Simulation-Informed Decision Making

William L. Oberkampf, Sandia National Laboratories (retired), wloconsulting@gmail.com

Simulation is becoming the primary tool in predicting the performance, reliability, and safety of engineered systems. Terminology such as “virtual prototyping,” “virtual testing,” and “full physics simulation” are extremely appealing when budgets and schedules are highly constrained, or when competitive pressures convince project managers to move forward with little testing of new systems or manufacturing processes. Many contend that higher fidelity physics modeling, combined with faster computers, is the path forward for improved decision making informed by simulation. I argue that these factors are important, but business managers and policy makers who make consequential decisions also necessitate information on the uncertainty of simulation results. Many of these decision makers understand that some uncertainties are well characterized, whereas some are very poorly understood; potentially not even included in the simulation. To capture a wide range of uncertainty sources and characterizations, the term predictive capability or total predictive capability has been used in certain communities. In contrast to traditional uncertainty estimation which concentrates on random variables, predictive capability attempts to capture all potential sources of uncertainty. These include numerical solution error, model form uncertainty, and uncertainty in the environments and scenarios to which the system could be exposed, either intentionally or unintentionally. This talk will contrast traditional uncertainty quantification approaches and approaches based on imprecise probabilities which can simultaneously include both random variability and lack of knowledge uncertainty. It is argued that imprecise probability approaches are more informative and revealing for a decision makers.

Speaker biosketch

Dr. Oberkampf has 50 years of experience in research and development in fluid dynamics, heat transfer, flight dynamics, and solid mechanics. After his completion of graduate studies at the University of Notre Dame in 1970, he was on the faculty at the University of Texas at Austin until 1979. From 1979 until 2007 he worked at Sandia National Laboratories in both staff and management positions. During the last 25 years, Dr. Oberkampf emphasized research and development in methodologies and procedures for verification, validation, and uncertainty quantification for a wide variety of applications. He has over 185 journal articles, book chapters, conference papers, and reports, and has taught 60 short courses in the field of verification and validation, and uncertainty quantification. He and Prof. Chris Roy co-authored the book Verification and Validation in Scientific Computing published by Cambridge University Press. He is a fellow of the American Institute of Aeronautics and Astronautics and NAFEMS.