ASME V&V Conferences

SmartUQ at ASME V&V 2018

Hyatt Regency Minneapolis, Minneapolis, MN

May 16 - 18

We invite you to stop by our booth at ASME V&V 2018; meet experts in engineering analytics and uncertainty quantification, see demonstrations, and explore how SmartUQ can improve your analysis.

Meet Us

Conference Tutorial

Industry Challenges in Uncertainty Quantification: Bridging the Gap Between Simulation and Test

May 18 - 10:30 AM to 12:35 PM EDT - Room: Great Lakes A1
Presented by Dr. Mark Andrew, SmartUQ Technology Steward

This tutorial will provide an overview of UQ concepts and methodology and discuss the strategies for addressing these challenges. One of the strategies is performing statistical calibration to understand how well numerical simulation represents reality. Using a case study for illustration, the tutorial will sequentially walk through the statistical calibration process used to quantify uncertainties for simulations and physical experiments. Attendees should leave the tutorial with an understanding of UQ concepts and techniques, how to apply statistical calibration to their combined simulation and testing environments, and the fundamental value that UQ brings.

Conference Presentation

Uncertainty Quantification and Digital Engineering Applications in Turbine Engine System Design and Life Cycle Management

May 17 - 1:30 PM to 3:35 PM EDT - Room: Great Lakes A1
Kevin O'Flaherty, SmartUQ Application Engineer

This presentation illustrates both conceptual and practical applications of using Uncertainty Quantification (UQ) techniques to perform probabilistic analyses. The application of UQ techniques to the output from engineering analyses using model-based approaches is essential to providing critical decision-quality information at key decision points in a aerospace system’s life cycle. Approaches will be presented for the continued collection and application of UQ knowledge over each stage of a generalized life cycle framework covering system design, manufacture, and sustainment. The use of this approach allows engineers to quantify and reduce uncertainties systematically and provides decision makers with probabilistic assessments of performance, risk, and costs which are essential to critical decisions. As an illustration, a series of probabilistic analyses performed as part of the initial design of a turbine blade will be used to demonstrate the utility of UQ in identifying program risks and improving design quality. The application of UQ concepts to life cycle management will be addressed, highlighting the benefits to decision makers of having actionable engineering information throughout a system’s life cycle.