A Response Surface Methodology for Probabilistic Life Safety Analysis using Advanced Fire Engineering Tools

Albrecht, Cornelius; Hosser, D.

doi:10.3801/iafss.fss.10-1059

Cited by 10 publications

(2 citation statements)

References 3 publications

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“…Thus, the mean of occupant density is taken as 1.0 persons/m 2 in this case. Due to the scarce available data on stochastic variables of occupant evacuation, standard deviations of uncertain parameters are usually assumed to be 10-20% of their mean values [34]. Herein, standard deviations of the child-occupant load ratio and occupant density are selected to be 20% and 10% of their mean values.…”

Section: Two-stage Nested Monte Carlo Simulationmentioning

confidence: 99%

An optimization method for the distance between exits of buildings considering uncertainties based on arbitrary polynomial chaos expansion

Xie

Wang

et al. 2016

Reliability Engineering & System Safety

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optimization method for the distance between exits of buildings considering uncertainties based on arbitrary polynomial chaos expansion, ReliabilityEngineering and System Safety, http://dx. ABSTRACTThe distance between exits is an important design parameter in fire safety design of buildings. In order to find the optimal distance between exits under uncertainties with a low computational cost, the surrogate model (i.e. approximation model) of evacuation time is constructed by the arbitrary polynomial chaos expansion. Through a two-stage nested Monte Carlo simulation of this surrogate model, the optimal distance between exits under uncertainty is found efficiently. In order to demonstrate the proposed method, a single room with two exits is presented as a fire compartment and uncertainties of occupant density and child-occupant load ratio are also considered. In this case, the results showed that the optimal distance between exits changes with the level of probability of evacuation time, and there is a critical level of probability for the transition of the optimal value of the distance between exits. Furthermore, the traditional Monte Carlo simulation method is used to compare the accuracy of the surrogate model with the computer evacuation model FDS+Evac developed by the VTT Technical Research Centre of Finland [1]. The results indicate that the proposed surrogate-based optimization method can achieve a similar accuracy with a much lower computational cost.

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Section: Two-stage Nested Monte Carlo Simulationmentioning

confidence: 99%

An optimization method for the distance between exits of buildings considering uncertainties based on arbitrary polynomial chaos expansion

Xie

Wang

et al. 2016

Reliability Engineering & System Safety

View full text Add to dashboard Cite

show abstract

“…Random sampling can be both computationally expensive and time consuming since the number of calculations required increases with the number of variables in the system. To reduce the large number of analyses required for Monte-Carlo analysis, other work on the reliability of life safety and suppression systems in fire proposes the use of response surface modelling and linear regression techniques to identify critical variables for reliability estimation and then employ iterative algorithms to reduce the number of calculations required [11,12]. These techniques lead to less computationally expensive analyses than traditional Monte Carlo techniques.…”

Section: Introductionmentioning

confidence: 99%

An application of the PEER performance based earthquake engineering framework to structures in fire

Lange¹,

Devaney²,

Usmani³

2014

Engineering Structures

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a b s t r a c tThe Pacific Earthquake Engineering Research (PEER) Center's Performance Based Earthquake Engineering (PBEE) framework is well documented. The framework is a linear methodology which is based upon obtaining in turn output from each of the following analyses: hazard analysis; structural analysis; loss analysis, and finally decision making based on variables of interest, such as downtime or cost to repair. The strength of the framework is in its linearity, its clear flexibility and in the consideration of uncertainty at every stage of the analysis. The framework has potential applications to other forms of extreme loading; however in order for this to be achieved the 'mapping' of the framework to the analysis of structures for other loading situations must be successful. This paper illustrates one such 'mapping' of the framework for Performance Based Fire Engineering (PBFE) of structures. Using a combination of simple analytical techniques and codified methods as well as random sampling techniques to develop a range of response records, the PEER framework is followed to illustrate its application to structural fire engineering. The end result is a successful application of the earthquake framework to fire which highlights both the assumptions which are inherent in the performance based design framework as well as subjects of future research which will allow more confidence in the design of structures for fire using performance based techniques.This article describes the PEER framework applied to structural earthquake design then follows the framework from start to completion applying suitable alternative tools to perform each stage of the analysis for structures in fire.

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Building Fire Risk Analysis

Meacham

Charters

Johnson

et al. 2016

SFPE Handbook of Fire Protection Engineering

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A Response Surface Methodology for Probabilistic Life Safety Analysis using Advanced Fire Engineering Tools

Cited by 10 publications

References 3 publications

An optimization method for the distance between exits of buildings considering uncertainties based on arbitrary polynomial chaos expansion

An optimization method for the distance between exits of buildings considering uncertainties based on arbitrary polynomial chaos expansion

An application of the PEER performance based earthquake engineering framework to structures in fire

Building Fire Risk Analysis

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