MINISTERO DELL’INTERNO

DIPARTIMENTO DEI VIGILI DEL FUOCO,

DEL SOCCORSO PUBBLICO E DELLA DIFESA CIVILE

DIREZIONE CENTRALE PER LA FORMAZIONE

An Application In Fire Safety Engineering

C. Barbera, A. Bascià, G. Di Salvo, A. Galfo, R. Lala,

S. Lucidi, D. Maisano, G. Mancini, V. Puccia, F. Vorraro

I e II Corso Direttori Antincendi

Istituto Superiore Antincendi Roma Fire Service College Moreton-in-Marsh

FIRE SAFETY

Deterministic Approach Laws and regulations

FIRE ENGINEERING APPLICATIONS

• In absence of specific laws and regulations

• When specific laws and regulations can’t be complied with

• Fire investigation

• High risk activities (safety report)

Fire Engineering Approach

Fire Models

FIRE ENGINEERING: OPERATIVE VS. NUMERICAL MODELS

Fitted parameters models (or operative models or zone models)

Distributed parameters models (or numerical models or field models)

• They solve numerically (i.e., approximately) a set of exact balance equations (momentum, energy, mass)

• The computational domain is meshed by means of a calculation grid, whose refinement affects the accuracy of the result

• They yield temperature and concentration profiles as a function of time and space

• They solve exactly a set of simplified semi – empirical equations (momentum, energy, mass)

• The computational domain is divided into mixed zones, where intensive properties (i.e., P, T, concentrations) are assumed to be homogeneous

• They yield temperature and gases and smoke concentration in each zone

AN OPERATIVE MODEL: CFAST

• Confined fires

• Two mixed volumes: upper layer (hot layer) + lower layer (cold layer)

• comb << = V / Q

Hypotheses

S: stoichiometric ratio air / fuel m: specific combustion rate [=] kg m-2 s-1

A: compartment section [=] m-2

me: air mass flow rate [=] kg s-1

])/( exp / 1[X X -0

em

A m S •equivalence factor

Controlling parameters

Correlation equation X: output variable X0 : X evaluated in unconfined fires : correlation parameters

ventilation controlled fire

•Ventilation factor,

•Heat Release Rate (HRR)

AN OPERATIVE MODEL: CFAST

Equations

ii m

dt

dm mass equation

UL hhVdt

dP

1 pressure equation

)(1

dT

dPVh

dt

dEii

i

energy equation

))1((1

dT

dPVh

Pdt

dVii

i

volume equation

)1

)((1

dT

dPVTmch

VTcdt

d iiipi

iip

i

density equation

))((1

dT

dPVTmch

Vcdt

dTiiipi

iip

i

temperature equation

AN OPERATIVE MODEL: CFAST

Inputs

• Geometry (compartment dimension, ventilation surface, etc.)

• Material properties (thermal conductivities, etc.)

• Fire geometry and position

• HRR vs. time curve

Outputs

• Average temperature in both layers

• height of layer interfacies

• O2 concentration

• CO concentration

• visibility index

• mass and enthalpy exchange rates

A NUMERICAL MODEL: FDS (Fire Dynamics Simulator)

• Both confined and unconfined fires

• Rate of Heat Release (HRR) not depending on O2 concentration

Hypotheses

Equations

• Mass conservation

• Momentum conservation (three scalar equations)

• Constitutive law (nine scalar equations)

• Energy conservation

• Chemical species conservation

Inputs• Geometry (compartment dimension, ventilation surface, etc.)

• Material properties (thermal conductivities, etc.)

• Position and characteristics of ignition sources

• Rate of Heat Release (HRR): depends on fuel and combustion conditions

Outputs

• Pressure, temperature, velocity and chemical species concentrations as a function of time and space

• Fluxes and exchange rates

A NUMERICAL MODEL: FDS (Fire Dynamics Simulator)

COMPUTATIONAL DOMAIN (D.M. 16/2/1982 All.I – act. 87)

Plan

Cross Section

North View

South View

COMPUTATIONAL DOMAIN (D.M. 16/2/1982 All.I – act. 87)

• GeometryTwo compartments

Ventilation surfaces (2 windows + 1 external door + 1 internal door)

• Material properties

Concrete walls ( = 2100 kg m-3; cp = 0.88 kJ kg-1 K-1; kT = 1 W m-1 K-1)

