Webinars

Modern engineering development depends on simulation, test, and digital twin data, but extracting reliable insight from these data can be challenging. Modern design of experiments (DOEs) enable engineers to collect the most informative data efficiently, while surrogate models trained with the collected data can provide fast, accurate predictions of complex system behavior. Statistical calibration can be used as part of the process to better align simulations and surrogate models with physical data such as from test, experiment, or operational data while accounting for uncertainty and model discrepancy. Statistical calibration has the benefit of being unique in its ability to calibrate models by addressing disagreement due to both uncertainty in model parameters and due to the model form (e.g. modeling assumptions and simplifications). Fast predicting statistically calibrated surrogate models can be used as digital twins due to their ability to provide real-time predictions that remain aligned with observed physical system behavior. SmartUQ has implemented all these capabilities in an industry leading statistics and machine learning software package now in version 11.1. SmartUQ software is used by many Fortune 500 companies across a wide range of industries. Join us for this webinar in which SmartUQ Principal Application Engineer, Gavin Jones, will introduce the SmartUQ software for engineering applications. Customer use cases and demonstrations will be included as part of the presentation.