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A GPU-based framework for finite element analysis of elastoplastic problems by Utpal Kiran; Deepak Sharma; Sachin Singh Gautam is a Computer Science article available to read on EtoBox.

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Elastoplasticity is observed in a wide range of materials like metals that have real-world applications. The design and optimization process of such materials depends strongly on elastoplastic analysis for the prediction of displacement and stress. However, elastoplastic simulation is computationally expensive and often requires the use of parallel computers in real-world applications like crashworthiness and metal forming. This paper presents a novel parallel framework for finite element analysis of elastoplastic problems on massively parallel Graphics Processing Units (GPUs) architecture. We propose GPU-based parallel algorithms for all expensive steps in elastoplastic analysis, namely the computation of elemental matrices and their assembly, the computation of stress using the well-known radial-return method and the computation of internal force vectors and their assembly. Since GPUs have limited memory, assembly is done directly into a sparse storage format that can be seamlessly integrated with a GPU-based linear solver. The proposed algorithms are optimized for efficient memory access and fine-grain parallelism and prefer computation over data storage and reuse. In the propos

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Author

Utpal Kiran; Deepak Sharma; Sachin Singh Gautam

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)