• Fire geometry and position

7 cellulosic material stacks

• Heat Release Rate (HRR):

depends on fuel and combustion conditions

CFAST NUMERICAL RUNS

2tHRR

t3

HRR [=] MW

t [=] st2t1t0

Runs

0.0029kW s-2

2

0.0049kW s-2

3

0.0069kW s-2

4

0.009kW s-2

5

0.011kW s-2

6

0.02kW s-2

HRRmax (MW) 27.55 32.83 36.90 40.22 42.97 52.39

t0 (s) 0 0 0 0 0 0

t1 (s) 3080 2585 2300 2110 1975 1620

t2 (s) 9240 7755 6900 6330 5925 4860

t3 (s) 12320 10340 9200 8440 7900 6480

Run 1: sensitivity analysis on the role of

A TYPICAL CFAST OUTPUT WINDOW

Values

Profiles

= 0.0069 kW s-2

= 0.02 kW s-2 = 0.011 kW s-2

= 0.009 kW s-2

OUTPUTS OF CFAST RUN 1

Run 1

0.0029kW s-2

2

0.0049kW s-2

3

0.0069kW s-2

4

0.009kW s-2

5

0.011kW s-2

6

0.02kW s-2

h1 (m) 1.21 1.21 1.21 1.21 1.21 1.21

h2 (m) 0.89 0.88 0.87 0.86 0.86 0.86

Tu1 (°C) 670 654 643 636 630 610

Tl1 (°C) 585 567 554 546 538 514

Tu2 (°C) 289 282 278 275 272 265

Tl2 (°C) 61 60 59 59 58.7 58

h1: interfacies height in compartment 1

h2: interfacies height in compartment 2 Tu1: maximum temperature in the upper layer in compartment 1 Tl1: maximum temperature in the lower layer in compartment 1 Tu2: maximum temperature in the upper layer in compartment 2 Tl2: maximum temperature in the lower layer in compartment 2

CFAST NUMERICAL RUNS

Run 2: sensitivity analysis on the role of ventilation factor

OUTPUTS OF CFAST RUN 2

Run 2

(6 = 0.02)

Vf1

0.031Vf

0.034

Vf

0.0366

Vf

0.046

t600 (min) 77.8 56.2 46.3 28.1

h1 (m) 1.21 1.21 1.22 1.27

h2 (m) 0.86 0.92 0.99 1.11

Tu1 (°C) 610 665 704 813

Tl1 (°C) 514 564 596 707

Tu2 (°C) 265 271 273 282

Tl2 (°C) 58 54 50 44

t600: t corresponding to Tu = 600 °C

FDS NUMERICAL RUNS

Operative assumptionsDistributed parameters model Fire load can be splitted!

7 stacks with HRR = HRRmax / 7

Fire starts from stack 1

Each stack burns when T ≥ 200°C (ignition temperature)

Run1: without sprinklers Run 2: with sprinklers

OUTPUTS OF FDS RUN 1

Ceiling temperature

20,0

120,0

220,0

320,0

420,0

520,0

620,0

720,0

0,0 200,0 400,0 600,0 800,0 1000,0 1200,0 1400,0 1600,0 1800,0 2000,0

Time [s]

Tc1

Tc2

Tc3

Tc4

Tc5

Tc6

Tc7

Ceiling temperature vs. time

t (T1max) = 338 s

Ceiling temperature distribution at t = 338 s

OUTPUTS OF FDS RUN 1

Smoke propagation:

even though at t = 180 s only one stack burns, smoke invades both the compartments.

t = 60 s t = 120 s

t = 180 s t = 338 s

FDS NUMERICAL RUN 2

Sprinklers lay-out

• Operating pressure: 0.483 bar• K: 79 l min-1 bar -1/2

• Activation temperature: 74°C• RTI (Response Time Index): 110 (m·s)1/2

Sprinklers characteristics

OUTPUTS OF FDS RUN 2

Ceiling temperature

0

100

200

300

400

500

600

700

0 100 200 300 400 500 600Time [s]

Tem

per

atu

re [

°C]

no sprinkler

sprinklerTc1

0

50

100

150

200

250

300

0 100 200 300 400 500 600

Time [s]

Tem

per

atu

re [

°C]

no sprinkler

sprinklerTc4

0

50

100

150

200

250

300

0 100 200 300 400 500 600

Time [s]

Tem

per

atu

re [

°C]

no sprinkler

sprinkler

Tc7

20,00

70,00

120,00

170,00

220,00

270,00

320,00

370,00

0,00 100,00 200,00 300,00 400,00 500,00 600,00

Time [s]

Tem

pera

ture

[°C

]

Tc1

Tc2

Tc3

Tc4

Tc5

Tc6

Tc7

Synoptic

OUTPUTS OF FDS RUN 2

Smoke propagation and sprinkler activation:

the first sprinkler activates at t = 111.6 s…

… and the last one at t = 330 s

CONCLUSIONS…

• Zone models are very sensitive to ventilation factor and HRR vs. time curve (controlling parameters): they are quick and simple

• Field models allow a more realistic and flexible problem description: accurate input estimation is required and simulations are very time expensive

• T vs. t curves yielded by the two models are different but similarly shaped

… AND FURTHER INVESTIGATIONS

• A set of numerical runs has to be carried out in order to gain a deeper insight in T vs. t curves

• A comparison between model prediction and deterministic approach results can be performed