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Metal additive manufacturing simulation across length, time, and computing scales.

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Title: Metal additive manufacturing simulation across length, time, and computing scales.
Authors: Plotkowski, Alex1 (AUTHOR) plotkowskiaj@ornl.gov, Rolchigo, Matt1 (AUTHOR), Wagner, Gregory2 (AUTHOR), Reeve, Samuel Temple1 (AUTHOR), Coleman, John1 (AUTHOR), Knapp, Gerry1 (AUTHOR), Levine, Lyle3 (AUTHOR), To, Albert4 (AUTHOR), DeWitt, Stephen1 (AUTHOR), Dugast, Florian4 (AUTHOR), Mahadevan, Sankaran5 (AUTHOR), Newman, Christopher6 (AUTHOR), Stump, Benjamin1 (AUTHOR), Bement, Matt1 (AUTHOR), Turner, John1 (AUTHOR)
Source: International Materials Reviews. May2026, Vol. 71 Issue 3, p254-293. 40p.
Subjects: Computer simulation, Simulation methods & models, Graphics processing units, Metal fabrication, Scientific computing, Mechanical behavior of materials, Process optimization, Microstructure
Abstract: Metal additive manufacturing (AM) offers a unique opportunity for production of advanced materials and complex geometries. However, variability in microstructure and properties challenges conventional approaches to design, process optimization, qualification, and materials selection. Modeling and simulation can improve understanding of AM processing and materials, but also poses major challenges for existing computational methods. Simultaneously, modern scientific computing hardware has become increasingly complex, most notably with the adoption of hybrid architectures such as Graphical Processing Units (GPUs). If appropriately utilized, emerging computational capabilities provide an opportunity to reveal new insight into AM processing and the resulting material structure and properties. In this review we describe the computational AM landscape, identify critical gaps, and highlight opportunities to impact the development and application of AM. First, the requirements and challenges of representative AM problem statements will be defined. These problems range from scientific studies to industrial applications and are designed to capture the breadth of challenges facing the AM community. Next, the current state of AM modeling and simulation is evaluated, broken down by enabling hardware and software, process simulation, microstructure simulation, and property simulation. Each section describes the diversity of simulation approaches and associated trade-offs in physical fidelity and computational expense. Each area is then assessed based on their suitability and readiness for current and developing computational architectures. Lastly, the greatest opportunities for future research and application are highlighted, including gaps in modeling capabilities, opportunities for near-term application, and key scientific challenges. [ABSTRACT FROM AUTHOR]
Copyright of International Materials Reviews is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
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DbLabel: Engineering Source
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Metal additive manufacturing simulation across length, time, and computing scales.
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  Data: <searchLink fieldCode="AR" term="%22Plotkowski%2C+Alex%22">Plotkowski, Alex</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> plotkowskiaj@ornl.gov</i><br /><searchLink fieldCode="AR" term="%22Rolchigo%2C+Matt%22">Rolchigo, Matt</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wagner%2C+Gregory%22">Wagner, Gregory</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Reeve%2C+Samuel+Temple%22">Reeve, Samuel Temple</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Coleman%2C+John%22">Coleman, John</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Knapp%2C+Gerry%22">Knapp, Gerry</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Levine%2C+Lyle%22">Levine, Lyle</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22To%2C+Albert%22">To, Albert</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22DeWitt%2C+Stephen%22">DeWitt, Stephen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dugast%2C+Florian%22">Dugast, Florian</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mahadevan%2C+Sankaran%22">Mahadevan, Sankaran</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Newman%2C+Christopher%22">Newman, Christopher</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Stump%2C+Benjamin%22">Stump, Benjamin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bement%2C+Matt%22">Bement, Matt</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Turner%2C+John%22">Turner, John</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Materials+Reviews%22">International Materials Reviews</searchLink>. May2026, Vol. 71 Issue 3, p254-293. 40p.
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  Data: Metal additive manufacturing (AM) offers a unique opportunity for production of advanced materials and complex geometries. However, variability in microstructure and properties challenges conventional approaches to design, process optimization, qualification, and materials selection. Modeling and simulation can improve understanding of AM processing and materials, but also poses major challenges for existing computational methods. Simultaneously, modern scientific computing hardware has become increasingly complex, most notably with the adoption of hybrid architectures such as Graphical Processing Units (GPUs). If appropriately utilized, emerging computational capabilities provide an opportunity to reveal new insight into AM processing and the resulting material structure and properties. In this review we describe the computational AM landscape, identify critical gaps, and highlight opportunities to impact the development and application of AM. First, the requirements and challenges of representative AM problem statements will be defined. These problems range from scientific studies to industrial applications and are designed to capture the breadth of challenges facing the AM community. Next, the current state of AM modeling and simulation is evaluated, broken down by enabling hardware and software, process simulation, microstructure simulation, and property simulation. Each section describes the diversity of simulation approaches and associated trade-offs in physical fidelity and computational expense. Each area is then assessed based on their suitability and readiness for current and developing computational architectures. Lastly, the greatest opportunities for future research and application are highlighted, including gaps in modeling capabilities, opportunities for near-term application, and key scientific challenges. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Materials Reviews is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1177/09506608251394155
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      – Code: eng
        Text: English
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        PageCount: 40
        StartPage: 254
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      – SubjectFull: Computer simulation
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      – SubjectFull: Simulation methods & models
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      – SubjectFull: Graphics processing units
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      – SubjectFull: Metal fabrication
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      – SubjectFull: Scientific computing
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      – SubjectFull: Mechanical behavior of materials
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      – SubjectFull: Process optimization
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      – SubjectFull: Microstructure
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              Text: May2026
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