GPU based numerical simulation of core shooting process
GPU based numerical simulation of core shooting process
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DOI：
10.1007/s41230-017-7172-1
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发表时间：
2017-09
期刊：
影响因子：
1.6
通讯作者：
Yi-zhong Zhang;Gao-chun Lu;Chang-jiang Ni;T. Jing;Lin-long Yang;Qin-fang Wu
中科院分区：
文献类型：
--
作者：
Yi-zhong Zhang;Gao-chun Lu;Chang-jiang Ni;T. Jing;Lin-long Yang;Qin-fang Wu
射芯工艺是砂芯制作中应用最广泛的工艺，对砂芯的质量起着重要的作用。虽然数值模拟有望优化取心过程，但对取心过程的数值模拟研究非常有限。基于双流体模型（TFM）和动摩本构关系，开发了岩心射出过程的三维数值模拟程序，与现场实验结果吻合较好。为了适应工程应用的需要，还采用了图形处理单元（GPU）来提高计算效率。基于CUDA （Compute Unified Device Architecture）平台的并行算法可以显著减少多线程GPU的计算时间。本文采用CUDA并行化方法开发了计算程序，并与高速相机拍摄的现场实验结果进行了对比，保证了计算的准确性。讨论了并行算法的设计与优化。砂芯试件的仿真结果表明，GPU提高了计算效率。开发的程序还通过透明芯盒，高速摄像机和压力测量系统的现场实验进行了验证。并行程序的计算时间减少了近95%，而仿真结果与实验数据仍然很吻合。GPU并行化方法成功解决了三维喷砂模拟程序计算效率低的问题，开发的GPU程序适合工程应用。
Core shooting process is the most widely used technique to make sand cores and it plays an important role in the quality of sand cores. Although numerical simulation can hopefully optimize the core shooting process, research on numerical simulation of the core shooting process is very limited. Based on a two-fluid model (TFM) and a kinetic-friction constitutive correlation, a program for 3D numerical simulation of the core shooting process has been developed and achieved good agreements with in-situ experiments. To match the needs of engineering applications, a graphics processing unit (GPU) has also been used to improve the calculation efficiency. The parallel algorithm based on the Compute Unified Device Architecture (CUDA) platform can significantly decrease computing time by multi-threaded GPU. In this work, the program accelerated by CUDA parallelization method was developed and the accuracy of the calculations was ensured by comparing with in-situ experimental results photographed by a high-speed camera. The design and optimization of the parallel algorithm were discussed. The simulation result of a sand core test-piece indicated the improvement of the calculation efficiency by GPU. The developed program has also been validated by in-situ experiments with a transparent core-box, a high-speed camera, and a pressure measuring system. The computing time of the parallel program was reduced by nearly 95% while the simulation result was still quite consistent with experimental data. The GPU parallelization method can successfully solve the problem of low computational efficiency of the 3D sand shooting simulation program, and thus the developed GPU program is appropriate for engineering applications.