Modeling and optimization of process parameters of biofilm reactor for wastewater treatment
- Maurya, A. K.; Reddy, B. S.; Theerthagiri, J.; Narayana, P. L.; Park, C. H.; Hong, J. K.; Yeom, J-T; Cho, K. K.; Reddy, N. S.
- Issue Date
- Artificial neural networks (ANN); Biofilm reactor; Wastewater treatment; Heavy metal removal; (IRI); Weight distribution
- SCIENCE OF THE TOTAL ENVIRONMENT, v.787
- Journal Title
- SCIENCE OF THE TOTAL ENVIRONMENT
- The efficiency of heavy metal in biofilm reactors depends on absorption process parameters, and those relationships are complicated. This study explores artificial neural networks (ANNs) feasibility to correlate the biofilm reactor process parameters with absorption efficiency. The heavy metal removal and turbidity were modeled as a function of five process parameters, namely pH, temperature(degrees C), feed flux(ml/min), substrate flow(ml/min), and hydraulic retention time(h). We developed a standalone ANN software for predicting and analyzing the absorption process in handling industrial wastewater. The model was tested extensively to confirm that the predictions are reasonable in the context of the absorption kinetics principles. The model predictions showed that the temperature and pH values are the most influential parameters affecting absorption efficiency and turbidity. (c) 2021 Elsevier B.V. All rights reserved.
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- 공과대학 > 나노신소재공학부금속재료공학전공 > Journal Articles
- 공학계열 > Dept.of Materials Engineering and Convergence Technology > Journal Articles
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