Multi-objective performance optimization of regenerative S-CO2 Brayton cycle based on neural network prediction

Multi-objective performance optimization of regenerative S-CO2 Brayton cycle based on neural network prediction

The regenerative supercritical CO2 Brayton cycle (RSCBC) has great development potential in waste heat recovery and utilization, and it is necessary to carry out performance analysis and optimization. This article first applies the theory of finite time thermodynamics to establish a RSCBC model with...

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Bibliographic Details
Main Authors: Qinglong Jin, Shaojun Xia, Penglei Li, Tianchao Xie
Format: Article
Language:English
Published: Elsevier 2022-05-01
Series:Energy Conversion and Management: X
Subjects:
Regenerative supercritical carbon-dioxide Brayton cycle
Finite time thermodynamics
Neural networks
Multi-objective performance optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S2590174522000265

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http://www.sciencedirect.com/science/article/pii/S2590174522000265

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