Head Loss Prediction Model for a Pontoon Mesh Rotary Filter Based on Dimensional Analysis

This study aims to investigate the effects of filtration flow rate (260–400 m3/h) and backwash flow rate (1.02–1.50 m3/h) on the head loss characteristics of a pontoon mesh rotary filter (PMRF) under clean water conditions. A series of physical model experiments were conducted to analyze the impacts of filtration and backwash flow rates on head loss. A predictive model for head loss was developed using ANOVA, dimensional analysis, and multiple linear regression. The results indicated that the filtration flow rate significantly influenced head loss, exhibiting a power-law relationship, whereas the impact of the backwash flow rate was relatively minor. The developed predictive model for head loss showed high accuracy (R2=0.9910, root-mean-square error=0.0314 m). Model validation revealed that the mean relative error between predicted and observed values was only 1.19%, with a maximum relative error of 2.27%. This predictive model provides an effective tool for predicting head loss in PMRFs under clean water conditions, offering valuable guidance for design optimization and practical applications, while also contributing to the datasets on the hydraulic performance of prepump filters.