Parametric Analysis of Thick FGM Plates Based on 3D Thermo-Elasticity Theory: A Proper Generalized Decomposition Approach
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Parametric Analysis of Thick FGM Plates Based on 3D Thermo-Elasticity Theory: A Proper Generalized Decomposition Approach
by Mohammad-Javad Kazemzadeh-Parsi
1,* [ORCID] , Amine Ammar
1 [ORCID] and Francisco Chinesta
2
1
LAMPA & ESI Group Chair, Arts et Metiers Institute of Technology, 49035 Angers, France
2
PIMM Lab & ESI Group Chair, Arts et Metiers Institute of Technology, 75013 Paris, France
*
Author to whom correspondence should be addressed.
Materials 2023, 16(4), 1753; https://doi.org/10.3390/ma16041753
Submission received: 19 December 2022 / Revised: 10 February 2023 / Accepted: 17 February 2023 / Published: 20 February 2023
(This article belongs to the Topic Artificial Intelligence and Computational Methods: Modeling, Simulations and Optimization of Complex Systems)
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Abstract
In the present work, the general and well-known model reduction technique, PGD (Proper Generalized Decomposition), is used for parametric analysis of thermo-elasticity of FGMs (Functionally Graded Materials). The FGMs have important applications in space technologies, especially when a part undergoes an extreme thermal environment. In the present work, material gradation is considered in one, two and three directions, and 3D heat transfer and theory of elasticity equations are solved to have an accurate temperature field and be able to consider all shear deformations. A parametric analysis of FGM materials is especially useful in material design and optimization. In the PGD technique, the field variables are separated to a set of univariate functions, and the high-dimensional governing equations reduce to a set of one-dimensional problems. Due to the curse of dimensionality, solving a high-dimensional parametric problem is considerably more computationally intensive than solving a set of one-dimensional problems. Therefore, the PGD makes it possible to handle high-dimensional problems efficiently. In the present work, some sample examples in 4D and 5D computational spaces are solved, and the results are presented.
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