Advantages and and Disadvantages Disadvantages of Fire Modelling
Dr Guillermo Rein School of Engineering University of Edinburgh & Imperial College London
Dr Guillermo Rein
9 May 2012 Chief Fire Officers’ Association Annual Conference Conference 2012 Comhdh Comhdháil áil Bhliant Bhliantúi úill Chuman Chumann n Phríom Phríomh-O h-Oifi ifigi gigh gh Dóiteá Dóiteáin in 2012
Fire Modelling is ubiquitous Fire modelling is now very common for most fire safety calculations
On What? Ignition, Flame, Plume, Smoke, Spread, Visibility, Visibility, Toxicity, Extinction…
For What? Live safety, Structural behaviour, Performance based Design, Forensic investigations, Risk, …
When used with caution, very powerful tool
Very dangerous when miss-used
FDS is king
1. 2. 3.
Fire Dynamics Simulator (FDS) Simulator (FDS) solves well all important fire mechanisms It is the most commonly used CFD model for fire applications, because: It is Free Its open source nature make it excellent for Research 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 s ole use of FDS The impression that FDS is fully validated
Example from web
Hamins et al, Characterization Characterization of Candle Candle Flames, Journal of Fire Protection Engineering 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 exper imental 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 pre diction and recreation? The following slides are the work of The University of Edinburgh investigating these questions since 2006
The need for Round-Robin 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 priori predictions of Dalmarnock Fire Test One using a common set of information describing the scenario.
Dalm Dalmar arno nock ck Fir Fires es - July July 200 2006 6 N
Abecassis-Empis et al., Characterisation of Dalmarnock Fire Test Test One, Experimental Thermal and Fluid Science 32 (7), pp. 1334-1343, 2008.
Dalm Dalmar arno nock ck Fir Fires es - July July 200 2006 6
Fire
Abecassis-Empis et al., Characterisation of Dalmarnock Fire Test Test One, Experimental Thermal and Fluid Science 32 (7), pp. 1334-1343, 2008.
Flat Layout
Abecassis-Empis et al., Characterisation of Dalmarnock Fire Test Test One, Experimental Thermal and Fluid Science 32 (7), pp. 1334-1343, 2008.
Fuel Load
Mixed livingroom/office space 2 Fuel load is ~ 32 kg/m of “equivalent wood” set-up designed for robustness robustness and and high repeatability repeatability Test set-up
Heavily Instrumented Deflection Gauges 8 Lasers
ENLARGE
ENLARGE
20 Heat Flux Gauges
ENLARGE
10 Smoke Detectors
10 CCTV
ENLARGE
270 Thermocouple
14 Velocity Probes
Average Compartment Temperature
Abecassis-Empis et al., Characterisation of Dalmarnock Fire Test 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 beforehand because it is much better to prophesy after the event has already taken place" Sir Winston Churchill, circa 1945
Results: Heat Release Rate
Rein et al. Fire Safety Journal 44 (4) pp. 590-602, 2009
Hot Layer Temperature
Hot Layer Height
Local Temperatures Temperatures
Diversity of viewsÆ diversity 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 modelling vs. the fire fire model (=painting (=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” Carll F Gauss Car Gauss (177 (1777 7 – 1855) 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 (*)
a Priori vs. a Posteriori
a Priori
a Posteriori
Fire Modelling
Fire Model
Safety, Design and Engineering
Model development and Research
Maximum error
Minimum error
a Posteriori of Dalmarnock Simulations conducted after having full access to all the measurements
using FDSv4
Jahn et al, 9th IAFSS Symp, 2008
Grid Dependency
Jahn et al, Fire Safety Science 9, pp. 1341-1352, 2008. http://hdl.handle.net/1842/2696 http://hdl.handle.net/1842/2696
Ensemble of HHR curves slow fire
medium fire
Local Temperature Predictions
A Priori vs. vs. A Posteriori Hot Layer Temperature Predictions
a priori
a posteriori
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: – –
A priori was: – –
10 to 50% for average hot layer temperature 20 to 200% for local temperatures 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 e ffective 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 large compartments to study smoke movement
The scenario can be compared to analytical solutions, 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 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 12.5 m
height of 8.5 m
for a 1.3 MW fire
height of 20 m
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 Temperature near the walls height of 15 m
height of 10 m
for a 1.3 MW fire
height of 5 m
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) curve is known – we do not not predict predict this this but • HRR curve 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
Thanks! Villemard, Villemard , 1910, National Library of France
Paleofuture Paleofuture: prediction made in 1900 of the fire-fighting of the year 2000
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
