation pit bottom experienced the greatest displacement, whereas those farther away had relatively smaller displacements. The findings offer crucial theoretical support for the design and implementation of excavation projects.
Abstract
With the swift advancement of underground space development, large deep excavation projects above subway stations are becoming more common. This study employs the Finite element [...]
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Control-Relevant Identification of the Unstable Inertial Systems
I. Cojuhari

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 40

Abstract
Nowadays, with the rise of computing power, control-relevant identification methods have gained attention in various industrial applications, incorporating the requirements for control design into the process of system identification. Mathematical identification of stable linear dynamical systems is a widely studied problem in the literature, and it is prevalently performed in open-loop structures that may lead to high-order models suitable for control system design with imposed control objectives. However, in the case of unstable systems identification can become a challenge task, and usually is performed using closed-loop identification techniques. This paper presents the control-relevant identification approach for two kinds of unstable processes. The contribution focuses on establishing a well-fitted identified model by using a strategy that involves collecting data from the closed-loop system’s operation with a proportional controller when the system achieves an underdamped step response. In addition, a proportional-integral-derivative (PID) controller for each process was synthesized using maximal stability degree method. Concerning identification, the simulation results were compared with those of the genetic algorithm and offered better model estimation than the genetic algorithm. On the other hand, it is also demonstrated that the designed control algorithm offered a high degree of stability to the system and is more reliable in stabilizing the behavior of the unstable system than the genetic algorithm and the parametric optimization method.
Abstract
Nowadays, with the rise of computing power, control-relevant identification methods have gained attention in various industrial applications, incorporating the requirements [...]
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Effects of radar absorption materials application on stealth performance of inlet based on risk theory
S. Liu, Z. Guo, L. Chen

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 42

Abstract
One significant technical measure to reduce the forward radar cross section (RCS) of the aircraft was to design the inlet into an S-shape. Additionally, the application of radar-absorbing material (RAM) can further decrease the RCS of the air intake which approach enhances the stealth capabilities of the aircraft. Nevertheless, the use of RAM will simultaneously increase the inherent weight of the air intake. The electromagnetic scattering characteristics of Sshaped inlets without RAM coating and seven coating schemes are calculated by numerical simulation. The risk theory was employed to assess the impact of the coating RAM on the radar cross-section. The simulation results indicate that coating RAM can further reduce the forward average RCS value. Compared to the full coating scheme the S-shaped inlets with RAM on the intake region can achieve 90% of the RCS reduction effect and cut down approximately forty percent of the coating.
Abstract
One significant technical measure to reduce the forward radar cross section (RCS) of the aircraft was to design the inlet into an S-shape. Additionally, the application of [...]
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Detection of small rod-end joint bearings via deep feature fusion and confidence propagation clustering
J. Peng, R. Ye, S. Lan, T. Xiao, C. Xu, Y. Song

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 41

Abstract
Machine vision is used to detect dense, small rod-end joint bearings in sliding ball surfaces with little feature information and high variability. However, this leads to inaccurate identification, affecting production efficiency. This study proposes a deeplearning object-detection algorithm model that allows the network to retain more semantic information. We introduced the space-to-depth convolution (SPD-Conv) step-free convolution module to improve the backbone network and developed a multi-level feature fused SPD (MFSPD) deep feature fusion module to redesign the neck network to improve the feature extraction ability and detection accuracy for small targets. Furthermore, we added a small P4 detection head in the head network (i.e., prior box acquisition on the dataset using the weighted k-means algorithm), increased the matching degree of the prior box and feature layer, and accelerated the model convergence. To improve the confidence propagation clustering (CP-Cluster) analysis algorithm for post-processing, we optimized the prediction box confidence degree and detection speed. The algorithm performance was evaluated on homemade, T-LESS, and COCO datasets. The mAP@.5 values of the target detection algorithm for the homemade and T-LESS datasets were 96.9% and 93.8%, respectively, and the mAP was 55.9% for the COCO dataset. The experimental results indicate that the algorithm has a high detection accuracy and good feature extraction ability. Thus, it has considerable advantages for small-object detection and provides a reference for the detection of small parts.
Abstract
Machine vision is used to detect dense, small rod-end joint bearings in sliding ball surfaces with little feature information and high variability. However, this leads to [...]
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The Segmentation of Debris Flow Fans Based on Spatial Coordinate Attention Mechanism
X. Song, B. Wang

