IJsbrand van Straalen, Ph.D. Senior scientist TNO The Netherlands

Transcription

1 PROBABILISTIC METHODS FOR FIRE SAFETY ENGINEERING IJsbrand van Straalen, Ph.D. Senior scientist TNO The Netherlands Madrid, del 23 al 25 de febrero de 2010 / Madrid, 23rd to 25th of February of 2011

2 Contents presentation Application of fire safety within performance-based regulations Background probabilistic approach Research activities TNO Examples of applying probabilistic approach Summary and conclusions

3 Application of fire safety within performance- based regulations Fire safety regulations are mostly prescriptive-based p nowadays Need for change to improve fire safety within modern built environment (under condition of optimum costs) Verification by fire safety engineering Should be place in performance-based context

4 Application of fire safety within performance- based regulations Need of research regarding g Fire scenarios Performance criteria Risk-based analyses Fire safety engineering methods Have to deal with uncertainties scenarios, input, output and performances Can be solved with use of probabilistic approach

5 Background probabilistic approach Development of structural reliability methods Middle ages experience ancient builders Early 19th century Industrial revolution and calculation by design (Navier) Around 2nd World War discussions more consistent reliability concepts First development probabilistic techniques in 1950s Application in nuclear industry 1960s Followed by civil engineering and building sectors

6 Background probabilistic approach Eastern Scheldt barrier Netherlands

7 Principles Background probabilistic approach Calculates possibility that certain occasion occurs Makes use of simulation model Can handle stochasic input parameters Monte Carlo technique (TNO program Prob2BTM) F max = A f yield freque ency strength

8 Background probabilistic approach Limit state concept Z = R S Z is limit state R is performance S is circumstance If Z > 0, building fulfils its function If Z < 0, undesired event occurs If Z = 0, limit state is reached

9 Background probabilistic approach P(Z < 0) = f R R< S (r) f S (s) drds circum mstance s Z < 0 undesired event occurs Z = 0 limit state lines of equal density Z > 0 building fulfils f S (s) performance r f R (r) r

10 Research activities TNO Evacuation problem limit state concept Scenario analyses Bayesians believe network

11 Example evacuation problem Room 10x10 m 2, 4 high objects and 10 persons present Open-source module FDS+Evac of VTT Probabilistic technique: Monte Carlo

12 Example evacuation problem Fictitious disctribution of evacuation, considering Detection time Pre evacuation time Body diameter Walking speed Assumed probability of fatality as function of escape time

13 Example evacuation problem Histogram of expected number of fatalities Probability of undesired event: 14%

14 Example evaluation of fire scenarios Two event trees represented by Bayesians believe p y y network: Fire compartment & Automatic fire detection system

15 Example evaluation of fire scenarios Limit state Available minus Required time (ASET-RSET) for both situations Cumulative probability Basissituatie Alternative situatie ASET-RSET [s]

16 Summary and conclusions Probabilistic approach Developed 2nd half last century Limit state concept applicable for fire safety TNO has started research activities Evacuation problem Evaluation of fire scenarios Update and extend performance-based regulatory systems Developing fire safety scenarios Applying existing fire safety engineering methods Identifying matching performance criteria

17 Gracias por su atención Thanks for your attention IJsbrand van Straalen, Ph.D. Senior scientist TNO The Netherlands Madrid, del 23 al 25 de febrero de 2010 / Madrid, 23rd to 25th of February of 2011