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Stohastic modelling of nanofluid heat transfer

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.

stochastic modeling ; nanofluid ; heat transfer ; stochastic collocation

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