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Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy
The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial intelligence (AI) has emerged as a reliable method to tackle this engineering problem. This review summarizes existing studies that applied AI...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919694/ https://www.ncbi.nlm.nih.gov/pubmed/33672068 http://dx.doi.org/10.3390/molecules26041022 |
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author | Nguyen, Hoang T. Nguyen, Kate T. Q. Le, Tu C. Zhang, Guomin |
author_facet | Nguyen, Hoang T. Nguyen, Kate T. Q. Le, Tu C. Zhang, Guomin |
author_sort | Nguyen, Hoang T. |
collection | PubMed |
description | The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial intelligence (AI) has emerged as a reliable method to tackle this engineering problem. This review summarizes existing studies that applied AI to predict the fire performance of different construction materials (e.g., concrete, steel, timber, and composites). The prediction of the flame retardancy of some structural components such as beams, columns, slabs, and connections by utilizing AI-based models is also discussed. The end of this review offers insights on the advantages, existing challenges, and recommendations for the development of AI techniques used to evaluate the fire performance of construction materials and their flame retardancy. This review offers a comprehensive overview to researchers in the fields of fire engineering and material science, and it encourages them to explore and consider the use of AI in future research projects. |
format | Online Article Text |
id | pubmed-7919694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79196942021-03-02 Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy Nguyen, Hoang T. Nguyen, Kate T. Q. Le, Tu C. Zhang, Guomin Molecules Review The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial intelligence (AI) has emerged as a reliable method to tackle this engineering problem. This review summarizes existing studies that applied AI to predict the fire performance of different construction materials (e.g., concrete, steel, timber, and composites). The prediction of the flame retardancy of some structural components such as beams, columns, slabs, and connections by utilizing AI-based models is also discussed. The end of this review offers insights on the advantages, existing challenges, and recommendations for the development of AI techniques used to evaluate the fire performance of construction materials and their flame retardancy. This review offers a comprehensive overview to researchers in the fields of fire engineering and material science, and it encourages them to explore and consider the use of AI in future research projects. MDPI 2021-02-15 /pmc/articles/PMC7919694/ /pubmed/33672068 http://dx.doi.org/10.3390/molecules26041022 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Nguyen, Hoang T. Nguyen, Kate T. Q. Le, Tu C. Zhang, Guomin Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy |
title | Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy |
title_full | Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy |
title_fullStr | Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy |
title_full_unstemmed | Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy |
title_short | Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy |
title_sort | review on the use of artificial intelligence to predict fire performance of construction materials and their flame retardancy |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919694/ https://www.ncbi.nlm.nih.gov/pubmed/33672068 http://dx.doi.org/10.3390/molecules26041022 |
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