A mesoscopic digital twin that bridges length and time scales for control of additively manufactured metal microstructures. (14th June 2021)

• Record Type: Journal Article
• Authors: Heo, Tae Wook; Khairallah, Saad A; Shi, Rongpei; Berry, Joel; Perron, Aurelien; Calta, Nicholas P; Martin, Aiden A; Barton, Nathan R; Roehling, John; Roehling, Tien; Fattebert, Jean-Luc; Anderson, Andy; Nichols, Albert L; Wopschall, Steven; King, Wayne E; McKeown, Joseph T; Matthews, Manyalibo J
• Is Part Of: JPhys materials. Volume 4:Number 3(2021)
• Publication Date: 2021-06-14
• Subjects: digital twin -- additive manufacturing -- metals -- microstructures -- processing -- properties; Solid state physics -- Periodicals; Materials science -- Periodicals; 530.41
• DOI: 10.1088/2515-7639/abeef8
• Languages: English
• ISSNs: 2515-7639

Abstract

Abstract: We present our recent development of an integrated mesoscale digital twin (DT) framework for relating processing conditions, microstructures, and mechanical responses of additively manufactured (AM) metals. In particular, focusing on the laser powder bed fusion technique, we describe how individual modeling and simulation capabilities are coupled to investigate and control AM microstructural features at multiple length and time scales. We review our prior case studies that demonstrate the integrated modeling schemes, in which high-fidelity melt pool dynamics simulations provide accurate local thermal profiles and histories to subsequent AM microstructure simulations. We also report our new mechanical response modeling results for predicted AM microstructures. In addition, we illustrate how our DT framework has been validated through modeling–experiment integration, as well as how it has been practically utilized to guide and analyze AM experiments. Finally, we share our perspectives on future directions of further development of the DT framework for more efficient, accurate predictions and wider ranges of applications.