advantages and disadvantages of fire modelling (chief fire officers conference)

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