Use of an artificial neural network to predict the heat transfer of supercritical R134a in a horizontal internally ribbed tube-Reference-Cited by-同舟云学术

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Use of an artificial neural network to predict the heat transfer of supercritical R134a in a horizontal internally ribbed tube

Published:2023-06 Issue: Volume:228 Page:120429
ISSN:1359-4311
Container-title:Applied Thermal Engineering
language:en
Short-container-title:Applied Thermal Engineering

Author:

Wang Dabiao,Guo Shizhang,Zhao Yuan,Li Sichong,Li Lanlan

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Energy Engineering and Power Technology,Fluid Flow and Transfer Processes,Mechanical Engineering

Reference40 articles.

1. A Hot Water Split-Flow Dual-Pressure Strategy to Improve System Performance for Organic Rankine Cycle;Wang;Energies,2020

2. Enhanced thermal efficiency organic Rankine cycle for renewable power generation;Caldiño Herrera;Appl. Therm. Eng.,2021

3. Supercritical CO2 flowing upward in a vertical tube subject to axially nonuniform heating;Li;Numerical Heat Transfer Part a-Applications,2020

4. Turbulent Convection Heat Transfer Analysis of Supercritical Pressure CO2 Flow in a Vertical Tube Based on the Field Synergy Principle;Wang;Heat Transfer Eng.,2019

5. Experimental investigation on convection heat transfer of supercritical hydrocarbon fuel in a long mini tube;Yan;Exp. Therm Fluid Sci.,2020

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Study on heat transfer characteristics of supercritical R134a in square microchannel based on GA-BP neural network;Thermal Science and Engineering Progress;2024-06

2. Thermo-fluid performance for helical coils inserted in a tube using hybrid CFD-ANN approach;Thermal Science and Engineering Progress;2024-06

3. Low-grade thermal energy utilization: Technologies and applications;Applied Thermal Engineering;2024-05

4. Data-driven propagation prediction of subsonic and supersonic turbulent jets by combining self-similarity analysis model and artificial neural network;Applications in Energy and Combustion Science;2024-03

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