Description: This proposal addresses methods for efficient quantification of margins and uncertainties (QMU) for models that couple multiple, large-scale commercial or proprietary simulation codes, effective methods for treating epistemic uncertainty in large scale simulations, scalability to models with hundreds or thousands of uncertain parameters, and competition with traditional Monte Carlo Based methods. The Reduced-Order Clustering Uncertainty Quantification (ROCUQ) methodology described in this proposal has been under development over the past several years at the University of Illinois, and is being commercialized by IllinoisRocstar LLC. ROCUQ uses a combination of common stratified Monte Carlo techniques, coupled with well-chosen reduced order models, statistical clustering, and a few (less than tens) high-fidelity simulation runs to provide estimates of the uncertainty distributions for the System Response Quantities (SRQs) of interest to the modelers. The goal of the ROCUQ methodology is to minimize the number of high-fidelity, computationally-intensive simulation runs that are needed in order to provide estimates of output uncertainties of interest, especially when it is not possible to run the high-fidelity model more than a few (e.g., 5 to 10) times. ROCUQ has been, or is currently being applied to solid propellant rocket internal ballistics uncertainties, coupled fluid-structure interaction modeling of stresses in an Air Force Training Fighter wing, and structural dynamics/vibration of a specially-designed experimental apparatus for studying simulation validation under uncertainty.

Benefits: This program will provide pathways to two commercial products: software and engineering services. Engineering services: Consulting services will be available based on the extensibility of the proposed system. IllinoisRocstar has the broad-based experience with a wide variety of supercomputing platforms to allow support of the proposed system on platforms located at NASA, DoD components, DOE, and private companies. Assisting companies and government agencies with customization of the reduced-order models for their specific applications will provide a market, as well as a source of reduced-order library models for these services.

This program will provide pathways to two commercial products: software and engineering services. Software: The completed module will be architected in such as manner as to allow introduction of specialized reduced-order model modules without requiring changes to the base software. IllinoisRocstar has significant expertise in building modular, extensible software. As a module operable within the open-source Dakota framework, it will be useable by a wide variety of entities and organizations.