A new ANN based crystal plasticity model for FCC materials and its application to non-monotonic strain paths

Ibragimova, Olga; Brahme, Abhijit; Muhammad, Waqas; Lévesque, Julie; Inal, Kaan

doi:10.1016/j.ijplas.2021.103059

Cited by 71 publications

(15 citation statements)

References 73 publications

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“…Several recent studies using this method reported a significant reduction in computational cost compared to conventional multiscale models. [240][241][242][243] Ibragimova et al developed an ensemble of feed-forward neural networks by combining machine learning and CP models to predict the mechanical response and texture evolution of fcc crystals under a non-monotonic strain path. [242] The calculation speed is improved by 99.9% compared to CP model and the errors of stress-strain data and texture are within 10 MPa and 1°, respectively.…”

Section: Data-driven Integrated Computational Materials Engineeringmentioning

confidence: 99%

Integrated Computational Materials Engineering for Advanced Automotive Technology: With Focus on Life Cycle of Automotive Body Structure

Park

Min

Kim

et al. 2022

Adv Materials Technologies

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Integrated computational materials engineering (ICME) is a simulation‐driven design approach that employs multiscale‐multiphysics modeling and is based on the understanding of process–structure–property–performance relationships. The ICME approach has attracted considerable attention in the automotive industry, considering that it significantly reduces development cost and time in optimization of materials and processes through computational advancement. This study presents a comprehensive review of ICME activities in advanced automotive manufacturing technology, which focuses on the life cycle of the automotive body structure such as structural material design, manufacturing process optimization, and reliability improvement in service quality. Results show that the ICME approach has been widely implemented in automotive manufacturing processes, from development of lightweight materials to performance management. However, further advances and technological strategies should be sought to develop more robust methodologies that can replace conventional experiment‐based design approaches.

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Section: Data-driven Integrated Computational Materials Engineeringmentioning

confidence: 99%

Integrated Computational Materials Engineering for Advanced Automotive Technology: With Focus on Life Cycle of Automotive Body Structure

Park

Min

Kim

et al. 2022

Adv Materials Technologies

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“…Unlike the phenomenological constitutive theory and multiscale modelling, data-driven models do not require parameter calibration and phenomenological assumptions, neither do they request unaffordable computational resources to infer stress responses from strain paths. Although it is not new to apply neural networks to model the stress-strain relations of concrete and sands (Ellis et al, 1995;Ghaboussi et al, 1991;Ghaboussi and Sidarta, 1998), the revolutionary development of deep learning over recent years re-inspires extensive explorations in data-driven constitutive models (Guan et al, 2023;Ibragimova et al, 2022;Ibragimova et al, 2021;Jordan et al, 2020;Tancogne-Dejean et al, 2021). For example, and developed reinforcement learning and game theory-based deep learning models for the constitutive modelling of granular materials.…”

Section: Introductionmentioning

confidence: 99%

Deep active learning for constitutive modelling of granular materials: From representative volume elements to implicit finite element modelling

Guan

Feng

et al. 2023

International Journal of Plasticity

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“…The fully implicit integration procedure for a twinning-induced plasticity model based on the CP approach is also presented by Khan et al (2022). The propositions of other new models using the CP theory in order to simulate the behaviour of material in a microscopic scale are also available in literature (Li et al, 2022;Ibragimova et al, 2021;Li et al, 2020;Jeong & Voyiadjis, 2022).…”

Section: Introductionmentioning

confidence: 99%

Crystal Plasticity Elastic-Plastic Rate-Independent Numerical Analyses of Pollycrystalline Materials

Wójcik

Skrzat

Stachowicz

et al. 2023

AMME

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Macroscopic analyses of plastic forming processes give only the overall description of the problem without the consideration of mechanisms of plastic deformation and the microstructure evolution. For the consideration of these processes, numerical simulations within crystal plasticity include the change of texture, anisotropy, and strain hardening of the material are used. In this paper, a crystal plasticity rate-independent model proposed by Anand and Kothari is applied for numerical analyses of polycrystalline materials. The slip was considered as the main mechanism of the plastic deformation. Basic constitutive equations of crystal plasticity for large deformation theories are presented. The selected results of elastic-plastic problems obtained using both macro- and micro- scales software for the explicit and implicit integration are featured here. The heterogeneous distribution of strain and stress in different grains are obtained, which is associated with the various crystal orientation. The crystal plasticity modelling of materials subject to plastic deformation involves not only the information about the change of a material’s shape in a macro-scale, but also describes the phenomena occurring in material in a micro-scale.

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A new ANN based crystal plasticity model for FCC materials and its application to non-monotonic strain paths

Cited by 71 publications

References 73 publications

Integrated Computational Materials Engineering for Advanced Automotive Technology: With Focus on Life Cycle of Automotive Body Structure

Integrated Computational Materials Engineering for Advanced Automotive Technology: With Focus on Life Cycle of Automotive Body Structure

Deep active learning for constitutive modelling of granular materials: From representative volume elements to implicit finite element modelling

Crystal Plasticity Elastic-Plastic Rate-Independent Numerical Analyses of Pollycrystalline Materials

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