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Metals
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New Insights into Metal Additive Manufacturing through Modeling and Simulation
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New Insights into Metal Additive Manufacturing through Modeling and Simulation

A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Additive Manufacturing".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 4760

Special Issue Editor

Dr. Dayalan Gunasegaram

E-Mail Website
Guest Editor
Commonwealth Scientific and Industrial Research Organization, Clayton, Australia
Interests: additive manufacturing; multiphysics modeling; machine learning; digital twins; real-time control of processes
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modelling and simulation play a critical role in developing insights into the metal additive manufacturing (AM) process and the design of AM parts. The difficulty of observing the highly dynamic process adds weight to modelling efforts that help to recreate the process. Models can be interrogated by scientists and engineers for the development of new knowledge into underlying physical phenomena and their interactions. Furthermore, modelling assists in optimizing the process. Finally, modelling helps to design AM parts by facilitating the simulations of their performance under service conditions while taking advantage of the design freedom offered by the process.

Various types of models are being used in AM. These include, but are not limited to, machine learning, physics-based, and statistics-based models.

We are pleased to invite authors to submit original research articles and review articles that will contribute to the broad areas of modelling and simulation in metal additive manufacturing processes. Potential topics include, but are not limited to:

  • Directed energy deposition (DED);
  • Metal powder bed fusion (PBF);
  • Wire arc additive manufacturing (WAAM);
  • Cold spray additive manufacturing;
  • Laser cladding additive manufacturing;
  • Novel AM processes and machine configurations;
  • Microstructure modelling;
  • Property prediction;
  • Defect control;
  • Residual stress and distortion control;
  • Novel sensor systems and imaging techniques;
  • Process control strategies and systems;
  • Data analytics and machine learning;
  • Physics-informed machine learning;
  • Topology optimization for AM parts;
  • AI for the design of AM parts;
  • Tool path or scan path generation.

Dr. Dayalan Gunasegaram
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

  • modeling and simulation
  • additive manufacturing
  • microstructure
  • residual stress
  • topology optimization
  • artificial intelligence
  • machine learning

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

Published Papers (2 papers)

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Research

17 pages, 11431 KiB  
Article
Numerical Simulation of Thermal Field and Performance Study on H13 Die Steel-Based Wire Arc Additive Manufacturing
by Yu Zhu, Jufang Chen and Xiaoping Li
Metals 2023, 13(8), 1484; https://doi.org/10.3390/met13081484 - 18 Aug 2023
Cited by 3 | Viewed by 1541
Abstract
In order to explore the relationship between welding thermal cycles and the thermal field during the repair process of dies, a numerical simulation software (SYSWELD) was employed to construct a thermo-mechanical coupled model. The influence of various inter-layer cooling times was investigated on [...] Read more.
In order to explore the relationship between welding thermal cycles and the thermal field during the repair process of dies, a numerical simulation software (SYSWELD) was employed to construct a thermo-mechanical coupled model. The influence of various inter-layer cooling times was investigated on heat accumulation, residual stress, and deformation of the repaired component. The results showed that the numerical simulation results agreed well with experimental data. The temperature within the cladding layer gradually rose as the number of weld beads increased, leading to a more pronounced accumulation of heat. The residual stress exhibited a double-peak profile, where the deformation of the repaired component was large at both ends but small in the middle. The less heat was accumulated in the cladding layer with a prolonged cooling time. Meanwhile, the residual stress and deformation in the repaired component experienced a gradual decrease in magnitude. The numerical simulation results demonstrated that the microstructure of the repaired component predominantly consisted of martensite and residual austenite at the optimal cooling time (300 s). Furthermore, the microhardness and wear resistance of the cladding zone significantly surpassed those of the substrate. In conclusion, this study suggested the prolonged cooling time mitigated heat accumulation, residual stress, and deformation in repaired components, which provided a new direction for future research on the die steel repairments. Full article
(This article belongs to the Special Issue New Insights into Metal Additive Manufacturing through Modeling and Simulation)
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20 pages, 4937 KiB  
Article
Numerical Simulations to Predict the Melt Pool Dynamics and Heat Transfer during Single-Track Laser Melting of Ni-Based Superalloy (CMSX-4)
by Mohammad Reza Azadi Tinat, Murali Uddagiri, Ingo Steinbach and Inmaculada López-Galilea
Metals 2023, 13(6), 1091; https://doi.org/10.3390/met13061091 - 8 Jun 2023
Cited by 3 | Viewed by 2582
Abstract
Computational Fluid Dynamics (CFD) simulations are used in this work to study the dynamic behavior of the melt pool and heat transfer during the single-track laser melting process of a nickel-based superalloy (CMSX-4). To include the effects of powder inhomogeneities and obtain a [...] Read more.
Computational Fluid Dynamics (CFD) simulations are used in this work to study the dynamic behavior of the melt pool and heat transfer during the single-track laser melting process of a nickel-based superalloy (CMSX-4). To include the effects of powder inhomogeneities and obtain a realistic distribution of the powder layer on the bed chamber, the CFD model is coupled with a Discrete Element Method (DEM) solver. The coupled model is implemented in the open-source software package OpenFOAM. In the CFD model’s governing equations, some key physical mechanisms, such as the Marangoni effect and recoil pressure, are considered. With the help of the coupled CFD-DEM model, we have investigated the effect of key process parameters, such as laser power, scanning speed of the laser, powder size, and powder shape, on the size and homogeneity of the melt pool. From the simulation results, it was discovered that high laser power and slow scanning speed create a deep and narrow keyhole that leads to porosity. In contrast, balling defects are found to be caused by a small melt pool obtained from fast scanning speeds and inadequate laser power. Full article
(This article belongs to the Special Issue New Insights into Metal Additive Manufacturing through Modeling and Simulation)
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