Numerical Simulation and Parametric Reduced Order Modeling of the Natural Convection of Water-Copper Nanofluid

In this article, a coupled computational framework is presented for the numerical simulation of mass transfer under the effects of natural convection phenomena in a field contains water-copper nano-fluid. this cfd model is build up based on accurate algorithms for spatial derivatives and time integration. the spatial derivatives have been calculated using first order upwind and second order central differencing approaches. also, time integration is performed using the fourth order runge-kutta method. a parametric reduced order model is developed to compute the whole flow field under the effects of some important parameters. this model is constructed using pod-snapshots method based on karhunen-loeve decomposition. the pod modes have been calculated based on the solution of an eigenvalues problem. the obtained eigenfunctions are pod modes which are arranged using energy-based criteria based on total kinetic energy of the flow field. this approach leads to the model order reduction procedure, and the outcome model can be used as a surrogate model of cfd high order model. the results obtained from the reduced order model show close agreements to the benchmark dns data and proving high accuracy of the proposed model.