prediction of membrane desalination process performance in the water industrial units by artificial neural networks (ann)

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#