4.7 Article

OpenMP and MPI implementations of an elasto-viscoplastic fast Fourier transform-based micromechanical solver for fast crystal plasticity modeling

期刊

ADVANCES IN ENGINEERING SOFTWARE
卷 126, 期 -, 页码 46-60

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.advengsoft.2018.09.010

关键词

Crystal plasticity; Constitutive equations; Cray supercomputer; Parallel computing; MPI

资金

  1. Los Alamos National Laboratory [388715]
  2. U.S. National Science Foundation [CMMI-1650641]

向作者/读者索取更多资源

We explore several parallel implementations of an elasto-viscoplastic fast Fourier transform (EVPFFT) model using Message Passing Interface (MPI), OpenMP, and a hybrid of MPI and OpenMP to efficiently predict micromechanical response of polycrystals. Performance studies using EVPFFT are performed based on domain decomposition over voxels of a periodic cell, which is a representative volume element (RVE) of polycrystalline copper. We begin by parallelizing the computationally intensive Newton-Raphson (NR) single crystal solver within EVPFFT. Next, we compare the performance of the serial and parallel FFTW (Fastest Fourier Transform in the West) using OpenMP (OpenMP-FFTW) and MPI (MPI-FFTW) with the original Numerical Recipes-based FOURN routine within EVPFFT. In the parallel environment, we find that the FFT calculations are best performed using the MPI version of FFTW. Finally, the remainder of the code, except read/write subroutines, is parallelized. Significant speedups of the original EVPFFT model are achieved using MPI on shared memory multicore workstations. Furthermore, results achieved on a distributed memory Cray supercomputer show promising strong and weak scalability and in some cases even super scalability for the single crystal NR solver in EVPFFT. MPI-FFTW also scales perfectly for microstructure RVEs larger than 64(3) FFT voxels. For example, the MPI-EVPFFT parallel version of the code accelerates the simulations for approximately two orders of magnitude using 64 cores over the old serial code for an RVE size of 128(3). The parallel EVPFFT code developed in this work can run massive voxel-based microstructural RVEs taking the advantages of thousands of logical cores provided by more advanced clusters.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Materials Science, Multidisciplinary

Crystal mechanics-based thermo-elastic constitutive modeling of orthorhombic uranium using generalized spherical harmonics and first-order bounding theories

Russell E. Marki, Kyle A. Brindley, Rodney J. McCabe, Marko Knezevic

Summary: This paper presents a mathematical procedure for invertible microstructure-property linkages for orthorhombic polycrystalline metals using the generalized spherical harmonics (GSH) spectral basis. The procedure allows for the computation of property closures and enables the simulation of microstructurally heterogeneous components under thermo-mechanical loadings in a computationally efficient manner. The developed framework has been demonstrated using alpha-uranium as a case study.

JOURNAL OF NUCLEAR MATERIALS (2022)

Article Astronomy & Astrophysics

Energy Transport during 3D Small-scale Reconnection Driven by Anisotropic Plasma Turbulence

Jeffersson A. Agudelo Rueda, Daniel Verscharen, Robert T. Wicks, Christopher J. Owen, Georgios Nicolaou, Kai Germaschewski, Andrew P. Walsh, Ioannis Zouganelis, Santiago Vargas Dominguez

Summary: Energy dissipation in collisionless plasmas, particularly the energy transfer and transport associated with 3D small-scale magnetic reconnection events, is still not well understood. This study investigates the spatial energy transfer during a highly dynamic and asymmetric reconnection event in anisotropic and decaying Alfvenic turbulence. The findings suggest that electron bulk flow transports thermal energy density more efficiently than kinetic energy density, and the energy density transfer is dominated by plasma compression.

ASTROPHYSICAL JOURNAL (2022)

Article Engineering, Mechanical

Crystal plasticity modeling of strain-induced martensitic transformations to predict strain rate and temperature sensitive behavior of 304 L steels: Applications to tension, compression, torsion, and impact

Zhangxi Feng, Reeju Pokharel, Sven C. Vogel, Ricardo A. Lebensohn, Darren Pagan, Eloisa Zepeda-Alarcon, Bjorn Clausen, Ramon Martinez, George T. Gray, Marko Knezevic

Summary: This paper presents crystallographically-based phase transformation models and deformation mechanism models for predicting strain-induced austenite to martensite transformation. The models can predict the strain-path sensitive, strain-rate and temperature sensitive deformation of stainless steels. The deformation of constituent grains is modeled as a combination of anisotropic elasticity, crystallographic slip, and phase transformation, while the hardening is based on the evolution of dislocation density and phase fractions. The models are calibrated and validated using experimental data and are used to simulate the deformation processes of stainless steel materials. The simulation results are compared and analyzed with experimental results in terms of geometry, mechanical response, phase fractions, and texture evolution.

