THERMAL SCIENCE

International Scientific Journal

AN ADAPTIVE NEURO-FUZZY MODEL OF A RE-HEAT TWO-STAGE ADSORPTION CHILLER

ABSTRACT
Since the adsorption chillers do not use primary energy as driving source the possibility to employ low temperature waste heat sources in cooling energy production receives nowadays much attention of the industry and science community. However, the performance of the thermally driven adsorption systems is lower than that of other heat driven heating/cooling systems. Low coefficients of performance are one of the main disadvantages of adsorption coolers. It is the result of a poor heat transfer coefficient between the bed and the immersed heating surfaces of a built-in heat exchanger system. The purpose of this work is to study the effect of thermal conductance values of sorption elements and evaporator as well as other design parameters on the performance of a re-heat two-stage adsorption chiller. One of the main energy efficiency factors in cooling production, i. e. cooling capacity for wide-range of both design and operating parameters is analyzed in the paper. Moreover, the work introduces artificial intelligence approach for the optimization study of the adsorption cooler. The ANFIS was employed in the work. The increase in both the bed and evaporator conductance provides better performance of the considered innovative adsorption chiller. The highest obtained value of cooling capacity is 21.7 kW and it can be achieved for the following design and operational parameters of the considered re-heat two-stage adsorption chiller: Msorb = 40 kg, t = 1300 s, T = 80ºC, Csorb/Cmet = 50, hAsorb = 4000 W/K, hAevap = 4000 W/K.
KEYWORDS
PAPER SUBMITTED: 2018-08-14
PAPER REVISED: 2018-11-10
PAPER ACCEPTED: 2019-01-24
PUBLISHED ONLINE: 2019-09-22
DOI REFERENCE: https://doi.org/10.2298/TSCI19S4053K
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2019, VOLUME 23, ISSUE Supplement 4, PAGES [S1053 - S1063]
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© 2019 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence