Computer simulation of MHD blood conveying gold nanoparticles as a third grade non-Newtonian nanofluid in a hollow porous vessel

https://cyberleninka.org/article/n/1199103.pdf

Natural convection of sodium alginate (SA) non-Newtonian nanofluid flow between two vertical flat plates by analytical and numerical methods

Heat transfer and flow analysis for SA-TiO2 non-Newtonian nanofluid passing through the porous media between two coaxial cylinders

GPGPU has drawn much attention on accelerating non-graphic applications. The simulation by D3Q19 model of the lattice Boltzmann method was executed successfully on multi-node GPU cluster by using CUDA programming and MPI library. The GPU code runs on the multi-node GPU cluster TSUBAME of Tokyo Institute of Technology, in which a total of 680 GPUs of NVIDIA Tesla are equipped. For multi-GPU computation, domain partitioning method is used to distribute computational load to multiple GPUs and GPU-to-GPU data transfer becomes severe overhead for the total performance. Comparison and analysis were made among the parallel results by 1D, 2D and 3D domain partitionings. As a result, with 384x384x384 mesh system and 96 GPUs, the performance by 3D partitioning is about 3-4 times higher than that by 1D partitioning. The performance curve is deviated from the idealistic line due to the long communicational time between GPUs. In order to hide the communication time, we introduced the overlapping technique between computation and communication, in which the data transfer process and computation were done in two streams simultaneously. Using 8-96 GPUs, the performances increase by a factor about 1.1-1.3 with a overlapping mode. As a benchmark problem, a large-scaled computation of a flow around a sphere at Re=13,000 was carried on successfully using the mesh system 2000x1000x1000 and 100 GPUs. For such a computation with 2 Giga lattice nodes, 6.0h were used for processing 100,000 time steps. Under this condition, the computational time (2.79h) and the data communication time (3.06h) are almost the same.

Multi-GPU performance of incompressible flow computation by lattice Boltzmann method on GPU cluster

The generalized Newtonian fluid, as an important kind of non-Newtonian fluids, has been widely used in both science and engineering. In this paper, we present a multiple-relaxation-time lattice Boltzmann model for generalized Newtonian fluid, and validate the model through a detailed comparison with analytical solutions and some published results. The accuracy and stability of the present model are also studied, and compared with those of the popular single-relaxation-time lattice Boltzmann model. Finally, the limit and potential of the multiple-relaxation-time lattice Boltzmann model are briefly discussed.

Multiple-relaxation-time lattice Boltzmann model for generalized Newtonian fluid flows

A new numerical method for incompressible non-Newtonian fluid flows based on the lattice Boltzmann method (LBM) is proposed. The essence of the present method lies in the determination of shear-dependent viscosity of the fluid by using a variable parameter related to the local shear rate. Also, the relaxation time in the BGK collision term is kept at unity taking account of numerical stability. The method is applied to two representative test case problems, power-law fluid flows in a reentrant corner geometry and non-Newtonian fluid flows in a three-dimensional porous structure. These simulations indicate that the method can be useful for practical non-Newtonian fluid flows, such as shear-thickening (dilatant) and shear-thinning (pseudoplastic) fluid flows.

/pdf/a-numerical-method-for-incompressible-non-newtonian-fluid-3x2metvoeh.pdf

Y. Hotta

Papers

A numerical method for incompressible non-Newtonian fluid flows based on the lattice Boltzmann method