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Quantifying Uncertainty in Dielectric Solids’ Mechanical Properties Using Isogeometric Analysis and Conditional Generative Adversarial Networks

Shuai Li1, Xiaodong Zhao1,2,*, Jinghu Zhou1, Xiyue Wang1

1 College of Civil Engineering & Architecture, Dalian University, Dalian, 116622, China
2 Research Center for Geotechnical and Structural Engineering Technology of Liaoning Province, Dalian University, Dalian, 116622, China

* Corresponding Author: Xiaodong Zhao. Email: email

Computer Modeling in Engineering & Sciences 2024, 140(3), 2587-2611. https://doi.org/10.32604/cmes.2024.052203

Abstract

Accurate quantification of the uncertainty in the mechanical characteristics of dielectric solids is crucial for advancing their application in high-precision technological domains, necessitating the development of robust computational methods. This paper introduces a Conditional Generation Adversarial Network Isogeometric Analysis (CGAN-IGA) to assess the uncertainty of dielectric solids’ mechanical characteristics. IGA is utilized for the precise computation of electric potentials in dielectric, piezoelectric, and flexoelectric materials, leveraging its advantage of integrating seamlessly with Computer-Aided Design (CAD) models to maintain exact geometrical fidelity. The CGAN method is highly efficient in generating models for piezoelectric and flexoelectric materials, specifically adapting to targeted design requirements and constraints. Then, the CGAN-IGA is adopted to calculate the electric potential of optimum models with different parameters to accelerate uncertainty quantification processes. The accuracy and feasibility of this method are verified through numerical experiments presented herein.

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APA Style
Li, S., Zhao, X., Zhou, J., Wang, X. (2024). Quantifying uncertainty in dielectric solids’ mechanical properties using isogeometric analysis and conditional generative adversarial networks. Computer Modeling in Engineering & Sciences, 140(3), 2587-2611. https://doi.org/10.32604/cmes.2024.052203
Vancouver Style
Li S, Zhao X, Zhou J, Wang X. Quantifying uncertainty in dielectric solids’ mechanical properties using isogeometric analysis and conditional generative adversarial networks. Comput Model Eng Sci. 2024;140(3):2587-2611 https://doi.org/10.32604/cmes.2024.052203
IEEE Style
S. Li, X. Zhao, J. Zhou, and X. Wang, “Quantifying Uncertainty in Dielectric Solids’ Mechanical Properties Using Isogeometric Analysis and Conditional Generative Adversarial Networks,” Comput. Model. Eng. Sci., vol. 140, no. 3, pp. 2587-2611, 2024. https://doi.org/10.32604/cmes.2024.052203



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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