Federal agencies, including the US Department of Defense, the US Department of Energy, the National Institutes of Health, and the National Science Foundation, should develop new crosscutting programs to advance the mathematical, statistical, and computational foundations underlying digital twin technologies, says a new report from the National Academies of Sciences, Engineering, and Medicine.
Digital twins hold immense potential to accelerate scientific discovery, drive improvements in climate sciences, and revolutionize health care, manufacturing, and other sectors, but an integrated agenda is needed to harmonize research across sectors and focus efforts on realistic applications.
“Digital twins have great promise in bringing value across areas of science and technology, including engineering, the natural world, and medicine. Our report makes clear that there is a real opportunity here to bring together domains and disciplines in new, valuable ways, but to achieve that value requires investment in interdisciplinary foundations,” said Karen Willcox, director of the Oden Institute for Computational Engineering and Sciences and professor of aerospace engineering and engineering mechanics at The University of Texas at Austin and chair of the committee that wrote the report. “There are serious research questions to tackle, and any responsible development of digital twin technologies must maintain an integral focus on establishing and maintaining trust.”
A digital twin uses modeling and simulation to create a virtual representation that mimics the structure, context, and behavior of a physical counterpart. The report sets down a cohesive definition for the term “digital twin,” emphasizing that, in addition to modeling and simulation, there should also be bidirectional interaction between the virtual and physical, forming a feedback loop that allows the digital twin to take in data from the physical counterpart and update itself. The twin should have predictive capability and inform decision-making for the physical counterpart. Such decisions may be fully automated, comprise recommendations to inform a human’s decision, or fall somewhere in between.
Establishing trust in digital twins is a foundational need, and the report says that it is critical that verification, validation, and uncertainty quantification―processes to determine whether a computer program correctly solves the equations of the mathematical model, to determine the degree to which the model is an accurate representation of the real world, and to quantify uncertainties within the model’s calculations―be deeply embedded in the technologies from design to deployment.
The report says research into digital twins could translate into improved decision-making in biomedical settings, enhanced capabilities for making weather forecasts and simulating climate variability and change, and lead to more efficient operations and production strategies. Advances in digital twins could also open up new avenues for scientific and industrial growth and innovation.