Computational Plasticity

A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Computation and Simulation on Metals".

Deadline for manuscript submissions: closed (1 March 2024) | Viewed by 3912

Special Issue Editors


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Guest Editor
Department of Civil and Environmental Engineering, Technical University of Catalonia, UPC BarcelonaTech, 08034 Barcelona, Spain
Interests: computational mechanics; computational plasticity; contact mechanics; coupled thermomechanical problems; finite element method
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Guest Editor
Department of Civil and Environmental Engineering, Technical University of Catalonia, UPC BarcelonaTech, 08034 Barcelona, Spain
Interests: computational mechanics; finite element method; computational plasticity; coupled thermomechanical problems

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Guest Editor
School of Aerospace, Civil, Electrical, General Engineering and Mechanical Engineering, Swansea University, Singleton Park, Swansea SA2 8PP, UK
Interests: computational methods in solid; structural and fluid mechanics; computational modelling of material behaviour; multiscale modelling of materials and structures; fluid-structure interaction; free surface and interface flows; adaptive solution strategies for non-linear problems

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Guest Editor
School of Aerospace, Civil, Electrical, General Engineering and Mechanical Engineering, Swansea University, Singleton Park, Swansea SA2 8PP, UK
Interests: multi-scale modelling of solids; computational homogenisation methods; modelling and simulation of biological tissues; modelling of polycrystalline metals; topological derivative; microstrucural optimisation

Special Issue Information

Dear Colleagues,

This Special Issue will collect a number of full-length versions of selected papers, in line with the Metals journal topics, presented at the International Conference on Computational Plasticity, COMPLAS 2023, which will be held in Barcelona, Spain, on 5–7 September, 2023.

Topics of interest for this Special Issue and addressed in COMPLAS 2023 include the following:

  • Advanced discretization techniques;
  • Advanced material models and computational material design;
  • Atomistic, nano and micro-mechanics of materials;
  • Big data analytics techniques;
  • Contact mechanics;
  • Damage, fracture, fatigue and failure mechanics;
  • Data-driven modeling in science and engineering;
  • Data science, machine learning and artificial intelligence;
  • High-performance computing;
  • Industrial applications in science and engineering;
  • Inverse problems, optimization and design;
  • Manufacturing and material forming processes;
  • Model reduction and real-time computing techniques;
  • Multi-body and nonlinear dynamics;
  • Multi-scale material models and multi-physics problems;
  • Numerical methods in science and engineering.

Participants of COMPLAS 2023 are encouraged to submit their contributions to this Special Issue of the open access journal Metals.

A special 30% discount on the article-processing charge (APC) has been offered by Metals to the participants of COMPLAS 2023 who are willing to publish their full-length paper in this Special Issue.

We are looking forward to welcoming you in COMPLAS 2023 and receiving your contributions to this Special Issue.

Prof. Dr. Carlos Agelet de Saracibar
Prof. Dr. Michele Chiumenti
Prof. Dr. Djordje Peric
Prof. Dr. Eduardo De Souza Neto
Guest Editors

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.

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Published Papers (3 papers)

