Insights into modelling and evaluation of thermodynamic and transport properties of refrigerants using machine-learning methods

Abolfazl Sajadi Noushabadi; Ebrahim Nemati Lay; Amir Dashti; Amir H. Mohammadi; Abdoulmohammad Gholamzadeh Chofreh; Feybi Ariani Goni; Jiří Jaromír Klemeš

doi:10.1016/j.energy.2022.125099

Insights into modelling and evaluation of thermodynamic and transport properties of refrigerants using machine-learning methods

Abolfazl Sajadi Noushabadi
, Ebrahim Nemati Lay^*
, Amir Dashti
, Amir H. Mohammadi
, Abdoulmohammad Gholamzadeh Chofreh
, Feybi Ariani Goni
, Jiří Jaromír Klemeš

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

9 Citations (SciVal)

Original language	English
Article number	125099
Journal	Energy
Volume	262
DOIs	https://doi.org/10.1016/j.energy.2022.125099
Publication status	Published (VoR) - 1 Jan 2023

Funding

This research has been supported by the EU project “Sustainable Process Integration Laboratory – SPIL”, project No. CZ.02.1.01/0.0/0.0/15_003/0000456 funded by EU “CZ Operational Programme Research, Development and Education”, Priority 1: Strengthening capacity for quality research.

Funders	Funder number
European Commission	CZ.02.1.01/0.0/0.0/15_003/0000456

Keywords

Correlation
Machine learning
Refrigerants
Thermodynamic properties
Transport properties

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10.1016/j.energy.2022.125099

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title = "Insights into modelling and evaluation of thermodynamic and transport properties of refrigerants using machine-learning methods",

keywords = "Correlation, Machine learning, Refrigerants, Thermodynamic properties, Transport properties",

author = "Noushabadi, \{Abolfazl Sajadi\} and Lay, \{Ebrahim Nemati\} and Amir Dashti and Mohammadi, \{Amir H.\} and Chofreh, \{Abdoulmohammad Gholamzadeh\} and Goni, \{Feybi Ariani\} and Kleme{\v s}, \{Ji{\v r}{\'i} Jarom{\'i}r\}",

note = "Publisher Copyright: {\textcopyright} 2022 Elsevier Ltd",

year = "2023",

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doi = "10.1016/j.energy.2022.125099",

language = "English",

volume = "262",

journal = "Energy",

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TY - JOUR

T1 - Insights into modelling and evaluation of thermodynamic and transport properties of refrigerants using machine-learning methods

AU - Noushabadi, Abolfazl Sajadi

AU - Lay, Ebrahim Nemati

AU - Dashti, Amir

AU - Mohammadi, Amir H.

AU - Chofreh, Abdoulmohammad Gholamzadeh

AU - Goni, Feybi Ariani

AU - Klemeš, Jiří Jaromír

PY - 2023/1/1

Y1 - 2023/1/1

KW - Correlation

KW - Machine learning

KW - Refrigerants

KW - Thermodynamic properties

KW - Transport properties

UR - https://www.scopus.com/pages/publications/85138099992

UR - https://www.scopus.com/pages/publications/85138099992#tab=citedBy

U2 - 10.1016/j.energy.2022.125099

DO - 10.1016/j.energy.2022.125099

M3 - Article

AN - SCOPUS:85138099992

SN - 0360-5442

VL - 262

JO - Energy

JF - Energy

M1 - 125099

ER -

Insights into modelling and evaluation of thermodynamic and transport properties of refrigerants using machine-learning methods

Funding

Keywords

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