The Experts below are selected from a list of 45 Experts worldwide ranked by ideXlab platform
Fei Chen - One of the best experts on this subject based on the ideXlab platform.
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modeling the dynamic recrystallization in austenitic stainless steel using cellular automaton method
Computational Materials Science, 2014Co-Authors: Fei Chen, Zhenshan Cui, Xinmin LaiAbstract:Abstract The paper presents a two-dimensional CA approach for quantitative and topographic prediction of the microstructure evolution of 316LN austenitic stainless steel during hot deformation. To describe the effect of deformation on grain topology more accurately, an updated topology deformation technique was used in the built model, in which a cellular Coordinate System and a Material Coordinate System were established separately. The cellular Coordinate System remains unchangeable in the whole simulation; the Material Coordinate System and the corresponding grain boundary shape change with deformation. The grain topography, recrystallization fraction and average grain size were also obtained. The simulated results agree well with the experimental data in terms of average grain size and flow stress, suggesting that the developed CA model is a reliable numerical approach for predicting microstructure evolution during dynamic recrystallization (DRX) for the 316LN steel.
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mesoscale simulation of the high temperature austenitizing and dynamic recrystallization by coupling a cellular automaton with a topology deformation technique
Materials Science and Engineering A-structural Materials Properties Microstructure and Processing, 2010Co-Authors: Fei Chen, Zhenshan Cui, Juan Liu, Wen Chen, Shijia ChenAbstract:This paper reports on work in developing a cellular automaton (CA) model coupling with a topology deformation technique to simulate the microstructural evolution of 30Cr2Ni4MoV rotor steel during the high-temperature austenitizing and dynamic recrystallization (DRX). The state transition rules for simulating the normal grain growth was established based on the curvature-driven mechanism, thermodynamic driving mechanism and established based on the curvature-driven mechanism, thermodynamic driving mechanism and the lowest energy principle. To describe the compression effect on the topology of grain deformation more accurately, the update topology deformation model was proposed in which a cellular Coordinate System and a Material Coordinate System were established separately. The cellular Coordinate System remains unchangeable, but the Material Coordinate System and the corresponding grain boundary shape will change with deformation in the update topology deformation model. The effects of a wide range of thermomechanical parameters (e.g., temperature and strain rate) on the DRX kinetics and mean grain size were investigated. It was found that increasing the temperature and/or decreasing the strain rate can reduce the incubation period, and decreasing the temperature and/or increasing the strain rate can refine the DRX grain size. The simulation results are validated by comparing the experimental results.
W. Brocks - One of the best experts on this subject based on the ideXlab platform.
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On a finite strain viscoplastic theory based on a new internal dissipation inequality
International Journal of Plasticity, 2004Co-Authors: R.c. Lin, W. BrocksAbstract:Abstract This work is focused on the theoretical development and numerical implementation of a viscoplastic law. According to the second law of thermodynamics a dissipation inequality described in the rotated Material Coordinate System is developed. Based on this dissipation inequality and the principle of maximum dissipation a finite strain viscoplastic model described also in the rotated Material Coordinate System is formulated. The evolution equations are expressed in terms of the Material time derivatives of the rotated elastic logarithmic strain, the accumulated plastic strain and the strain-like tensor conjugate to the rotated back stress. The mathematical structure of this theory is concise and similar to that of the infinitesimal viscoplastic theory. These characteristics make the numerical implementation of this theory easy. The stress integration algorithm and the algorithmic tangent moduli for the infinitesimal theory can be applied to the numerical implementation of the present finite strain theory with a little reformulation. The complicated algorithmic formulations for most of other finite plastic laws can be therefore circumvented. In order to check the effectivity of the present finite strain theory a set of numerical examples under strict deformation conditions are presented. These numerical examples prove the excellent performance of the present viscoplastic Material law at describing the finite strain elastoplastic and viscoplastic problems.
Zhenshan Cui - One of the best experts on this subject based on the ideXlab platform.
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modeling the dynamic recrystallization in austenitic stainless steel using cellular automaton method
Computational Materials Science, 2014Co-Authors: Fei Chen, Zhenshan Cui, Xinmin LaiAbstract:Abstract The paper presents a two-dimensional CA approach for quantitative and topographic prediction of the microstructure evolution of 316LN austenitic stainless steel during hot deformation. To describe the effect of deformation on grain topology more accurately, an updated topology deformation technique was used in the built model, in which a cellular Coordinate System and a Material Coordinate System were established separately. The cellular Coordinate System remains unchangeable in the whole simulation; the Material Coordinate System and the corresponding grain boundary shape change with deformation. The grain topography, recrystallization fraction and average grain size were also obtained. The simulated results agree well with the experimental data in terms of average grain size and flow stress, suggesting that the developed CA model is a reliable numerical approach for predicting microstructure evolution during dynamic recrystallization (DRX) for the 316LN steel.
