基于邊界渦量動力學(xué)理論的離心泵葉輪水力優(yōu)化研究
發(fā)布時間：2019-06-19 16:24
【摘要】：離心泵在國民經(jīng)濟生產(chǎn)和生活中有廣泛的應(yīng)用前景,但其葉輪水力設(shè)計理論和方法陳舊,仍存在諸多問題,進行離心泵葉輪的優(yōu)化設(shè)計研究意義重大。本文立足于江蘇省研究生培養(yǎng)創(chuàng)新工程項目“基于邊界渦量流的離心泵葉輪內(nèi)流診斷和水力優(yōu)化研究”,運用邊界渦量動力學(xué)理論對離心泵進行內(nèi)流診斷分析,研究內(nèi)流參數(shù)邊界渦量流(BVF)與離心泵水力性能參數(shù)之間的內(nèi)在聯(lián)系和規(guī)律,以內(nèi)流參數(shù)為目標(biāo):一方面研究BP網(wǎng)絡(luò)和徑向基函數(shù)網(wǎng)絡(luò)(RBF)兩種不同人工神經(jīng)網(wǎng)絡(luò)(ANN)對離心泵葉輪內(nèi)流參數(shù)預(yù)測可靠性的影響;另一方面研究遺傳算法(GA)和粒子群算法(PSO)兩種智能優(yōu)化算法對離心泵葉輪優(yōu)化設(shè)計結(jié)果的影響,確定應(yīng)用于離心泵葉輪水力性能的多目標(biāo)遺傳算法的優(yōu)化策略。本文的主要研究內(nèi)容及結(jié)論如下:1.BVF分布和離心泵內(nèi)流場及外特性的關(guān)系。首先以一臺流道式離心泵為研究對象,采用數(shù)值模擬方法獲得了模型泵葉輪內(nèi)部流場的局部流動細(xì)節(jié),重點分析了葉片壓力面和吸力面附近的不良流動狀況;結(jié)合邊界渦量動力學(xué)理論,分析了葉片壓力面和吸力面上的BVF、摩擦力線以及渦線分布規(guī)律,揭示了BVF分布與葉片表面流動分離、漩渦產(chǎn)生與耗散以及水力性能之間的內(nèi)在聯(lián)系。研究表明:葉輪內(nèi)表面的BVF峰值和均值越低,BVF分布均勻指數(shù)越高,葉輪內(nèi)部流動狀況越好,流動分離得到抑制,流體對葉輪的做功效果越好,葉輪的揚程和效率更高。2.人工神經(jīng)網(wǎng)絡(luò)在離心泵內(nèi)流參數(shù)預(yù)測中的應(yīng)用研究�；贛ATLAB平臺的二次開發(fā)功能,探究隱含層數(shù)、徑向基函數(shù)的擴展速度分別對BP神經(jīng)網(wǎng)絡(luò)和RBF神經(jīng)網(wǎng)絡(luò)性能預(yù)測精度的影響;然后以預(yù)測值和CFD計算值的誤差范數(shù)作為評判兩種神經(jīng)網(wǎng)絡(luò)預(yù)測性能優(yōu)劣的標(biāo)準(zhǔn),選取適用于離心泵葉輪內(nèi)流參數(shù)預(yù)測的最優(yōu)人工神經(jīng)網(wǎng)絡(luò)。研究表明:當(dāng)隱含層取18時,BP神經(jīng)網(wǎng)絡(luò)預(yù)測誤差最小,神經(jīng)網(wǎng)絡(luò)結(jié)構(gòu)最優(yōu);當(dāng)徑向基函數(shù)擴展速度Spread取0.3時,RBF網(wǎng)絡(luò)預(yù)測誤差最小,神經(jīng)網(wǎng)絡(luò)結(jié)構(gòu)最優(yōu)。將兩者預(yù)測結(jié)果對比分析后發(fā)現(xiàn):RBF神經(jīng)網(wǎng)絡(luò)的預(yù)測誤差更小,程序運行時間更短,運行穩(wěn)定性更高。3.基于智能優(yōu)化算法的離心泵葉輪水力性能優(yōu)化方法研究。研究并建立了以內(nèi)流場參數(shù)BVF為優(yōu)化目標(biāo)的離心泵葉輪水力優(yōu)化問題的數(shù)學(xué)模型,確定了對應(yīng)的約束條件和優(yōu)化變量;確定了優(yōu)化目標(biāo)及優(yōu)化變量的取值范圍和編、解碼方案;對比了GA和PSO在離心泵葉輪水力優(yōu)化問題中的適用性,對算法進行改進獲得了適用于離心泵葉輪水力優(yōu)化的最優(yōu)算法,并制定了高效可靠的尋優(yōu)策略。研究表明:以BVF為優(yōu)化目標(biāo),應(yīng)用GA和PSO對離心泵葉輪進行單目標(biāo)優(yōu)化,效果良好,而且GA的優(yōu)化結(jié)果葉輪1,無論從內(nèi)流場分布還是外特性參數(shù),均優(yōu)于基于PSO得到的結(jié)果葉輪2,但以BVF峰值為目標(biāo),無法保證葉輪表面BVF均勻性指數(shù)最優(yōu);以BVF峰值和均勻指數(shù)為目標(biāo),應(yīng)用多目標(biāo)遺傳算法對離心泵葉輪進行求解,優(yōu)化后的葉輪3的內(nèi)部流動得到改善,葉輪表面BVF均勻指數(shù)也得到提高,且優(yōu)于葉輪2的相關(guān)參數(shù),葉輪的揚程和效率都相應(yīng)提升。結(jié)合RBF神經(jīng)網(wǎng)絡(luò)的多目標(biāo)遺傳算法,其全局尋優(yōu)能力強,程序運行時間短,最優(yōu)結(jié)果的精度高。
[Abstract]:The centrifugal pump has a wide application prospect in the production and life of the national economy, but the hydraulic design theory and method of the impeller are old, there are still many problems, and the optimization design of the centrifugal pump impeller is of great significance. In this paper, based on the "Study on the internal flow diagnosis and hydraulic optimization of centrifugal pump impeller based on boundary vortex flow" of Jiangsu Post-graduate Training Innovation Project, the internal relationship and the law of the internal flow parameter boundary vorticity flow (BVF) and the hydraulic performance parameters of the centrifugal pump are studied by using the boundary vorticity dynamics theory to analyze the internal flow of the centrifugal pump. The internal flow parameters are the target: on the one hand, the influence of two different artificial neural networks (ANN) of BP network and radial basis function network (ANN) on the prediction reliability of the internal flow parameters of the impeller of the centrifugal pump is studied. On the other hand, the influence of two intelligent optimization algorithms of genetic algorithm (GA) and particle swarm optimization (PSO) on the optimization design of the impeller of centrifugal pump is studied, and the optimization strategy of the multi-objective genetic algorithm applied to the hydraulic performance of the impeller of the centrifugal pump is determined. The main contents and conclusions of this paper are as follows:1. The relationship between the BVF distribution and the flow field and the external characteristics in the centrifugal pump. In this paper, a flow channel type centrifugal pump is used as the research object, and the numerical simulation method