Response surface methodology for predicting the dimethylphenol removal from wastewater via reverse osmosis process
| Autor: | Mudhar A. Al-Obaidi, Iqbal M. Mujtaba, Basman M. Al-Nedawe, Abdulrahman Th Mohammad |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Materials science
General Chemical Engineering 02 engineering and technology 010501 environmental sciences Pulp and paper industry 01 natural sciences 020401 chemical engineering Wastewater Modeling and Simulation Scientific method Sewage treatment Response surface methodology 0204 chemical engineering Reverse osmosis 0105 earth and related environmental sciences |
| Zdroj: | Chemical Product and Process Modeling. 16:193-203 |
| ISSN: | 1934-2659 |
| DOI: | 10.1515/cppm-2020-0025 |
| Popis: | Reverse Osmosis (RO) process can be considered as one of the intensively used pioneering equipment for reusing wastewater of several applications. The recent study presented the development of an accurate model for predicting the dimethylphenol removal from wastewater via RO process. The Response Surface Methodology (RSM) was applied to carry out this challenge based on actual experimental data collected from the literature. The independent variables considered are the inlet pressure (5.83–13.58) atm, inlet temperature (29.5–32) ° C, inlet feed flow rate (2.166–2.583) × 10–4 m3/s, and inlet concentration (0.854–8.049) × 10-3 kmol/m3 and the dimethylphenol removal is considered as the response variable. The analysis of variance showed that the inlet temperature and feed flow rate have a negative influence on dimethylphenol removal from wastewater while the inlet pressure and concentration show a positive influence. In this regard, F-value of 240.38 indicates a considerable contribution of the predicted variables of pressure and concentration against the process dimethylphenol rejection. Also, the predicted R2 value of 0.9772 shows the high accuracy of the model. An overall assessment of simulating the performance of RO process against the operating parameters has been systematically demonstrated using the proposed RSM model. |
| Databáze: | OpenAIRE |
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