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mesoscale simulation of the high temperature austenitizing and dynamic recrystallization by coupling a cellular automaton with a topology deformation technique
Materials Science and Engineering A-structural Materials Properties Microstructure and Processing, 2010Co-Authors: Fei Chen, Zhenshan Cui, Juan Liu, Wen Chen, Shijia ChenAbstract:This paper reports on work in developing a cellular automaton (CA) model coupling with a topology deformation technique to simulate the microstructural evolution of 30Cr2Ni4MoV rotor steel during the high-temperature austenitizing and dynamic recrystallization (DRX). The state transition rules for simulating the normal grain growth was established based on the curvature-driven mechanism, thermodynamic driving mechanism and established based on the curvature-driven mechanism, thermodynamic driving mechanism and the lowest energy principle. To describe the compression effect on the topology of grain deformation more accurately, the update topology deformation model was proposed in which a cellular Coordinate System and a Material Coordinate System were established separately. The cellular Coordinate System remains unchangeable, but the Material Coordinate System and the corresponding grain boundary shape will change with deformation in the update topology deformation model. The effects of a wide range of thermomechanical parameters (e.g., temperature and strain rate) on the DRX kinetics and mean grain size were investigated. It was found that increasing the temperature and/or decreasing the strain rate can reduce the incubation period, and decreasing the temperature and/or increasing the strain rate can refine the DRX grain size. The simulation results are validated by comparing the experimental results.
Ichsani Wheeler - One of the best experts on this subject based on the ideXlab platform.
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digital mapping of soil carbon
Advances in Agronomy, 2013Co-Authors: Budiman Minasny, Alex B Mcbratney, Brendan P Malone, Ichsani WheelerAbstract:There is a global demand for soil data and information for food security and global environmental management. There is also great interest in recognizing the soil System as a significant terrestrial sink of carbon. The reliable assessment of soil carbon (C) stocks is of key importance for soil conservation and in mitigation strategies for increased atmospheric carbon. In this article, we review and discuss the recent advances in digital mapping of soil C. The challenge to map carbon is demonstrated with the large variation of soil C concentration at a field, continental, and global scale. This article reviews recent studies in mapping soil C using digital soil mapping approaches. The general activities in digital soil mapping involve collection of a database of soil carbon observations over the area of interest; compilation of relevant covariates (scorpan factors) for the area; calibration or training of a spatial prediction function based on the observed dataset; interpolation and/or extrapolation of the prediction function over the whole area; and finally validation using existing or independent datasets. We discuss several relevant aspects in digital mapping: carbon concentration and carbon density, source of data, sampling density and resolution, depth of investigation, map validation, map uncertainty, and environmental covariates. We demonstrate harmonization of soil depths using the equal-area spline and the use of a Material Coordinate System to take into consideration the varying bulk density due to management practices. Soil C mapping has evolved from 2-D mapping of soil C stock at particular depth ranges to a semi-3-D soil map allowing the estimation of continuous soil C concentration or density with depth. This review then discusses the dynamics of soil C and the consequences for prediction and mapping of soil C change. Finally, we illustrate the prediction of soil carbon change using a semidynamic scorpan approach.
Xinmin Lai - One of the best experts on this subject based on the ideXlab platform.
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modeling the dynamic recrystallization in austenitic stainless steel using cellular automaton method
Computational Materials Science, 2014Co-Authors: Fei Chen, Zhenshan Cui, Xinmin LaiAbstract:Abstract The paper presents a two-dimensional CA approach for quantitative and topographic prediction of the microstructure evolution of 316LN austenitic stainless steel during hot deformation. To describe the effect of deformation on grain topology more accurately, an updated topology deformation technique was used in the built model, in which a cellular Coordinate System and a Material Coordinate System were established separately. The cellular Coordinate System remains unchangeable in the whole simulation; the Material Coordinate System and the corresponding grain boundary shape change with deformation. The grain topography, recrystallization fraction and average grain size were also obtained. The simulated results agree well with the experimental data in terms of average grain size and flow stress, suggesting that the developed CA model is a reliable numerical approach for predicting microstructure evolution during dynamic recrystallization (DRX) for the 316LN steel.