Optimal coupling design for organic Rankine cycle and radial turbine rotor using CFD modeling, machine learning and genetic algorithm-Reference-Cited by-同舟云学术

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Optimal coupling design for organic Rankine cycle and radial turbine rotor using CFD modeling, machine learning and genetic algorithm

Published:2023-01 Issue: Volume:275 Page:116493
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Yu Zeting,Wang Changjiang,Rong Fanhua,Liang Wenxing

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference68 articles.

1. Capturing the invisible resource: Analysis of waste heat potential in Chinese industry;Lu;Appl Energy,2016

2. Low-grade heat conversion into power using organic Rankine cycles – A review of various applications;Tchanche;Renew Sustain Energy Rev,2011

3. Innovative visualization technique for energy flow analysis: Waste heat recovery and energy savings opportunities;Savulescu;Appl Therm Eng,2013

4. Update on current approaches, challenges, and prospects of modeling and simulation in renewable and sustainable energy systems;Yoro;Renew Sustain Energy Rev,2021

5. Thermo-economic analysis of transcritical CO2 power cycle and comparison with Kalina cycle and ORC for a low-temperature heat source;Meng;Energ Conver Manage,2019

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2. Performance optimization of a neon turboexpander based on the Kriging model and genetic algorithm;Cryogenics;2024-10

3. Design and optimization of the radial inflow turbogenerator for organic Rankine cycle system based on the Genetic Algorithm;Applied Thermal Engineering;2024-09

4. Optimal design and tip leakage flow characteristics analysis of radial inflow turbine used in organic Rankine and vapor compression refrigeration system;Energy;2024-08

5. Incorporating nickel foam with nano-encapsulated phase change material and water emulsion for battery thermal management: Coupling CFD and machine learning;Case Studies in Thermal Engineering;2024-08

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