The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 42 of 2522
Back to Result List

ANFIS pattern for molecular membranes separation optimization

  • 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

Download full text files

Export metadata

Metadaten
Document Type:Preprint
Author: Mashallah Rezakazemi, Postdoc Amir MosaviORCiD, Saeed Shirazian
DOI (Cite-Link):https://doi.org/10.25643/BAUHAUS-UNIVERSITAET.3821Cite-Link
URN (Cite-Link):https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20181122-38212Cite-Link
Language:English
Date of Publication (online):2018/11/06
Date of first Publication:2018/11/06
Release Date:2018/11/22
Publishing Institution:Bauhaus-Universität Weimar
Institutes:Fakultät Bauingenieurwesen / Institut für Strukturmechanik
Volume:2018
First Page:1
Last Page:20
Tag:CFD; Membrane contactors; Molecular Liquids; machine learning; optimization
GND Keyword:Fluid; Simulation
Dewey Decimal Classification:000 Informatik, Informationswissenschaft, allgemeine Werke
600 Technik, Medizin, angewandte Wissenschaften
BKL-Classification:06 Information und Dokumentation
30 Naturwissenschaften allgemein
35 Chemie
54 Informatik
58 Chemische Technik, Umwelttechnik, verschiedene Techno-
Licence (German):License Logo Creative Commons 4.0 - Namensnennung (CC BY 4.0)
Note:
This is the pre-peer reviewed version of the following article:
https://www.sciencedirect.com/science/article/pii/S0167732218345008, which has been published in final form at https://doi.org/10.1016/j.molliq.2018.11.017.