發(fā)布時(shí)間：2018-01-20 05:29

  本文關(guān)鍵詞： 軸流泵 程序集成 最優(yōu)拉丁超立方設(shè)計(jì) 優(yōu)化設(shè)計(jì) 徑向基神經(jīng)網(wǎng)絡(luò)　出處：《排灌機(jī)械工程學(xué)報(bào)》2017年06期 　論文類型：期刊論文

【摘要】：參數(shù)化設(shè)計(jì)和計(jì)算流體力學(xué)被廣泛應(yīng)用于流體機(jī)械的優(yōu)化設(shè)計(jì).采用旋轉(zhuǎn)機(jī)械設(shè)計(jì)軟件CFturbo對(duì)軸流泵進(jìn)行水力設(shè)計(jì).為縮短優(yōu)化周期,基于Isight多學(xué)科優(yōu)化平臺(tái),通過編寫批處理命令將CFturbo與PumpLinx集成,實(shí)現(xiàn)了軸流泵的CFD自動(dòng)優(yōu)化.以提高軸流泵的水力效率為優(yōu)化目標(biāo),采用最優(yōu)拉丁超立方設(shè)計(jì)對(duì)葉輪和導(dǎo)葉的7個(gè)設(shè)計(jì)變量進(jìn)行空間采樣,設(shè)計(jì)了72組方案.基于PumpLinx的數(shù)值模擬結(jié)果,建立了目標(biāo)函數(shù)與設(shè)計(jì)變量之間的徑向基神經(jīng)網(wǎng)絡(luò)模型,并采用多島遺傳算法對(duì)其進(jìn)行優(yōu)化,結(jié)果表明:數(shù)值模擬結(jié)果與試驗(yàn)結(jié)果吻合較好,且徑向基神經(jīng)網(wǎng)絡(luò)模型能準(zhǔn)確預(yù)測(cè)軸流泵效率與設(shè)計(jì)變量的關(guān)系.優(yōu)化后,設(shè)計(jì)點(diǎn)效率提高了4.46%,而揚(yáng)程幾乎不變.通過Pareto圖分析,獲得了設(shè)計(jì)變量對(duì)目標(biāo)影響的顯著水平,可為軸流泵的優(yōu)化設(shè)計(jì)提供一定的參考.
[Abstract]:Parametric design and computational fluid dynamics (CFD) are widely used in the optimization design of fluid machinery. The hydraulic design of axial flow pump is carried out by the rotating machine design software CFturbo. Based on the Isight multidisciplinary optimization platform, CFturbo and PumpLinx are integrated by writing batch commands. The CFD automatic optimization of axial flow pump is realized. In order to improve the hydraulic efficiency of axial flow pump, the optimal Latin hypercube design is used to sample the seven design variables of impeller and guide vane. 72 groups of schemes are designed. Based on the numerical simulation results of PumpLinx, the radial basis function neural network model between the objective function and the design variables is established, and the multi-island genetic algorithm is used to optimize the model. The results show that the numerical simulation results are in good agreement with the experimental results, and the radial basis function neural network model can accurately predict the relationship between the axial flow pump efficiency and the design variables. After optimization, the design point efficiency is increased by 4.46%. By Pareto diagram analysis, the significant level of the influence of the design variables on the target is obtained, which can provide a certain reference for the optimization design of the axial flow pump.
【作者單位】： 江蘇大學(xué)國(guó)家水泵及系統(tǒng)工程技術(shù)研究中心;江蘇省水利工程科技咨詢有限公司;
【基金】：國(guó)家科技支撐計(jì)劃項(xiàng)目(2015BAD20B01) 江蘇省水利科技項(xiàng)目(2015042) 江蘇高校自然科學(xué)研究項(xiàng)目(09KJB570001)
【分類號(hào)】：TH312
【正文快照】： 陸榮,袁建平,李彥軍,等.基于神經(jīng)網(wǎng)絡(luò)模型和CFD的軸流泵自動(dòng)優(yōu)化[J].排灌機(jī)械工程學(xué)報(bào),2017,35(6):481-487.LU Rong,YUAN Jianping,LI Yanjun,et al.Automatic optimization of axial flow pump based on radial basis functions neural net-work and CFD[J].Journal of drain

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