GENERIC FIRE RISK ASSESSMENT FOR



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Transcription:

GENERIC FIRE RISK ASSESSMENT FOR RESIDENTIAL AND INDUSTRIAL BUILDINGS Malta, 13. April 2012 Gianluca De Sanctis desanctg@ethz.ch

EFFICIENT SAFETY REQUIREMENTS FOR THE CODES Design Format of the Codes Prescriptive Performance-Based Safety Level Building Financial Losses Human Losses Safety Investments Expected Financial Portfolio Losses Expected Human Portfolio Losses Portfolio Safety Investments Institute of Structural Engineering ETH Zurich 2

GENERIC RISKASSESSMENT Requirements for a generic risk model Applicable for most buildings in a portfolio Quantitative assessment of the risk Physical effects of the required fire safety measures Unbiased assessment of the portfolio risk Generic System Representation Risk Analysis Institute of Structural Engineering ETH Zurich 3

RISK ANALYSIS Engineering models are able to quantify the losses based on the risk indicators and physical or empirical understanding of the problem Probabilistic engineering models allow to consider the uncertainties of the risk indicators consistently Due to simplification and approximations, engineering models will never predict the real behaviour of a system exactly. The resulting loss estimation will be biased. This lack of fit could be considered by model parameters Model Parameters Institute of Structural Engineering ETH Zurich 4

COMBINING AN ENGINEERING APPROACH WITH DATA A calibration of the model with observed data leads to an unbiased estimation of the expected losses on portfolio level The aim is to quantify the model parameters through the available data Methods: Maximum Likelihood Method select model parameters such that the observed values obtain the greatest probability Bayesian Updating for involving prior information Model parameter and its associated uncertainties can be assessed for the hole portfolio e e e e e= evidence Institute of Structural Engineering ETH Zurich 5

PORTFOLIO RISK ASSESSMENT Design Format of the Codes Prescriptive Performance-Based Safety Level n 2 1 Building Building Generic Risk Assessment Building Building Risk Indicators Generic Design of the Building Model Parameters Probabilistic Engineering Models Financial Losses Human Losses Safety Investments Expected Financial Portfolio Losses Expected Human Portfolio Losses Portfolio Safety Investments Institute of Structural Engineering ETH Zurich 6

EFFICIENT FIRE SAFETY MEASURES Life Safety A rational acceptance criterion for decisions regarding life safety can be derived based on the Life Quality Index (LQI) The LQI define a threshold for the societal willingness to pay for a marginal increase in life safety Financial Losses Minimizing the total expected costs while the fire safety measures fulfil the Life Safety conditions derived from the LQI principle Financialloss Optimum Total expected costs LQI-threshold Investment costs Expected consequences Safety investments Risk to life Acceptable region Institute of Structural Engineering ETH Zurich 7

SINGLE FAMILY HOUSES An economical examination: should smoke alarms be required for single family houses? Model Parameters 1 Discovery Time CDF 0.9 0.8 0.7 0.6 0.5 0.4 0.3 Smoke Alarm: Increasing probability of fire discovery (derived from statistical data [1][2] ) Increasing probability that the fire brigade will arrive sooner 0.2 0.1 No Smoke Alarm With Smoke Alarm 0 0 10 20 30 40 50 60 Time [min] [1] Holborn, Nolan & Golt (2004) [2] Department for Communities and Local Government (2006) Institute of Structural Engineering ETH Zurich 8

SINGLE FAMILY HOUSES Estimation of the model parameters using a dataset of 1996 fires incidents e e Cumulative distribution function F(x) 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Data Model Exceedance Probability 1-F(x) 0 10 2 10 3 10 4 10 5 10 6 10 5 10 6 Financial Financial Portfolio Loss Loss [CHF] [CHF] Financial Financial Portfolio Loss Loss [CHF] [CHF] Institute of Structural Engineering ETH Zurich 9 10-1 10-2 10-3 10-4 e No Smoke Alarm Model With Smoke Alarm Data

SINGLE FAMILY HOUSES Risk reduction by demanding Smoke Alarms for single family houses: E Lno Smoke Alarm E LSmoke Alarm 4.8CHF r a SFH 7.4% E L 64.5CHF Exceedance Probability 1-F(x) 10-1 10-2 10-3 no Smoke Alarm No Smoke Alarm With Smoke Alarm a SFH 10-4 10 5 10 6 Financial Loss [CHF] Institute of Structural Engineering ETH Zurich 10 Financial Portfolio Loss [CHF]

NEXT STEPS Ongoing research at ETH Risk based review of the Swiss Fire Safety Regulations Quantitative influence of fire protection measures on the risk Efficiency of fire safety measures Future research possibilities Application of the concept to performance based codes Calibration of the Fire Safety Code for a portfolio target Institute of Structural Engineering ETH Zurich 11

PROBLEMS Generic System Representation and Available Data: Available data does not correspond to the needed input / output for the engineering models Error in the estimation of input parameters based on the available data Data (Switzerland) does not classify the damage according the fire spread in the building Probabilistic Engineering Models Missing simple engineering models for natural fire conditions, i.e. charring rate for timber, fire resistance of fire barriers (EI), fire spread in multi compartment buildings etc. Investments cost Generic assessment of safety investment costs dependent on the code format Institute of Structural Engineering ETH Zurich 12

THANK YOU FOR YOUR ATTENTION YOUR QUESTIONS PLEASE! Gianluca De Sanctis desanctg@ethz.ch Institute of Structural Engineering ETH Zurich 13

GENERIC RISKMODEL Single Family House Buildings 1:N G Model Parameters Available Data Model Input Model Output Available Data Building Volume Constr. Year Insurance Value Room Height Living Area Number of Rooms Fire Brigade Intervention Building Area A tot Initial Area A 0 Number of cells Room arrangement I RA Probabilistic Engineering Model Damaged Area A Damage Ratio A/A tot = Loss S Loss Ratio S/V Institute of Structural Engineering ETH Zurich 14