Simulation-Informed Decision Making for Managers

Simulation-Informed Decision Making for Managers



Computer simulations are increasingly relied upon to inform business management and regulatory decisions ranging from new product innovation to regulatory approval of complex, high-consequence systems. Business managers and regulatory authorities routinely utilize a combination of simulation, experimental testing, and experience with previous systems when making design, performance, and safety decisions. When simulation is integrated with physical testing and previous operational experience with similar systems, the decision-making process is said to be simulation-informed. Regardless of the balance between simulation, testing, and experience, and computer simulation, each should be viewed as an information source that (a) supports a specific decision-making process, and (b) is assessed with regard to credibility, objectivity, completeness, and interpretability. Key contributors to simulation information quality are the activities of verification, model validation, and uncertainty quantification due to all relevant sources. These activities provide additional, independent, evidence concerning information quality beyond the qualifications and experience of the analyst conducting the simulation. The value proposition of simulation quality should be viewed as a trade-off between increased confidence in simulation results versus increased risk by management and regulators of using simulation results with unknown or unsupported credibility.




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About the speakers

Dr Oberkampf

Dr. Oberkampf is an engineering consultant working with various government laboratories and business organizations in both the US and Europe. He specializes in issues concerning computational modeling and simulation, particularly verification, model validation and experimental activities, model parameter calibration, sensitivity analyses, uncertainty quantification, and risk assessment. He has taught over 50 short courses on these topics both in the US, Europe, and China. He has published over 180 journal articles, book chapters, and conference papers. He is the co-author of “Verification and Validation in Scientific Computing,” Cambridge University Press, 2010. He served in staff and management positions at Sandia National Laboratories over a period of 29 years. Early in his career, he was a faculty member in the Department of Mechanical Engineering at the University of Texas at Austin. He earned his PhD in Aerospace Engineering from the University of Notre Dame in 1970. He has received the Outstanding Engineering Graduate Award from the University of Notre Dame. He is a Fellow of the American Institute of Aeronautics and Astronautics and NAFEMS.


Dr. Martin Pilch

Dr. Martin Pilch earned a PhD in Nuclear Engineering (1981) from the University of Virginia. Currently, MPilchConsulting specializes in establishing the credibility of computer simulations, verification, validation, uncertainty quantification, and risk assessment for engineering applications spanning the full spectrum of engineering disciplines. Pilch retired in 2016 from Sandia National Laboratories after 35 years of service, having held distinguished staff, management, and program positions. Pilch played a key transformational role within the laboratory for the development, demonstration, and deployment of methodologies for Quantifying Margins and Uncertainties (QMU) that support risk-informed decisions affecting the stockpile of US nuclear weapons. He also played a central role in the first large scale integration of high-end modeling and simulation with more traditional testing for a major nuclear weapon life extension program. He previously managed for six years the V&V sub-element of the Advanced Simulation and Computing Program at Sandia and was a line manager of the Validation and Uncertainty Quantification Department in the Engineering Sciences Center. As the V&V Program Manager, Pilch managed an R&D and applications portfolio with a goal of establishing credibility and quantifying uncertainties in the use of high-end modeling and simulation for a wide range of nuclear weapon issues. Pilch spent the first nineteen years of his career developing and validating models for severe accident issues associated with the operation of nuclear power plants. During this time, he participated in and led major activities using a risk-informed approach, which integrated modeling and experiments in a probabilistic framework, for addressing and resolving safety issues that arose because of the accident at Three Mile Island.