INTERNATIONAL JOURNAL OF PLASTICITY (2022)

Article Materials Science, Multidisciplinary

Density functional theory-informed dislocation density hardening within crystal plasticity: Application to modeling deformation of Ni polycrystals

Adnan Eghtesad, John D. Shimanek, Shun -Li Shang, Ricardo Lebensohn, Marko Knezevic, Zi-Kui Liu, Allison M. Beese

Summary: This study successfully integrates first-principles calculations based on density functional theory (DFT) into the dislocation density hardening law of the crystal plasticity fast Fourier transform (CPFFT) model, improving the robustness of the model and reducing the uncertainties in calibrating the macroscopic flow response.

COMPUTATIONAL MATERIALS SCIENCE (2022)

Article Engineering, Multidisciplinary

An implicit FFT-based method for wave propagation in elastic heterogeneous media

R. Sancho, V. Rey-de-Pedraza, P. Lafourcade, R. A. Lebensohn, J. Segurado

Summary: An FFT-based algorithm is proposed to simulate the propagation of elastic waves in heterogeneous domains. The method incorporates the application of Dirichlet boundary conditions and uses a stable beta-Newmark approach for time discretization. By solving the equilibrium equations in Fourier space and employing a preconditioned Krylov solver, the method achieves high accuracy and computational efficiency. Numerical examples demonstrate its effectiveness in simulating wave propagation in different mediums.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2023)

Article Materials Science, Multidisciplinary

Non-local large-strain FFT-based formulation and its application to interface-dominated plasticity of nano-metallic laminates

Miroslav Zecevic, Ricardo A. Lebensohn, Laurent Capolungo

Summary: This paper presents a new formulation and numerical implementation of a strain-gradient crystal plasticity model within a large-strain elasto-viscoplastic fast Fourier transform-based micromechanical model. The model is used to study the formation of kink bands during layer-parallel compression of nano-metallic laminates. The interaction between dislocations and interfaces is considered in the model to accurately simulate the behavior of the layered composites.

JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS (2023)

Article Engineering, Mechanical

Implementation and experimental validation of nonlocal damage in a large-strain elasto-viscoplastic FFT-based framework for predicting ductile fracture in 3D polycrystalline materials

C. K. Cocke, H. Mirmohammad, M. Zecevic, B. R. Phung, R. A. Lebensohn, O. T. Kingstedt, A. D. Spear

Summary: This study extends a large-strain FFT-based crystal plasticity model to simulate ductile fracture of polycrystalline materials. By incorporating a triaxiality-based continuum damage mechanics (CDM) formulation into a large-strain elasto-viscoplastic FFT (LS-EVPFFT) framework and using an integral-based nonlocal regularization approach, the model is able to accurately predict the macroscopic stress-strain response and necking behavior of ductile polycrystals.

INTERNATIONAL JOURNAL OF PLASTICITY (2023)

Article Engineering, Multidisciplinary

The Elastic Properties of Dilute Solid Suspensions with Imperfect Interfacial Bonding: Variational Approximations Versus Full-Field Simulations

Valentin Gallican, Miroslav Zecevic, Ricardo A. Lebensohn, Martin I. Idiart

Summary: Approximations for the elastic properties of dilute solid suspensions with imperfect interfacial bonding are derived and assessed. Two approximations are generated using a variational procedure, with one dependent on an arithmetic mean and the other dependent on a harmonic mean for averaging the interfacial compliance. The harmonic approximation is found to be more accurate than the arithmetic approximation, which has practical relevance given the widespread use of the latter in existing descriptions.

