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Metals
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Numerical and Experimental Advances in Metal Processing
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Numerical and Experimental Advances in Metal Processing

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: 20 September 2025 | Viewed by 8353

Special Issue Editors

Dr. Abel Dias dos Santos

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Guest Editor
Department of Mechanical Engineering, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
Interests: manufacturing processes; metal forming technology and processing; sheet metal forming; numerical simulation; experimental validation; material testing and constitutive modelling
Special Issues, Collections and Topics in MDPI journals
Dr. Abílio M. P. De Jesus

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
Interests: manufacturing processes; simulation; fracture mechanics
Special Issues, Collections and Topics in MDPI journals
Dr. Rui L. Amaral

E-Mail Website
Guest Editor
Institute of Science and Innovation in Mechanical and Industrial Engineering, R. Dr. Roberto Frias, 400, 4200-465, Porto, Portugal
Interests: metal forming processes; material characterization; constitutive modelling; numerical simulation; experimental validation; inverse optimization techniques
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to provide the most recent advances in the manufacturing processes of metallic materials and to identify directions both in experimental and numerical research, including the requirements for sustainable technologies and processes.

The covered topics will be of major interest for scientists and professionals working at universities, research institutes, laboratories and industries concerned with established and novel manufacturing methodologies using conventional and emerging materials.

A key aspect is proper process design in order to guarantee the compliance of the final product with the intended functionality, while at the same time minimizing resource usage. Metal processing optimization and the strength of the final products, including their fatigue performance, could be anticipated at the design stage by resorting to advanced modelling, including numerical simulation (e.g., FEA). The continuous development of these technologies and processes, research on suitable numerical tools and models, and experimental procedures allow proper process design for tailored product performance, which is mandatory for industry competitiveness and the sustainability of society.

The Special Issue will cover, but will not be limited to, the following topics:

  • Formability in metal forming processes;
  • Modeling and designing of forming and joining processes;
  • Ductile damage and fracture: experiments, modeling and numerical prediction;
  • Modeling of anisotropic behavior in plasticity;
  • Inverse identification of constitutive material models;
  • Additive, subtractive and hybrid manufacturing;
  • Emerging manufacturing processes;
  • Intelligent metal processing technologies.
  • Processes of lightweight metals and numerical modeling;
  • Product design and process optimization;
  • Mechanical performance of products.

Dr. Abel Dias dos Santos
Dr. Abílio M. P. De Jesus
Dr. Rui L. Amaral
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.

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

  • manufacturing
  • metals
  • manufacturing processes
  • fatigue
  • fracture
  • product design
  • finite element analysis
  • structural integrity
  • surface integrity
  • residual stresses

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (7 papers)

