Modeling thermo-physical properties of hydrogen utilizing machine learning schemes: Viscosity, density, diffusivity, and thermal conductivity-Reference-Cited by-同舟云学术

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Modeling thermo-physical properties of hydrogen utilizing machine learning schemes: Viscosity, density, diffusivity, and thermal conductivity

Published:2024-06 Issue: Volume:72 Page:1127-1142
ISSN:0360-3199
Container-title:International Journal of Hydrogen Energy
language:en
Short-container-title:International Journal of Hydrogen Energy

Author:

Lv Qichao,Li Zhaomin,Li Xiaochen,Naghizadeh Arefeh,Amiri-Ramsheh Behnam^ORCID,Sharifi Mohammad^ORCID,Zhou Tongke^ORCID,Hemmati-Sarapardeh Abdolhossein^ORCID

Publisher

Elsevier BV

Reference106 articles.

1. Global warming: energy, environmental pollution, and the impact of power electronics;Bose;IEEE Industrial Electronics Magazine,2010

2. Perspective on hydrogen energy carrier and its automotive applications;Cipriani;Int J Hydrogen Energy,2014

3. Clean hydrogen and power from impure water;Acar;J Power Sources,2016

4. A review on potential use of hydrogen in aviation applications;Dincer;International Journal of Sustainable Aviation,2016

5. Natural gas as a bridge to hydrogen transportation fuel: insights from the literature;Ogden;Energy Pol,2018

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. Modeling the thermal transport properties of hydrogen and its mixtures with greenhouse gas impurities: A data-driven machine learning approach;International Journal of Hydrogen Energy;2024-09

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