Fire Technology

, Volume 47, Issue 1, pp 221–253 | Cite as

A Novel Multiscale Methodology for Simulating Tunnel Ventilation Flows During Fires

  • Francesco Colella
  • Guillermo Rein
  • Romano Borchiellini
  • Jose L. Torero
Article

Abstract

This paper applies a novel and fast modelling approach to simulate tunnel ventilation flows during fires. The complexity and high cost of full CFD models and the inaccuracies of simplistic zone or analytical models are avoided by efficiently combining mono-dimensional (1D) and CFD (3D) modelling techniques. A simple 1D network approach is used to model tunnel regions where the flow is fully developed (far field), and a detailed CFD representation is used where flow conditions require 3D resolution (near field). This multi-scale method has previously been applied to simulate tunnel ventilation systems including jet fans, vertical shafts and portals (Colella et al., Build Environ 44(12): 2357–2367, 2009) and it is applied here to include the effect of fire. Both direct and indirect coupling strategies are investigated and compared for steady state conditions. The methodology has been applied to a modern tunnel of 7 m diameter and 1.2 km in length. Different fire scenarios ranging from 10 MW to 100 MW are investigated with a variable number of operating jet fans. Comparison of cold flow cases with fire cases provides a quantification of the fire throttling effect, which is seen to be large and to reduce the flow by more than 30% for a 100 MW fire. Emphasis has been given to the discussion of the different coupling procedures and the control of the numerical error. Compared to the full CFD solution, the maximum flow field error can be reduced to less than few percents, but providing a reduction of two orders of magnitude in computational time. The much lower computational cost is of great engineering value, especially for parametric and sensitivity studies required in the design or assessment of ventilation and fire safety systems.

Keywords

Tunnel Ventilation systems Multiscale modelling CFD Jet fans 

Nomenclature

a,b,c

Fan characteristic curve coefficients

cp

Air specific heat [kJ/kg K]

Dh

Hydraulic diameter [m]

Df

Diameter of the fire source [m]

f

Major losses coefficient

G

Mass flow rate through a branch [kg/s]

Gext

Mass flow rate exchanged with the external environment in a node [kg/s]

Gg

Mass flow rate of the gases released from the fire source [kg/m3]

g

Gravity acceleration [m/s2]

h

Convective heat transfer coefficient [W/m2 K]

L

Branch length [m]

LD

Distance from the fan/fire region to the downstream boundary interface [m]

LCFD

Length of the CFD domain in the multi-scale representation [m]

p

Pressure [Pa]

P

Branch perimeter [m]

Pr

Prandtl number

R

Wall-lining thermal resistance [K m2/W]

T

Temperature [K]

Text

External environment temperature [K]

Tg

Temperature of the gases released from the fire source [K]

U

Overall heat transfer coefficient [W/m2 K]

v

Flow velocity [m/s]

z

Node elevation [m]

β

Minor losses coefficient

θ

Generic flow quantity [temperature or velocity]

ε

Average error of the multiscale model [%]

Φ

Fire heat release rate [W]

Φ*

Dimensionless fire heat release rate

φc

Convective fire heat release rate per unit length [W/m]

λ

Flame radiative fraction

ρ

Air density [kg/m3]

ρext

Air density at external environment [kg/m3]

Δpfan

Pressure gain induced by jet fan [Pa]

Δploss

Pressure losses due to friction [Pa]

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Francesco Colella
    • 1
  • Guillermo Rein
    • 1
  • Romano Borchiellini
    • 2
  • Jose L. Torero
    • 1
  1. 1.BRE Centre for Fire Safety EngineeringUniversity of EdinburghEdinburghUK
  2. 2.Dipartimento di EnergeticaPolitecnico di TorinoTorinoItaly

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