Coupling of a multi-GPU accelerated elasto-visco-plastic fast Fourier transform constitutive model with the implicit finite element method
Abstract
This paper presents an implementation of the elasto-visco-plastic fast Fourier transform (EVPFFT) crystal plasticity model in the implicit finite element (FE) method of Abaqus standard through a user material (UMAT) subroutine to provide a constitutive relationship between stress and strain at FE integration points. To facilitate the implicit coupling ensuring fast convergence rates, an analytical Jacobian is derived. The constitutive response at every integration point is obtained by the full-field homogenization over an explicit microstructural cell. The implementation is a parallel computing approach involving multi-core central processing units (CPUs) and graphics processing units (GPUs) for computationally efficient simulations of large plastic deformation of metallic components with arbitrary geometry and loading boundary conditions. To this end, the EVPFFT solver takes advantages of GPU acceleration utilizing Nvidia’s high performance computing software development kit (SDK) compiler and compute unified device architecture (CUDA) FFT libraries, while the FE solver leverages the message passing interface (MPI) for parallelism across CPUs. The high-performance hybrid CPU-GPU multi-level framework is referred to as FE-GPU-EVPCUFFT. Simulations of simple compression of Cu and large strain cyclic reversals of dual phase (DP) 590 have been used to benchmark the accuracy of the implementation in predicting the mechanical response and texture evolution. Subsequently, two applications are presented to illustrate the potential and utility of the multi-level simulation strategy: 4-point bending of textured Zr bars, in which the model captures the shape variations as a consequence of texture with respect to the bending plane and another bending of DP1180, in which the model reveals details of spatial micromechanical fields.
Publication Date
3-15-2022
Publisher
Elsevier
Journal Title
Computational Materials Science
Digital Object Identifier (DOI)
Document Type
Article
Recommended Citation
Adnan Eghtesad, Kai Germaschewski, Marko Knezevic, Coupling of a multi-GPU accelerated elasto-visco-plastic fast Fourier transform constitutive model with the implicit finite element method, Computational Materials Science, Volume 208, 2022, 111348, ISSN 0927-0256, https://doi.org/10.1016/j.commatsci.2022.111348.
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