Meta-Narrative Review of Artificial Intelligence Applications in Fire Engineering with Special Focus on Heat Transfer through Building Elements

Artificial intelligence (AI), as a research and analysis method, has recently been gaining ground in the ever-evolving scientific field of fire engineering in buildings. Despite the initial delay in utilising machine learning and neural networks due to the shortfall of available computational power,...

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Main Authors: Iasonas Bakas, Karolos J. Kontoleon
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Fire
Subjects:
Online Access:https://www.mdpi.com/2571-6255/6/7/261
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author Iasonas Bakas
Karolos J. Kontoleon
author_facet Iasonas Bakas
Karolos J. Kontoleon
author_sort Iasonas Bakas
collection DOAJ
description Artificial intelligence (AI), as a research and analysis method, has recently been gaining ground in the ever-evolving scientific field of fire engineering in buildings. Despite the initial delay in utilising machine learning and neural networks due to the shortfall of available computational power, a review of cutting-edge scientific research demonstrates that scientists are now exploring and routinely incorporating such systems in their research processes. As such, a considerable volume of new research is being produced comprising applications of AI in fire engineering. These findings and research questions ought to be summarised, organised, and made accessible for further investigation and refinement. The present study aims to identify recent scientific publications relating to artificial intelligence applications in fire engineering, with particular focus on those tackling the issue of heat transfer through building elements. The method of the meta-narrative review, as implemented in the field of medical advancement research, is discussed, adapted, and finally utilised to weave a narrative that enables the reader to follow the most recent, influential, and impactful works. Efforts are made to uncover trends in the search for heat transfer models and properties under fire loading using AI. The review concludes with our thoughts on how future research can enrich the current findings on heat transfer in buildings exposed to fire actions and elevated temperatures.
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spelling doaj.art-279c7a917e9242e4b323cc6f291f31162023-11-18T19:17:32ZengMDPI AGFire2571-62552023-07-016726110.3390/fire6070261Meta-Narrative Review of Artificial Intelligence Applications in Fire Engineering with Special Focus on Heat Transfer through Building ElementsIasonas Bakas0Karolos J. Kontoleon1Laboratory of Building Construction & Building Physics, Department of Civil Engineering, Faculty of Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, GreeceLaboratory of Building Construction & Building Physics, Department of Civil Engineering, Faculty of Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, GreeceArtificial intelligence (AI), as a research and analysis method, has recently been gaining ground in the ever-evolving scientific field of fire engineering in buildings. Despite the initial delay in utilising machine learning and neural networks due to the shortfall of available computational power, a review of cutting-edge scientific research demonstrates that scientists are now exploring and routinely incorporating such systems in their research processes. As such, a considerable volume of new research is being produced comprising applications of AI in fire engineering. These findings and research questions ought to be summarised, organised, and made accessible for further investigation and refinement. The present study aims to identify recent scientific publications relating to artificial intelligence applications in fire engineering, with particular focus on those tackling the issue of heat transfer through building elements. The method of the meta-narrative review, as implemented in the field of medical advancement research, is discussed, adapted, and finally utilised to weave a narrative that enables the reader to follow the most recent, influential, and impactful works. Efforts are made to uncover trends in the search for heat transfer models and properties under fire loading using AI. The review concludes with our thoughts on how future research can enrich the current findings on heat transfer in buildings exposed to fire actions and elevated temperatures.https://www.mdpi.com/2571-6255/6/7/261artificial intelligencemachine learningneural networksfire engineeringheat transferbuilding
spellingShingle Iasonas Bakas
Karolos J. Kontoleon
Meta-Narrative Review of Artificial Intelligence Applications in Fire Engineering with Special Focus on Heat Transfer through Building Elements
Fire
artificial intelligence
machine learning
neural networks
fire engineering
heat transfer
building
title Meta-Narrative Review of Artificial Intelligence Applications in Fire Engineering with Special Focus on Heat Transfer through Building Elements
title_full Meta-Narrative Review of Artificial Intelligence Applications in Fire Engineering with Special Focus on Heat Transfer through Building Elements
title_fullStr Meta-Narrative Review of Artificial Intelligence Applications in Fire Engineering with Special Focus on Heat Transfer through Building Elements
title_full_unstemmed Meta-Narrative Review of Artificial Intelligence Applications in Fire Engineering with Special Focus on Heat Transfer through Building Elements
title_short Meta-Narrative Review of Artificial Intelligence Applications in Fire Engineering with Special Focus on Heat Transfer through Building Elements
title_sort meta narrative review of artificial intelligence applications in fire engineering with special focus on heat transfer through building elements
topic artificial intelligence
machine learning
neural networks
fire engineering
heat transfer
building
url https://www.mdpi.com/2571-6255/6/7/261
work_keys_str_mv AT iasonasbakas metanarrativereviewofartificialintelligenceapplicationsinfireengineeringwithspecialfocusonheattransferthroughbuildingelements
AT karolosjkontoleon metanarrativereviewofartificialintelligenceapplicationsinfireengineeringwithspecialfocusonheattransferthroughbuildingelements