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 44

Abstract
In response to the low accuracy and poor performance of traditional machine learning methods in identifying debris flow fans. This paper proposes an optimized Simple, Parameter-Free Attention Module (SimAM) attention mechanism named Spatial Coordinate Attention Module. It combines with convolutional neural networks to achieve precise segmentation of debris flow fans. Firstly, the energy function of the SimAm is improved to retain the spatial coordinate information of features. Secondly, the closed-form solution of the module is obtained through optimization theory to ensure lightweightness, resulting in the Spatial Coordinate Attention Module. Finally, the Spatial Coordinate Attention Module is embedded into classic segmentation network models to compare with mainstream attention mechanisms. Experimental results demonstrate that the proposed method outperforms mainstream attention mechanisms in various classic models, yielding more complete segmentation results. This approach effectively enhances the segmentation performance of the network models in the task of debris flow fans segmentation
Abstract
In response to the low accuracy and poor performance of traditional machine learning methods in identifying debris flow fans. This paper proposes an optimized Simple, Parameter-Free [...]
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Validation of VSPAERO for Basic Wing Simulation
J. Rosas-Cordova, C. Santana-Delgado, D. Hernadez-Alcantara, L. Amezquita-Brooks

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 45

Abstract
Potential flow theory-based numerical solvers have gained popularity for rapid and straightforward aerodynamic modeling across various applications, particularly in the early stages of design and in resource-limited projects such as small unmanned aerial vehicles (UAVs). These solvers offer a cost-effective solution for analyzing aerodynamic performance, and several well-established methods have demonstrated strong alignment with experimental data. Among these solvers is VSPAERO, a relatively recent addition integrated within the National Aeronautics and Space Administration’s (NASA) OpenVSP aircraft design software. Despite its growing use, a comprehensive validation of the VSPAERO solver remains necessary to ensure its reliability in diverse scenarios. This article presents a validation of the VSPAERO solver by conducting a series of case studies. The assessment includes comparisons against reference values obtained through empirical relationships, results from other established aerodynamic solvers and experimental data from wind tunnel testing. The assessment covers a range of geometries and flow conditions, highlighting areas where the solver performs well and identifying any limitations in its application. The findings provide insights into the meshing parameters required for accurate simulations, as well as the types of geometries and flow conditions for which VSPAERO can be considered a reliable tool. As a conclusion, the article presents a series of best practices and guidelines that are recommended to improve the accuracy and efficiency of future erodynamic simulations conducted using this software. These recommendations are intended to serve as a valuable reference for both researchers and engineers involved in aerodynamic modeling, particularly those working on projects with tight budgets or in the preliminary stages of aircraft design.
Abstract
Potential flow theory-based numerical solvers have gained popularity for rapid and straightforward aerodynamic modeling across various applications, particularly in the early [...]
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A Bi-Objective Evacuation Path Optimization Method Based on Meta-Heuristic Integration
G. Yang, J. Chen

Rev. int. métodos numér. cálc. diseño ing. (2024). Vol. 40, (3), 38

Abstract
Urban underground public spaces are relatively enclosed, with high daily passenger flow and diverse directions. Enhancing evacuation capabilities through dynamic guidance systems is a crucial solution. Therefore, this paper proposes a double-layer computational framework based on meta-heuristic integration of a bi-objective evacuation path optimization method. Firstly, the outer layer computation explores the population by combining the genetic algorithm and simulated annealing. It uses temperature parameters to probabilistically accept worse solutions, enhancing global search capability and avoiding local optima. Secondly, the inner layer calculates the fitness value of each solution from the outer layer, considering both the shortest path and minimum risk objectives. The path optimization is carried out by A∗ algorithm on the basis of constructing the safety matrix by using breadth-first search algorithm, and the distance matrix by using Dijkstra’s algorithm. Finally, this method can search for the shortest safe path, effectively guiding people safely from the starting point to the exit. The experiments show that compared to traditional evacuation path planning methods, the proposed method significantly improves path optimization capabilities, quickly planning the shortest and safest evacuation route. It can provide guidance for fire safety and emergency plans for evacuations.
Abstract
Urban underground public spaces are relatively enclosed, with high daily passenger flow and diverse directions. Enhancing evacuation capabilities through dynamic guidance [...]
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Generalitzar la Formació Professional DUAL
M. Carrión

