engleski

Stochastic analysis of nanofluid simulations

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.

Computational fluid dynamics ; Stochastic collocation method ; Variance based sensitivity analysis

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