發(fā)布時間：2018-07-27 17:18

【摘要】：針對混合潤滑數(shù)值分析將動壓效應(yīng)、彈性變形和界面接觸特性耦合而非常耗時的問題,基于共享內(nèi)存并行系統(tǒng)的多線程程序設(shè)計語言O(shè)penMP,提出一種多線程混合潤滑并行計算數(shù)值方法——紅黑線交叉并行計算法.該并行計算模型是將雷諾方程求解域分成兩個相互獨立的子求解域,依次對兩個子求解域進行并行數(shù)值求解,可以有效克服CPU線程間數(shù)據(jù)爭用問題,加快求解速度.著重研究了并行計算核數(shù)、網(wǎng)格數(shù)量和工作站配置對并行計算性能的影響,分析結(jié)果表明:并行計算模型能夠有效提高滑動軸承混合潤滑計算速度,并行計算速度的提升幅度與并行計算核數(shù)成非線性關(guān)系,隨著CPU核數(shù)的增加計算速度的增加幅度逐漸減小;此外,與內(nèi)存和緩存相比,CPU的主頻對并行計算速度有非常大的影響.
[Abstract]:In view of the problem that the dynamic pressure effect, elastic deformation and interface contact characteristics are coupled by the numerical analysis of mixed lubrication, Based on OpenMP-based multithread programming language of shared memory parallel system, a numerical method of hybrid multithreading lubrication parallel computation, red and black line cross parallel computing method, is proposed. The parallel computing model divides the Reynolds equation into two independent subdomains, and performs the parallel numerical solution of the two subdomains in turn, which can effectively overcome the problem of data contention between CPU threads and speed up the solution. The effects of parallel computing kernel number, mesh number and workstation configuration on parallel computing performance are emphatically studied. The results show that the parallel computing model can effectively improve the speed of hybrid lubrication calculation of sliding bearings. The increase of parallel computing speed has a nonlinear relationship with the number of parallel computing kernels, and decreases gradually with the increase of the number of CPU kernels. In addition, the main frequency of CPU has a great influence on parallel computing speed compared with memory and cache.
【作者單位】： 重慶大學機械傳動國家重點實驗室;重慶大學汽車工程學院;四川大學空天科學與工程學院;
【基金】：國家自然科學基金資助項目(51375506,51475051)
【分類號】：TH133.31;TH117.2
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本文編號：2148573