Miquel Carrión's personal collection (2024). 1

Abstract
El fet que les empreses no trobin les persones professionals que necessiten és un fenomen cada vegada més extensiu, especialment en àmbits estratègics com el digital o les instal·lacions així com en diferents perfils associats a oficis professionals. A aquets context cal afegir que la creació de llocs de treball es pronostica que sigui, respectivament, en noves ocupacions i per reposició de molts d’aquests perfils d’oficis professionals. Davant d’aquesta realitat la formació professional Dual es postula com una de les receptes perquè les empreses puguin formar el talent que no troben degudament preparat o disposat al mercat de treball. Tanmateix, una manca de cultura de la formació continuada, la por a la fuita del talent quan comença a decréixer la corba d’aprenentage, el desconeixement de la formació professional per part de les empreses i la tipologia d’empreses (mipime), fan que no sigui encara una pràctica prou generalitzada. De fet, la modalitat dels contracte de formació en alternança és absolutament testimonial en el conjunt de la contractació a Catalunya (amb prou feines arriben als 3.000 contractes; un 0,1% del total). Contràriament aquesta és una de les poques modalitats de contractació de durada determinada que s’ha mantingut després de la darrera reforma laboral del 2021, i conté interessants elements d’incentiu i bonificació. Paral·lelament a aquesta realitat, el Servei Públic d’Ocupació de Catalunya ha apostat des de fa uns anys per la creació d’un programa de política activa d’ocupació que inclou aquesta modalitat de contractació (FPO DUAL). Aquest programa ha tingut una extraordinària recepció per part de les empreses, els centres de formació i entitats impulsores que fan possible aquest nexe entre formació, empresa i destinataris del programa. De fet, el primer any es va destinar un pressupost de 17M€, amb un total de 61 projectes atorgats, 875 persones joves participants i 275 empreses contractants; el segon any es van destinar 25 M€, amb un total de 95 projectes atorgats, 1.333 persones joves participants i 585 empreses contractants; i en la darrera convocatòria, de 38 M€ ens trobem amb un total de 86 projectes, que suposen 1.599 participants i 459 empreses. Val a dir que l’import de les sol·licituds en aquesta darrera edició van superar els 50M€. Tant és així, que el programa de DUAL va suposar més d’un 60% de tots els contractes de formació en alternança que es van fer a Catalunya l’any 2023. Aquest mes de juliol de 2024 es rebrà l’avaluació de les primeres edicions i es podran observar els resultats de la seva execució, el seu impacte i la seva incidència en tots els actors que hi intervenen. Especialment en el col·lectiu al qual va especialment adreçat, que són persones sense qualificació professional (incloent joves que van patir abandonaments escolars prematurs). A aquesta realitat encara cal afegir-hi l’entrada en vigor del nou model de Formació Professional, definit en la nova llei orgànica 3/2022 i desplegat a través del recent RD 659/23; que converteix tota la formació professional en modalitat dual i crea la modalitat intensiva, que es durà a terme a través dels contractes de formació en alternança. En aquest context tot indica que el repte de la política pública és crear un marc de desenvolupament de la Formació Professional Dual prou atractiu perquè doni resposta a persones que necessiten entorns retribuïts de formació teòrico-pràctica per reconciliar-se amb la formació i els aprenentatges i per iniciar carreres professionals; i que alhora doni resposta a les empreses que no troben el talent que necessiten al mercat de treball. En aquesta comunicació s’analitzarà la realitat de manca de professionals en el mercat de treball i els efectes que aquesta manca de talent està comportant; l’ús de la modalitat dual en la Formació Professional i la percepció per part de les empreses i les persones participants; les característiques i resultats del programa FPOA DUAL del Servei Públic d’Ocupació de Catalunya; així com les noves amenaces i oportunitats que comporta el nou de Formació Professional sobre la DUAL. Finalment, la comunicació apuntarà quines podrien ser les mesures en la redefinició d’aquest programa, per contribuir a generalitzar l’ús de la formació professional dual a Catalunya, i que aquesta tingui el màxim impacte positiu possible sobre les persones i les empreses que hi participen.
Abstract
El fet que les empreses no trobin les persones professionals que necessiten és un fenomen cada vegada més extensiu, especialment en àmbits estratègics [...]
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Revisão Bibliográfica Sobre Instrumentação Geotécnica em Barragens: Vantagens e Desvantagens da Automação
T. França, C. Honório

