AIMC Topic: Waste Disposal, Fluid

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Constructing porous ZnFC-PA/PSF composite spheres for highly efficient Cs removal.

Journal of environmental sciences (China) May 20, 2023
Radioisotope leaking from nuclear waste has become an intractable problem due to its gamma radiation and strong water solubility. In this work, a novel porous ZnFC-PA/PSF composite sphere was fabricated by immobilization of ferrocyanides modified zin...
Cesium Water Pollutants, Chemical Polymers Adsorption Sulfones Wastewater Porosity Water Purification Zinc Waste Disposal, Fluid
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Artificial intelligence and machine learning-based monitoring and design of biological wastewater treatment systems.

Bioresource technology Dec 14, 2022
Artificial intelligence (AI) and machine learning (ML) are currently used in several areas. The applications of AI and ML based models are also reported for monitoring and design of biological wastewater treatment systems (WWTS). The available inform...
Wastewater Water Purification Waste Disposal, Fluid Artificial Intelligence Machine Learning
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Water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system.

Environmental research Feb 19, 2022
Wastewater recycling is the measure with enormous potentiality to achieve carbon neutrality in wastewater treatment plants. High-precision online monitoring can improve the stability of wastewater treatment system and help wastewater recycling. A new...
Waste Disposal, Fluid Carbon Water Quality Reproducibility of Results Deep Learning Wastewater Water Purification
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Application of deep learning for predicting the treatment performance of real municipal wastewater based on one-year operation of two anaerobic membrane bioreactors.

The Science of the total environment Nov 24, 2021
In this study, data-driven deep learning methods were applied in order to model and predict the treatment of real municipal wastewater using anaerobic membrane bioreactors (AnMBRs). Based on the one-year operating data of two AnMBRs, six parameters r...
Anaerobiosis Bioreactors Membranes, Artificial Wastewater Deep Learning Waste Disposal, Fluid
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ANN based modelling of hydrodynamic cavitation processes: Biomass pre-treatment and wastewater treatment.

Ultrasonics sonochemistry Dec 28, 2020
We have developed artificial neural network (ANN) based models for simulating two application examples of hydrodynamic cavitation (HC) namely, biomass pre-treatment to enhance biogas and degradation of organic pollutants in water. The first case repo...
Neural Networks, Computer Wastewater Biomass Waste Disposal, Fluid Hydrodynamics
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Combined effects of volume ratio and nitrate recycling ratio on nutrient removal, sludge characteristic and microbial evolution for DPR optimization.

Journal of environmental sciences (China) Dec 17, 2020
The optimization of volume ratio (V/V/V) and nitrate recycling ratio (R) in a two-sludge denitrifying phosphorus removal (DPR) process of Anaerobic Anoxic Oxic-Moving Bed Biofilm Reactor (A/O-MBBR) was investigated. The results showed that prolonged ...
Sewage Waste Disposal, Fluid Denitrification Bioreactors Nutrients Biofilms In Situ Hybridization, Fluorescence Nitrogen Phosphorus Nitrates
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Predicting the higher heating value of syngas pyrolyzed from sewage sludge using an artificial neural network.

Environmental science and pollution research international Dec 6, 2019
Sludge pyrolysis is a complex process including complicated reaction chemistry, phase transition, and transportation phenomena. To better evaluate the use of syngas, the monitoring and prediction of a higher heating value (HHV) is necessary. This stu...
Waste Disposal, Fluid Catalysis Sewage Neural Networks, Computer Temperature Heating Pyrolysis
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Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach.

Chemosphere Nov 25, 2019
Polymer-assisted flocculation-dewatering of mineral processing tailings (MPT) is crucial for its environmental disposal. To reduce the number of laboratory experiments, this study proposes a novel and hybrid machine learning (ML) method for the predi...
Waste Disposal, Fluid Principal Component Analysis Minerals Flocculation Polymers Machine Learning
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An influent responsive control strategy with machine learning: Q-learning based optimization method for a biological phosphorus removal system.

Chemosphere Jun 14, 2019
Biological phosphorus removal (BPR) is an economical and sustainable processes for the removal of phosphorus (P) from wastewater, achieved by recirculating activated sludge through anaerobic and aerobic (An/Ae) processes. However, few studies have sy...
Biological Oxygen Demand Analysis Sewage Metabolism Models, Theoretical Water Pollutants, Chemical Wastewater Models, Biological Algorithms Phosphorus Machine Learning Bioreactors Waste Disposal, Fluid
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Sequential treatment of paper and pulp industrial wastewater: Prediction of water quality parameters by Mamdani Fuzzy Logic model and phytotoxicity assessment.

Chemosphere Apr 5, 2019
Recycling of industrial wastewater meeting quality standards for agricultural and industrial demands is a viable option. In this study, paper and pulp industrial wastewater were treated with three biological treatments viz. aerobic, anaerobic and seq...
Fuzzy Logic Water Quality Recycling Biological Oxygen Demand Analysis Industrial Waste Water Purification Waste Disposal, Fluid Models, Theoretical Wastewater Mustard Plant
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