JOURNAL OF ELASTICITY (2023)

Article Materials Science, Multidisciplinary

Coupled chemo-mechanical modeling of point-defect diffusion in a crystal plasticity fast Fourier transform framework

Aritra Chakraborty, Ricardo A. Lebensohn, Laurent Capolungo

Summary: At moderate-to-high temperatures and below the yield strength, the inelastic deformation of metals is mainly controlled by vacancy diffusion-mediated processes. Vacancies (or atoms) can diffuse preferentially along grain boundaries or along dislocations, resulting in climb and self-climb. The proposed thermodynamically-consistent model considers the coupling between grain boundary and grain bulk diffusion-mediated plasticity mechanisms and predicts the strain rate dependencies and steady-state creep rate scaling with respect to grain size, temperature, and stress.

JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS (2023)

Article Materials Science, Multidisciplinary

Unraveling kinking: A plasticity enhancing failure mode in high strength nano metallic laminates

Yifan Zhang, Miroslav Zecevic, Aritra Chakraborty, Rodney J. McCabe, Thomas J. Nizolek, Ricardo A. Lebensohn, John S. Carpenter, Nan Li, Laurent Capolungo

Summary: This study investigates the dependence of kinking on microstructural attributes in NMLs through in situ micropillar compression, microstructure characterization, simulations, and modeling. The development of internal stresses during loading activates local layer-parallel glide triggering kinking in NMLs. The effect of key microstructural features on kink band formation in NMLs is also revealed.

ACTA MATERIALIA (2023)

Article Engineering, Mechanical

Machine learning-enabled identification of micromechanical stress and strain hotspots predicted via dislocation density-based crystal plasticity simulations

Adnan Eghtesad, Qixiang Luo, Shun -Li Shang, Ricardo A. Lebensohn, Marko Knezevic, Zi-Kui Liu, Allison M. Beese

Summary: This study combines a full-field crystal plasticity model with a first principles-informed dislocation density hardening law and a machine learning approach to investigate the microstructural features correlated with micromechanical field localization in polycrystalline Ni. The results show that regions near grain boundaries, higher Schmid factors, low slip transmissions, and high intergranular misorientations are more prone to being micromechanical hotspots. The integration of physics-based crystal plasticity with machine learning provides insights into the initiation zones of micromechanical damage in polycrystalline metals.

INTERNATIONAL JOURNAL OF PLASTICITY (2023)

Article Chemistry, Physical

Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy

Dongil Shin, Ryan Alberdi, Ricardo A. Lebensohn, Remi Dingreville

Summary: Recent developments in micromechanics and neural networks have provided promising paths for accurately predicting the response of heterogeneous materials. The deep material network, with its multi-layer design and trained micromechanics building blocks, offers the ability to extrapolate material behavior to different constitutive laws without retraining. However, the random initialization of network parameters in current training methods leads to unavoidable errors. In this study, we propose a visualization technique using an analogous unit cell to initialize deeper networks and improve the accuracy and calibration performance, while also providing a more intuitive representation of the network for explainability.

NPJ COMPUTATIONAL MATERIALS (2023)

Article Geography, Physical

Can changes in deformation regimes be inferred from crystallographic preferred orientations in polar ice?

Maria-Gema Llorens, Albert Griera, Paul D. Bons, Ilka Weikusat, David J. Prior, Enrique Gomez-Rivas, Tamara de Riese, Ivone Jimenez-Munt, Daniel Garcia-Castellanos, Ricardo A. Lebensohn

Summary: This study investigates the influence of ice deformation history on the development of crystallographic preferred orientations (CPOs) using full-field numerical simulations. The results show that the second deformation event tends to destroy the first inherited fabric, but the transition is slow when crystallographic axes are critically oriented with respect to the second imposed regime. Therefore, caution must be exercised when interpreting observed CPOs in areas with complex deformation histories.

CRYOSPHERE (2022)

Proceedings Paper Computer Science, Artificial Intelligence

Inference and De-noising of Non-gaussian Particle Distribution Functions: A Generative Modeling Approach

John Donaghy, Kai Germaschewski

Summary: This article introduces the use of normalizing flows to learn an approximate model of the noisy particle distribution function. It balances the trade-off between computational cost and intrinsic noise, and models the distribution function that contains noise, is temporally dynamic, and can be non-Gaussian and multi-modal.

MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE (LOD 2021), PT I (2022)

暂无数据