Revisão Bibliográfica Sobre Instrumentação Geotécnica em Barragens: Vantagens e Desvantagens da Automação (2024).

Abstract
This article comprehensively evaluates the advantages and disadvantages of automating the main geotechnical instruments used to monitor dams. Geotechnical instrumentation plays a fundamental role in characterizing the performance and maintaining the safety of the structure. With the advance of technology and the updating of dam regulations, there has been a trend towards the automation of geotechnical instruments. The automation of this monitoring process generates several benefits, such as the ability to collect data in real time, improving the accuracy, efficiency and reliability of information acquisition. However, the article also highlights the disadvantages, such as the high cost of implementation and operational complexity. Based on a literature review, this study looks at: i) the main geotechnical instruments; ii) Brazilian legislation and standards for monitoring; and iii) the advantages and disadvantages of automating instrumentation. Understanding the trends and limitations of technological evolution is essential for the effective application of geotechnical instrumentation in dams.
Abstract
This article comprehensively evaluates the advantages and disadvantages of automating the main geotechnical instruments used to monitor dams. Geotechnical instrumentation [...]
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TÍTOL: El finançament públic al sistema de recerca defineix l’èxit d’un país. Criteris per al seu repartiment.
A. Jornet

Anna Font Jornet's personal collection (2024). 2
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Plataformes de fintech per al finançament empresarial a Catalunya: estat actual i perspectives
E. Noya

Eloi Noya's personal collection (2024). 2

Abstract
En aquest document s’analitza l'ecosistema fintech català, amb un enfoc en les empreses de tecnologia financera que faciliten crèdit al teixit empresarial. El document ofereix una visió sobre l'impacte del fintech en la disponibilitat de finançament alternatiu per a petites i mitjanes empreses, especialment en un context de restricció de crèdit bancari des de la crisi de 2008. Les plataformes es classifiquen segons els tipus de solució financera que ofereixen, com ara el crowdlending, l’equity crowdfunding, el finançament de circulant i el finançament basat en ingressos. A més, s'aborden algunes tendències i desafiaments clau per al sector i el paper de Catalunya com a centre emergent en el sector fintech europeu. Finalment, l'informe intenta quantificar l'impacte econòmic d'aquestes fintechs, destacant-ne la generació d'ocupació i l'aportació al PIB català.
Abstract
En aquest document s’analitza l'ecosistema fintech català, amb un enfoc en les empreses de tecnologia financera que faciliten crèdit al teixit empresarial. [...]
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Análisis Global del Sector Inversor en Europa y el Mundo: Perspectivas en la Industria Sostenible y Circular.
D. Bermejo Perramón