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Research

13 pages, 2612 KiB  
Article
Application of Bayesian Statistics in Analyzing and Predicting Carburizing-Induced Dimensional Changes in Torsion Bars
by Guojin Sun, Zhenggui Li, Yanxiong Jiao and Qi Wang
Metals 2025, 15(5), 546; https://doi.org/10.3390/met15050546 - 15 May 2025
Viewed by 153
Abstract
This study investigates the application of Bayesian statistical methods to analyze and predict the dimensional changes in torsion bars made from 20CrMnTi alloy steel during carburizing heat treatment. The process parameters, including a treatment temperature of 920 °C followed by oil quenching, were [...] Read more.
This study investigates the application of Bayesian statistical methods to analyze and predict the dimensional changes in torsion bars made from 20CrMnTi alloy steel during carburizing heat treatment. The process parameters, including a treatment temperature of 920 °C followed by oil quenching, were selected to optimize surface hardness while maintaining core toughness. The dimensional changes were measured pre- and post-treatment using precise caliper measurements. Bayesian statistics, particularly conjugate normal distributions, were utilized to model the dimensional variations, providing both posterior and predictive distributions. These models revealed a marked concentration of the posterior distributions, indicating enhanced accuracy in predicting dimensional changes. The findings offer valuable insights for improving the control of carburizing-induced deformations, thereby ensuring the dimensional integrity and performance reliability of torsion bars used in high-stress applications such as pneumatic clutch systems in mining ball mills. This study underscores the potential of Bayesian approaches in advancing precision engineering and contributes to the broader field of statistical modeling in manufacturing processes. Full article
(This article belongs to the Special Issue Numerical and Experimental Advances in Metal Processing)
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26 pages, 5250 KiB  
Article
Predicting Fatigue Life of 51CrV4 Steel Parabolic Leaf Springs Manufactured by Hot-Forming and Heat Treatment: A Mean Stress Probabilistic Modeling Approach
by Vítor M. G. Gomes, Miguel A. V. de Figueiredo, José A. F. O. Correia and Abílio M. P. de Jesus
Metals 2025, 15(3), 315; https://doi.org/10.3390/met15030315 - 13 Mar 2025
Viewed by 390
Abstract
The longevity of railway vehicles is an important factor in their mechanical and structural design. Fatigue is a major issue that affects the durability of railway components, and, therefore, knowledge of the fatigue resistance characteristics of critical components, such as leaf springs, must [...] Read more.
The longevity of railway vehicles is an important factor in their mechanical and structural design. Fatigue is a major issue that affects the durability of railway components, and, therefore, knowledge of the fatigue resistance characteristics of critical components, such as leaf springs, must be extensively investigated. This research covers the fatigue resistance of 51CrV4 steel under bending and axial tension, for distinct stress ratios, in the low-cycle fatigue regime (LCF), high-cycle fatigue regime (HCF), and very high-cycle fatigue regime (VHCF) using experimental data collected in this work and from previous experiments. Two fatigue models were analyzed: the Walker model (WSN) and the Castillo–Fernández–Cantelli model, CFC, adapted for the presence of mean stress (ACFC). According to the analysis carried out, both fatigue resistance prediction models provided good results for the experimental data, with the ACFC model showing good fitting when considering all the failure data and outliers. Additionally, fracture surfaces showed a higher trend for crack initiation on the surface for positive stress ratios despite internal defects also possibly being responsible for some fatigue failures. This investigation aimed to provide a probabilistic fatigue model encompassing the LCF, HCF, and VHCF fatigue regimes for distinct stress ratios for the fatigue design analysis of 51CrV4 steel parabolic leaf springs manufactured by hot-forming processes with subsequent heat treatments. Full article
(This article belongs to the Special Issue Numerical and Experimental Advances in Metal Processing)
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17 pages, 8159 KiB  
Article
Numerical Study on Continuous-Bending-Under-Tension of 3rd Generation Steel
by João F. A. Pereira, Pedro A. Prates, Marilena C. Butuc and Gabriela Vincze
Metals 2025, 15(2), 138; https://doi.org/10.3390/met15020138 - 29 Jan 2025
Viewed by 698
Abstract
Sheet metal forming is one of the key processes in the manufacturing of parts for several industries, such as automotive, aerospace and packaging. However, it is often constrained by the onset of plastic instability, which limits uniform deformation. To address this challenge, considerable [...] Read more.
