Comparison of different approaches for numerical modeling of nanofluid subcooled flow boiling and proposing predictive models using artificial neural network-Reference-Cited by-同舟云学术

Comparison of different approaches for numerical modeling of nanofluid subcooled flow boiling and proposing predictive models using artificial neural network

Published:2023-02 Issue: Volume:156 Page:104540
ISSN:0149-1970
Container-title:Progress in Nuclear Energy
language:en
Short-container-title:Progress in Nuclear Energy

Author:

El Jery Atef,P Satishkumar,Mahmood Salman Hayder,majeed saeed Shaymaa,Mohamed Khedher Khaled

Funder

King Khalid University

Deanship of Scientific Research, King Saud University

Deanship of Scientific Research, King Faisal University

Publisher

Elsevier BV

Subject

Waste Management and Disposal,Energy Engineering and Power Technology,Safety, Risk, Reliability and Quality,Nuclear Energy and Engineering

Reference61 articles.

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2. Experimental study of transition flow from single phase to two phase flow boiling in nanofluids;Abedini;J. Mol. Liq.,2017

3. Numerical investigation of vapor volume fraction in subcooled flow boiling of a nanofluid;Abedini;J. Mol. Liq.,2017

4. Optimization of subcooled flow boiling in a vertical pipe by using artificial neural network and multi objective genetic algorithm;Alimoradi;Appl. Therm. Eng.,2017

5. Experimental investigation on improvement of wet cooling tower efficiency with diverse packing compaction using ANN-PSO algorithm;Alimoradi;Energies,2020

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