Please use this identifier to cite or link to this item: https://sci.ldubgd.edu.ua/jspui/handle/123456789/13995
Title: Special Features of Using Mathematical Modeling for the Study of Tetrahedral Elements
Authors: PASTERNAK, Viktoriya
RUBAN, Artem
PASYNCHUK, Kyrylo
POLYANSKYI, Pavlo
Keywords: iteration
convergence of methods
modelling
three-dimensional space
finite element method
approximation
Issue Date: 2024
Publisher: Trans Tech Publications Ltd
Series/Report no.: Advances in Science and Technology;Vol. 156
Abstract: In this scientific work, mathematical modeling of tetrahedron elements in the finite element method is presented, which includes the determination of geometric shape, shape functions, and material properties. Unknown fields such as displacement vectors, strain, and stress tensors are considered. The methodology of applying the principle of virtual work and equilibrium equations is described, allowing the derivation of a system of differential equations to describe the behavior of the tetrahedral element. Integration over the volume and consideration of boundary conditions help reduce the equations to a system of linear algebraic equations for numerical solution using the finite element method. It was found that modeling tetrahedral elements with a specific given radius (for example, R=0.3 mm) involves stages such as geometry determination, element generation, shape function formation, stiffness matrix computation, and solving a system of linear equations. The radius R of tetrahedral elements is taken into account at all stages, ensuring accuracy and reliability in tetrahedra modeling. The research also focuses on the fact that the occurrence of minor errors in iterative processes may result from several factors, including iteration step, the number of iterations, stopping criteria, linear or nonlinear material behavior, solution method selection, the presence of geometric inhomogeneities, and element size
Description: Mathematical modeling is the process of constructing mathematical representations of real systems or phenomena with the aim of studying their properties and behavior [1, 2]. The use of mathematical modeling based on finite element methods has numerous characteristics, including [3]: 1) Abstraction of reality (mathematical models allow abstraction from complex details of real systems and define fundamental aspects relevant to specific research or tasks, facilitating the analysis and understanding of complex systems) [4]; 2) Prediction and optimization (mathematical models enable predicting the behavior of a system under different conditions and optimizing parameters to achieve specific goals) [5, 6]; 3) Time and resource savings (mathematical modeling allows efficient examination of the impact of various factors without the need for expensive experiments in real life, significantly saving time and resources) [7, 8]; 4) Explanation and interpretation (mathematical models can serve as tools for explaining cause-and-effect relationships and interpreting interactions between different variables in a system) [9, 10] 5) Warning about possible risks (mathematical modeling can help identify potential risks and forecast possible consequences under different scenarios and situations) [11]; 6) Numerical analysis method (mathematical modeling uses numerical methods to solve complex mathematical equations, allowing obtaining results where analytical methods may be inefficient or impossible) [12]; 7) Development of new theories (models can be used to develop new theories and hypotheses, which may be important objects for further research) [13]; 8) Discretization of space and time (mathematical modeling and the finite element method are used to approximate partial derivatives of differential equations with finite differences. Space and time are divided into a grid, and derivatives are approximated on this grid) [14]
URI: https://sci.ldubgd.edu.ua/jspui/handle/123456789/13995
ISSN: 1662-0356
Appears in Collections:2024

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