Sheet metal forming is one of the key processes in the manufacturing of parts for several industries, such as automotive, aerospace and packaging. However, it is often constrained by the onset of plastic instability, which limits uniform deformation. To address this challenge, considerable attention has been given to methods that enhance strength, formability, and energy absorption during forming processes. One such method is the continuous-bending-under-tension (CBT) deformation mechanism, which has shown potential in mitigating localized instability during plastic deformation. This study presents a numerical investigation of the CBT process using Abaqus 2017 to evaluate the forces generated in both the CBT equipment and material when processing high-strength materials. The reference material used is the USS CR980XG3™ AHSS, a third-generation, high-strength, high-elongation steel grade with retained austenite (980T/600Y). The study systematically analyzes the effects of key parameters, such as roll diameter, distance between rolls, depth setting, specimen thickness, and the number of deformation cycles, on the evolution of forces during the CBT process. The results demonstrate that both the forces applied by the rolls and those experienced by the specimen are significantly influenced by the distance between rolls, depth setting, and specimen thickness. In contrast, the roll diameters have minimal influence. These findings contribute to the optimization of the CBT process and provide valuable insights for future studies aimed at enhancing the performance and formability of various materials. Full article
(This article belongs to the Special Issue Numerical and Experimental Advances in Metal Processing)
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16 pages, 7720 KiB  
Article
Hot Deformation Behavior and Processing Maps of Vapor-Phase-Grown Carbon Nanofiber Reinforced 7075Al Composites
by Mengying Zhu, Zhefeng Xu, Junhua Wu, Satoshi Motozuka, Caili Tian, Jianglong Gu and Jinku Yu
Metals 2024, 14(11), 1245; https://doi.org/10.3390/met14111245 - 1 Nov 2024
Viewed by 810
Abstract
The present study prepared 7075Al composites reinforced with vapor-phase-grown carbon nanofibers (VGCNFs) using the spark plasma sintering (SPS) method. Constitutive equations of the composites were calculated, and thermal processing maps were constructed by performing thermal compression tests on the VGCNF/7075Al composites at deformation [...] Read more.
The present study prepared 7075Al composites reinforced with vapor-phase-grown carbon nanofibers (VGCNFs) using the spark plasma sintering (SPS) method. Constitutive equations of the composites were calculated, and thermal processing maps were constructed by performing thermal compression tests on the VGCNF/7075Al composites at deformation temperatures ranging from 300 to 450 °C and strain rates from 0.01 to 1 s−1. This study analyzed the microstructural evolution of the VGCNF/7075Al composites during the thermomechanical processing. The experimental results demonstrated that dynamic recrystallization (DRX) primarily governed the softening mechanism of VGCNF/7075Al composites during thermomechanical processing. At high strain rates, a combination of dynamic recovery (DRV) and DRX contributed to the softening behavior. The incorporation of VGCNFs results in higher dislocation density and a larger orientation deviation within the 7075Al matrix during the thermomechanical deformation process, providing stored energy that facilitated DRX. The activation energy for deformation of VGCNF/7075Al composites was 175.98 kJ/mol. The constitutive equation of the flow stress showed that a hyperbolic sinusoidal form could effectively describe the relationship between flow stress, strain, strain rate, and temperature of VGCNF/7075Al composites. The optimal thermomechanical deformation parameters for VGCNF/7075Al composites were 400–450 °C and 0.01–0.1 s−1 when the strain ranged from 0.05 to 0.15. For strains between 0.25 and 0.35, the optimal thermomechanical parameters were 380–430 °C and 0.01–1 s−1. Full article
(This article belongs to the Special Issue Numerical and Experimental Advances in Metal Processing)
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17 pages, 12375 KiB  
Article
Effect of Material Extrusion Method on the Microstructure and Mechanical Properties of Copper Parts
by Naiara Aldeiturriaga, Itziar Fraile, Erika Dominguez, Aitor Zuriarrain, Pedro José Arrazola and Daniel Soler
Metals 2024, 14(8), 941; https://doi.org/10.3390/met14080941 - 17 Aug 2024
Cited by 1 | Viewed by 1200
Abstract
In the present study, three extrusion-based Additive Manufacturing (AM) technologies were considered: Fused Filament Fabrication (FFF), Pellet Extrusion Process (PEP) and Atomic Diffusion Additive Manufacturing (ADAM). In order to compare these technologies, the same initial material was employed: a copper filament commercialized by [...] Read more.
In the present study, three extrusion-based Additive Manufacturing (AM) technologies were considered: Fused Filament Fabrication (FFF), Pellet Extrusion Process (PEP) and Atomic Diffusion Additive Manufacturing (ADAM). In order to compare these technologies, the same initial material was employed: a copper filament commercialized by Markforged® (Waltham, MA, USA). The copper filament was employed as received for ADAM and FFF technologies and shredded for PEP technology. Different printing parameters were studied for each technology (except for ADAM, which does not allow it) and the manufactured disc-shaped and tensile test parts were debindered and sintered under the same conditions. Part density, micrography and mechanical properties were analyzed. The density was observed to change with geometry, showing a relative density of around 95% for the tensile test parts through all the technologies but lower relative densities for the disc-shaped parts: around 90% for ADAM, between 85–88% for PEP and between 90–94% for optimized FFF printing parameters. The micrographies present big cavities between infill and contour for ADAM, whereas such cavities were not observed in either PEP or FFF parts. On the other hand, the parts made with PEP showed less and smaller porosity, but they had poor surface finishing, indicating that some printing parameters should be readjusted. Finally, the FFF parts had a better finishing but exhibited a non-uniform pore distribution. Concerning the mechanical properties, all the printed parts show similar properties. Full article
