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Discrete particle simulation of gas-solid two-phase flows with multi-scale CPU-GPU hybrid computation

机译:多尺度CPU-GPU混合计算的气固两相流离散粒子模拟

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摘要

Though discrete particle simulation (DPS) has been widely used for investigating gas-solid flows from a more detailed level as compared to traditional two-fluid models (TFMs), it is still seriously limited by the computational cost when large scale systems are simulated. CPUs (graphic processing units), with their massive parallel architecture and high floating point performance, provide new possibilities for large-scale DPS. In this paper, a multi-scale CPU (central processing unit)-GPU hybrid computation mode is developed, in which the fluid flow is computed by CPU(s) while the particle motion is computed by GPU(s). To explore its feasibility, this mode is adopted to simulate the flow structures in the fluidization of Geldart D and A particles, respectively. Further coupled with an EMMS (energy minimization multi-scale) based meso-scale model, the flow behavior in an industrial fluidized bed is finally simulated, shedding light on the engineering applications of DPS, as an alternative to TFM.
机译:尽管与传统的两流体模型(TFM)相比,离散粒子模拟(DPS)已被广泛用于从更详细的层次研究气固流,但是在模拟大型系统时,它仍然受到计算成本的严重限制。具有大规模并行架构和高浮点性能的CPU(图形处理单元)为大规模DPS提供了新的可能性。在本文中,开发了一种多尺度CPU(中央处理器)-GPU混合计算模式,其中流体流由CPU计算,而粒子运动由GPU计算。为了探索其可行性,采用这种模式分别模拟了Geldart D和A颗粒流化过程中的流动结构。进一步结合基于EMMS(最小化能量的多尺度)的中尺度模型,最终模拟了工业流化床中的流动行为,为DFM的替代物提供了DPS的工程应用的启示。

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