David Bermejo Perramón's personal collection (2024). 1

Abstract
El interés de la comunicación en este contexto se centra en ofrecer una visión profunda del sector inversor enfocado en la sostenibilidad y la economía circular. Esta comunicación pretende ser un instrumento analítico que permita entender las dinámicas, los actores y los criterios que están influyendo en las decisiones de inversión en estos ámbitos, tanto a nivel local (España), como regional (Europa) y global. La evolución reciente del sector inversor ha mostrado una clara tendencia hacia la especialización y diferenciación. Los actores y criterios de inversión en sostenibilidad y economía circular se han distinguido cada vez más del sector inversor tradicional. Por ello, resulta esencial realizar un análisis específico que aborde estas particularidades. Los resultados o conclusiones de este análisis se pueden estructurar en cinco grandes bloques temáticos: 1. Evaluación del Mercado y Tendencias de Innovación: Dentro de este análisis, también se tomará en consideración la evaluación del tamaño del mercado y las tendencias de innovación. Entender el tamaño del mercado puede proporcionar una visión clara de las oportunidades y el potencial de un sector específico, mientras que la evaluación de las tendencias de innovación permitirá identificar las tecnologías, modelos de negocio y prácticas que están configurando el sector de la sostenibilidad y la economía circular. 2. Evolución de la inversión privada: Este punto analizará la trayectoria de la inversión privada en sostenibilidad y economía circular en los últimos años. Qué sectores o segmentos han captado más financiamiento y qué factores han influido en esta evolución. 3. Principales Agentes de Inversión: Identificar quiénes son los actores clave interesados en invertir en proyectos de sostenibilidad a nivel europeo. Esto incluye fondos de inversión, capital riesgo, family offices, entidades gubernamentales, entre otros. Cada uno de estos actores tiene sus propias motivaciones y objetivos. 4. Criterios de Inversión: Analizar cuáles son prioritarios para estos inversores especializados en sostenibilidad. Estos criterios pueden incluir aspectos ambientales, sociales, de gobernanza (ESG), retorno financiero, impacto social, entre otros. Comprender estos criterios es fundamental para alinear los proyectos empresariales con las expectativas de los inversores y aumentar las posibilidades de éxito. 5. Impacto de la Regulación, Taxonomía Financiera y el Green Deal: Evaluar cómo las regulaciones y políticas europeas (Directivas CSRD, Net Zero 50, etc.), como la taxonomía financiera y el Green Deal, están influyendo en el sector inversor.
Abstract
El interés de la comunicación en este contexto se centra en ofrecer una visión profunda del sector inversor enfocado en la sostenibilidad y la economía [...]
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Promising technologies to reduce global and local aviation emissions
K. Synylo, O. Zaporozhets, A. Krupko, S. Karpenko

ECCOMAS 2024.

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- 136
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Scalable approximation and solvers for ionic electrodiffusion in cellular geometries
P. Benedusi, A. ELLINGSRUD, H. HERLYNG, M. ROGNES

ECCOMAS 2024.

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- 24
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The Continuous Adjoint Method with Consistent Discretization Schemes for Transitional Flows and the Use of Deep Neural Networks in Shape Optimization in Fluid Mechanics
M. Kontou

ECCOMAS 2024.

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Object-Based Full Waveform Inversion with Quantified Uncertainty in Stratified Media
A. Carpio, G. Oleaga, E. Cebrián, C. Abugattas

ECCOMAS 2024.

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- 33
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Universality and scaling relations for turbulent/non-turbulent interfaces in free shear flows
M. Zecchetto

ECCOMAS 2024.

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Investigating SFRC Jacketing for Seismic Retrofitting of Reinforced Concrete Multistorey Buildings
G. Markou, E. Antwerpe, K. Braun

ECCOMAS 2024.

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- 10
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A Parametric Investigation of the Train-Test Ratio for Machine Learning Algorithms in Structural Mechanics Applications
G. Markou, D. Rademan

ECCOMAS 2024.

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- 7
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Structural strain method for the fatigue evaluation of rib-deck joints with insufficient weld penetration
B. Villoria

ECCOMAS 2024.

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- 6
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Aerodynamic design of a high aspect ratio strut-braced wing
D. Costoso, E. Van, O. Atinault, M. Méheut

ECCOMAS 2024.

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- 27
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Extra Corporeal Membrane Oxygenation Support For Perfusion In Cardiac Shock: A Computational Analysis
E. Vignali, E. Gasparotti, M. Mazzoli, D. Haxhiademi, S. Celi

ECCOMAS 2024.

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- 76
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Prospects of Novel Technologies for SAF Production
R. Adami, P. Lamberti, A. Yakovlieva, S. Boichenko, M. Sarno, V. Tucci

ECCOMAS 2024.

