摘要
为减小射流泵装置在含沙水流中运行时射流泵遭到的磨损破坏,对射流泵的抗磨损性能进行优化.首先提出了一种经济有效的材料表面磨损情况预测方法,再利用该方法得到抗磨损性能最佳的参数组合.结合粒子垂直撞击平板试验与数值模拟结果,得到在特定材料(316L不锈钢)下的磨损等高线图,并通过不同喷嘴出口速度的垂直撞击平板试验对磨损等高线图的通用性进行了试验验证,结果证实该方法可用于预测.通过Plackett-Burman试验设计得到显著影响材料磨损情况的射流泵参数,利用D-optimal试验设计得到性能最佳的射流泵参数组合.结果表明:当射流泵的参数组合为喷嘴角度39.85°、面积比5.84、喷嘴直径18 mm时,射流泵的抗磨损性能和水力性能都达到最佳,即最大磨损深度8.6μm、效率16.8%.根据最佳参数组合加工射流泵样机,验证了预测结果的可靠性,并通过扫描电镜对喷嘴处的磨损疤痕进行观察,结论与数值模拟分析结果一致.
The wear of solid particles is a major concern in the fluid transporting field,which affects the efficiency or even causes safety problems like abrupt failure.Wear damages within jet pumps and other fluid equipments are prevalent in the process industries where sands are found,such as the deep well jet pump device,especially the suction chamber around its nozzle.To mitigate the wear,the anti-wear performance of the jet pump is optimized.For saving the cost of material wear test,a prediction method through combining a wear map of specific material(316L stainless steel)and numerical simulation results were proposed.Then three parameters(nozzle angle,area ratio and nozzle exit dia-meter)were chosen to be optimized,following Plackett-Burman experimental design.After that,the optimal combination of parameters was obtained from the multi-objective optimization(high efficiency and low erosion rate)through D-optimal factorial design experiments.The results show that the new model provides a wear reduction and is validated by the test.According to the observations of nozzle wear scars by scanning electron microscopy(SEM),the conclusion is consistent with the results of numerical simulation analysis.
作者
邹晨海
李红
THOMPSON Harvey
KHATIR Zindine
向清江
ZOU Chenhai;LI Hong;THOMPSON Harvey;KHATIR Zindine;XIANG Qingjiang(National Research Center of Pumps,Jiangsu University,Zhenjiang,Jiangsu 212013,China;Machinery School,Leeds University,Leeds,LS29JT,UK)
出处
《排灌机械工程学报》
EI
CSCD
北大核心
2020年第2期109-114,共6页
Journal of Drainage and Irrigation Machinery Engineering
基金
“十三五”国家重点研发专项(2017YFD0201502)
国家自然科学基金资助项目(51379090)
关键词
射流泵
磨损
试验设计
预测方法
jet pump
wear
experimental design
prediction method
