Aug. 30, 2022, 1:11 a.m. | Adam Thelen, Xiaoge Zhang, Olga Fink, Yan Lu, Sayan Ghosh, Byeng D. Youn, Michael D. Todd, Sankaran Mahadevan, Chao Hu, Zhen Hu

cs.LG updates on arXiv.org arxiv.org

As an emerging technology in the era of Industry 4.0, digital twin is gaining
unprecedented attention because of its promise to further optimize process
design, quality control, health monitoring, decision and policy making, and
more, by comprehensively modeling the physical world as a group of
interconnected digital models. In a two-part series of papers, we examine the
fundamental role of different modeling techniques, twinning enabling
technologies, and uncertainty quantification and optimization methods commonly
used in digital twins. This second paper …

arxiv battery digital digital twin optimization part perspectives quantification review roles uncertainty

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