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- 62
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On the Training of Algorithms Using Finite-Element Computation Data for Damage Identification in Sensorised Composite Structures
R. Chabukswar, C. Mullen, K. Kouramas

ECCOMAS 2024.

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- 133
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Laminate-like functionally graded composites
G. Serhat

ECCOMAS 2024.

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- 20
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Fluid-Structure Interaction Simulation of Transcatheter Aortic Valve Implantation Using Smoothed Particle Hydrodynamics
C. Catalano, O. Zahalka, T. Turgut, V. Bouwman, S. Pasta

ECCOMAS 2024.

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- 16
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On the Modeling of Left Atrial Appendage Inversion: a Reverse Growth Analysis
R. Scuoppo, S. Pasta

ECCOMAS 2024.

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- 37
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Digital Twin Model of an Early Medieval Church: Entanglement of Historical Studies and Mathematical Methods
E. Babilio, S. Rapuano

ECCOMAS 2024.

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- 214
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Modeling Sand Ripples in Mine Countermeasure Simulations by means of Stochastic Optimal Control
P. Blondeel, F. Utterbeeck, B. Lauwens

ECCOMAS 2024.

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- 18
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Data-Driven Calibration of RANS Transition Models with Deep Learning
J. Capel Jorquera, M. Módena, L. González Gutiérrez, E. Sánchez

ECCOMAS 2024.

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- 36
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On The Instability of One Versus Two Proximate Masses Moving on an Infinite Beam Supported by Viscoelastic Layers
Z. Dimitrovová

ECCOMAS 2024.

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- 8
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Market Prospects For a Hybrid Turbo-electric Propulsion (HTEP) With Fuel Cells Fors a Regional Aircraft With 80 Seats
M. Zamarreño Suárez, R. Jurado, F. Moreno, V. Comendador, R. Valdés

ECCOMAS 2024.

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- 13
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Unstructured conservative level-set method for interfacial transport processes on adaptive and fixed collocated meshes
N. Balcazar-Arciniega, J. Rigola, A. Oliva

ECCOMAS 2024.

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- 141
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Coupling CFD with 1D Model for the Prediction of Performance of a Hemodialysis Module with Undulated Fibers
A. Giordano, N. Cancilla, M. Ciofalo, D. Donato, G. Marotta, A. Tamburini, G. Micale

ECCOMAS 2024.

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- 96
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A Phase-Field Approach to Model Ductile Quasi-Static and Fatigue Fracture in Short Fiber Reinforced Polymer Composites
A. Dean, P. Kumar, E. Mahdi, R. Rolfes

ECCOMAS 2024.

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- 10
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Numerical Analysis of Different Seismic Isolation Systems
K. Guo, G. Milani

ECCOMAS 2024.

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- 3
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Assessing Inattend Human Elements in Critical Driving Safety Events
J. Raiyn, G. Weidl

ECCOMAS 2024.

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- 0
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Symmetry-preserving approximate deconvolutions
F. Trias, A. Gorobets, A. Oliva

ECCOMAS 2024.

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- 12
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Differentially Heated Turbulent Channel Flow Two-Point Correlations
M. Garcia-Berenguer, L. Gasparino, O. Lehmkhul, I. Rodríguez

ECCOMAS 2024.

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- 10
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Towards Active Flow Control Strategies Through Deep Reinforcement Learning
R. Montalà, B. Font, O. Lehmkuhl, R. Vinuesa, I. Rodríguez

ECCOMAS 2024.

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- 143
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Fleet and Traffic Management Systems for Conducting Future Cooperative Mobility
G. Papa, V. Vukašinović, F. Massi

ECCOMAS 2024.

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- 84
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Mathematical Modeling Of Damage-Plasticity Concrete Material Model Subjected To High-Strain Rate Loading
S. Pattajoshi, S. Ray

ECCOMAS 2024.

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- 157
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Implementation of RHT Material Model For Boulders And Concrete In Multi-Layered Composite Target Under Projectile Impact
S. Kapoor, S. Ray

ECCOMAS 2024.

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- 55
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A plugin framework for large-scale multi-formulation topology optimization
M. Neiva, A. Nale, I. Menezes, A. Chiozzi

ECCOMAS 2024.

