The demand on the predictive capability of modern Computer Aided Engineering (CAE) toolchains constantly increases. This implies that simulation models are not only required to correctly represent the underlying physical system, but also that real-world variability and uncertainty must be taken into account for enabling a shifting of the product development cycle more and more from physical experiments to the computer. Uncertainty quantification (UQ) is key in improving the predictive capabilities of state-of-the-art Computer Aided Engineering (CAE) workflows. Furthermore, it speeds up the product design and development processes, particularly in the early phases of those processes, which not only reduces the time required to develop a product, but also the number of potentially expensive physical experiments. For all our clients as well as all visitors of our website who are interested in UQ and its enormous potential, we would like to provide a white paper as an introduction to the why and how of UQ.
AdCo EngineeringGW bundles know-how from statistics, machine learning and engineering to provide innovative algorithms for the quantification of uncertainties in our software QUEENS. Thereby, we enable our clients to harness the full potential that digital product development tools and processes can offer. Please visit our page on UQ.