AIMC Topic: Waste Disposal, Fluid

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Optimizing models for the prediction of one step ahead extreme flows to wastewater treatment plants using different synthetic sampling methods.

Journal of environmental management
High-flow events that significantly impact Water Resource Recovery Facility (WRRF) operations are rare, but accurately predicting these flows could improve treatment operations. Data-driven modeling approaches could be used; however, high flow events...

Escaping Historical Lock-in─Redesigning Wastewater Treatment Plants and Their Microbiomes for the 21st Century.

Environmental science & technology
Wastewater treatment plants (WWTPs) have gradually, over the last hundred years, been designed and extended to deal with a sequence of problems, including a) odor, b) suspended solids, c) organics, d) ammonia, e) nitrate and phosphate, and f) recalci...

AI-driven wastewater management through comparative analysis of feature selection techniques and predictive models.

Scientific reports
The integration of artificial intelligence (AI) in wastewater treatment management offers a promising approach to optimizing effluent quality predictions and enhancing operational efficiency. This study evaluates the performance of machine learning m...

Multi-functionalities of citric acid assisted thermal hydrolysis for sludge pretreatment: A novel method assisting in sludge treatment targeting multiple-objectives.

Journal of hazardous materials
Pretreatment is essential for enhancing sludge treatment efficiency, including anaerobic digestion, phosphorus recovery, sludge dewatering, and heavy metal removal. However, few techniques simultaneously address multiple treatment objectives. In this...

Enhancing energy consumption prediction and interpretability in wastewater treatment plants: A novel temporal difference-weighted resampling framework with cross validation for imbalanced regression.

Journal of environmental management
Accurate prediction of energy consumption is crucial for optimizing wastewater treatment plant (WWTP) operations. However, imbalanced data caused by variable influent conditions often compromises machine learning (ML) model accuracy. This study propo...

Machine learning-based optimization of biogas and methane yields in UASB reactors for treating domestic wastewater.

Biodegradation
This study aimed to optimize biogas and methane production from Up-flow anaerobic sludge blanket reactors for treating domestic wastewater using advanced machine learning models-namely, eXtreme Gradient Boosting (XGBoost) and its hybridized form, XGB...

Underestimated roles of phages in biological wastewater treatment systems: Recent advances and challenges.

Journal of hazardous materials
Bacteriophages (phages) are vital components in biological wastewater ecosystems, whose concentrations are far exceeding those bacteria. Despite their importance, they are often overlooked and regarded as the "dark matter" in biological treatment pro...

Optimization of nitrogen removal through an intelligent automated operational strategy based on real-time process simulation in an A2O membrane bioreactor.

Journal of environmental management
In this study, an intelligent automated operational strategy (IAOS) was developed and evaluated to enhance nitrogen removal efficiency in an anaerobic-anoxic-oxic (A2O) membrane bioreactor (MBR). To effectively respond to fluctuations in inflow load,...

Multimodal Learning-Assisted Identification of Effluent Water Quality and Toxicity in Wastewater Treatment Plants.

Environmental science & technology
Effluent of wastewater treatment plants (WWTPs) poses significant ecological risks due to potential biological toxicity, demanding effective monitoring and assessment of water quality and toxicity. However, the complexity of the wastewater treatment ...

Deep reinforcement learning control as an innovative approach for urban drainage systems: review and prospects.

Water research
Urban drainage systems (UDSs) are vital for managing stormwater and wastewater but face growing challenges due to urbanization, climate change and aging infrastructure. Real-time control (RTC) enhances UDSs' performance and circumvents the need for s...