Browsing by Author "Kuo, F. -A."

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A true-direction reconstruction of the quiet direct simulation method for inviscid gas flows
(2013-11-01)
Lin, Y. -J.
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Smith, M. R.
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Kuo, F. -A.
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Cave, H. M.
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Huang, J. -C.
In this paper, a true-direction flux reconstruction of the second-order quiet direct simulation (QDS-2N) Smith et al. (2009)[3] as an equivalent Euler equation solver, called QDS-N-2, is proposed. Because of the true-directional nature of QDS, where volume-to-volume (true-direction) fluxes are computed, as opposed to fluxes at cell interfaces as employed by traditional finite volume schemes, a volumetric reconstruction is required to reach a totally true-direction scheme. The conserved quantities are permitted to vary (according to a polynomial expression) across all simulated dimensions. Prior to the flux computation, QDS particles are introduced using properties based on weighted moments taken over the polynomial reconstruction of the conserved quantity fields. The resulting flux expressions are shown to exactly reproduce the existing second-order extension for a one-dimensional flow, while providing a means for true multi-dimensional reconstruction. The new reconstruction is demonstrated in several verification studies. These include a shock-bubble interaction problem, an Euler-four-shock interaction problem, and the advection of a vortical disturbance. These results are presented, and the increased computation time and the effect of higher-order extension are discussed in this paper. The results show that the proposed multi-dimensional reconstruction provides a significant increase in the accuracy of the solution. We show that, despite the increase in the computational expense, the computational speed of the proposed QDS-N-2 method is several times higher than that of the previously proposed QDS-2N scheme for a fixed degree of numerical accuracy, at least, for the test problem of the advection of vertical disturbances. (C) 2013 Published by Elsevier B.V.
Development of parallel direct simulation Monte Carlo method using a cut-cell Cartesian grid on a single graphics processor
(2014-09-20)
Lo, M. -C.
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Su, C. -C.
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Wu, J-S
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Kuo, F. -A.
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機械工程學系
This study developed a parallel two-dimensional direct simulation Monte Carlo (DSMC) method using a cut-cell Cartesian grid for treating geometrically complex objects using a single graphics processing unit (GPU). Transient adaptive sub-cell (TAS) and variable time-step (VTS) approaches were implemented to reduce computation time without a loss in accuracy. The proposed method was validated using two benchmarks: 2D hypersonic flow of nitrogen over a ramp and 2D hypersonic flow of argon around a cylinder using various free-stream Knudsen numbers. We also detailed the influence of TAS and VTS on computational accuracy and efficiency. Our results demonstrate the efficacy of using TAS in combination with VTS in reducing computation times by more than 10x. Compared to the throughput of a single core Intel CPU, the proposed approach using a single GPU enables a 13-35x increase in speed, which varies according to the size of the problem and type of GPU used in the simulation. Finally, the transition from regular reflection to Mach reflection for supersonic flow through a channel was simulated to demonstrate the efficacy of the proposed approach in reproducing flow fields in challenging problems. (C) 2014 Elsevier Ltd. All rights reserved.
Large-scale simulations on multiple Graphics Processing Units (GPUs) for the direct simulation Monte Carlo method
(2012-10-01)
Su, C. -C.
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Smith, M. R.
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Kuo, F. -A.
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Wu, J. -S.
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Hsieh, C. -W.
In this study, the application of the two-dimensional direct simulation Monte Carlo (DSMC) method using an MPI-CUDA parallelization paradigm on Graphics Processing Units (GPUs) clusters is presented. An all-device (i.e. GPU) computational approach is adopted where the entire computation is performed on the GPU device, leaving the CPU idle during all stages of the computation, including particle moving, indexing, particle collisions and state sampling. Communication between the GPU and host is only performed to enable multiple-GPU computation. Results show that the computational expense can be reduced by 15 and 185 times when using a single GPU and 16 GPUs respectively when compared to a single core of an Intel Xeon X5670 CPU. The demonstrated parallel efficiency is 75% when using 16 GPUs as compared to a single GPU for simulations using 30 million simulated particles. Finally, several very large-scale simulations in the near-continuum regime are employed to demonstrate the excellent capability of the current parallel DSMC method. (C) 2012 Elsevier Inc. All rights reserved.
Quiet Direct Simulation (QDS) of Viscous Flow Using the Chapman-Enskog Distribution
(2011-01-01)
Smith, M. R.
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Kuo, F. -A.
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Cave, H. M.
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Jermy, M. C.
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Wu, J. -S.
Presented here is the QDS method modified to employ an arbitrary governing velocity probability distribution. An algorithm is presented for the computation of QDS particle "blueprints". The method, which employs a known continuous velocity probability distribution function, uses a set of fixed QDS particle "weights", which can be arbitrarily selected. Provided the weights, particle "blueprint" velocities are computed by taking multiple moments around the governing velocity probability distribution function to provide the discrete representation employed by QDS. In particular, we focus on the results obtained when the governing distribution function is the Chapman-Enskog distribution function. Results are shown for several benchmark tests including a one dimensional standing shock wave and a two dimensional lid driven cavity problem. Finally, the performance of QDS when applied to General Purpose computing on Graphics Processing Units (GPGPU) is demonstrated.