Abstract Design optimization of structural and multidisciplinary systems under uncertainty
has been an active area of research due to its evident advantages over deterministic design …

Ever-increasing demands of uncertainty-based design, analysis, and optimization in
aerospace vehicles motivate the development of Monte Carlo methods with wide …

In this work, a data-driven technique is proposed for efficient design exploration and
optimisation of the Kaplan turbine. To avoid the curse of dimensionality, the proposed …

In this chapter we introduce a combined parameter and model reduction methodology and
present its application to the efficient numerical estimation of a pressure drop in a set of …

Inexpensive surrogates are useful for reducing the cost of science and engineering studies
involving large-scale, complex computational models with many input parameters. A ridge …

We perform a Bayesian calibration of the freestream velocity and density starting from
measurements of the pressure and heat flux at the stagnation point of a hypersonic high …

Integrated hydrological modeling of domains with complex subsurface features requires
many highly uncertain parameters. Performing a global uncertainty analysis using an …

View Video Presentation: https://doi. org/10.2514/6.2022-0075. vid Integrated computational
materials engineering (ICME) calls for integrating simulation tools and/or experiments to …

In global sensitivity analysis and ensemble-based model calibration, it is essential to create
a large enough sample of model simulations with different parameters that all yield plausible …

Aleatory and epistemic uncertainties are being increasingly incorporated in verification,
validation, and uncertainty quantification (UQ). However, the crucial UQ of high efficiency …