Please use this identifier to cite or link to this item: https://doi.org/10.1177/0954408911416439
DC FieldValue
dc.titleAn entropy generation and genetic algorithm optimization of two-bed adsorption cooling cycle
dc.contributor.authorMyat, A.
dc.contributor.authorThu, K.
dc.contributor.authorNg, K.C.
dc.contributor.authorKim, Y.-D.
dc.date.accessioned2014-06-17T06:11:38Z
dc.date.available2014-06-17T06:11:38Z
dc.date.issued2012-05
dc.identifier.citationMyat, A., Thu, K., Ng, K.C., Kim, Y.-D. (2012-05). An entropy generation and genetic algorithm optimization of two-bed adsorption cooling cycle. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 226 (2) : 142-156. ScholarBank@NUS Repository. https://doi.org/10.1177/0954408911416439
dc.identifier.issn09544089
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/59451
dc.description.abstractThis article presents the performance analysis of adsorption cooling, shortly AD, system using a thermodynamic framework with an entropy generation analysis. The model captures the transient and the cyclic steady-state performances of the adsorption-desorption cycles operating under assorted heat source temperatures. Type-RD silica gel, with a pore surface area of 720 m2/g and diameters 0.4-0.7 mm, is used as an adsorbent and its high affinity for thewater vapour adsorbate gives a high equilibrium uptake. The key advantages of the AD are (a) it has no moving parts rendering less maintenance and (b) the energy efficient means of cooling by the adsorption process with a low-temperature heat source and (c) it is environmental friendly with low carbon footprint. By incorporating the genetic algorithm onto the entropy minimization technique, it is possible to locate the optimal system performance point or the global minima with respect to entropy generation using the system parameters such as coolant and heat source water temperatures, heat transfer areas, etc. The system analysis shows that the minimization of entropy generation in the AD cycle leads to the maximization of the coefficient of performance and this translates into a higher delivery of useful cooling effects at the particular input resource temperature. © Authors 2011.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1177/0954408911416439
dc.sourceScopus
dc.subjectadsorption cooling
dc.subjectentropy generation
dc.subjectgenetic algorithm
dc.subjectminimization
dc.subjectsilica gel
dc.subjectwaste heat recovery
dc.typeArticle
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.doi10.1177/0954408911416439
dc.description.sourcetitleProceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering
dc.description.volume226
dc.description.issue2
dc.description.page142-156
dc.description.codenPMEEE
dc.identifier.isiut000305563200005
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