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Performance analysis and modelling of circular jets aeration in an open channel using soft computing techniques
Diksha Puri1, Raj Kumar2, Sushil Kumar3
1School of Environmental Science, Shoolini University, Solan, Himachal Pradesh, 173229, India.
Scientific Reports
|February 7, 2024
Summary
Aeration enhances dissolved oxygen (DO) in water, crucial for water quality. This study found Artificial Neural Networks (ANN) accurately predict aeration efficiency, with channel angle being the most influential factor.
Area of Science:
- Environmental Engineering
- Water Quality Management
- Fluid Mechanics
Background:
- Dissolved oxygen (DO) is a critical indicator of water quality, often depleted by eutrophication.
- Aeration is the primary method for increasing DO concentrations in aquatic systems.
- Understanding aeration efficiency in open channels is vital for effective water treatment.
Purpose of the Study:
- To experimentally investigate the aeration efficiency (E20) of circular jets in open channels.
- To model the relationship between aeration efficiency and key input parameters.
- To develop and compare soft computing models for predicting aeration efficiency.
Main Methods:
- Experimental investigation of aeration efficiency with varying channel inclination, discharge, and number of jets.
- Statistical analysis to determine significant aeration parameters (8-64 jets).
- Development of Artificial Neural Network (ANN), M5P, and Random Forest (RF) models using WEKA software.
Main Results:
- ANN demonstrated superior performance in predicting aeration efficiency (CC=0.9823, MAE=0.0098, RMSE=0.0123).
- Sensitivity analysis identified channel angle of inclination as the most influential factor.
- Discharge and number of jets were also significant predictors of aeration efficiency.
Conclusions:
- Artificial Neural Networks provide a highly accurate method for predicting aeration efficiency in open channels.
- Channel angle of inclination is the most critical parameter influencing aeration.
- The study offers valuable insights for optimizing aeration systems to improve water quality.
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