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Invited review article: Metal-additive manufacturing—Modeling strategies for application-optimized designs AITranslate

Washington State University; Washington State University
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Publisher: Elsevier
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Abstract AITranslate

Next generation, additively-manufactured metallic parts will be designed with application-optimized geometry, composition, and functionality. Manufacturers and researchers have investigated various techniques for increasing the reliability of the metal-AM process to create these components, however, understanding and manipulating the complex phenomena that occurs within the printed component during processing remains a formidable challenge—limiting the use of these unique design capabilities. Among various approaches, thermomechanical modeling has emerged as a technique for increasing the reliability of metal-AM processes, however, most literature is specialized and challenging to interpret for users unfamiliar with numerical modeling techniques. This review article highlights fundamental modeling strategies, considerations, and results, as well as validation techniques using experimental data. A discussion of emerging research areas where simulation will enhance the metal-AM optimization process is presented, as well as a potential modeling workflow for process optimization. This review is envisioned to provide an essential framework on modeling techniques to supplement the experimental optimization process. Graphical abstract Download : Download high-res image (178KB) Download : Download full-size image

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DOI:https://doi.org/10.1016/j.addma.2018.06.024

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Citation Information:

Next generation, additively-manufactured metallic parts will be designed with application-optimized geometry, composition, and functionality. Manufacturers and researchers have investigated various techniques for increasing the reliability of the metal-AM process to create these components, however, understanding and manipulating the complex phenomena that occurs within the printed component during processing remains a formidable challenge—limiting the use of these unique design capabilities. Among various approaches, thermomechanical modeling has emerged as a technique for increasing the reliability of metal-AM processes, however, most literature is specialized and challenging to interpret for users unfamiliar with numerical modeling techniques. This review article highlights fundamental modeling strategies, considerations, and results, as well as validation techniques using experimental data. A discussion of emerging research areas where simulation will enhance the metal-AM optimization process is presented, as well as a potential modeling workflow for process optimization. This review is envisioned to provide an essential framework on modeling techniques to supplement the experimental optimization process. Graphical abstract Download : Download high-res image (178KB) Download : Download full-size image

quote

GB/T 7714-2015 [1] Amit Bandyopadhyay, Kellen D. Traxel. Additive Manufacturing, 2018(22). DOI:10.1016/j.addma.2018.06.024.
MLA [1] Amit Bandyopadhyay, and Kellen D. Traxel. Additive Manufacturing, no. 22, 2018, https://doi.org/10.1016/j.addma.2018.06.024.
APA [1] Amit Bandyopadhyay, & Kellen D. Traxel. (2018). Additive Manufacturing(22). https://doi.org/10.1016/j.addma.2018.06.024
IEEE [1] Amit Bandyopadhyay and Kellen D. Traxel, Additive Manufacturing, no. 22, 2018, doi: 10.1016/j.addma.2018.06.024.