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A Novel Multiscale Methodology for Simulating Tunnel Ventilation Flows During Fires

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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.

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Abbreviations

a,b,c :

Fan characteristic curve coefficients

c p :

Air specific heat [kJ/kg K]

D h :

Hydraulic diameter [m]

D f :

Diameter of the fire source [m]

f :

Major losses coefficient

G :

Mass flow rate through a branch [kg/s]

G ext :

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

G g :

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]

L D :

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

L CFD :

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]

T ext :

External environment temperature [K]

T g :

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]

Δp fan :

Pressure gain induced by jet fan [Pa]

Δp loss :

Pressure losses due to friction [Pa]

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Acknowledgements

The authors would like to thank Dr Vittorio Verda and Dr Ricky Carvel for their help and the interesting discussions on the subject permitting the publication of this paper.

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Authors and Affiliations

  1. BRE Centre for Fire Safety Engineering, University of Edinburgh, Edinburgh, UK

    Francesco Colella, Guillermo Rein & Jose L. Torero

  2. Dipartimento di Energetica, Politecnico di Torino, Torino, Italy

    Romano Borchiellini

Authors
  1. Francesco Colella
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  2. Guillermo Rein
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  3. Romano Borchiellini
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  4. Jose L. Torero
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Corresponding author

Correspondence to Francesco Colella.

Additional information

Francesco Colella, Dipartimento di Energetica, Politecnico di Torino, Torino, Italy.

Appendices

Appendix A: Additional Grid Independence Plots

Some of the temperature and velocity contours calculated in the grid independence study are presented in Figure 16. It shows the contours of temperature and horizontal velocity at Reference Section 2 located 100 m downstream the fire source. They are computed for four difference meshes whose characteristics are summarized in Sect. 3.1. As expected from the previous results, the computed solutions show larger deviations for the courses meshes 1 and 2 while convergence is obtained for finer meshes 3 and 4.

Figure 16
figure 16

Comparison of the longitudinal velocity (left) and temperature (right) contours for meshes #1 to #4 in the tunnel Reference Section 2 for a 30 MW fire. Velocity and temperature values are expressed in m/s and K, respectively

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Appendix B: Additional Boundary Independence Plots

The results of the boundary independence study relative to the tunnel Reference Section 2, located 100 m downstream the fire are presented in Figure 17. Also in this case, the analysis of the temperature and velocity fields shows that highly accurate results can be achieved with 3D domains whose downstream boundary is at a minimum distance of 100 m from the furthest location where a CFD accurate solution is required.

Figure 17
figure 17

Effect of the CFD domain length L CFD on the horizontal velocity and temperature fields at Reference Section 2 for a 30 MW fire. Velocity and temperature values are expressed in m/s and K, respectively

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Appendix C: Scenarios 2–4––Comparison of the Field Results for Multiscale and Full CFD Representations

Additional results on the temperature and velocity fields computed using multiscale and full CFD techniques are presented here. They include the ventilation scenarios 2–4 (see Figures 18, 19 and 20). These field data also confirm that high numerical accuracy can be achieved by using a multiscale technique.

Figure 18
figure 18

Comparison of results near the fire for the multiscale and the full CFD simulations for a fire of 30 MW and ventilation scenario 2. Velocity and temperature values are expressed in m/s and K, respectively. The longitudinal coordinates start at the upstream boundary of the corresponding CFD domain

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Figure 19
figure 19

Comparison of results near the fire for the multiscale and the full CFD simulations for a fire of 30 MW and ventilation scenario 3. Velocity and temperature values are expressed in m/s and K, respectively. The longitudinal coordinates start at the upstream boundary of the corresponding CFD domain

Full size image
Figure 20
figure 20

Comparison of results near the fire for the multiscale and the full CFD simulations for a fire of 30 MW and ventilation scenario 4. Velocity and temperature values are expressed in m/s and K, respectively. The longitudinal coordinates start at the upstream boundary of the corresponding CFD domain

Full size image

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Colella, F., Rein, G., Borchiellini, R. et al. A Novel Multiscale Methodology for Simulating Tunnel Ventilation Flows During Fires. Fire Technol 47, 221–253 (2011). https://doi.org/10.1007/s10694-010-0144-2

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