Documents published in Scipedia

• Eddy Current Modeling and Simulations for the Characterization of Low Thickness Multilayer Materials_prueba_latex

  S. Bennoud, J. Sánchez Pinedo, E. Sari

  (Select a year).

  
  

  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 differentOPEN 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 [...]

  • 0
  •  read

• 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 [...]

  • 28
  •  read

• 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 [...]

  • 68
  •  read

• 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 [...]

  • 48
  •  read

• 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 [...]

  • 251
  •  read

• 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. [...]

  • 7
  •  read

• 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 [...]

  • 76
  •  read

• 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 [...]

  • 37
  •  read

• 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 [...]

  • 29
  •  read

• 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 [...]

  • 0
  •  read