Uncertainty Quantification and Propagation for ACORN

Learn about uncertainty quantification and propagation methods specifically applied to the ACORN framework in this 33-minute conference talk by Lukas Peron from IPhT-TV. Explore the mathematical foundations and practical implementation of uncertainty analysis techniques, examining how uncertainties are identified, measured, and propagated through complex systems within the ACORN computational environment. Discover methodologies for quantifying various sources of uncertainty, including parametric, model, and numerical uncertainties, and understand how these uncertainties affect final results and predictions. Gain insights into statistical approaches, Monte Carlo methods, and other computational techniques used to assess and manage uncertainty in scientific computing applications. Examine case studies and examples that demonstrate the practical application of these uncertainty quantification methods, providing valuable knowledge for researchers and practitioners working with computational models and simulations where uncertainty analysis is critical for reliable results.