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Special Issue "Modeling and Simulation of Solid State Phenomena in Metals and Alloys"

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A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Materials Simulation and Design".

Deadline for manuscript submissions: 20 July 2024 | Viewed by 2887

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Prof. Dr. Marc Bernacki

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CEMEF - MINES ParisTech, 06904 Sophia Antipolis, France
Interests: multiscale modeling; numerical methods; numerical metallurgy
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Dear Collesgues,

The mechanical and functional properties of metals are strongly related to their microstructures, which are, themselves, inherited from thermal and mechanical processing. Thus, the precise numerical modeling of metallic materials is an important topic, largely due to the interest in using predictive simulations of material behavior to facilitate the development of new materials, as well as the academic interest in such strategies to improve our understanding of metallurgical phenomena. In recent decades, several discretization/resolution-based numerical methods have been developed to model solid-state phenomena that occur during thermomechanical treatments of metallic materials under the concepts of computational metallurgy, digital materials, digital shadows and digital twins. Metallurgical mechanisms include: recrystallization, grain growth, recovery, ductile damage, fracture, martensitic transformations, solid/solid diffusive phase transformations and, more globally surface and volume diffusion mechanisms; the latter lead to precipitation, precipitate coalescence, spheroidization, Ostwald ripening, powder consolidation and densification in powder metallurgy. This Special Issue is dedicated to the illustration of recent works in this discipline.

Prof. Dr. Marc Bernacki
Guest Editor

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Keywords

modeling
metallic materials
solid-state phenomena
digital materials
computational metallurgy

Published Papers (4 papers)

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Research

24 pages, 8416 KiB

Open AccessArticle

Comparison of Grain-Growth Mean-Field Models Regarding Predicted Grain Size Distributions

and

Materials 2023, 16(20), 6761; https://doi.org/10.3390/ma16206761 - 19 Oct 2023

Viewed by 382

Abstract

Mean-field models have the ability to predict the evolution of grain size distribution that occurs through thermomechanical solicitations. This article focuses on a comparison of mean-field models under grain-growth conditions. Different microstructure representations are considered and discussed, especially regarding the consideration of topology in the neighborhood construction. Experimental data obtained with a heat treatment campaign on 316L austenitic stainless steel are used for the identification of material parameters and as a reference for model comparisons. Mean-field models are also applied to both mono- and bimodal initial grain size distributions to investigate the potential benefits of introducing neighborhood topology in microstructure prediction models. This article demonstrates that improvements in the predictions can be obtained in monomodal cases for topological models. In the bimodal test, no comparison with experimental data was performed as no data were available. But relative comparisons between models indicated few differences in the predictions. Although of interest, the consideration of neighborhood topology in grain-growth mean-field models generally results in only small improvements compared to classical mean-field models, especially in terms of implementation complexity. Full article

(This article belongs to the Special Issue Modeling and Simulation of Solid State Phenomena in Metals and Alloys)

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13 pages, 2552 KiB

Open AccessArticle

Optimization of Johnson–Cook Constitutive Model Parameters Using the Nesterov Gradient-Descent Method

Sergey A. Zelepugin

Roman O. Cherepanov

and

Nadezhda V. Pakhnutova

Materials 2023, 16(15), 5452; https://doi.org/10.3390/ma16155452 - 03 Aug 2023

Viewed by 478

Abstract

Numerical simulation of impact and shock-wave interactions of deformable solids is an urgent problem. The key to the adequacy and accuracy of simulation is the material model that links the yield strength with accumulated plastic strain, strain rate, and temperature. A material model often used in engineering applications is the empirical Johnson–Cook (JC) model. However, an increase in the impact velocity complicates the choice of the model constants to reach agreement between numerical and experimental data. This paper presents a method for the selection of the JC model constants using an optimization algorithm based on the Nesterov gradient-descent method. A solution quality function is proposed to estimate the deviation of calculations from experimental data and to determine the optimum JC model parameters. Numerical calculations of the Taylor rod-on-anvil impact test were performed for cylindrical copper specimens. The numerical simulation performed with the optimized JC model parameters was in good agreement with the experimental data received by the authors of this paper and with the literature data. The accuracy of simulation depends on the experimental data used. For all considered experiments, the calculation accuracy (solution quality) increased by 10%. This method, developed for selecting optimized material model constants, may be useful for other models, regardless of the numerical code used for high-velocity impact simulations. Full article

(This article belongs to the Special Issue Modeling and Simulation of Solid State Phenomena in Metals and Alloys)

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12 pages, 2605 KiB

Open AccessArticle

Model of a 3D Magnetic Permeability Tensor Considering Rotation and Saturation States in Materials with Axial Anisotropy

Dominika Kopala

Anna Ostaszewska-Liżewska

Peter Råback

and

Roman Szewczyk

Materials 2023, 16(9), 3477; https://doi.org/10.3390/ma16093477 - 29 Apr 2023

Viewed by 994

Abstract

The paper proposes a 3D extension of the linear tensor model of magnetic permeability for axially anisotropic materials. In the proposed model, all phases of a magnetization process are considered: linear magnetization, magnetization rotation, and magnetic saturation. The model of the magnetization rotation process is based on the analyses of both anisotropic energy and magnetostatic energy, which directly connect the proposed description with physical phenomena occurring during a magnetization process. The proposed model was validated on the base of previously presented experimental characteristics. The presented extension of the tensor description of magnetic permeability enables the modelling of inductive devices with cores made of anisotropic magnetic materials and the modelling of magnetic cores subjected to mechanical stresses. It is especially suitable for finite element modelling of the devices working in a magnetic saturation state, such as fluxgate sensors. Full article

(This article belongs to the Special Issue Modeling and Simulation of Solid State Phenomena in Metals and Alloys)

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21 pages, 4284 KiB

Open AccessArticle

A Comparative Study of Deterministic and Stochastic Models of Microstructure Evolution during Multi-Step Hot Deformation of Steels

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Materials 2023, 16(9), 3316; https://doi.org/10.3390/ma16093316 - 23 Apr 2023

Viewed by 679

Abstract

Modern construction materials, including steels, have to combine strength with good formability. In metallic materials, these features are obtained for heterogeneous multiphase microstructures. Design of such microstructures requires advanced numerical models. It has been shown in our earlier works that models based on stochastic internal variables meet this requirement. The focus of the present paper is on deterministic and stochastic approaches to modelling hot deformation of multiphase steels. The main aim was to survey recent advances in describing the evolution of dislocations and grain size accounting for the stochastic character of the recrystallization. To present a path leading to this objective, we reviewed several papers dedicated to the application of internal variables and statistical approaches to modelling recrystallization. Following this, the idea of the model with dislocation density and grain size being the stochastic internal variables is described. Experiments composed of hot compression of cylindrical samples are also included for better presentation of the utility of this approach. Firstly, an empirical data describing the loads as a function of time during compression and data needed to create histograms of the austenite grain size after the tests were collected. Using the measured data, identification and validation of the models were performed. To present possible applications of the model, it was used to produce a simulation imitating industrial hot-forming processes. Finally, calculations of the dislocation density and the grain size distribution were utilized as inputs in simulations of phase transformations during cooling. Distributions of the ferrite volume fraction and the ferrite grain size after cooling recapitulate the paper. This should give readers good overview on the application of collected equations in practice. Full article

(This article belongs to the Special Issue Modeling and Simulation of Solid State Phenomena in Metals and Alloys)

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Special Issue "Modeling and Simulation of Solid State Phenomena in Metals and Alloys"

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