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Research

16 pages, 5826 KiB  
Article
Modular Finite Element Modeling of Heavy Plate Rolling Processes Using Customized Model Reduction Approaches
by Andreas W. Nemetz, Erik Parteder, Paula Reimer, Thomas Kaltenbrunner, Bodo Heise, Jagoba Lekue, Thomas Gross, Stefan Falkner, Rupert Egger and Klaus Zeman
Metals 2024, 14(4), 444; https://doi.org/10.3390/met14040444 - 11 Apr 2024
Viewed by 833
Abstract
Heavy plates are indispensable semi-finished products. Quality is strongly linked with production, so the rolling process must be performed within well-defined narrow tolerances. To meet this challenge, adequate modeling has become a necessity. In contrast to continuous strip rolling, where the workpiece can [...] Read more.
Heavy plates are indispensable semi-finished products. Quality is strongly linked with production, so the rolling process must be performed within well-defined narrow tolerances. To meet this challenge, adequate modeling has become a necessity. In contrast to continuous strip rolling, where the workpiece can be modeled as a semi-infinite strip and 2D modeling can be argued quite well, this strategy is insufficient for the comprehensive modeling of heavy plate rolling. The geometry of the heavy plate favors an inhomogeneous distribution of relevant state variables, such as temperature. In addition, if the process involves longitudinal and spreading passes, the required plate rotation spoils the assumption of a symmetric arrangement that might have been acceptable before rotation. Consequently, the derivation of suitably reduced models is not trivial, and modeling tailored to the specific objective of investigation is of utmost importance. Models intended to resolve the evolution of inhomogeneities in the field variables are demanding and computationally expensive. An effective modular modeling strategy was developed for such models to be used offline. Mutually complementing and interchangeable modules may constitute an efficient modeling strategy valid for the specific subject of interest. The presented approach reduces the enormous cost of complete 3D simulation as much as the model purpose allows for. Full article
(This article belongs to the Special Issue Computational Plasticity)
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15 pages, 4301 KiB  
Article
Impact of Boundary Parameters Accuracy on Modeling of Directed Energy Deposition Thermal Field
by Calogero Gallo, Laurent Duchêne, Thinh Quy Duc Pham, Ruben Jardin, Víctor Tuninetti and Anne-Marie Habraken
Metals 2024, 14(2), 173; https://doi.org/10.3390/met14020173 - 30 Jan 2024
Viewed by 1076
Abstract
Within the large Additive Manufacturing (AM) process family, Directed Energy Deposition (DED) can be used to create low-cost prototypes and coatings, or to repair cracks. In the case of M4 HSS (High Speed Steel), a reliable computed temperature field during DED process allows [...] Read more.
Within the large Additive Manufacturing (AM) process family, Directed Energy Deposition (DED) can be used to create low-cost prototypes and coatings, or to repair cracks. In the case of M4 HSS (High Speed Steel), a reliable computed temperature field during DED process allows the optimization of the substrate preheating temperature value and other process parameters. Such optimization is required to avoid failure during the process, as well as high residual stresses. If 3D DED simulations provide accurate thermal fields, they also induce huge computation time, which motivates simplifications. This article uses a 2D Finite Element (FE) model that decreases the computation cost through dividing the CPU time by around 100 in our studied case, but it needs some calibrations. As described, the identification of a correct data set solely based on local temperature measurements can lead to various sets of parameters with variations of up to 100%. In this study, the melt pool depth was used as an additional experimental measurement to identify the input data set, and a sensitivity analysis was conducted to estimate the impact of each identified parameter on the cooling rate and the melt pool dimension. Full article
(This article belongs to the Special Issue Computational Plasticity)
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15 pages, 25589 KiB  
Article
Mechanical Responses of Ductile Aluminum Alloy under Biaxial Non-Proportional Tensile Reverse Loading Patterns
by Zhichao Wei, Steffen Gerke and Michael Brünig
Metals 2023, 13(12), 1922; https://doi.org/10.3390/met13121922 - 22 Nov 2023
Cited by 1 | Viewed by 895
Abstract
This paper deals with the study of the mechanical responses of ductile metals under biaxial non-proportional cyclic loading tests. The biaxially loaded HC specimens manufactured from 4 mm thick aluminum alloy sheets (EN AW 6082-T6) are subjected to various loading paths, including monotonic [...] Read more.
This paper deals with the study of the mechanical responses of ductile metals under biaxial non-proportional cyclic loading tests. The biaxially loaded HC specimens manufactured from 4 mm thick aluminum alloy sheets (EN AW 6082-T6) are subjected to various loading paths, including monotonic and cyclic loading conditions. The aim is to investigate the plastic, damage, and fracture behavior of the material under these different loading scenarios. In terms of numerical aspects, a modified anisotropic two-surface cyclic plastic–damage continuum model is used to predict the material behavior in the load-displacement field and different strain fields. Numerically predicted stress states are analyzed in detail to gain a better understanding of the damage mechanisms. Moreover, the scanning electronic microscopy (SEM) pictures taken from the fracture surfaces confirm the dependency of the damage mechanisms on the loading histories. The present work indicates the importance of considering different loading conditions for the accurate prediction of material responses. Full article
(This article belongs to the Special Issue Computational Plasticity)
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