How can we make global sensitivity analysis accessible and viable for engineering practice? In this translation article, we present a methodology to enable sensitivity analysis for structural and geotechnical engineering for built environment design and assessment workflows. Our technique wraps computational mechanics and geomechanics finite element (FE) simulations and combines high-performance computing on public cloud with surrogate modeling using machine learning. A key question we address is: “Is there a noticeable loss in fidelity of results from the sensitivity analysis when substituting a simulation model with a surrogate model?” We answer this question for both linear and nonlinear FE simulations.
