Modeling and genetic algorithm-based multi-objective optimization of the MED-TVC desalination system

This study proposes a systematic approach of analysis and optimization of the multi-effect distillation-thermal vapor compression (MED-TVC) desalination system. The effect of input variables, such as temperature difference, motive steam mass flow rate, and preheated feed water temperature was invest...

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Vydáno v:	Desalination Ročník 292; s. 87 - 104
Hlavní autoři:	Janghorban Esfahani, Iman, Ataei, Abtin, Shetty K, Vidya, Oh, TaeSuk, Park, Jae Hyung, Yoo, ChangKyoo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 16.04.2012 Elsevier
Témata:	algorithms Applied sciences Artificial neural network Chemical engineering Desalination Distillation Drinking water and swimming-pool water. Desalination Economic costs Exact sciences and technology exergy freshwater least squares mass flow Mathematical modeling MED-TVC Multi-objective optimization neural networks Pollution response surface methodology steam water flow water temperature Water treatment and pollution MED-TVC Mathematical modeling Multi-objective optimization Economic costs Artificial neural network Desalination Compression Water flow Neural network Water vapor Modeling Optimization Mass flow rate Genetic algorithm Exergy analysis Multiple effect distillation Production Partial least squares
ISSN:	0011-9164, 1873-4464
On-line přístup:	Získat plný text
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