Evaluating and optimizing of steam ejector performance considering heterogeneous condensation using machine learning framework-Reference-Cited by-同舟云学术

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Evaluating and optimizing of steam ejector performance considering heterogeneous condensation using machine learning framework

Published:2024-10 Issue: Volume:305 Page:132240
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Momeni Dolatabadi Amir,Mottahedi Hamid Reza,Faghih Aliabadi Mohammad Ali^ORCID,Saffari Pour Mohsen,Wen Chuang,Akrami Mohammad

Publisher

Elsevier BV

Reference69 articles.

1. Assessment of the utilization of equivalent warming impact metrics in refrigeration, air conditioning and heat pump systems;Mota-Babiloni;Renew Sustain Energy Rev,2020

2. Performance assessment of CO2 supermarket refrigeration system in different climate zones of China;Sun;Energy Convers Manag,2020

3. Accurate condensing steam flow modeling in the ejector of the solar-driven refrigeration system;Zhang;Energy,2020

4. Thermodynamic analyses of ejector refrigeration cycle with zeotropic mixture;Liu;Energy,2023

5. Experimental and modeling studies of thermally-driven subcritical and transcritical ejector refrigeration systems;Huang;Energy Convers Manag,2020

Cited by 1 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. A comprehensive investigation and optimization of superheat degree on performance of supersonic nozzle by considering non-equilibrium condensation and entropy generation analysis;Physics of Fluids;2024-09-01

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