(This article belongs to the Special Issue Numerical and Experimental Advances in Metal Processing)
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17 pages, 25787 KiB  
Article
Machine-Learning-Assisted Design of Novel TiZrNbVAl Refractory High-Entropy Alloys with Enhanced Ductility
by Xinyi Zhao, Zihang Wei, Junfeng Zhao, Yandong Jia, Shuo Cao, Dan Wang and Yucheng Lei
Metals 2024, 14(8), 894; https://doi.org/10.3390/met14080894 - 5 Aug 2024
Cited by 2 | Viewed by 2088
Abstract
Refractory high-entropy alloys (RHEAs) typically exhibit excellent high-temperature strength but limited ductility. In this study, a comprehensive machine learning strategy with integrated material knowledge is proposed to predict the elongation of TiZrNbVAl RHEAs. By referring to the ductility theories, a set of cost-effective [...] Read more.
Refractory high-entropy alloys (RHEAs) typically exhibit excellent high-temperature strength but limited ductility. In this study, a comprehensive machine learning strategy with integrated material knowledge is proposed to predict the elongation of TiZrNbVAl RHEAs. By referring to the ductility theories, a set of cost-effective material features is developed with various mathematical forms of thermodynamic parameters. These features are proven to effectively incorporate material knowledge into ML modeling. They also offer potential alternatives to those obtained from costly first-principles calculations. Based on Pearson correlation coefficients, the linear relationships between pairwise features were compared, and the seven key features with the greatest impact on the model were selected for ML modeling. Regression tasks were performed to predict the ductility of TiZrNbVAl, and the CatBoost gradient boosting algorithm exhibiting the best performance was eventually selected. The established optimized model achieves high predictive accuracies exceeding 0.8. These key features were further analyzed using interpretable ML methods to elucidate their influences on various ductility mechanisms. According to the ML results, different compositions of TiZrNbVAl with excellent tensile properties were prepared. The experimental results indicate that Ti44Zr24Nb17V5Al10 and Ti44Zr26Nb8V13Al9 both exhibited ultimate tensile strengths of approximately 1180 MPa and elongations higher than 21%. They verified that the ML strategy proposed in this study is an effective approach for predicting the properties of RHEAs. It is a potential method that can replace costly first-principles calculations. Thermodynamic parameters have been shown to effectively predict alloy ductility to a certain extent. Full article
(This article belongs to the Special Issue Numerical and Experimental Advances in Metal Processing)
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11 pages, 2990 KiB  
Article
Cold Rolling Technology Optimization for EN AW 4343/3003/4343 Cladded Aluminum Alloys and Influence of Parameters on Microstructure, Mechanical Properties and Sustainable Recyclability
by Bojan Kropf, Peter Cvahte, Matija Arzenšek and Jakob Kraner
Metals 2024, 14(2), 230; https://doi.org/10.3390/met14020230 - 14 Feb 2024
Cited by 1 | Viewed by 2101
Abstract
The present study investigates the accumulative roll bonding process applied to the EN AW 3003 aluminum alloy, serving as a composite material on both sides and consisting of the EN AW 4343 aluminum alloy. For the characterization of the optical microscopy, corrosion tests [...] Read more.
The present study investigates the accumulative roll bonding process applied to the EN AW 3003 aluminum alloy, serving as a composite material on both sides and consisting of the EN AW 4343 aluminum alloy. For the characterization of the optical microscopy, corrosion tests with saltwater acetic acid and mechanical properties before and after the braze test were employed. The numerical simulations accurately predicted the industrial cold rolling values for the rolling force and surface temperature. The most comprehensive understanding of the cold rolling parameters for both side-cladded materials was achieved by combining predictions for cladded and uncladded materials. The thickness of the cladded layer presented as a percentage after roll bonding was 18.7%. During the cold rolling and annealing, the cladded thickness was increased to 24.7% of the final 0.3 mm of the total cold-rolled product thickness. According to the performed braze test for final thickness, the ultimate tensile strength and yield strength were decreased, and the elongation increased to 18.1%. In addition to the described changes in mechanical properties, the material’s anisotropy improved from 5.4% in the cold-rolled condition to 2.0% after the braze test. After multiple re-meltings of the cladded material, the analyzed chemical compositions allow for recycling and reuse as different 4xxx, 5xxx, and 6xxx alloys. Full article
(This article belongs to the Special Issue Numerical and Experimental Advances in Metal Processing)
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