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Study on finite deformation finite element analysis algorithm of turbine blade based on CPU+GPU heterogeneous parallel computation

机译:基于CPU + GPU异构并行计算的涡轮叶片有限变形有限元分析算法研究

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Blade is one of the core components of turbine machinery. The reliability of blade is directly related to the normal operation of plant unit. However, with the increase of blade length and flow rate, non-linear effects such as finite deformation must be considered in strength computation to guarantee enough accuracy. Parallel computation is adopted to improve the efficiency of classical nonlinear finite element method and shorten the blade design period. So it is of extraordinary importance for engineering practice. In this paper, the dynamic partial differential equations and the finite element method forms for turbine blades under centrifugal load and flow load are given firstly. Then, according to the characteristics of turbine blade model, the classical method is optimized based on central processing unit + graphics processing unit heterogeneous parallel computation. Finally, the numerical experiment validations are performed. The computation speed of the algorithm proposed in this paper is compared with the speed of ANSYS. For the rectangle plate model with mesh number of 10 k to 4000 k, a maximum speed-up of 4.31 can be obtained. For the real blade-rim model with mesh number of 500 k, the speed-up of 4.54 times can be obtained.
机译:叶片是涡轮机械的核心部件之一。叶片的可靠性直接关系到机组的正常运行。但是,随着叶片长度和流量的增加,在强度计算中必须考虑诸如有限变形之类的非线性影响,以确保足够的精度。采用并行计算可提高经典非线性有限元方法的效率并缩短叶片设计周期。因此,对于工程实践而言,它具有极其重要的意义。本文首先给出了涡轮叶片在离心载荷和流载荷作用下的动力学偏微分方程和有限元方法形式。然后,根据涡轮叶片模型的特点,基于中央处理单元+图形处理单元的异构并行计算对经典方法进行了优化。最后,进行数值实验验证。将本文提出的算法的计算速度与ANSYS的速度进行了比较。对于网格数为10 k到4000 k的矩形板模型,可以获得4.31的最大加速。对于网格数为500 k的真实叶片-轮辋模型,可以获得4.54倍的加速。

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