A new micromechanics based full field numerical framework to simulate the effects of dynamic recrystallization on the formability of HCP metals

Nagra, Jaspreet Singh; Brahme, Abhijit; Lévesque, Julie; Mishra, Raja K.; Lebensohn, Ricardo A.; Inal, Kaan

doi:10.1016/j.ijplas.2019.09.011

Cited by 37 publications

(11 citation statements)

References 70 publications

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“…In coupled crystal plasticity (CP) -cellular automata (CA) approaches the grain-scale plastic deformation behavior is predicted by crystal plasticity simulations either using a grid based finiteelement solver [313], [314], [322], [323] or a voxel-based fast Fourier transformation solver [312], [324], [325]. In this approach the results from a (generally) coarser grid CP simulations are first interpolated into a finer and regularly spaced cellular automata grid where the conditions of nucleation and grain growth during the recrystallization process is evaluated.…”

Section: Modeling Recrystallizationmentioning

confidence: 99%

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

Nicolas

Chakraborty

Paulson

et al. 2020

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This report summarizes the current state of modeling and simulation methods for predicting the initial structure and properties of material in components assembled using advanced manufacturing technologies (AMTs). The report is the first volume in a two-volume series. This first volume focuses on predicting initial microstructures of AM material. The second volume discusses predicting material properties given the initial microstructure. The focus is on technologies of particular relevance to the design and manufacture of nuclear reactor components. The purpose of the report is to help develop the technical knowledge base to support regulatory decisions that will be needed to assess nuclear components manufactured with AMTs as these components are installed at nuclear power plants (NPPs). The report develops a list of AMTs of particular interest to the NRC and summarizes the key microstructural features and corresponding processing parameters relevant to each technology. Further sections describe available physically-based and data-driven prediction methods and survey widely available software tools. The report concludes with a summary of gaps that may be of particular interest to the NRC when evaluating modeling and simulation methods for AMTs. v

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Section: Modeling Recrystallizationmentioning

confidence: 99%

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

Nicolas

Chakraborty

Paulson

et al. 2020

View full text Add to dashboard Cite

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“…Recently, this approach was further improved by Zhang et al (2020), who modeled the thermal interface grooving and deformation anisotropy of titanium alloys with a lamellar colony by a combination of the Monte Carlo (MC) methodand CPFEM. Lately, Nagra et al (2020) creatively improved the rate-tangent-crystal plasticity-fast Fourier transform framework proposed by Nagra et al (2017Nagra et al ( , 2018 to model the DRX behavior of hexagonal closed-packed (HCP) AZ31 alloys and further investigated the formability of the alloys by coupling the M-K approach with the CA method. The improved numerical framework has the advantage of quantifying the intrinsic characteristics, including macro stress, strain, twining volume fraction, micromechanical fields, texture evolution, and local dislocation density of HCP alloys.…”

Section: Introductionmentioning

confidence: 99%

Multiscale modeling of discontinuous dynamic recrystallization during hot working by coupling multilevel cellular automaton and finite element method

Chen

Zhu

Chen³

et al. 2021

International Journal of Plasticity

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“…Because the deformation temperature, strain, and strain rate affect the microstructure evolution of the material, several studies have focused on how the deformation temperature and strain rate affect DRX behavior, [22][23][24] and the DRX model was established based on the above factor. [25][26][27] However, few studies have investigated the deformation state, mainly focusing on whether the strain reaches the critical strain of DRX. Although extensive research has been carried out on hot processing mapping, model correction, stress-strain curve correction, and metadynamics, no single study adequately covers the relationships between the deformation parameters, power dissipation efficiency, microstructure, and DRX mechanism for the purposes of investigating DRX behavior during the flexible rolling process.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Recrystallization Behavior of Low‐Carbon Steel during the Flexible Rolling Process: Modeling and Characterization

Liu

Mapelli

Peng

et al. 2021

steel research int.

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Dynamic recrystallization (DRX) is the predominant softening mechanism under high‐temperature large‐plastic deformation and determines the microstructure evolution of steel. Herein, an equivalent substitution method is proposed to investigate the coupling effect of deformation conditions on microstructural evolution during the flexible rolling process. Low‐carbon steel is compressed using a Gleeble 3800‐GTC thermal–mechanical physical simulation system at temperatures ranging from 900 to 1100 °C and strain rates ranging from 0.01 to 10 s−1. The flow stress behaviors under different deformation conditions are discussed. Accordingly, the relationship between strain rate and temperature is established using the Zener–Hollomon equation. Further, a new DRX model is proposed by combining the theoretical implications of previous models. The effectiveness of the experimental model and predicted model is statistically evaluated to accurately determine the DRX volume fraction of the experimental steel. Based on the dynamic material model, a hot processing map of the experimental steel is also developed to evaluate the steel's hot workability. Finally, the microstructure of the experimental steel is analyzed under specific deformation parameters. The results demonstrate that DRX behavior decreases as the upper roller is raised and the lower roller is lowered during the flexible rolling process.

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A new micromechanics based full field numerical framework to simulate the effects of dynamic recrystallization on the formability of HCP metals

Cited by 37 publications

References 70 publications

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

Multiscale modeling of discontinuous dynamic recrystallization during hot working by coupling multilevel cellular automaton and finite element method

Dynamic Recrystallization Behavior of Low‐Carbon Steel during the Flexible Rolling Process: Modeling and Characterization

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