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| DOI：10.13522/j.cnki.ggps.2023480 |
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| Efficiency and hydraulic performance of the micro-pressure filter in front of the pump studied using PPR and NSGA-II |
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TAO Hongfei, LI Qi, ZHOU Yang, Mahemujiang·Aihemaiti, LI Qiao, JIANG Youwei
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1. College of Water Conservancy and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China;
2. Xinjiang Key Laboratory of Water Conservancy Engineering Safety and Water Disaster Control, Urumqi 830052, China;
3. Xinjiang Institute of Water Resources and Hydropower Research, Urumqi 830049, China
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| Abstract: |
| 【Objective】Pump often has a filter installed in the front of it to filter sediments and debris. This paper studied its efficiency and performance.【Method】The study was based on physical model, with flow rate being 2-8 m3/h, sediment content being 0.5-2.0 g/L. The area of the filter varied from 1 105 to 2 060 cm2, and water separator type was Type 1, Type 2, Type 3. Without a separator was the control. A prediction model was used to evaluate sediment interception and total filtration efficiency. Based on these measurements, we determined the optimal operating conditions for the pump.【Result】The factors that influenced water head loss across the filter were ranked in the order of inlet flow > sediment content > filter area; the factors that affected the quality of sediment interception were ranked in the order of sediment content > filter area > inlet flow; the factors impacting the total filtration efficiency were ranked in the order of filter area > sediment content > inlet flow. The accuracy of the PPR model for predicting sediment interception quality and total filtration efficiency was 100%, with a relative error less than 10%, while its accuracy for predicting water head loss across the filter was 70%, which needs further improvement. The optimal operating conditions for the filter were sand content 2 g/L, inlet water flow rate 7 m3/h, and filter area 2 060 cm2.【Conclusion】The PPR prediction model was accurate for sediment interception and total filtration efficiency, but it resulted in errors for calculating water head loss across the filter. Dimensional analysis and multiple regression can be used as an alternative to predict the water head loss. |
| Key words: filter; head loss; model; hydraulic performance; filtration performance |
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