射流泵装置性能预测方法

提出了一种射流泵装置性能预测方法,并进行了试验验证.以射流泵试验所得射流泵的流量比与压力比曲线,以及离心泵的流量扬程曲线作为预测初始条件,通过射流泵装置2种吸上高度4.5和9.0 m的性能试验,比较各流量比时装置工况点试验值与预测值精度,发现数值解法整体误差较小,能更好地反映射流泵扬程随流量比变化的情况,但与试验值相比仍存在误差且个别工况点误差较大,需进一步修正.引入预测值与试验值的比值作为修正系数,通过Plackett-Burman试验设计,从吸上高度、面积比、喷嘴直径、流量比、喉嘴距、喉管长径比、泵转速等因子中筛选出对射流泵扬程影响效应显著的面积比及流量比作为修正公式的关键参数,利用遗传算法和公式自动搜索拟合,得到射流泵扬程的计算公式,且相关系数超过0.99.通过射流泵装置在吸上高度为3.5和8.0 m的试验结果比较,表明具有较高的可信度.

Analytical method for predicting of hydraulic performance of jet pump installations

An analytical method for predicting hydraulic performance of a jet pump installation was proposed by updating the existing graphic method and validated experimentally. Based on the measured dimensionless head-flow rate curve of a jet pump and the head-flow rate curve of a centrifugal pump, the hydraulic performance curves of the jet pump installation were predicted at various dimensionless flow rates and compared with those measured at 4.5 m and 9.0 m suction heights, respectively. It turned out that that the error in the analytical method is overall lower than in the graphic method, as a result, the dependence of the jet pump head on its dimensionless flow rate has been even better represented by the former. Note that the error at a few operating points still is notably large, obviously, an update on the method is need. In do so, a correction factor, i.e. the ratio of a predicted head to the tested head was used to correct the jet pump head H_c. Then influences of suction height, area ratio, nozzle diameter, flow rate ratio, distance between throat and nozzle, length of throat and pump rotational speed on H_c were identified by employing Plackett-Burman experimental design method. The critical factors affecting the correction factor was found to be the area ratio and flow rate ratio. Finally, an empirical formula for the correction factor was best fitted(correlation coefficient 0.99)by using genetic algorithm in terms of flow rate q and area ratio m. The predicted jet pump heads were contrasted with those measured at 3.5 m and 8.0 m suction heights. It was shown that the errors in the head are less than 5% at each working point. Thus, the heads predicted are subject to a high reliability.