Multi-fidelity uncertainty quantification of irradiated particle-laden turbulence

TL;DR

This paper develops multi-fidelity methods to efficiently quantify uncertainties in complex, high-cost simulations of irradiated particle-laden turbulence, reducing computational effort while maintaining accuracy.

Contribution

It introduces and assesses multi-fidelity strategies specifically tailored for uncertainty quantification in turbulent flow simulations involving particles.

Findings

Multi-fidelity methods significantly reduce computational costs.

The approach achieves accurate uncertainty estimates with fewer high-fidelity simulations.

Validated on a solar energy receiver flow case.

Abstract

The study of complex systems is often based on computationally intensive, high-fidelity, simulations. To build confidence in the prediction accuracy of such simulations, the impact of uncertainties in model inputs on the quantities of interest must be measured. This, however, requires a computational budget that is a possibly large multiple of the cost of a single simulation, and thus may become infeasible for expensive simulation models featuring a large number of uncertain inputs and highly nonlinear behavior. Therefore, this work explores multi-fidelity strategies to accelerate the estimation of the effect of uncertainties. The main idea behind multi-fidelity models is to utilize cheaper, lower-fidelity models - than the intended high-fidelity, expensive model of the problem - to generate a baseline solution that together, with relatively small number of high-fidelity simulations can lead to accurate predictions. The methods are briefly presented, and their performance assessed on an irradiated particle-laden turbulent flow case related to Stanford's PSAAP II particle-based solar energy receiver.