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Pages 15-35

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From page 15...
... 2020. "Digital Twin: Definition & Value." AIAA and AIA Position Paper, AIAA, Reston, VA.
From page 17...
... With the potential to transform traditional scientific and industrial practices and enhance operational efficiency, digital twins have captured the attention and imagination of professionals across various disciplines and 17
From page 18...
... While there is significant enthusiasm around industry developments and applications of digital twins, the focus of this report is on identifying research gaps and opportunities. The report's recommendations are particularly targeted toward what agencies and researchers can do to advance mathematical, statistical, and computational foundations of digital twins.
From page 19...
... The committee held several data-gathering meetings in support of this study, including three public workshops on the use of digital twins in atmospheric and climate sciences (NASEM 2023a) , biomedical sciences (NASEM 2023b)
From page 20...
... 2023a. Opportunities and Challenges for Digital Twins in Atmospheric and Climate Sciences: Proceedings of a Work shop -- in Brief.
From page 21...
... DEFINITIONS  Noting that the scope of this study is on identifying foundational research gaps and opportunities for digital twins, it is important to have a shared understanding of the definition of a digital twin. For the purposes of this report, the committee uses the following definition of a digital twin: A digital twin is a set of virtual information constructs that mimics the structure, context, and behavior of a natural, engineered, or social system (or system of-systems)
From page 22...
... In place of the term "asset," the committee refers to "a natural, engineered, or social system (or system-of-systems) " to describe digital twins of physical systems in the broadest sense possible, including the engineered world, natural phenomena, biological entities, and social systems.
From page 23...
... With that expansion has come a broadening in the views of what constitutes a digital twin along with differing specific digital twin definitions within different application contexts. During information-gathering sessions, the committee heard multiple different definitions of digital twins.
From page 24...
... More details are provided in the following subsections. The Physical Counterpart and Its Virtual Representation There are numerous and diverse examples of physical counterparts for which digital twins are recognized as bringing high potential value, including aircraft, body organs, cancer tumors, cities, civil infrastructure, coastal areas, farms, forests, global atmosphere, hospital operations, ice sheets, nuclear reactors, patients, and many more.
From page 25...
... Decision tasks might include personalized therapy control decisions, such as the dose and schedule of delivery of therapeutics over time, and data collection decisions, such as the frequency of serial imaging studies, blood tests, and other clinical assessments. These deci sions can be automated as part of the digital twin or made by a human informed by the digital twin's output.a  Digital Twin of an Aircraft Engine The virtual representation of an aircraft engine might comprise machine learn ing (ML)
From page 26...
... . The set of models comprising the virtual representation of a digital twin of a complex system will span multiple disciplines and multiple temporal and spatial scales.
From page 27...
... Decision tasks might include actions related to policy-making, energy system design, deployment of new observing systems, and emergency prepared ness for extreme weather events. These decisions may be made automatically as part of the digital twin or made by a human informed by the digital twin's output.c  Digital Twin of a Manufacturing Process Manufacturing environments afford many opportunities for digital twins.
From page 28...
... If this need is addressed by, for example, the use of Bayesian formulations, then the formulation of the virtual representation must also define prior information for parameters, numerical model parameters, and states. Bidirectional Feedback Flow Between Physical and Virtual The bidirectional interaction between the virtual representation and the physical counterpart forms an integral part of the digital twin.
From page 29...
... User-centered design is central to extracting value from the digital twin. Verification, Validation, and Uncertainty Quantification VVUQ is essential for the responsible development, implementation, monitoring, and sustainability of digital twins.
From page 30...
... The challenges lie in the features that set digital twins apart from traditional modeling and simulation, with the most important difference being the bidirectional feedback loop between the virtual and the physical. Evolution of the physical counterpart in real-world use conditions, changes in data collection hardware and software, noisiness of data, addition and deletion of data sources, changes in the distribution of the data shared with the virtual twin, changes in the prediction and/or decision tasks posed to the digital twin, and evolution of the digital twin virtual models all have consequences for VVUQ.
From page 31...
... . Particularly unique to digital twins is inclusion of uncertainties due to integration of multiple modalities of data and models, and bidirectional and sometimes realtime interaction between the virtual representation, the physical counterpart, and the possible human-in-the-loop interactions.
From page 32...
... Conclusion 2-2: Digital twins require VVUQ to be a continual process that must adapt to changes in the physical counterpart, digital twin virtual models, data, and the prediction/decision task at hand. A gap exists between the class of problems that has been considered in traditional modeling and simulation settings and the VVUQ problems that will arise for digital twins.  The importance of a rigorous VVUQ process for a potentially powerful tool such as a digital twin cannot be overstated.
From page 33...
... One wonders: Is it the methods themselves that pose a risk to the human enterprise, or is it the way in which they are deployed without due attention to VVUQ and certification? When it comes to digital twins and their deployment in critical engineering and scientific applications, humanity cannot afford the cavalier attitude that pervades other applications of AI.
From page 34...
... In both the biomedical workshop and atmospheric and climate sciences workshop on digital twins, speakers warned of the bias inherent in algorithms due to missing data as a result of historical and systemic biases (NASEM 2023a,b)
From page 35...
... Below, the committee identifies some novel challenges that arise in the context of digital twins.  By virtue of the personalized nature of a digital twin (i.e., the digital twin's specificity to a unique asset, human, or system) , the virtual construct aggregates sensitive data, potentially identifiable or re-identifiable, and models that offer tailored insights about the physical counterpart.


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