advantages and disadvantages of fire modelling (chief fire officers conference)
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Invited talk given by Dr Guillermo Rein at the 2012 Irish Chief Fire Officers Association Annual Conference (CFOA), Dundalk, 9th May.TRANSCRIPT
Dr Guillermo Rein
9 May 2012
Chief Fire Officers’ Association Annual Conference 2012
Comhdháil Bhliantúil Chumann Phríomh-Oifigigh Dóiteáin 2012
Advantages and Disadvantages
of Fire Modelling
Dr Guillermo Rein
School of Engineering
University of Edinburgh
&
Imperial College London
Fire Modelling is ubiquitous
�� On What? On What? Ignition, Flame, Plume,
Smoke, Spread, Visibility, Toxicity,
Extinction…
�� For What?For What? Live safety, Structural
behaviour, Performance based Design,
Forensic investigations, Risk, …
Fire modelling is now very
common for most fire safety
calculations
� When used with caution, very powerful tool
� Very dangerous when miss-used
FDS is king
� Fire Dynamics Simulator (FDS) solves well all important fire mechanisms
� It is the most commonly used CFD model for fire applications, because:
1. It is Free
2. Its open source nature make it excellent for Research
3. There are hundreds of Papers showing good results
This has led to:
� A critical mass of industry and academic users
� Approval of many key infrastructure projects by the sole use of FDS
� The impression that FDS is fully validated
Example from web
Hamins et al, Characterization of Candle Flames, Journal of Fire Protection Engineering 15, 2005
Example from web
Video: http://video.google.com/videoplay?docid=-9024280504374819454#
Example from web
Video: http://video.google.com/videoplay?docid=4830080566059919470#
Prediction or Recreation?
� The previous examples on fire modelling are
remarkable
� But these were conducted after the experiments and
after having access to the experimental data of the
phenomena under simulation
� What would be the result if the simulations are
conducted before the experiment instead of after?
� What is the difference between forecast, prediction and
recreation?
The following slides are the work of The University of
Edinburgh investigating these questions since 2006
The need for Round-Robin Studies
� In 2006, Edinburgh organized a Round-Robin study of fire
modelling using the large-scale tests conducted in
Dalmarnock.
� International pool of experts independently provide a a
prioripriori predictions of Dalmarnock Fire Test One using a
common set of information describing the scenario.
Dalmarnock Fires - July 2006
N
Abecassis-Empis et al., Characterisation of Dalmarnock Fire Test One,Experimental Thermal and Fluid Science 32 (7), pp. 1334-1343, 2008.
Dalmarnock Fires - July 2006
Fire
Abecassis-Empis et al., Characterisation of Dalmarnock Fire Test One,Experimental Thermal and Fluid Science 32 (7), pp. 1334-1343, 2008.
Flat Layout
Abecassis-Empis et al., Characterisation of Dalmarnock Fire Test One,Experimental Thermal and Fluid Science 32 (7), pp. 1334-1343, 2008.
Fuel Load
�Mixed livingroom/office space
�Fuel load is ~ 32 kg/m2 of “equivalent wood”
�Test set-up designed for robustness and high repeatability
Heavily Instrumented
8 Lasers
ENLARGE ENLARGE ENLARGE ENLARGE
DeflectionGauges
20 Heat Flux Gauges
270 Thermocouple
10 Smoke Detectors
14 Velocity Probes
10 CCTV
Average Compartment Temperature
Abecassis-Empis et al., Characterisation of Dalmarnock Fire Test One,Experimental Thermal and Fluid Science 32 (7), pp. 1334-1343, 2008.
Compartment Temperature
Stern-Gottfried et al., Fire Safety Journal 45, pp. 249–261, 2010. doi:10.1016/j.firesaf.2010.03.007
Aftermath
Information given to Modelling Teams
� Detailed geometry (plan and dimensions)
� Detailed fuel load (dimensions, locations, photographs,
descriptions)
� Ventilation conditions (including breakage of one
window)
� Photographs of set up in the compartment
� HRR of sofa as measured in the laboratory
Information to be complimented by the team’s decisions
As in any other fire modelling work
Simulations
� 10 Submitted simulations: 8 Field Models (FDS v4) and 2
Zone models (CFAST v6)
NOTE: teams were asked to forecast as accurately as
possible and not to use safety factors or applied it to
design purposes
Rein et al. Round-Robin Study of a priori Modelling Predictions of The Dalmarnock Fire Test One,Fire Safety Journal 44 (4) pp. 590-602, 2009
"I always avoid prophesying "I always avoid prophesying beforehand beforehand
because it is much better to because it is much better to prophesy after the event has prophesy after the event has already taken place"already taken place"
Sir Winston Churchill, circa Sir Winston Churchill, circa 19451945
Results: Heat Release Rate
Rein et al. Fire Safety Journal 44 (4) pp. 590-602, 2009
Hot Layer Temperature
Hot Layer Height
Local Temperatures
Diversity of viewsÆdiversity of Behaviours
Dalmarnock Conclusions
� Real fire frequently faced by Fire and Rescue Services all around the world
� Large scatter around the measurements (much larger than experimental error)
� During the growth phase: 20 to 500% error in hot layer temperature. 20 to 800% in local temperatures
� Inherent difficulties of predicting dynamics
� Fire modelling vs. the fire model (=painting vs. the brush)
Degrees of Freedom
� The excess in degrees of freedom
� Ill-defined and uncertain parameters that cannot be
rigorously and uniquely determined lead to errors, doubts,
curve fitting and arbitrary value selection.
