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dc.contributor.author
Mussati, Sergio Fabian  
dc.contributor.author
Gernaey, Krist V.  
dc.contributor.author
Morosuk, Tatiana  
dc.contributor.author
Mussati, Miguel Ceferino  
dc.date.available
2018-03-15T20:55:33Z  
dc.date.issued
2016-11  
dc.identifier.citation
Mussati, Sergio Fabian; Gernaey, Krist V.; Morosuk, Tatiana; Mussati, Miguel Ceferino; NLP modeling for the optimization of LiBr-H2O absorption refrigeration systems with exergy loss rate, heat transfer area, and cost as single objective functions; Pergamon-Elsevier Science Ltd; Energy Conservation and Management; 127; 11-2016; 526-544  
dc.identifier.issn
0196-8904  
dc.identifier.uri
http://hdl.handle.net/11336/39035  
dc.description.abstract
Based on a nonlinear mathematical programming model, the sizes and operating conditions of the process units of single-effect absorption refrigeration systems operating with a LiBr–H2O solution are optimized for a specified cooling capacity by minimizing three single objective functions: the total exergy loss rate, the total heat transfer area, and the total annual cost of the system. It was found that the optimal solution obtained by minimization of the total exergy loss rate provides “theoretical” upper bounds not only for the total heat transfer area of the system but also for each process unit and all stream temperatures, while the optimal solution obtained by minimization of the total heat transfer area provides the lower bounds for these model variables, to solve a cost optimization problem. The minimization of the total exergy loss rate by varying parametrically the available total heat transfer area between these bounds was also performed, allowing to see how the optimal distribution of the available total heat transfer area among the system components, as well as the operating conditions (stream temperature, pressure, composition, and mass flow rate) and heat loads, vary qualitatively and quantitatively with increasing available total heat transfer area. These optimization results allowed to find a “practical” value of the total heat transfer area, i.e. no benefits can be obtained by increasing the available total heat transfer area above this value since the minimal total exergy loss value cannot be significantly improved by distributing additional heat transfer area among the process units. The optimal solution corresponding to this practical value significantly improves the upper bounds for an economic optimization problem with respect to the optimal solution corresponding to the theoretical value. The optimal solutions corresponding to the theoretical and the practical upper bound values for the total heat transfer area (100 m2 and 61 m2, respectively) as well as the optimal solution obtained by minimization of the total annual cost are discussed for a case study considering a cooling capacity of 50 kW, upon the model assumptions made and a given cost model. Around three-quarters of the minimal total annual cost correspond to capital expenditures and the rest to operating expenditures. The generator and evaporator represent together around 70% of the capital expenditures. The absorber is the largest contributor to both the total heat transfer area and the total exergy loss rate, with around 33.19 and 39.16%, respectively, when the total annual cost is minimized.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Pergamon-Elsevier Science Ltd  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Absorption Refrigeration Systems  
dc.subject
Cost Minimization  
dc.subject
Exergy Loss Minimization  
dc.subject
Gams  
dc.subject
Libr&Ndash;H2o  
dc.subject
Nlp Modeling  
dc.subject
Optimal Area Distribution  
dc.subject.classification
Otras Ingeniería Química  
dc.subject.classification
Ingeniería Química  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
NLP modeling for the optimization of LiBr-H2O absorption refrigeration systems with exergy loss rate, heat transfer area, and cost as single objective functions  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-03-08T19:07:03Z  
dc.journal.volume
127  
dc.journal.pagination
526-544  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Mussati, Sergio Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina  
dc.description.fil
Fil: Gernaey, Krist V.. Technical University Of Denmark. Dept.of Chemical Engineering; Dinamarca  
dc.description.fil
Fil: Morosuk, Tatiana. Technishe Universitat Berlin; Alemania  
dc.description.fil
Fil: Mussati, Miguel Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina  
dc.journal.title
Energy Conservation and Management  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1016/j.enconman.2016.09.021  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0196890416307993