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   Prediction of Membrane Desalination Process Performance in the Water Industrial Units By Artificial Neural Networks (Ann)  
   
DOR 20.1001.2.9919199705.1399.11.1.462.7
نویسنده - - ,- -
منبع كنگره مهندسي شيمي - 1399 - دوره : 11 - یازدهمین کنگره بین المللی مهندسی شیمی - کد همایش: 99191-99705
چکیده    Desalination of all membrane-based devices is one of the promising applications of membrane distillation (md) systems# the development of detailed models to predict the performance of membrane distillation systems plays an important role in the design of such an industrial application# in this paper, a business model of permeate gap membrane distillation (pgmd) is modeled using artificial neural networks (ann)# condenser inlet temperature, evaporator inlet temperature, feed flow flux and feed water-salt concentration were selected as model inputs, while product flux and specific thermal energy consumption (stec) were selected as the response# the results show that the artificial neural networks model is able to predict module behavior more accurately for all input variables# the results show that the artificial neural networks model is able to predict module behavior more accurately for all input variables# since all the data used are industrial data, the results of this modeling are very useful for industry use and better utilization of membrane-based units#
کلیدواژه Membrane ,Desalination ,Membrane Distillation (Md) ,Artificial Neural Networks (Ann)
آدرس Semnan University, Iran, Semnan University, Iran
 
     
   
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