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- 15
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One-Shot Optimization for the Inverse Design of a Quasi 1-D De Laval Nozzle
V. Georgopoulos, L. Zampini, G. Coussement, T. Verstraete

ECCOMAS 2024.

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- 14
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Comparative Numerical Analysis of Flat and Round Tips on Aerodynamic Efficiency and Performance in IEA 10MW Wind Turbine Blades
R. Jeganathan, N. Manelil, J. Theron, L. Höning, B. Stoevesandt

ECCOMAS 2024.

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- 26
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Design of a hybrid turbo-electric propulsion (HTEP) with fuel cells for a regional aircraft with 80 seats. Demonstration and verification of some solutions for HTEP.
M. Kirichkov, S. Dmytriyev, O. Yelanskiy, I. Kravchenko

ECCOMAS 2024.

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- 16
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Modelling and Simulation of High Velocity Impact of Particles in Cold Spray Additive Manufacturing
J. Qi, R. RAOELISON, M. Rachik

ECCOMAS 2024.

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- 26
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Modeling of structural compressive fatigue propagation in concrete using the microplane sliding model MS1
A. Baktheer, S. Esfandiari, M. Aguilar, H. Becks, M. Classen, R. Chudoba

ECCOMAS 2024.

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- 24
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On the embedding of nonlinear multipoint constraints in the finite element method
J. Wackerfuβ, J. Boungard

ECCOMAS 2024.

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- 15
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Numerical Method Employing Preconditioned Artificial Dissipation for Gas-liquid Two-phase Flow
T. Zhao, B. Shin

ECCOMAS 2024.

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- 21
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Phase-field Topology Optimization of Elasto-plastic Contact Structures
A. Myśliński

ECCOMAS 2024.

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- 14
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Node-level performance analysis of the structural mechanics solver b2000++pro
N. Pour, H. Klimach

ECCOMAS 2024.

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- 2
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Cost-accuracy analysis for symmetry-preserving methods
J. Hopman, À. Alsalti-Baldellou, J. Rigola, F. Trias

ECCOMAS 2024.

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- 0
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Assessment of the accuracy and robustness of different numerical methods in wall-bounded flows
S. Toosi, J. Larsson, P. Schlatter

ECCOMAS 2024.

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- 33
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Validation of a Numerical Model of Seismic Newtonian Noise for the Einstein Telescope
P. Reumers, S. François, G. Degrande

ECCOMAS 2024.

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- 29
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Leveraging advanced numerical calibration to filter out temperature effects on vibration-based monitoring data: application to the Mogadouro clock tower
A. Barontini, D. Pellegrini, F. Testa, M. Girardi, M. Masciotta, N. Mendes, C. Padovani, L. Ramos, P. Lourenço

ECCOMAS 2024.

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- 63
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Wavelet Analysis for the Vertical Isolation Ratio of RC Hospital Structures Subjected to Near-Fault Earthquakes
F. Mazza, A. Braile, R. Labernarda

ECCOMAS 2024.

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- 20
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An innovative lightweight integrated seismic - energy coating system for the retrofit of a masonry clustered building in Timisoara city (Romania)
G. Longobardi, M. Mosoarca, A. Formisano

ECCOMAS 2024.

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- 15
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Deep Learning Surrogate Models for the Autmotive Industry
B. Eiximeno, A. Miró, I. Rodríguez, O. Lehmkuhl

ECCOMAS 2024.

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- 19
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A Displacement-Based Design Procedure of Hysteretic Dissipative Steel Exoskeletons for the Seismic Retrofitting of RC Hospital Buildings
F. Mazza, D. Rizzo

ECCOMAS 2024.

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- 7
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Promising technologies to reduce aviation noise at airports
O. Zaporozhets, K. Kazhan, V. Makarenko, V. Tokarev, A. Chyla, M. Bukala

ECCOMAS 2024.

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- 59
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Approximated Bayesian Reinforcement Learning
V. Arnaoutis, B. Rosic

ECCOMAS 2024.

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- 6
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Flow Control with Data-Driven Approaches
A. Corrochano, J. Canals, L. Saavedra, S. Le-Clainche

ECCOMAS 2024.

