Artificial Intelligence tool for fire safety design (IFETool): Demonstration in large open spaces

Zeng, Yanfu; Zhang, Xiaoning; Su, Ling-chu; Wu, Xiaoni; Huang, Xinyan

doi:10.1016/j.csite.2022.102483

“…For example, much work has been done to model fire dynamics in an effort to reduce the current limitations of equations and methods. Similar studies, including [25][26][27], show the need for more realistic fire modeling capabilities. Other ML studies have explored a variety of structural materials and member types, each showing that ML can provide improved accuracy and understanding of such complicated phenomena.…”

Section: Introductionmentioning

confidence: 91%

Simple Visual Aids for Predicting Fire Response of RC Columns: Nomograms via Machine Learning

Naser,

Tapeh,

Hostetter

et al. 2023

EJCEA

0

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Assessing the ability of reinforced concrete (RC) columns to withstand the effects of fire is a multifaceted and intricate problem due to the various factors that influence their fire response. As such, engineers may find it challenging to precisely predict such fire resistance. While some codal provisions exist and fire testing/advanced modeling can be adopted, the same methods may suffer from poor predictivity and can be costly and/or complex. In this paper, we shift focus toward machine learning techniques (by means of Nomograms) that can produce simple visual aids to assess the fire resistance of RC columns. Our analysis shows that Nomograms can be accurate, account for a series of factors currently absent from our domain knowledge and provisions, and outperform existing methods adopted in building codes. Our analysis also infers that such Nomograms could be possible candidates for adoption in standardized settings, given their simplicity, ease of use, and lack of multi-stepped procedures.

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“…Nowadays, the first engineering AI algorithms are emerging, albeit in an initial phase, which offer almost infinite possibilities in the context of parameterised data. The future goal of the group is to build an engineering database and thus to research the development of AI integrated into modelling, computer fire, smoke and evacuation simulations (Zeng et al, 2022).…”

Section: Future Research Directions Of the Unitmentioning

confidence: 99%

Results and Future of Disaster Management Research in the System of Law Enforcement Sciences

Vass,

Ambrusz,

Restás

et al. 2024

BSZ

0

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Aim: The purpose of this study is to analyse and evaluate the main results and experiences of disaster management research and development activities, on the basis of which to determine future development directions. Methodology: The impact assessment prepared in the framework of the study presents the characteristics of disaster management research and development activities, and also makes structured proposals for solving the appeared research problems. Findings: The results of disaster management scientific activity carried out as part of law enforcement researches provide an opportunity to modernise the legal regulatory, professional and technical bases of disaster management administration in a manner appropriate to recent scientific development. Value: The disaster management research and development experiences processed in the framework of the study provide a suitable basis for a high level of compliance with the relevant social needs.

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“…Napjainkban, kezdeti fázisban ugyan, de megjelennek az első mérnöki MI algoritmusok, amelyek a parametrizált adatok kapcsán szinte végtelen lehetőséget rejtenek. A szakcsoport jövőbeni célkitűzése mérnöki adatbázis építése, és ezáltal a modellezésbe, a számítógépes tűz-, füst-és kiürítés szimulációkba integrált MI fejlesztésének a kutatása (Zeng et al, 2022). Az oktatás terén napjainkban hiátus mutatkozik az aktuális és a korszellem kihívásainak megfelelő, modern tűzmegelőzést ismertető könyvek, tankönyvek területén.…”

Section: A Szakcsoport Jövőbeni Kutatási Irányaiunclassified

A katasztrófavédelmi kutatások eredményei és fejlesztése a rendészettudomány rendszerében

Vass,

Ambrusz,

Restás

et al. 2024

BSZ

0

View full text Add to dashboard Cite

Aim: The purpose of this study is to analyse and evaluate the main results and experiences of disaster management research and development activities, on the basis of which to determine future development directions. Methodology: The impact assessment prepared in the framework of the study presents the characteristics of disaster management research and development activities, and also makes structured proposals for solving the appeared research problems. Findings: The results of disaster management scientific activity carried out as part of law enforcement researches provide an opportunity to modernise the legal regulatory, professional and technical bases of disaster management administration in a manner appropriate to recent scientific development. Value: The disaster management research and development experiences processed in the framework of the study provide a suitable basis for a high level of compliance with the relevant social needs.

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Artificial Intelligence tool for fire safety design (IFETool): Demonstration in large open spaces

Cited by 15 publications

References 32 publications

Simple Visual Aids for Predicting Fire Response of RC Columns: Nomograms via Machine Learning

Simple Visual Aids for Predicting Fire Response of RC Columns: Nomograms via Machine Learning

Results and Future of Disaster Management Research in the System of Law Enforcement Sciences

A katasztrófavédelmi kutatások eredményei és fejlesztése a rendészettudomány rendszerében

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