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Thermal analysis and performance optimization of supercritical carbon dioxide Brayton cycle based on ship waste heat
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DOI：10.1016/j.ijheatfluidflow.2025.110020.png)
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Abstract
En 中文
• SCO2 power cycle system using CO2-propanebinary mixture. • Established a Convolutional Neural Network model for predicting system performance. • Using response surface methodology for multi-objective optimization to determine the optimal operating conditions.
Keywords:
SCO2 power cycle
CO2-propane mixture
Convolutional Neural Network
Response surface methodology
Multi-objective optimization
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