Uncertainty is an inescapable reality that can be found in nearly all types of engineering analyses. It arises from sources like measurement inaccuracies, material properties, boundary and initial conditions, and modeling approximations. Moreover, with the increasing use of simulation models throughout industry, it has become vital to include Uncertainty Quantification (UQ) in engineering analysis. This webinar will introduce stochastic methods and Uncertainty Quantification (UQ) tools, discuss industry challenges of implementing them, and then use case studies to demonstrate the benefits of going beyond deterministic analysis.
The competitive benefits of UQ include reduced development time and cost, improved designs, better understanding of risk, and quantifiable confidence in analysis results and engineering decisions. Unfortunately, there are significant obstacles and technical challenges which prevent organizations from utilizing UQ methods and techniques in their engineering practice. This webinar will discuss past and present strategies for addressing these challenges, making it possible to use UQ to enhance engineering processes with fewer resources and in more situations.
The attendees for this webinar would be engineers, program managers, and data scientists who want to gain an understanding of how Uncertainty Quantification can maximize insight, improve design robustness, and increase time and resource efficiency.
