2012
DOI: 10.1016/b978-0-444-59506-5.50028-6
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Synthesis of Heat-Integrated Resource Conservation Networks

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Cited by 3 publications
(2 citation statements)
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References 72 publications
(132 reference statements)
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“…Initial efforts have been recently reported for the development of models that simultaneously integrate mass and energy (Savalescu et al, 2005a(Savalescu et al, , 2005bLiao et al, 2011;Martinez-Patiño et al, 2011Tan et al, 2012;Zhou et al, 2012aZhou et al, , 2012bBiox et al, 2012;Rojas-Torres et al, 2013;Ibric et al, 2013;Liu et al, 2013;Kravanja, 2013, 2014). In such works, the contribution of mass integration is typically based on the concentration of contaminants, thus ignoring the role that streams properties play in the design of the network.…”
Section: Nomenclaturementioning
confidence: 98%
“…Initial efforts have been recently reported for the development of models that simultaneously integrate mass and energy (Savalescu et al, 2005a(Savalescu et al, , 2005bLiao et al, 2011;Martinez-Patiño et al, 2011Tan et al, 2012;Zhou et al, 2012aZhou et al, , 2012bBiox et al, 2012;Rojas-Torres et al, 2013;Ibric et al, 2013;Liu et al, 2013;Kravanja, 2013, 2014). In such works, the contribution of mass integration is typically based on the concentration of contaminants, thus ignoring the role that streams properties play in the design of the network.…”
Section: Nomenclaturementioning
confidence: 98%
“…It should be noted that the algorithms underlying these solvers (e.g., outer approximation [153] in DICOPT) are based on decomposition techniques. Nevertheless the original mathematical formulation was not decomposed before solving [110,113,120,143]). Generally, an MINLP model requires good initialization which can be achieved by solving a relaxed instance of the original model either through fixing continuous variables (resulting in an MILP initialization model), fixing binary variables (mainly by excluding the HEN matches, and hence resulting in an NLP model [124,126,[129][130][131]134]), solving an MINLP model of water network with no heat integration [133], or by generating random values [38,135].…”
Section: Simultaneous With or Without Initializationmentioning
confidence: 99%