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- 43
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Traffic Forecasting With Uncertainty: A Case for Conformalized Quantile Regression
G. Petelin, J. Rožanec, G. Papa

ECCOMAS 2024.

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- 57
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Quadratic manifold for model order reduction of a geometrically nonlinear beam with friction contact
F. Mashayekhi

ECCOMAS 2024.

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- 20
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An Intersection Interaction Hybrid Method for Energy Flow at Mid-High Frequency for Complex Cavities Acoustic
T. Wanglomklang, F. Gillot, S. Besset

ECCOMAS 2024.

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- 10
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Plastic Design of Frame Structures under Uncertainty Conditions by A Stochastic Model
M. Staat, T. Ngoc

ECCOMAS 2024.

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- 116
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Evaluating Forecast Divergence in Fluid Dynamics: A Metric for Autoregressive Models in the Absence of True Solution Data
R. Abadía-Heredia, M. Lopez-Martín, S. Clainche

ECCOMAS 2024.

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- 24
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Uncertainty-aware Transonic Flow Predictions with Bayesian Deep Learning
M. Anhichem, S. Timme, J. Castagna, A. Peace, M. Maina

ECCOMAS 2024.

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- 74
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Performance and Stability Assessment of a Coupled Three-Field Thermal Fluid-Structure Interaction Simulation of a Simplified Thin-Walled Skin Heat Exchanger
L. Kreuzeberg, M. Haupt, D. Hahn, I. Antonau, S. Heimbs

ECCOMAS 2024.

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- 23
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Effect Of Rotation Of The Boundaries On The Stability Of A Flow Caused BY A Nonlinear Heat Source
A. Gritsans, A. Kolyshkin, F. Sadyrbaev, I. Yermachenko

ECCOMAS 2024.

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- 65
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Adaptively Tuned High-Order Methods for iLES
P. Tsoutsanis, X. NOGUEIRA, L. FU

ECCOMAS 2024.

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- 41
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Design of an auxetic and standard soft material for additive manufacturing using a heuristic RBSM approach
L. Silva, S. Casolo

ECCOMAS 2024.

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- 27
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Model-based and Data-driven Digital Twins for Railway Vehicle-Track Interaction Monitoring
B. Baasch, P. Oselin, J. Groos

ECCOMAS 2024.

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- 46
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Identification of losses from engine-airframe interaction for a passenger aircraft through integrated simulation
J. Mueller, K. Chiba, Y. Oba

ECCOMAS 2024.

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- 0
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A-priori Energy-Biased Training for the Prediction of Closure Terms of the VMS Navier-Stokes Equations
A. Bettini, S. Hulshoff

ECCOMAS 2024.

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- 20
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Pushover Analysis of Masonry Double Curvature Structures Subjected to Horizontal Loads: The Anime Sante Dome
A. Gandolfi, G. Milani

ECCOMAS 2024.

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- 24
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Optimization of seismic metamaterials using different performance measures for reduction of ground vibration due to surface loads
Z. Kabirian, G. Degrande, G. Lombaert

ECCOMAS 2024.

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- 6
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An Open-Source Phase Field Model for Fracture in Orthotropic FGM With Adaptive Mesh Refinement
P. SIDHARTH, N. Rao

ECCOMAS 2024.

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- 20
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Convolution Neural Network for Fluid Flow Simulations in Cascade with Oscillating Blades
V. Heidler, O. Bublík, J. Vimmr

ECCOMAS 2024.

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- 4
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Research on Airborne System Simulation Methodology Based on AI-Enhanced Surrogate modelling Approach
C. Wang, W. Zhao, S. Wan, C. Wang

ECCOMAS 2024.

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- 13
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A multi-material topology optimization approach for large-scale additive manufacturing of non-periodic architected structures
A. Chiozzi, A. Nale, F. Senhora, G. Paulino

ECCOMAS 2024.

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- 21
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A Novel Deformable Limit Analysis Modeling for the Masonry Arch or Vault Structures
Y. Hua, G. Milani

ECCOMAS 2024.

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- 0
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