“Give me four parameters, and I will draw an elephant for you; with five I will have him raise and lower his trunk and his tail”
Carl F Gauss (1777 – 1855)
Postmorten
� General classification of input files yields these groups:
Means to input/predict the HRR:
– 2 simulations used fully prescribed HRR (***)
– 7 simulations used partially prescribed HRR (**)
– 1 simulations used fully predicted HRR (*)
Means to input the ignition source:
– 3 simulations used provided sofa HRR but
extrapolated it (**)
– 5 simulations did not used provided sofa HHR but
other (**)
– 1 simulation used provided sofa HRR as measured (*)
Fire Model
Model development and
Research
Minimum error
a Priori a Posteriori
Fire Modelling
Safety, Design and Engineering
Maximum error
a Priori vs. a Posteriori
Jahn et al, 9th IAFSS Symp, 2008
using FDSv4
a Posteriori of DalmarnockSimulations conducted after having full access to all the measurements
Grid Dependency
Jahn et al, Fire Safety Science 9, pp. 1341-1352, 2008. http://hdl.handle.net/1842/2696
Ensemble of HHR curvesmedium fireslow fire
Local Temperature Predictions
A Priori vs. A Posteriori
a priori a posteriori
Hot Layer Temperature Predictions
A Posteriori Modelling
� When HRR is unknown, an assemble of possible HRR can be considered and results reported as upper and lower bounds
� A posteriori level of agreement reached with measurements is:
– 10 to 50% for average hot layer temperature
– 20 to 200% for local temperatures� A priori was:
– 20 to 500% for average hot layer temperature
– 20 to 800% for local temperatures
� Drastic reduction of the uncertainty from a priori to a posteriori after adjusting uncertain parameters
Final Remarks
� CFD is a cost effective and powerful tool but potentially
misleading
� Parameter values used can be as important as the
mathematical model used
� Fire modelling is one decade behind empirical knowledge
What to ask from a fire modelling study
1. Sensitivity to other parameter values?
2. Can results be confirmed by alternative means?
3. Validated model & modeller for similar scenarios?
4. Ask for 3rd party review from experts
Example
� Application of FDS in large compartments to study smoke
movement
� The scenario can be compared to analytical solutions, thus
allowing for an informed grid selection
� Also, experiments are available to the same scenario so
validation and checking for order of magnitude is possible
A Simple yet Meaningful Fire Scenario
� Cubic enclosure of sides 20 m long
� Scenario related to smoke movement and life safety in atria
� Pool fires in the range from 1 to 3 MW (measured mass loss
rate)
Gutiérrez-Montes, Experimental Data and Numerical Modelling of 1.3 and 2.3 MW Fires in a 20 m Cubic Atrium,Building and Environment 44, pp. 1827–1839, 2009
20-m Cubic Enclosure
Gutiérrez-Montes, Experimental Data and Numerical Modelling of 1.3 and 2.3 MW Fires in a 20 m Cubic Atrium,Building and Environment 44, pp. 1827–1839, 2009
Grid effects vs. Plume Theory
1.3 MW fire 2.3 MW fire
Gutiérrez-Montes, Experimental Data and Numerical Modelling of 1.3 and 2.3 MW Fires in a 20 m Cubic Atrium,Building and Environment 44, pp. 1827–1839, 2009
2006 Murcia Fire Tests in a 20-m cube
Gutiérrez-Montes, Experimental Data and Numerical Modelling of 1.3 and 2.3 MW Fires in a 20 m Cubic Atrium,Building and Environment 44, pp. 1827–1839, 2009
Experiments vs. Modelling: Plume Temperature
height of 4.5 m height of 8.5 m
height of 12.5 m height of 20 m
for a 1.3 MW fire
Gutiérrez-Montes, Experimental Data and Numerical Modelling of 1.3 and 2.3 MW Fires in a 20 m Cubic Atrium,Building and Environment 44, pp. 1827–1839, 2009
Experiments vs. Modelling: Temperature near the walls
height of 15 m height of 10 m
height of 5 m
for a 1.3 MW fire
Gutiérrez-Montes, Experimental Data and Numerical Modelling of 1.3 and 2.3 MW Fires in a 20 m Cubic Atrium,Building and Environment 44, pp. 1827–1839, 2009
Conclusions
• Sensitivity to reasonable grid sizes shows numerical uncertainly range
• Grid chosen based on analytical solution (~confirmation via alternative means)
• HRR curve is known – we do not predict this but implement it as input
• Results show predictions improved with distance from flames
• Gas and wall temperatures in the far field are much better than in the near field
Paleofuture: prediction made in 1900 of the
fire-fighting of the year 2000
Villemard, 1910, National Library of France
Thanks!
What to ask of a CFD study
1. Grid independence study?
Time step independence study?
2. Boundary independence study?
3. Sensitivity to Parameters?
4. The results have been confirmed by alternative means
(calculation and/or experiments)?
5. Validation of the code and users in similar scenarios?
Aftermath
Tests One and Two: Repeatability