Webinars

Simulation is essential to modern engineering, but even sophisticated models can differ significantly from physical reality. Uncertain inputs, simplifying assumptions, incomplete physics, numerical approximations, and real-world variability can all contribute to disagreement between simulation and test data. This webinar presents a practical statistical framework for understanding why these differences occur and what they mean for engineering decisions. Using modern methods including design of experiments, Gaussian process modeling, and statistical calibration, participants will learn how to identify sources of disagreement, quantify prediction uncertainty, determine which inputs and assumptions matter most, and use physical data to calibrate and improve simulation models. The webinar is available as a one-hour technical session, with practical examples and a software demonstration, or a 30-minute management briefing focused on the framework, its engineering and business value, and practical applications. The methods presented are implemented in SmartUQ 11.1, originally developed for a Fortune 100 jet engine company and now used by Fortune 500 companies across multiple industries.