Arash Karimipour

Bio: Arash Karimipour is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Nanofluid & Heat transfer. The author has an hindex of 65, co-authored 257 publications receiving 10833 citations. Previous affiliations of Arash Karimipour include Virginia Tech College of Natural Resources and Environment & University of Sistan and Baluchestan.

Mixed convection of copper-water nanofluid in a shallow inclined lid driven cavity using the lattice Boltzmann method

Abstract: The goal of this work is to study the laminar mixed convection of water–Cu nanofluid in an inclined shallow driven cavity using the lattice Boltzmann method. The upper lid of the cavity moves with constant velocity, U 0 , and its temperature is higher than that of the lower wall. The side walls are assumed to be adiabatic. The effects of different values of the cavity inclination angle and nanoparticles volume fraction at three states of free, force and mixed convection domination are investigated while the Reynolds number is kept fixed as Re = 100 and Re = 10 . Validation of present results with those of other available ones shows a suitable agreement. Streamlines, isotherms, Nusselt numbers, and velocity and temperature profiles are presented. More Nusselt numbers can be achieved at larger values of the inclination angle and nanoparticles volume fraction at free convection domination. Results imply the appropriate ability of LBM to simulate the mixed convection of nanofluid in a shallow inclined cavity.

Simulation of copper-water nanofluid in a microchannel in slip flow regime using the lattice Boltzmann method

Abstract: Laminar forced convection heat transfer of water–Cu nanofluids in a microchannel was studied utilizing the lattice Boltzmann method (LBM). The entering flow was at a lower temperature compared to the microchannel walls. Simulations were performed for nanoparticle volume fractions of 0.00 to 0.04 and slip coefficient from 0.005 to 0.02. The model predictions were found to be in good agreement with earlier studies. The effects of wall slip velocity and temperature jump of the nanofluid were studied for the first time by using lattice Boltzmann method. Streamlines, isotherms, longitudinal variations of Nusselt number, slip velocity and temperature jump as well as velocity and temperature profiles for different cross sections were presented. The results indicate that LBM can be used to simulate forced convection for the nanofluid micro flows. Moreover, the effect of the temperature jump on the heat transfer rate is significant. Also, the results showed that decreasing the values of slip coefficient enhances the convective heat transfer coefficient and consequently the Nusselt number (Nu) but increases the wall slip velocity and temperature jump values.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Numerical Heat Transfer And Fluid Flow

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