An entropy generation and genetic algorithm optimization of two-bed adsorption cooling cycle
Type
ArticleKAUST Department
Biological and Environmental Sciences and Engineering (BESE) DivisionWater Desalination and Reuse Research Center (WDRC)
Date
2011-09-28Online Publication Date
2011-09-28Print Publication Date
2012-05Permanent link to this record
http://hdl.handle.net/10754/561883
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This 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.Citation
Myat, A., Thu, K., Ng, K. C., & Kim, Y.-D. (2011). 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. doi:10.1177/0954408911416439Sponsors
The authors gratefully express their gratitude to Agency of Science, Technology and Research (A*STAR) for providing generous financial support for the project (grant no. R265-000-287-305).Publisher
SAGE Publicationsae974a485f413a2113503eed53cd6c53
10.1177/0954408911416439