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Machine learning optimization of a novel geothermal driven system with LNG heat sink for hydrogen production and liquefaction
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“The exergy efficiency, liquid H2 rate, and LCOH were calculated to be 23.34%, 154.95 kg/h, and 1.827 $/kg, respectively.”
From Strategies To Improve the Performance of Hydrogen Storage Systems by Liquefaction Methods: A Comprehensive Review (2023) · cites this paper as [298]
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Metadata
- Authors
- Mehrenjani, J. R., Gharehghani, A., & Sangesaraki, A. G.
- Affiliations
- Iran University of Science and Technology (IR)
- Corresponding author
- Gharehghani, A.
- Venue
- Energy Conversion and Management
- Publisher
- Elsevier BV
- Published
- 2022-02
- Volume
- 254
- Pages
- 115266
- ISSN
- 0196-8904 (ISSN-L)
- OpenAlex
- W4224288113
- Cited by
- 154
- References
- 51
- Citations by year
- 2026: 24 · 2025: 40 · 2024: 37 · 2023: 37 · 2022: 16
- FWCI
- 12.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Energy Conversion and Management (publishedVersion)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Thermodynamic and Exergetic Analyses of Power and Cooling Systems
- Physical Sciences › Energy › Energy Engineering and Power Technology › Hybrid Renewable Energy Systems
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
- Keywords
- geothermal energy, liquefied natural gas, hydrogen production, hydrogen liquefaction, Claude cycle, proton exchange membrane electrolyzer, LNG vaporizer, exergy analysis, multi-objective optimization, artificial neural networks, genetic algorithm, levelized cost of hydrogen
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