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Metals
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Advanced Computational Modeling of Metal Transformation Processes
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Advanced Computational Modeling of Metal Transformation Processes

A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Metal Casting, Forming and Heat Treatment".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 9887

Special Issue Editor

Prof. Dr. Jean-Michel Bergheau

E-Mail Website
Guest Editor
Université de Lyon, Ecole Centrale de Lyon, CNRS, LTDS, UMR5513, ENISE, 42023 Saint Etienne, France
Interests: computational mechanics; finite element method; mechanics of materials; thermo-mechanical processes; thermal stresses; multi-physics modeling; computational manufacturing; welding
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

I would like to call your attention to this Special Issue of Metals on “Advanced Computational Modeling of Metal Transformation Processes”. The numerical simulation of metal transformation processes has been gaining increasing interest among manufacturers for several years. Numerical simulation indeed enables us to optimize the parameters of transformation processes and to predict the consequences they will induce on the fabricated parts in terms of microstructure, material properties, geometrical changes, or residual stresses, each playing an important role in the lifetime of these parts.

Metal transformation processes involve the interaction between several highly non-linear physical phenomena, the modeling and the simulation of which constitute challenges for researchers.

The objective of this Special Issue is to gather articles aimed at understanding the physical phenomena implied in metal transformation processes using numerical simulation techniques. All types of processes are targeted, including the following:

  • Fusion manufacturing: additive manufacturing, casting, sintering;
  • Metal forming: forging, stamping, rolling;
  • Material removal: turning, grinding, drilling;
  • Joining: welding, riveting, bonding;
  • Heat and surface treatments: quenching, surface hardening, shot peening, carburizing, nitriding.

Topics of interest include, but are not limited to, the following:

  • New modeling capabilities;
  • Material behavior modeling;
  • Material characterization;
  • Advanced computational methods or simulation methodologies;
  • Combined experimental and numerical studies;
  • Numerical simulation of chaining of processes;
  • Prediction of the final state of the fabricated part in connection with lifetime analysis.

Prof. Dr. Jean-Michel Bergheau
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Computational methods
  • Constitutive models
  • Material characterization
  • Multiphysics couplings
  • Additive manufacturing
  • Metal forming
  • Machining
  • Joining
  • Surface treatment
  • Chaining of processes

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Published Papers (3 papers)

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Research

21 pages, 2600 KiB  
Article
Data-Driven Modeling for Multiphysics Parametrized Problems-Application to Induction Hardening Process
by Khouloud Derouiche, Sevan Garois, Victor Champaney, Monzer Daoud, Khalil Traidi and Francisco Chinesta
Metals 2021, 11(5), 738; https://doi.org/10.3390/met11050738 - 29 Apr 2021
Cited by 15 | Viewed by 2542
Abstract
Data-driven modeling provides an efficient approach to compute approximate solutions for complex multiphysics parametrized problems such as induction hardening (IH) process. Basically, some physical quantities of interest (QoI) related to the IH process will be evaluated under real-time constraint, without any explicit knowledge [...] Read more.
Data-driven modeling provides an efficient approach to compute approximate solutions for complex multiphysics parametrized problems such as induction hardening (IH) process. Basically, some physical quantities of interest (QoI) related to the IH process will be evaluated under real-time constraint, without any explicit knowledge of the physical behavior of the system. Hence, computationally expensive finite element models will be replaced by a parametric solution, called metamodel. Two data-driven models for temporal evolution of temperature and austenite phase transformation, during induction heating, were first developed by using the proper orthogonal decomposition based reduced-order model followed by a nonlinear regression method for temperature field and a classification combined with regression for austenite evolution. Then, data-driven and hybrid models were created to predict hardness, after quenching. It is shown that the results of artificial intelligence models are promising and provide good approximations in the low-data limit case. Full article
(This article belongs to the Special Issue Advanced Computational Modeling of Metal Transformation Processes)
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18 pages, 2554 KiB  
Article
Grouping Methods of Cluster Dynamics Model for Precipitation Kinetics
by Kun Xu, Brian G. Thomas, Yueyue Wu, Haichuan Wang, Hui Kong and Zhaoyang Wu
Metals 2020, 10(12), 1685; https://doi.org/10.3390/met10121685 - 16 Dec 2020
Cited by 1 | Viewed by 3116
Abstract
Due to its simplicity and efficiency, cluster dynamics modeling has been widely used to simulate microstructure evolution in materials, such as defect formation in metals. However, its computation cost becomes prohibitive when the clusters grow too large, so a particle-size-grouping method is often [...] Read more.
Due to its simplicity and efficiency, cluster dynamics modeling has been widely used to simulate microstructure evolution in materials, such as defect formation in metals. However, its computation cost becomes prohibitive when the clusters grow too large, so a particle-size-grouping method is often required. In this paper, three different size-grouping methods are compared with the exact solution of the ungrouped cluster dynamics model for Al3Sc precipitation in an Al-0.18 at.% Sc alloy. A new assumption of logarithmically-linear distribution of cluster number densities inside each size group is shown to be the most efficient way to match with all results of the ungrouped model. Finally, the calculated results are compared with the measured sizes and distributions of Al3Sc precipitates at different aging temperatures. The new size-grouping method is shown to have better accuracy for the chosen discretization and time-stepping method evaluated. This will enable significant computational savings, and the extension of time scales and cluster sizes to the ranges of realistic metallurgical systems, while preserving reasonable accuracy. Full article
(This article belongs to the Special Issue Advanced Computational Modeling of Metal Transformation Processes)
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18 pages, 3889 KiB  
Article
A New Nodal-Integration-Based Finite Element Method for the Numerical Simulation of Welding Processes
by Yabo Jia, Jean-Michel Bergheau, Jean-Baptiste Leblond, Jean-Christophe Roux, Raihane Bouchaoui, Sebastien Gallée and Alexandre Brosse
Metals 2020, 10(10), 1386; https://doi.org/10.3390/met10101386 - 17 Oct 2020
Cited by 11 | Viewed by 3416
Abstract
This paper aims at introducing a new nodal-integration-based finite element method for the numerical calculation of residual stresses induced by welding processes. The main advantage of the proposed method is to be based on first-order tetrahedral meshes, thus greatly facilitating the meshing of [...] Read more.
This paper aims at introducing a new nodal-integration-based finite element method for the numerical calculation of residual stresses induced by welding processes. The main advantage of the proposed method is to be based on first-order tetrahedral meshes, thus greatly facilitating the meshing of complex geometries using currently available meshing tools. In addition, the formulation of the problem avoids any locking phenomena arising from the plastic incompressibility associated with von Mises plasticity and currently encountered with standard 4-node tetrahedral elements. The numerical results generated by the nodal approach are compared to those obtained with more classical simulations using finite elements based on mixed displacement–pressure formulations: 8-node Q1P0 hexahedra (linear displacement, constant pressure) and 4-node P1P1 tetrahedra (linear displacement, linear pressure). The comparisons evidence the efficiency of the nodal approach for the simulation of complex thermal–elastic–plastic problems. Full article
(This article belongs to the Special Issue Advanced Computational Modeling of Metal Transformation Processes)
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