The UQ Toolkit (UQTk) is a collection of libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.0.4 offers intrusive and non-intrusive methods for propagating input uncertainties through computational models, tools for sensitivity analysis, methods for sparse surrogate construction, and Bayesian inference tools for inferring parameters from experimental data.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Harati, Ehsan; Ahmadi Noubari, Hossein: A novel model predictive controller for uncertain constrained systems (2016)
- Xiao, H.; Wu, J.-L.; Wang, J.-X.; Sun, R.; Roy, C. J.: Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: a data-driven, physics-informed Bayesian approach (2016)