Robustness and Validation of Model and Digital Twins Deployment

Technical Report · Mon Feb 01 04:00:00 EST 2021

DOI:https://doi.org/10.2172/1770631· OSTI ID:1770631

Stracuzzi, David John ^[1]; Shafer, Jenifer ^[2]; Volkova, Svitana ^[3]; Ray, Jaideep ^[1]; Pullum, Laura ^[4]; Barone, Matt ^[1]; Kramer, Sharlotte ^[1]; Ratner, Dan ^[5]; Glenski, Maria ^[3]; Huang, Andy ^[1]

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1. Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
5. SLAC National Accelerator Lab., Menlo Park, CA (United States)

For digital twins (DTs) to become a central fixture in mission critical systems, a better understanding is required of potential modes of failure, quantification of uncertainty, and the ability to explain a model’s behavior. These aspects are particularly important as the performance of a digital twin will evolve during model development and deployment for real-world operations.

• Research Organization: Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 1770631
• Report Number(s): SAND--2021-1560R; 694541
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING