Engineering organizations must increasingly rely on computational simulation for design and predicted performance, reliability, and safety of systems. Computational analysts, designers, decision makers, and project managers who rely on simulation should have practical techniques and methods for assessing simulation credibility.
This webinar presents an introduction to the topics of verification, validation, and predictive capability. These topics are applicable to essentially all engineering and science applications, including fluid dynamics, heat transfer, solid mechanics, and structural dynamics. The mathematical models for the systems of interest are typically given by partial differential or integral equations representing initial value and boundary value problems. The computer codes that implement the mathematical models can be developed by commercial, corporate, government, or research organizations; but they should all be subjected to rigorous testing by way of verification procedures. The accuracy of the mathematical models coded into software are assessed by way of comparisons of results with experimental measurements; referred to as validation activities.
This webinar will sketch a framework for incorporating a wide range error and uncertainty sources identified during the mathematical modeling, verification, and validation processes, with the goal of estimating the total predictive uncertainty of the simulation. This is referred to as predictive capability because typically no experimental measurements are available for the systems or subsystems at the application conditions of interest.
Welcome & Introduction
-Mr. Andrew Wood, NAFEMS Americas, Regional Representative
Verification, Validation, and Predictive Capability: What's What?
-Dr. William Oberkampf, Engineering Consultant
-Prof. Christopher Roy, Virginia Tech
Q & A Session
|Authors||Oberkampf. W Roy. C|
|Date||28th May 2015|