practical approaches to qra in fire practical approaches
TRANSCRIPT
Practical approaches to QRA in
fire protection engineering
Piotr Tofilo, PhD
Practical approaches to QRA in fire
protection engineering
Piotr Tofilo PhD
The Main School of Fire Service + FirePlatform Ltd
CERN Workshop: An engineering perspective on risk assessment - November 26-27, 2018
Risk analysis in fire applications
Starting point: Fire regulations and standards
Performance Based Design (fire engineering)
Risk analysis: qualitative, semi QRA, full QRA
Probabilistic interpretation can be done in many ways
Risk categorization, risk metrics, consequences...
What if we have various types of losses ? (life, health, money,
environment, time, jobs, homes, cultural value, intellectual value,
public image…. )
How to include what we don’t know that we don’t know ?
(Grenfel, WTC… )
Timber structure apartment buildings
High rise single stair buildings
Protection of escape routes (optimization)
Sprinklered vs. non sprinklered buildings
Fire spread between buildings
Lightweight industrial buildings (cost / benefit)
Industrial problems: thermal radiation, explosion effects, toxic
releases...
Practical subjects - examples
Uncertainties to consider
Initial conditions (fire load, ditribution)
External conditions (wind, temperature, humidity etc.)
Fire (initiation, spread, heat and smoke generation)
Human effects (evacuation, intervention, errors, other)
Structural conditions (state of barriers, failures)
Systems (reliability, failures, effectivenes)
Fire event tree
Risk matrix (SFPE)
Fault tree + fire event tree
Probability of failure
Full QRA - challenges
Completeness of the problem studied
Adequacy of models (accuracy, limitations, integration)
Uncertainty of input data
Frequencies, distributions, materials, scenarios...
Multiple calculations, sampling, data processing
Meaningful results: F-N curves, risk matrix ?
Practicality: effort, time, cost, approval risk...
Monte Carlo analysis
Random variables
Sampling
Simple (crude) Monte Carlo (MCS)
Latin Hypercube (LHS) – stratification, inverse transforms
Importance sampling – rare events (black swans, tails)
Many other optimization techniques are available as well as
numerical packages (e.g. Python, C#, Java, R)
Adequate optimization necessary for models with high computation
cost (CFD)
Some promising approaches:
Response surface modeling (Qu 2003, Albrecht 2011)
ME-MDR Method (Van Coile 2017)
Confidence intervals
Fire QRA – selected software
FireCAM, FIERAsystem
(Canada)
CESARE-Risk
(Australia)
CRISP, BuildingQRA
(UK)
SAFETI
(Netherlands)
B-Risk
(New Zealand)
Probabilistic Fire Simulator (Finland)
FirePlatform – complex models / tools
FireRad FireRad QuickZone
FDS Designer Egress Designer FireFEM
FirePlatform – simple models / tools
Smoke control Cylindrical fire Detector activation
Total flooding 1D Heat Transfer Eurocode – parametric fire
EC Parametric Fire (MC mode)
Fire load density distribution (10k samples)
EC Parametric Fire (MC mode)
Temperature distribution (10k samples)
EC Parametric Fire (MC mode)
Temperature distribution (10k samples)
Discontinuity due to EC PF model split – FC / VC fires
AAMKS
Probabilistic fire and evacuation simulator
AAMKS - Fire modeling (CFAST)
AAMKS – Evacuation modeling
AAMKS - Results
Complementary cumulative density function (ccdf) – FN curves
Histograms with scenario counts for numbers of casualties
AAMKS – real life example
Change of use: 5 storey office to hotel
Length of the escape route exceeded (office 20 m, hotel 10 m).
No fire alarm system (FAS) (above 50 accommodation places)
No fire doors EI 30
Design alternatives
Alternative E. routes Ventilation Sprinklers Wall
EI 60
E. signs Alarming Training,auditing
1.1 10 m - - - - II -
1.2 20 m √ √ - - II -
2.1 20 m √ - - 5 lux II -
2.2 20 m - √ - 5 lux II -
2.3 20 m - - √ 5 lux I √
2.4 20 m - - - 5 lux II -
Event tree
FN curves (casualties vs. probability)
W 2.4
W 1.2 W 2.1
W 2.2 W 2.3
W 1.1
Risk matrix
Option Risk of fire death
1.1 1.16 * 10 -4 /year
1.2 2.57 * 10 -7 /year
2.1 1.16 * 10 -5 /year
2.2 2.37 * 10 -6 /year
2.3 1.02 * 10 -4 /year
2.4 1.21 * 10 -4 /year
Decision alternatives
Option E. routes Ventilation Sprinkler Wall
EI 60
Luminescence
Alarming Training, procedures
Economy
1.2 20 m √ √ - - II - $$$$
2.2 20 m - √ - 5 lux II - $$$
2.1 20 m √ - - 5 lux II - $$$
2.3 20 m - - √ 5 lux I √ $$
1.1 10 m - - - - II - $$$
2.4 20 m - - - 5 lux II - $
Summary
Using QRA tools is informative, educational and it can help
understand the problem in a probabilistic space
Using simple models with Monte Carlo is often sufficient in FPE or it
can be used for initial scoping analysis
For high risk applications it may be necessary to use more
advanced or interfaced models models to capture complexity
Alternatively extra conservative assumptions should be used
Next steps for fire QRA:
Fast computing of multiple scenarios
Use of complex modeling: CFD, Evacuation, FEM
More data is needed - physical, statistical
Adequate scenario sampling must be used or developed
Fire & Risk – Recommended Literature
