Design Optimization of Plate-Fin Heat Exchanger in a Gas Turbine and Supercritical Carbon Dioxide Combined Cycle with Thermal Oil Loop

This paper presents an investigation on the optimum design for a plate-fin heat exchanger (PFHE) of a gas and supercritical carbon dioxide combined cycle which uses thermal oil as intermediate heat-transfer fluid. This may promote the heat transfer from low heat-flux exhaust to a high heat-flux supe...

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Bibliographic Details
Published inApplied sciences Vol. 12; no. 1; p. 42
Main Authors Cao, Yue, Zhan, Jun, Zhou, Jianxin, Si, Fengqi
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.01.2022
Subjects
Algorithms
Carbon dioxide
Climate change
Combined cycle
Design optimization
Efficiency
Energy
Fins
gas turbine
Gas turbines
Genetic algorithms
Heat exchangers
Heat flux
Heat recovery systems
Heat transfer
High temperature
Investigations
Multiple objective analysis
optimization
Parameters
plate-fin heat exchanger
Plate-fin heat exchangers
Pressure drop
Sorting algorithms
supercritical carbon dioxide
thermal oil loop
Turbines
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Summary:This paper presents an investigation on the optimum design for a plate-fin heat exchanger (PFHE) of a gas and supercritical carbon dioxide combined cycle which uses thermal oil as intermediate heat-transfer fluid. This may promote the heat transfer from low heat-flux exhaust to a high heat-flux supercritical carbon dioxide stream. The number of fin layers, plate width and geometrical parameters of fins on both sides of PFHE are selected as variables to be optimized by a non-dominated sorting genetic algorithm-II (NSGA-II), which is a multi-objective genetic algorithm. For the confliction of heat transfer area and pressure drop on the exhaust side, which are the objective indexes, the result of NSGA-II is a Pareto frontier. The technique for order of preference by similarity to ideal solution (TOPSIS) approach is applied to choose the optimum solution from the Pareto frontier. Finally, further simulation is performed to analyze the effect of each parameter to objective indexes and confirm the rationality of optimization results.
ISSN:2076-3417
2076-3417
DOI:10.3390/app12010042