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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.2
- 수록면
- 31 - 37 (7page)
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초록· 키워드
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The optimization of micellar-enhanced ultrafiltration (MEUF) of arsenic (As) contaminated aqueous solution using cetylpyridinium chloride (CPC) as surfactant was studied through experimental and artificial neural network (ANN) modeling. Experimental studies were carried out by varying operational conditions such as time, pressure, molar ratio of CPC to As, concentration of As and pH of feed solution. Root mean square error (RMSE) and coefficient of determination (R²) were considered as performance criterion to evaluate the predicted results of ANN model. The experimental studies provided optimum operating parameters such as pressure 1.8 bar, molar ratio of CPC to As was 5:1, As concentration 1 mM and pH 8.0 of feed solution. ANN model presented reliable results with RMSE values 0.259, 0.553 and 0.623 for training, validation and testing datasets, respectively, while R² values for training, validation and testing dataset were noted as 0.962, 0.942 and 0.932, respectively. The proposed ANN model traced input-output relationship to predict As removal efficiency (RE) of MEUF process. Therefore, ANN model can be considered as a competitive, powerful and fast alternate because of its high computational speed, accuracy and economics in MEUF process optimization without doing laborious experimental work.
목차
ABSTRACT
1. Introduction
2. Material and Methods
3. Results and Discussion
4. Conclusions
References
참고문헌 (31)
참고문헌 신청
Schwanck F, Simões JC, Handley M, Mayewski PA, Bernardo RT, Aquino FE. Anomalously high arsenic concentration in a West Antarctic ice core and its relationship to copper mining in Chile. Atmos. Environ. 2016;125:257-264.
Uppal JS, Zheng Q, Le XC. Arsenic in drinking water–Recent examples and updates from Southeast Asia. Curr. Opin. Environ. Sci. Heal. 2019;7:126-135.
EPA, National Primary Drinking Water Regulations; Arsenic and Clarifications to Compliance and New Source Contaminants Monitoring. 2001;66:6976-7066.
Mondal P, Tran ATK, Van der Bruggen B. Removal of As (V) from simulated groundwater using forward osmosis: Effect of competing and coexisting solutes. Desalination 2014;348:33-38.
Chen M, Shafer-Peltier K, Randtke SJ, Peltier E. Modeling arsenic(V) removal from water by micellar enhanced ultrafiltration in the presence of competing anions. Chemosphere 2018;213:285-294.
Uppal JS, Zheng Q, Le XC. Arsenic in drinking water–Recent examples and updates from Southeast Asia. Curr. Opin. Environ. Sci. Heal. 2019;7:126-135.
EPA, National Primary Drinking Water Regulations; Arsenic and Clarifications to Compliance and New Source Contaminants Monitoring. 2001;66:6976-7066.
Mondal P, Tran ATK, Van der Bruggen B. Removal of As (V) from simulated groundwater using forward osmosis: Effect of competing and coexisting solutes. Desalination 2014;348:33-38.
Chen M, Shafer-Peltier K, Randtke SJ, Peltier E. Modeling arsenic(V) removal from water by micellar enhanced ultrafiltration in the presence of competing anions. Chemosphere 2018;213:285-294.
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UCI(KEPA) : I410-ECN-0101-2020-539-000545599