"Essentially, all models are wrong, but some are useful" – George E. P. Box
The use of simulations to displace physical tests has become essential in accelerating analysis and reducing the cost of research and design. However, simulation results may be substantially different from reality making accurate model calibration and validation critical to achieving desired out comes. Using a method like statistical calibration can characterize model inadequacy by combining aspects of calibration and validation. Statistical calibration can reduce design cycle time and costs by ensuring that simulations are as close to reality as possible and by quantifying how close that really is.
Using case studies, this webinar will walk through the SmartUQ software showing the step-by-step process of statistical calibration and quantifying the uncertainty of the calibration parameters.