is adopted to obtain the local flow detail of the flow field inside the model pump impeller, and the adverse flow conditions near the pressure surface of the blade and the suction surface are emphatically analyzed, and the boundary vortex quantity dynamics theory is combined. The relationship between the distribution of BVF and the flow separation of the blade surface, the generation and dissipation of the vortex and the hydraulic performance of the BVF, the friction line and the distribution of the vortex line on the pressure surface and the suction surface of the blade are analyzed. The results show that the lower the BVF peak and the mean value of the inner surface of the impeller, the higher the distribution of BVF, the better the internal flow of the impeller, the better the flow separation, the better the effect of the fluid on the impeller, and the higher the lift and the efficiency of the impeller. The application of artificial neural network in the prediction of internal flow parameters of centrifugal pump. based on the secondary development function of the MATLAB platform, the influence of the hidden layer number and the expansion speed of the radial basis function on the performance prediction precision of the BP neural network and the RBF neural network is explored, and then the error norm of the predicted value and the CFD calculation value is used as a standard for judging the performance of the two neural networks to predict the performance, The optimal artificial neural network for the prediction of the internal flow parameters of the impeller of the centrifugal pump is selected. The results show that when the implicit layer is 18, the prediction error of the BP neural network is the least, the structure of the neural network is optimal, and when the spreading speed of the radial basis function is 0.3, the prediction error of the RBF network is the least, and the structure of the neural network is optimal. It is found that the prediction error of the RBF neural network is smaller, the program running time is shorter, and the running stability is higher. Research on hydraulic performance optimization of centrifugal pump impeller based on intelligent optimization algorithm. The mathematical model of the hydraulic optimization problem of the centrifugal pump impeller with the internal flow field parameter BVF as the optimization target is studied and the corresponding constraint condition and the optimization variable are determined, and the value range and the coding and decoding scheme of the optimization target and the optimization variable are determined. The applicability of GA and PSO in the hydraulic optimization of centrifugal pump impeller is compared, and the algorithm is improved to obtain the optimal algorithm suitable for the hydraulic optimization of the impeller of the centrifugal pump, and an efficient and reliable optimization strategy is developed. The results show that, with BVF as the optimization target, the single-objective optimization of the centrifugal pump impeller with GA and PSO is optimized, the effect is good, and the optimization result of GA is superior to the result impeller 2 based on the particle swarm optimization, whether the internal flow field distribution or the external characteristic parameter, but the BVF peak is the target, in that invention, the uniform index of the BVF of the surface of the impeller can not be guaranteed, the BVF peak value and the uniform index are used as the target, the multi-objective genetic algorithm is applied to solve the centrifugal pump impeller, the internal flow of the optimized impeller 3 is improved, and the uniform index of the BVF on the surface of the impeller is also improved, And the lift and the efficiency of the impeller are correspondingly improved. Combined with the multi-objective genetic algorithm of the RBF neural network, the global optimization capability is strong, the program running time is short, and the optimal result is high in precision.
【學(xué)位授予單位】：江蘇大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TH311
本文編號：2502478
[Abstract]:The centrifugal pump has a wide application prospect in the production and life of the national economy, but the hydraulic design theory and method of the impeller are old, there are still many problems, and the optimization design of the centrifugal pump impeller is of great significance. In this paper, based on the "Study on the internal flow diagnosis and hydraulic optimization of centrifugal pump impeller based on boundary vortex flow" of Jiangsu Post-graduate Training Innovation Project, the internal relationship and the law of the internal flow parameter boundary vorticity flow (BVF) and the hydraulic performance parameters of the centrifugal pump are studied by using the boundary vorticity dynamics theory to analyze the internal flow of the centrifugal pump. The internal flow parameters are the target: on the one hand, the influence of two different artificial neural networks (ANN) of BP network and radial basis function network (ANN) on the prediction reliability of the internal flow parameters of the impeller of the centrifugal pump is studied. On the other hand, the influence of two intelligent optimization algorithms of genetic algorithm (GA) and particle swarm optimization (PSO) on the optimization design of the impeller of centrifugal pump is studied, and the optimization strategy of the multi-objective genetic algorithm applied to the hydraulic performance of the impeller of the centrifugal pump is determined. The main contents and conclusions of this paper are as follows:1. The relationship between the BVF distribution and the flow field and the external characteristics in the centrifugal pump. In this paper, a flow channel type centrifugal pump is used as the research object, and the numerical simulation method is adopted to obtain the local flow detail of the flow field inside the model pump impeller, and the adverse flow conditions near the pressure surface of the blade and the suction surface are emphatically analyzed, and the boundary vortex quantity dynamics theory is combined. The relationship between the distribution of BVF and the flow separation of the blade surface, the generation and dissipation of the vortex and the hydraulic performance of the BVF, the friction line and the distribution of the vortex line on the pressure surface and the suction surface of the blade are analyzed. The results show that the lower the BVF peak and the mean value of the inner surface of the impeller, the higher the distribution of BVF, the better the internal flow of the impeller, the better the flow separation, the better the effect of the fluid on the impeller, and the higher the lift and the efficiency of the impeller. The application of artificial neural network in the prediction of internal flow parameters of centrifugal pump. based on the secondary development function of the MATLAB platform, the influence of the hidden layer number and the expansion speed of the radial basis function on the performance prediction precision of the BP neural network and the RBF neural network is explored, and then the error norm of the predicted value and the CFD calculation value is used as a standard for judging the performance of the two neural networks to predict the performance, The optimal artificial neural network for the prediction of the internal flow parameters of the impeller of the centrifugal pump is selected. The results show that when the implicit layer is 18, the prediction error of the BP neural network is the least, the structure of the neural network is optimal, and when the spreading speed of the radial basis function is 0.3, the prediction error of the RBF network is the least, and the structure of the neural network is optimal. It is found that the prediction error of the RBF neural network is smaller, the program running time is shorter, and the running stability is higher. Research on hydraulic performance optimization of centrifugal pump impeller based on intelligent optimization algorithm. The mathematical model of the hydraulic optimization problem of the centrifugal pump impeller with the internal flow field parameter BVF as the optimization target is studied and the corresponding constraint condition and the optimization variable are determined, and the value range and the coding and decoding scheme of the optimization target and the optimization variable are determined. The applicability of GA and PSO in the hydraulic optimization of centrifugal pump impeller is compared, and the algorithm is improved to obtain the optimal algorithm suitable for the hydraulic optimization of the impeller of the centrifugal pump, and an efficient and reliable optimization strategy is developed. The results show that, with BVF as the optimization target, the single-objective optimization of the centrifugal pump impeller with GA and PSO is optimized, the effect is good, and the optimization result of GA is superior to the result impeller 2 based on the particle swarm optimization, whether the internal flow field distribution or the external characteristic parameter, but the BVF peak is the target, in that invention, the uniform index of the BVF of the surface of the impeller can not be guaranteed, the BVF peak value and the uniform index are used as the target, the multi-objective genetic algorithm is applied to solve the centrifugal pump impeller, the internal flow of the optimized impeller 3 is improved, and the uniform index of the BVF on the surface of the impeller is also improved, And the lift and the efficiency of the impeller are correspondingly improved. Combined with the multi-objective genetic algorithm of the RBF neural network, the global optimization capability is strong, the program running time is short, and the optimal result is high in precision.
【學(xué)位授予單位】：江蘇大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TH311
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