THERMAL SCIENCE

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Sepehr Sanaye

,

Davood Modarrespoor

THERMAL-ECONOMIC MULTIOBJECTIVE OPTIMIZATION OF HEAT PIPE HEAT EXCHANGER FOR ENERGY RECOVERY IN HVAC APPLICATIONS USING GENETIC ALGORITHM

ABSTRACT
Cost and effectiveness are two important factors of heat pipe heat exchanger (HPHE) design. The total cost includes the investment cost for buying equipment (heat exchanger surface area) and operating cost for energy expenditures (related to fan power). The HPHE was thermally modeled using e-NTU method to estimate the overall heat transfer coefficient for the bank of finned tubes as well as estimating pressure drop. Fast and elitist non-dominated sorting genetic algorithm (NSGA-II) with continuous and discrete variables was applied to obtain the maximum effectiveness and the minimum total cost as two objective functions. Pipe diameter, pipe length, numbers of pipes per row, number of rows, fin pitch and fin length ratio were considered as six design parameters. The results of optimal designs were a set of multiple optimum solutions, called ‘Pareto optimal solutions’. The comparison of the optimum values of total cost and effectiveness, variation of optimum values of design parameters as well as estimating the payback period were also reported for various inlet fresh air volume flow rates.
KEYWORDS
heat pipe heat exchanger, heat recovery, effectiveness, total cost, multiobjective optimization, NSGA-II
PAPER SUBMITTED: 2011-10-24
PAPER REVISED: 2012-09-25
PAPER ACCEPTED: 2012-10-24
DOI REFERENCE: https://doi.org/10.2298/TSCI111024203S
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2014, VOLUME 18, ISSUE Supplement 2, PAGES [S375 - S391]
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Thermal-economic multiobjective optimization of heat pipe heat exchanger for energy recovery in HVAC applications using genetic algorithm

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, 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