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| 1 | Numerical Prediction and Performance Experiment in a Deep-well Centrifugal Pump with Different Impeller Outlet Width显示文摘The existing research of the deep-well centrifugal pump mainly focuses on reduce the manufacturing cost and improve the pump performance,and how to combine above two aspects together is the most difficult and important topic.In this study,the performances of the deep-well centrifugal pump with four different impeller outlet widths are studied by the numerical,theoretical and experimental methods in this paper.Two stages deep-well centrifugal pump equipped with different impellers are simulated employing the commercial CFD software to solve the Navier-Stokes equations for three-dimensional incompressible steady flow.The sensitivity analyses of the grid size and turbulence model have been performed to improve numerical accuracy.The flow field distributions are acquired and compared under the design operating conditions,including the static pressure,turbulence kinetic energy and velocity.The prototype is manufactured and tested to certify the numerical predicted performance.The numerical results of pump performance are higher than the test results,but their change trends have an acceptable agreement with each other.The performance results indicted that the oversize impeller outlet width leads to poor pump performances and increasing shaft power.Changing the performance of deep-well centrifugal pump by alter impeller outlet width is practicable and convenient,which is worth popularizing in the engineering application.The proposed research enhances the theoretical basis of pump design to improve the performance and reduce the manufacturing cost of deep-well centrifugal pump. | SHI Weidong ZHOU Ling LU Weigang PEI Bing LANG Tao | 2013 | Chinese Journal of Mechanical Engineering2013，26，1： | 20 |
| 2 | 基于GRBF神经网络的多级煤气压缩系统建模显示文摘以某钢厂燃气、蒸汽联合循环发电机组煤气压缩系统为背景,建立以煤水分离器、离心式压缩机和冷却器为核心的多级煤气压缩系统机理模型.采用自适应遗传算法辨识机理模型中某些难以确定的重要参数.由于多级煤气压缩系统的影响因素较多,机理模型预测结果不精确.利用基于广义径向基函数的神经网络补偿机理模型的误差,建立GRBF神经网络和机理模型并联的多级煤气系统的混合模型.试验结果表明相比于机理模型,混合模型有更高的预测精度. | 褚菲 董世建 王福利 王小刚 | 2012 | 东北大学学报(自然科学版)2012，33，7： | 1 |
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