000K utf8 1100 2018$c2018-11-06 1500 eng 2050 urn:nbn:de:gbv:wim2-20181122-38212 2051 10.25643/BAUHAUS-UNIVERSITAET.3821 3000 Rezakazemi, Mashallah 3010 Mosavi, Amir 3010 Shirazian, Saeed 4000 ANFIS pattern for molecular membranes separation optimization [Rezakazemi, Mashallah] 4060 20 Seiten 4209 In this work, molecular separation of aqueous-organic was simulated by using combined soft computing-mechanistic approaches. The considered separation system was a microporous membrane contactor for separation of benzoic acid from water by contacting with an organic phase containing extractor molecules. Indeed, extractive separation is carried out using membrane technology where complex of solute-organic is formed at the interface. The main focus was to develop a simulation methodology for prediction of concentration distribution of solute (benzoic acid) in the feed side of the membrane system, as the removal efficiency of the system is determined by concentration distribution of the solute in the feed channel. The pattern of Adaptive Neuro-Fuzzy Inference System (ANFIS) was optimized by finding the optimum membership function, learning percentage, and a number of rules. The ANFIS was trained using the extracted data from the CFD simulation of the membrane system. The comparisons between the predicted concentration distribution by ANFIS and CFD data revealed that the optimized ANFIS pattern can be used as a predictive tool for simulation of the process. The R2 of higher than 0.99 was obtained for the optimized ANFIS model. The main privilege of the developed methodology is its very low computational time for simulation of the system and can be used as a rigorous simulation tool for understanding and design of membrane-based systems. Highlights are, Molecular separation using microporous membranes. Developing hybrid model based on ANFIS-CFD for the separation process, Optimization of ANFIS structure for prediction of separation process 4950 https://doi.org/10.25643/BAUHAUS-UNIVERSITAET.3821$xR$3Volltext$534 4950 https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20181122-38212$xR$3Volltext$534 4961 https://www.db-thueringen.de/receive/dbt_mods_00060932 5051 004 5051 600 5550 CFD 5550 Fluid 5550 machine learning 5550 Membrane contactors 5550 Molecular Liquids 5550 optimization 5550 Simulation