Stohastic modelling of nanofluid heat transfer

Abstract

In this paper we couple a numerical method aimed at simulation of flow and heat transfer of nanofluids with stochastic modelling of input and material parameters. In order to simulate nanofluids, an in-house numerical method was developed based on the solution of 3D velocity-vorticity formulation of Navier-Stokes equations. Stochastic collocation method (SCM) is used as a wrapper around the deterministic flow simulation code in order to propagate the uncertainty from input to output parameters. One-at-a-time principle is used to detect the most important factors thus reducing stochastic problem from 12 to 5 dimensional one. Then, the full tensor SCM was used to assess the stochastic mean, variance and Sobol-like indices for sensitivity analysis. The results reveals that the uncertainty of input parameters influences the results more strongly in convection dominated flow regimes.

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.