Opportunities and Challenges for Digital Twins in Engineering Proceedings of a Workshop���in Brief (2023) / Chapter Skim
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Opportunities and Challenges for Digital Twins in Engineering: Proceedings of a Workshop - in Brief
Opportunities and Challenges for Digital Twins in Engineering: Proceedings of a Workshop - in Brief
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He Medicine hosted a public, virtual workshop to discuss emphasized that a digital twin is shaped by questions; characterizations of digital twins within the context as those questions evolve, the digital twin evolves to of engineering and to identify methods for their incorporate more detailed physical phenomena, geometry, development and use. Panelists highlighted key technical and data and to account for more sources of uncertainty.
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He Baron noted that the automotive industry has been described several research gaps and areas for investment, adapting digital twin technologies since the 1990s including the following: quantifying the level of model and emphasized that increased adoption of realfidelity sufficient to answer questions asked of the digital time digital twins could accelerate Industry 4.03 and twin, quantifying the physical system's initial or current improve customer-oriented manufacturing, design, and conditions and incorporating that information into the engineering. She defined a digital twin as a dynamic digital twin, obtaining data for model validation and virtual copy of a physical asset, process, system, or uncertainty quantification, developing new approaches environment that behaves identically to its real-world to human–computer interfaces, and enhancing education counterpart.
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He explained that securing the digital twin environment is a significant challenge, with data Grieves observed that digital twins typically have three from the asset, data in transit, data stored between those components: (1) the physical space of the product and two points, and data for modeling -- if the systems are the environment; (2)
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Baron explained that an effective digital twin illuminates where systems relate to one another. Providing Deshmukh emphasized that the digital twin "invention to contextual relationships between these vertical functions4 production journey is a team sport." Challenges include (Figure 1)
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The automotive industry outcome of the digital twin with respect to the groundhas embraced virtual crash testing because many more truth verification would be useful. Grieves added that types of testing can be done at a much lower cost.
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is a physically accurate, realistic digital representation of an asset, facility, or product that emulates its real- Deshmukh explained that data are at the core of digital world counterpart. The "connected twin" integrates twin success, and digital twin adoption is the critical end real-time and right-time data to provide insights into the point.
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Many frameworks are available, but a baseline level of protection prepares users with a plan PLENARY SESSION 2: DIGITAL TWINS FOR NATIONAL SECURITY to recover data and modeling tools if an attack occurs. AND RENEWABLE ENERGY He suggested that users consider protection both in Grace Bochenek, University of Central Florida, described terms of the cloud and the physical asset that moves digital twins as "innovation enablers" that are redefining around globally.
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She underscored Celaya pointed out that using the term "digital twin" to that because energy systems are large and complex, grid describe ongoing computational modeling would not unlock modernization demands advanced modeling capabilities new value or performance. New attributes are critical, and a and real-time interaction with data for predictive and digital representation could focus on a different perspective forensic analysis and energy resource protection.
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noted that significant gaps remain before the Airframe digital twin can be adopted by the Department of Defense. Incorporating questions from workshop participants, Cruz-Neira moderated a discussion among the panelists.
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Quantifying model form error Francom noted that a spectrum of digital twins would is also a key challenge, especially when one cannot rely be useful to explore different assumptions about and solely on empirical information, which is sometimes explanations for certain phenomena. Kobryn added that incorrect.
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validate and design models for deployment. Francom She cautioned that as a digital twin continues to be recognized that researchers can learn much from data updated in real time, more computational challenges will to improve modeling capabilities; a tighter integration arise, but implementation of zero trust networks could be of data and models could help pursue new scientific beneficial.
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He explained that be beneficial. Instead of creating an entirely "digital strategic investment is also needed for successful curriculum," Celaya suggested enhancing the current use cases that demonstrate how end users benefit core engineering curriculum with a new focus on from digital twins, for corporate partnerships, and computing capability, disparate sources of data, and for interdisciplinary collaboration.
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COMMITTEE ON FOUNDATIONAL RESEARCH GAPS AND FUTURE DIRECTIONS FOR DIGITAL TWINS Karen Willcox (Chair) , Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin; Derek Bingham, Simon Fraser University; Caroline Chung, MD Anderson Cancer Center; Julianne Chung, Emory University; Carolina Cruz-Neira, University of Central Florida; Conrad J
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