IAFSS agenda 2030 for a fire safe world

McNamee, Margaret; Meacham, Brian J.; Hees, Patrick Van; Bisby, Luke; Chow, Wan Ki; Coppalle, A.; Dobashi, Ritsu; Dlugogorski, Bogdan Z.; Fahy, Rita F.; Fleischmann, Charles; Floyd, Jason; Galea, Edwin R.; Gollner, Michael J.; Hakkarainen, Tuula; Hamins, Anthony P.; Hu, Longhua; Johnson, Peter; Karlsson, B.; Merci, Bart; Ohmiya, Yoshifuni; Rein, Guillermo; Trouvé, Arnaud; Wang, Yi; Weckman, Elizabeth J.

doi:10.1016/j.firesaf.2019.102889

Cited by 58 publications

(26 citation statements)

References 6 publications

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“…The above implies that the updating of traditional design approaches to adjust to innovations in the built environment or to specify requirements for exceptional designs [19] relies on 'lessons learned from failure' [36]. However to avoid disaster, to allow for the safe introduction of design innovation and the specification of adequate provisions for exceptional structures, and to properly mitigate evolving risk exposure (for example due to climate change and urbanization [27], an explicit consideration of the risk profile of the structure is necessary [40]. In other words, the full range of possible fires, and their associated probabilities must be taken into account, as well as the uncertainties in the structural fire performance and resulting consequences.…”

Section: Introductionmentioning

confidence: 99%

Potential of Surrogate Modelling for Probabilistic Fire Analysis of Structures

2021

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The interest in probabilistic methodologies to demonstrate structural fire safety has increased significantly in recent times. However, the evaluation of the structural behavior under fire loading is computationally expensive even for simple structural models. In this regard, machine learning-based surrogate modeling provides an appealing way forward. Surrogate models trained to simulate the behavior of structural fire engineering (SFE) models predict the response at negligible computational expense, thereby allowing for rapid probabilistic analyses and design iterations. Herein, a framework is proposed for the probabilistic analysis of fire exposed structures leveraging surrogate modeling. As a proof-of-concept a simple (analytical) non-linear model for the capacity of a concrete slab and an advanced (numerical) model for the capacity of a concrete column are considered. First, the procedure for training surrogate models is elaborated. Subsequently, the surrogate models are developed, followed by a probabilistic analysis to evaluate the probability density functions for the capacity. The results show that fragility curves developed based on the surrogate model agree with those obtained through direct sampling of the computationally expensive model, with the 10 -2 capacity quantile predicted with an error of less than 5%. Moreover, the computational cost for the probabilistic studies is significantly reduced by the adoption of surrogate models.

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Section: Introductionmentioning

confidence: 99%

Potential of Surrogate Modelling for Probabilistic Fire Analysis of Structures

2021

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“…One group that appears to be particularly at risk is older people [ 3 , 4 ]. Given predictions of an aging society [ 5 ], it is reasonable to expect the number of fire fatalities to grow rather than decline in this group.…”

Section: Introductionmentioning

confidence: 99%

Barriers and Facilitators for Implementation of Individualized Fire Safety (IFS) in Sweden

2021

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In 2010, the Swedish Civil Contingencies Agency (MSB) announced a “vision zero” of zero fire deaths in Sweden by 2050. Studies into fire deaths have identified that certain risk groups, including but not limited to older people, are overrepresented in fire death statistics in Sweden. The MSB has developed guidelines for how individualised fire safety (IFS) can be implemented in local communities for risk groups, in support of their vision zero for fire deaths. This paper presents the results of an interview study with a selection of Swedish municipalities to further explore how municipalities are working with IFS programs for community dwelling older people. The Consolidated Framework for Implementation Research has been used to analyse data developed through semi-structured interviews, from an analysis of the delegation of authority from MSB to local level and assessment of secondary documentation from national, regional and local organisations. The analysis has identified that IFS has, indeed, been implemented to varying degrees in Sweden, but that there are both facilitators and barriers which can be further leveraged to improve the implementation of IFS in the future.

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“…Society is facing new challenges in the built environment as urban populations grow. The growth of urban populations has recently been declared as one of the Societal Grand Challenges of fire safety science by the International Association of Fire Safety Science (IAFSS) [1]. IAFSS acknowledges that both the increase in urban population and the demographics of that population have changed dramatically in recent years and will keep changing in the future, which will affect the fire safety needs of society.…”

Section: Introductionmentioning

confidence: 99%

“…At the same time, people over 65 years is the fastest growing population group [4]. These developments demand a review of evacuation procedures for high-rise buildings [1,5].…”

Section: Introductionmentioning

confidence: 99%

Unannounced Evacuation Experiment in a High-Rise Hotel Building with Evacuation Elevators: A Study of Evacuation Behaviour Using Eye-Tracking

Mossberg

Nilsson

Andrée³

2020

Fire Technol

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Past studies suggest that people are often reluctant to use occupant evacuation elevators in case of fire. However, existing research is scarce and current knowledge is based on questionnaire studies and laboratory experiments. An unannounced evacuation experiment was therefore performed on the 16th floor of a 35-floor high-rise hotel building. Sixty-seven participants took part and eye-tracking glasses were used to collect data on exit choice and eye fixations. Three different scenarios were studied, including two different hotel room locations on the floor and a variation of guidance system for one of these locations, i.e., flashing green lights next to the evacuation sign at the elevators. Results suggest that people typically choose the elevator for evacuation, even if their hotel room was located closer to the evacuation stair. Flashing green lights next to an evacuation sign made people look more at this sign. However, in spite of looking more at the sign, the flashing light was not shown to significantly improve compliance with the sign. Also, the results suggest that a detector activated self-closing fire door without vision panels to the elevator lobby made it more difficult to find the evacuation elevators in an emergency.

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IAFSS agenda 2030 for a fire safe world

Cited by 58 publications

References 6 publications

Potential of Surrogate Modelling for Probabilistic Fire Analysis of Structures

Potential of Surrogate Modelling for Probabilistic Fire Analysis of Structures

Barriers and Facilitators for Implementation of Individualized Fire Safety (IFS) in Sweden

Unannounced Evacuation Experiment in a High-Rise Hotel Building with Evacuation Elevators: A Study of Evacuation Behaviour Using Eye-Tracking

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