Development of effluent removal prediction model efficiency in septic sludge treatment plant through clonal selection...

Area of Science:

• Environmental Engineering
• Artificial Intelligence
• Biotechnology

Background:

• Septic sludge treatment plants (SSTP) are crucial for wastewater management, particularly in regions like Sarawak, Borneo.
• Sequence batch reactor (SBR) technology is commonly employed in SSTPs, but predicting effluent quality remains a challenge.
• Effective effluent monitoring is essential to prevent environmental pollution and ensure regulatory compliance.

Purpose of the Study:

• To develop a novel predictive model for effluent discharge from septic sludge treatment plants (SSTP).
• To utilize a clonal selection algorithm (CSA), inspired by artificial immune systems (AIS), for SSTP performance forecasting.
• To assess the model's accuracy in predicting key effluent parameters like chemical oxygen demand (COD) and total suspended solids (TSS).

Main Methods:

• A clonal selection algorithm (CSA) was developed, mimicking the human immune system's adaptive capabilities.
• The CSA was applied to model the behavior of Sequence Batch Reactor (SBR) based septic sludge treatment plants.
• Monthly effluent data from Matang and Sibu SSTPs in Sarawak (2007-2012) were used for model training and cross-validation.

Main Results:

• The CSA-based SSTP model demonstrated high accuracy in predicting effluent performance.
• The model achieved successful long-term predictions: up to 84 months for Chemical Oxygen Demand (COD) and 109 months for Total Suspended Solids (TSS).
• Performance was evaluated using Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Correction Coefficient (R).

Conclusions:

• The developed CSA-based SSTP model serves as a beneficial engineering tool for forecasting long-term plant performance.
• This predictive capability helps prevent future environmental imbalances by ensuring compliance with effluent discharge standards.
• The study highlights the potential of artificial immune systems in environmental management and wastewater treatment optimization.