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To simulate the coupled plasma and fluid flow physics of dielectric-barrier discharge, a plasma-fluid model is utilized in conjunction with a compressible flow solver. The flow solver is responsible for determining the bulk flow kinetics of dominant neutral background species including mole fractions, gas temperature, pressure and velocity. The plasma solver determines the kinetics and energetics of the plasma species and accounts for finite rate chemistry. In order to achieve maximum reliability and best performance, we have utilized state-of-the-art numerical and theoretical approaches for the simulation of DBD plasma actuators. In this respect, to obtain a stable and accurate solution method, we tested and compared different existing numerical procedures, including operator-splitting algorithm, super-timestepping, and solution of the Poisson and transport equations in a semi-implicit manner. The implementation of the model is conducted in OpenFOAM. Four numerical test cases are considered in order to validate the solvers and to investigate the drawbacks/benefits of the solution approaches. The test problems include single DBD actuator driven by positive, negative and sinusoidal voltage waveforms, similar to the ones that could be found in literature. The accuracy of the results strongly depends to the choice of time step, grid size and discretization scheme. The results indicate that the super-time-stepping treatment improves the computational efficiency in comparison to explicit schemes. However, the semiimplicit treatment of the Poisson and transport equations showed better performance compared to the other tested approaches.

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The effects of surface waviness (k = 0, 0.125, 0.25, 0.5) and nanoparticle dispersion (/ = 0, 0.05, 0.1) on solidification of Cu-water nanofluid inside a vertical enclosure are investigated numerically for different Grashof number (Gr = 10 5 , 10 6 , 10 7 ). An enthalpy porosity technique is used to trace the solid and liquid interface. Comparisons with previously published works show the accuracy of the obtained results. A maximum of 25.9% relative variation of freezing time with surface waviness was observed for k = 0.5, while the relative variation of freezing time with nanoparticles in comparison with surface waviness was negative for high values of k. It was observed that surface waviness can be used to control the solidification time based on enhancing different mechanism of solidification.

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