Uncertainty Quantification: Beyond Probability
Abstract: The need to account for uncertainty is intuitively self-evident across all technical communities, but there is less concurrence on the means of doing it. Within the confines of our own communities we’re tempted to believe that the methods we use are widely accepted as canonical. However, diverse approaches have been adopted to uncertainty quantification using methods based on fundamentally disparate concepts, uncertainty metrics, and means of analysis. The reasons that an uncertainty method is favored can be many: ease of application, simplicity of communication, economy of required analytical resources, defensibility of quantification, practicality of standardization, and conceptual acceptability, among others. Because communities can attach different weights to these criteria, preferred approaches differ. In this presentation, Dr. Steve Unwin will look at the pros and cons of a range of quantitative uncertainty characterization approaches.
Bio: Dr. Unwin's career has centered on the development of uncertainty and risk-analytic methodologies, their application to multi-domain problems of national and commercial importance, and the founding of businesses on those capabilities. He has developed methods and models for risk-informed decision-making that continue to be applied in numerous sectors, including nuclear energy, oil & gas, power grid infrastructure, renewable energy, national security, climate adaptation, the chemical process industries, and the fossil energy sector. Before joining Pacific Northwest National Laboratory in 2006 he founded Brookhaven National Laboratory's Safety Integration Group, SAIC's Risk & Reliability Management Division, Battelle's Integrated Risk Management Group, and Unwin Company - Integrated Risk Management which is a continuing risk management resource to commercial and government clients. He has contributed substantially to the international literature on risk and uncertainty, and currently supports numerous federal sponsors in the risk-informed management of programs and resources. He holds a bachelors degree in physics from Imperial College, London and a doctorate in theoretical physics from the University of Manchester, UK.
