Modelling for Fire Modelling for Fire Investigation: Investigation:

Lessons from The Dalmarnock Lessons from The Dalmarnock Fire Tests Fire Tests

Guillermo Rein & J. L. ToreroBRE Centre for Fire Safety EngineeringUniversity of Edinburgh

The Art of Fire Modelling

Modelling of: Modelling of: Ignition, Flame, Plume, Smoke, Spread, Visibility, Toxicity, Extinction…

Modelling for:Modelling for: Performance based design, Live safety, Structural response, Risk analysis, Forensic investigations, …

Fire Modelling vs. Fire Models There are many papers addressing the validation

of fire models– Different models (FDS, SmartFire, CFX, FLUENT,

CFAST, …)– Different scenarios– Focus on the mathematical engines

Validations are done a posteriori This is of great value for research and development

but introduce a natural bias…

The Validation of Fire Modelling

1. Has the whole process of fire modelling been validated?

2. Are the results the same if modellers do not have access to the results a priori?

Do we really know all the Strengths and Limitations of fire modelling as in realistic scenarios?

The need for Round-Robin Studies

In 2006, Edinburgh organzied a Round-Rboin 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

Fire

N

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 spaceFuel load is ~ 32 kg/m2 of “equivalent wood”Test set-up designed for robustness and high repeatability

Heavily Instrumented

8 Lasers

CCTV

ENLARGE ENLARGE ENLARGE ENLARGE

DeflectionDeflectionGaugesGauges 20 Heat Flux 20 Heat Flux

GaugesGauges

270 Thermocouple

10 Smoke Detectors

14 Velocity Probes

10 CCTV

Video

Average Compartment Temperature

Abecassis-Empis et al., Characterisation of Dalmarnock Fire Test One, Experimental Thermal and Fluid Science 32 (7), pp. 1334-1343, 2008.

Aftermath

Modelling for Fire Investigation

Modelling needs to “Reconstruct” the events with no “data” of the fire

“Evidence” has to match the models and can not be used to “steer” the models

Requirements are very similar to an apriori model

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 usually applied for design purposes

G Rein et al. Round-Robin Study of a priori Modelling Predictions of The Dalmarnock Fire Test One, Fire Safety Journal (in press), 2009.

"I always avoid prophesying beforehand "I always avoid prophesying beforehand

because it is much better to because it is much better to prophesy after the event has already prophesy after the event has already taken place"taken place"

Sir Winston Churchill, circa 1945Sir Winston Churchill, circa 1945

Possible Outcomes: a priori discussions

A B

CVariables shown

here: HRR, Smoke layer,

Wall temperature and heat fluxes

Results: Heat Release Rate

Hot Layer Temperature

Hot Layer Height

Local Temperatures

Local Heat Flux to Wall (vs time)

Local Wall Temperatures (vs. time)

Strength in Diversity?

Analysis of Assumptions

Analysis of input file is a cumbersome task falling out of our scope

But general classification yields:Means to input/predict the HRR:

– 2 fully-prescribed HRR (***)– 7 partially prescribed HRR (**)– 1 fully predicted HRR (*)

Means to input the ignition source:– 5 did not used the Sofa curve measured (**)– 3 used the Sofa curve measured but extrapolated

(**)– 1 used the Sofa curve as measured (*)

G Rein et al. Round-Robin Study of a priori Modelling Predictions of The Dalmarnock Fire Test One, Fire Safety Journal (in press), 2009.

Conclusions

assessment of the state-of-the-art for a real scenario

Large scatter around the measurements (much larger than experimental error)

Results are very sensitive to assumptions of material properties, fire growth

Inherent difficulties of predicting dynamics

G Rein et al. Round-Robin Study of a priori Modelling Predictions of The Dalmarnock Fire Test One, Fire Safety Journal (in press), 2009.

But… Let’s look into the bright side

Work conducted by Universities of Jaen and Murcia

Cubic atrium 20 m long sides Pool fires in the range from 1 to 3 MW. Fully instrumented to asses fire prediction

capabilities in large enclosures, smoke movement and effect of exhaust fans

Gutiérrez-Montes, Experimental Data and Numerical Modelling of 1.3 and 2.3 MW Fires in a 20 m Cubic Atrium, Building and Environment (in press), 2009.

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 (in press), 2009.

Grid effects vs. Plume Theory

Gutiérrez-Montes, Experimental Data and Numerical Modelling of 1.3 and 2.3 MW Fires in a 20 m Cubic Atrium, Building and Environment (in press), 2009.

for a 1.3 MW fire

20-m Atrium Exp vs. Modelling:

Plume Temperature

height of 4.5 m height of 8.5 m

height of 12.5 m 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 (in press), 2009.

for a 1.3 MW fire

20-m Atrium Exp vs. Modelling:

Temperature near the side walls

height of 15 m height of 10 m

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 (in press), 2009.

for a 1.3 MW fire

Texas City – Dispersion Model

Damage Correlation

Qualitative correlation allows to explain areas of damage

Lessons and Recommendations

Fire predictions work well away from the flame and in simple geometries (where most fire models have been calibrated)

Modelling with prescribed source works well Modelling of fire growth does not provide good results Best practice is in absence of laboratory results is that

fire growth of “complex” scenarios should not be predicted by the model

Modelling is a complex skill that requires great knowledge and experience – it is not for everyone!

Work conducted in collaboration with: José L. Torero, Wolfram Jahn, Candido Gomez Montes, Jamie Stern-Gottfried, Noah L. Ryder, Sylvain Desanghere, Mariano Lázaro, Frederick

Mowrer, Andrew Coles, Allan Jowsey and Pedro Reszka

Thanks

Tests One and Two: Repeatability

Local Heat Flux to Wall (vs. height)

Local Wall Temperatures (vs. height)