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Pages 36-49

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From page 36...
... These challenges are discussed further in the context of automated and human-in-the-loop decision-making as part of Chapter 6. Security Characteristic of digital twins is the tight integration between the physical system and its virtual representation.
From page 37...
... In part as a result of the bespoke nature of many digital twin implementations, the relative maturity of digital twins varies significantly across problem spaces. This section explores some current efforts under way in addition to domain-specific needs and opportunities within aerospace and defense applications; atmospheric, climate, and sustainability sciences; and biomedical applications.  Digital Twin Examples, Needs, and Opportunities for Aerospace and Defense Applications There are many exciting and promising directions for digital twins in aerospace and defense applications.
From page 38...
... could benefit from the broader use of digital twins in asset management, incorporating the processes and practices employed in the commercial aviation industry for maintenance analysis (Gahn 2023)
From page 39...
... It is important to note that climate predictions do not necessarily require realtime updates, but some climate-related issues, such as wildfire response planning, might (Ghattas 2023) . Three specific thrusts could help to advance the sort of climate modeling needed to realize digital twins: research on parametric sparsity and generalizing observational data, generation of training data and computation for highest possible resolution, and uncertainty quantification and calibration based on both observational and synthetic data (Schneider 2023)
From page 40...
... . Digital Twin Examples, Needs, and Opportunities for Biomedical Applications Many researchers hold that digital twins are not yet in practical use for decision-making in the biomedical space, but extensive work to advance their development is ongoing.
From page 41...
... . Accounting for uncertainty in biomedical digital twins as well as communicating and making appropriate decisions based on uncertainty will be vital to their practical application.
From page 42...
... It is important to separate the aspirational from the actual to strengthen the credibility of the research in digital twins and to recognize that serious research questions remain in order to achieve the aspirational.  Conclusion 2-6: Realizing the potential of digital twins requires an inte grated research agenda that advances each one of the key digital twin ele ments and, importantly, a holistic perspective of their interdependencies and interactions. This integrated research agenda includes foundational needs that span multiple domains as well as domain-specific needs.  Recommendation 1: Federal agencies should launch new crosscutting programs, such as those listed below, to advance mathematical, statisti cal, and computational foundations for digital twins. As these new digital twin–focused efforts are created and launched, federal agencies should identify opportunities for cross-agency interactions and facilitate cross community collaborations where fruitful. An interagency working group may be helpful to ensure coordination.
From page 43...
... . DoD's Office of the Under Secretary of Defense for Research and Engineering should advance the appli cation of digital twins as an integral part of the digital engineering performed to support system design, performance analysis, devel opmental and operational testing, operator and force training, and operational maintenance prediction.
From page 44...
... For example, the National Oceanic and Atmospheric Administration, the National Institute of Stan dards and Technology, and the National Aeronautics and Space Administration should be included in the discussion of digital twin research and development, drawing on their unique missions and extensive capabilities in the areas of data assimilation and real time decision support. As described earlier in this chapter, VVUQ is a key element of digital twins that necessitates collaborative and interdisciplinary investment.
From page 45...
... Methods for validating atmospheric, climate, and sustainability sciences digital twin 1 predictions over long horizons and extreme events are needed.  Mechanisms to better facilitate cross-disciplinary collaborations are needed to 2 achieve inclusive digital twins for atmospheric, climate, and sustainability sciences.  Due to the heterogeneity, complexity, multimodality, and breadth of biomedical 1 data, the harmonization, aggregation, and assimilation of data and models to effectively combine these data into biomedical digital twins require significant technical research. Research Base Exists with Opportunities to Advance Digital Twins Uncertainty quantification is critical to digital twins for atmospheric, climate, and 2 sustainability sciences and will generally require surrogate models and/or improved sampling techniques. 
From page 46...
... 2023. "Towards Traceable Model Hierarchies." Presentation to the Workshop on Digital Twins in Atmospheric, Climate, and Sustainability Science.
From page 47...
... 2023. "Prognostic Digital Twins in Practice." Presentation to the Workshop on Opportuni ties and Challenges for Digital Twins in Biomedical Sciences.
From page 48...
... 2022. "Digital Twins and NVIDIA Omniverse." Presentation to the Committee on Founda tional Research Gaps and Future Directions for Digital Twins.
From page 49...
... Surrogate modeling needs and opportunities for digital twins are also discussed, including surrogate modeling for high-dimensional, complex multidisciplinary systems and the essential data assimilation, dynamic updating, and adaptation of surrogate models. FIT-FOR-PURPOSE VIRTUAL REPRESENTATIONS FOR DIGITAL TWINS  As discussed in Chapter 2, the computational models underlying the digital twin virtual representation can take many mathematical forms (including dynamical systems, differential equations, and statistical models)


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