Stochastic analysis of nanofluid simulations

Abstract

In this paper we couple a computational fluid dynamics simulation of flow and heat transfer of nanofluids with stochastic modelling of input parameters. An effective properties numerical model is used to describe nanofluid flow. We simulate the flow and heat transfer in a heated pipe, for which experimental measurements are available. In order to assess the influence of input parameters on the simulation results, we employ the stochastic collocation method (SCM) as a wrapper around the deterministic code. In this way, we are able to propagate the uncertainty from input to output parameters. First, we identify the two most important parameters using the One-at-a- time principle and then, the full tensor SCM was used to assess the stochastic mean, variance and Sobol-like indices for sensitivity analysis.

Mario Cvetković

Associate Professor | Department of Electrical Engineering Fundamentals

Associate professor at FESB in Split, with a research focus on numerical modeling including finite element and moment methods, computational bioelectromagnetics and heat transfer related phenomena. He is involved in IEEE’s ICES Technical Committee 95, various international projects and is committed to advancing both knowledge and practical applications in electromagnetic safety and biomedical engineering.