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MULTI-OBJECTIVE OPTIMIZATION ON SUPERCRITICAL CO2 RECOMPRESSION BRAYTON CYCLE USING KRIGING SURROGATE MODEL

ABSTRACT
Supercritical CO2 cycle has become one of the most popular research fields of thermal science. The selection of operation parameters on thermodynamic cycle process is an important task. The computational model of supercritical CO2 recompression cycle is built to solve the multi-objective problem in this paper. Then, the optimization of parameters is performed based on genetic algorithm. Several Kriging models are also used to reduce the quantity of samples. According to the calculation, the influence of sample quantity on the result and the time cost is obtained. The results show that it is required to improve the heat transfer when improvement of the cycle efficiency is desired.
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PAPER SUBMITTED: 2017-03-10
PAPER REVISED: 2017-05-01
PAPER ACCEPTED: 2017-05-10
PUBLISHED ONLINE: 2017-12-02
DOI REFERENCE: https://doi.org/10.2298/TSCI17S1309S
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2017, VOLUME 21, ISSUE Supplement 1, PAGES [S309 - S316]
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© 2017 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