Computational fluid dynamics(CFD)was used in conjunction with BP neural network to study theflow resistance characteristic of the combination-channel inside hydraulic manifold block(HMB).The in-put parameters of the c...Computational fluid dynamics(CFD)was used in conjunction with BP neural network to study theflow resistance characteristic of the combination-channel inside hydraulic manifold block(HMB).The in-put parameters of the combination-channel model were confirmed to have effect on the pressure-drop bythe numerical method,and a BP neural network model was accordingly constructed to predict the channelpressure-drops.The flow resistance characteristic curves of various channels were achieved,and a perfor-mance parameter was given to evaluate the through-flow characteristic of the channel according to thecurves.The predictions are' in agreement with the numerical computation,indicating that the method canbe utilized to accurately determine the flow characteristic of the combination channel with high efficiency.展开更多
Y2001-62725-523 0118856在 ATM 网络中基于浑沌神经网络的新的 VC 路由选择算法=A novel VC routing algorithm based on chaoticneural network in ATM networks[会,英]/Zhang,S.&Lv,G.//2000 IEEE International Symposium on Ci...Y2001-62725-523 0118856在 ATM 网络中基于浑沌神经网络的新的 VC 路由选择算法=A novel VC routing algorithm based on chaoticneural network in ATM networks[会,英]/Zhang,S.&Lv,G.//2000 IEEE International Symposium on Cir-cuits and Systems,Vol.3.—523～526(HC)在 ATM 网络中给定特殊 VP 拓扑结构,提出基于VC 路由选择算法的浑沌神经网络,此网络有更多测度,是瞬时浑沌和稳定收敛的,模拟说明此算法对 VC路由选择是有效的。展开更多
Minipump is widely used in microfluidics system, active cooling system, etc. But building a high efficiency minipump is still a challenging problem. In this paper, a systematic method was developed to design, characte...Minipump is widely used in microfluidics system, active cooling system, etc. But building a high efficiency minipump is still a challenging problem. In this paper, a systematic method was developed to design, characterize and optimize a particular mechanical minipump. The optimization work was conducted to cope with the conflict between pressure head and hydraulic efficiency by an improved back-propagation neural network （BPNN） with the non-dominated sorting genetic algorithm-II （NSGA-II）. The improved BPNN was utilized to predicate hydraulic performance and, moreover, was modified to improve the prediction accuracy. The NSGA-II was processed for minipump multi-objective optimization which is dominated by four impeller dimensions. During hydraulic optimization, the processing feasibility was also taken into consideration. Experiments were conducted to validate the above optimization methods. It was proved that the optimized minipump was improved by about 24 % in pressure head and 4.75 % in hydraulic efficiency compared to the original designed prototype. Meanwhile, the sensitivity test was used to analyze the influence of the four impeller dimensions. It was found that the blade outlet angle β2 and the impeller inlet diameter Do significantly influence the pressure head H and the hydraulic efficiency η, respec- tively. Detailed internal flow fields showed that the optimum model can relieve the impeller wake and improve both the pressure distribution and flow orientation.展开更多
基金the National Natural Science Foundation of China(No.50375023)
文摘Computational fluid dynamics(CFD)was used in conjunction with BP neural network to study theflow resistance characteristic of the combination-channel inside hydraulic manifold block(HMB).The in-put parameters of the combination-channel model were confirmed to have effect on the pressure-drop bythe numerical method,and a BP neural network model was accordingly constructed to predict the channelpressure-drops.The flow resistance characteristic curves of various channels were achieved,and a perfor-mance parameter was given to evaluate the through-flow characteristic of the channel according to thecurves.The predictions are' in agreement with the numerical computation,indicating that the method canbe utilized to accurately determine the flow characteristic of the combination channel with high efficiency.
文摘Y2001-62725-523 0118856在 ATM 网络中基于浑沌神经网络的新的 VC 路由选择算法=A novel VC routing algorithm based on chaoticneural network in ATM networks[会,英]/Zhang,S.&Lv,G.//2000 IEEE International Symposium on Cir-cuits and Systems,Vol.3.—523～526(HC)在 ATM 网络中给定特殊 VP 拓扑结构,提出基于VC 路由选择算法的浑沌神经网络,此网络有更多测度,是瞬时浑沌和稳定收敛的,模拟说明此算法对 VC路由选择是有效的。
文摘Minipump is widely used in microfluidics system, active cooling system, etc. But building a high efficiency minipump is still a challenging problem. In this paper, a systematic method was developed to design, characterize and optimize a particular mechanical minipump. The optimization work was conducted to cope with the conflict between pressure head and hydraulic efficiency by an improved back-propagation neural network （BPNN） with the non-dominated sorting genetic algorithm-II （NSGA-II）. The improved BPNN was utilized to predicate hydraulic performance and, moreover, was modified to improve the prediction accuracy. The NSGA-II was processed for minipump multi-objective optimization which is dominated by four impeller dimensions. During hydraulic optimization, the processing feasibility was also taken into consideration. Experiments were conducted to validate the above optimization methods. It was proved that the optimized minipump was improved by about 24 % in pressure head and 4.75 % in hydraulic efficiency compared to the original designed prototype. Meanwhile, the sensitivity test was used to analyze the influence of the four impeller dimensions. It was found that the blade outlet angle β2 and the impeller inlet diameter Do significantly influence the pressure head H and the hydraulic efficiency η, respec- tively. Detailed internal flow fields showed that the optimum model can relieve the impeller wake and improve both the pressure distribution and flow orientation.
