Decision analysis on fire safety design based on evaluating building fire risk to life

Fire simulations and sensors are widely used in building fires, various data such as temperature, CO and CO 2 concentration, visibility can be obtained by sensors and sensor-based simulation. It is important to generate a risk map based on such data so that we can use it to estimate safety of the building. In this paper, we propose a method to generate a dynamical, integrated risk map using sensor readings in a building fire. Such risk evaluation model is developed using similarity comparison between the space state and dangerous state by a likelihood distance calculating and data grouping from a two-step cluster method. The risk evaluation model considers the integrated influence on the occupants in the zone from high temperature, lack of oxygen, toxic and harmful gases and shows the relative fire risk map at certain time. Based on the simulation study, it is proved that multi-factor fire risk analysis would be more objective and accurate than single factor and two-factor risk analysis and the fire risk evaluation model can generate a risk map and provide the classification information and the whole building risk statistic results to support evacuation command and control. building fire, risk map, cluster analysis, fire simulation Citation: Chu Y Y, Zhang H, Shen S F, et al. Development of a model to generate a risk map in a building fire.

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“…And zone fire risk can be got by risk level probability calculation. Zone relative risk can be calculated as follows [14]:…”

Section: Fire Risk Analysis Using a Two-step Cluster Methodsmentioning

confidence: 99%

Development of a model to generate a risk map in a building fire

Chu

Zhang

Shen

et al. 2010

Sci. China Technol. Sci.

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“…For manual detection success, the detection time is assumed to occur when the smoke layer height descends below the ceiling by 10% of the compartment height. For the scenario where manual detection fails, the time when the smoke layer height descends below the ceiling by 15% of the compartment height is assumed to be the detection time (Chu, Sun 2008). The detection times for these three scenarios can be calculated by the following equation: ( 1) , 0.0227…”

Section: Fig 3 Heat Release Rate Curves Of Time-squared Firementioning

confidence: 99%

A Method for Linking Safety Factor to the Target Probability of Failure in Fire Safety Engineering

Kong

Frantzich

et al. 2014

Journal of Civil Engineering and Management

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Abstract. Ensuring occupants' safety in building fires is one of the most important aspects for fire safety engineering. Many uncertainties are inevitably introduced when estimating the occupant safety level, due to the high complexity of fire dynamics and the human behaviour in fires. Safety factor methods are traditionally employed to deal with such uncertainties. This kind of methods is easy to apply but leaves fire safety engineers unsure of the margin by which the design has failed. A method of linking safety factor and probability of failure in fire safety engineering is proposed in this study. An event tree is constructed to analyse potential fire scenarios that arise from the failure of fire protection systems. Considering uncertainties related to fire dynamics and evacuation, the traditional deterministic safety factor is considered as a random variable. Because there is no target probability of failure accepted by the whole fire safety engineering community, the concept of expected risk to life (ERL) is integrated to determine the target probability of failure. This method employs a Monte Carlo Simulation using Latin Hypercube Sampling (LHS) to calculate the required safety factor. A practical case study is conducted using the method proposed in this study.Keywords: probability of failure, safety factor, Monte Carlo simulation, fire safety engineering, uncertainty analysis. Reference to this paper should be made as follows: Kong, D.; Lu, S.; Frantzich, H.; Lo, S. M. 2013. A method for linking safety factor to the target probability of failure in fire safety engineering, Journal of Civil Engineering and Management 19(Supplement 1): S212-S221. http://dx

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“…Four people in the classroom need to escape. Once fire occurs, occupant evacuation is difficult to be accomplished which may induce many casualties [12]. Thus, it is important to recognize evacuees' behaviors and movements.…”

Section: Case Studymentioning

confidence: 99%

Research on pedestrian escape route without visibility based on Markov chain model

Zheng

Wang

2009

Front. Chem. Eng. China

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It is a pioneering work to use a Markov chain model to study the pedestrian escape route without visibility. In this paper, based on the Markov chain probability transition matrix, the algorithms with random numbers and the spatial-grid, an escape route in a limited invisible space is obtained. Six pace states (standing, crawling, walking, leaping, jogging, and running) are applied to describe the characteristics of pedestrian behaviors. Besides, eight main direction changes are used to describe the transition characteristic of a pedestrian. At the same time, this paper analyzes the escape route from two views, i.e., pedestrian pace states and directions. The research results show that the Markov chain model is more realistic as a means of studying pedestrian escape routes.

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Decision analysis on fire safety design based on evaluating building fire risk to life

Cited by 37 publications

References 21 publications

Development of a model to generate a risk map in a building fire

Development of a model to generate a risk map in a building fire

A Method for Linking Safety Factor to the Target Probability of Failure in Fire Safety Engineering

Research on pedestrian escape route without visibility based on Markov chain model

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