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Title : 工业装备数字孪生省重点实验室主任，大工碳中和研究院院长
Title of Paper:A Thermodynamics-Informed Deep Learning Approach for Lightweight Modelling of Gas Turbine Performance
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Date of Publication:2024-10-01
Journal:SSRN
ISSN No.:1556-5068
Key Words:Ambient conditions; Benchmarking; Compressibility of gases; Deep learning; Deep learning operator network; duty gas turbines; Efficiency; Electric power utilization; Gas compressors; Gases; Gas turbine performance; Heavy; Learning operator; Learning systems; Lightweight method; Operating condition; Operator networks; Performance Modeling
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