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Numerical Investigation of Sustained-Release Hydrogen Jet Combustion with Heat Transfer in a Vented Enclosure

Xiao J. J.1,*, Kuznetsov M.1, Travis J.2

1Karlsruhe Institute of Technology (KIT), Institute of Nuclear and Energy Technologies, Karlsruhe, Germany

2Engineering and Scientific Software Inc., Santa Fe, New Mexico, USA *Corresponding author email: jianjun.xiao@kit.edu

ABSTRACT Hydrogen jet fires can lead to serious safety problems for hydrogen and fuel cell systems. Experimental studies of hydrogen jet fires in a vented enclosure have been performed within the European Hyindoor project. Hydrogen is released from the bottom of the enclosure through a leak and forms a hydrogen jet flame due to the immediate ignition near the release nozzle. It has been found experimentally that heat losses can significantly affect the entire combustion process. The purpose of this paper is to further understand the effects of heat transfer phenomena on the dynamics and regimes of the enclosed hydrogen jet flames. Numerical simulations of an under-ventilated jet fire (WP4-036) were performed using the recently released CFD code GASFLOW-MPI. The effects of heat transfer mechanisms were investigated, including heat conduction in solid walls, steam condensation, convective heat transfer and thermal radiation. With heat transfer modeling, both initial pressure peak and pressure decay were very well predicted compared to the experimental data. Self-extinction and self-reignition were captured in the numerical simulation as well. In the adiabatic simulation case, the pressure and temperature were considerably over-predicted and the major physical phenomena occurring in the combustion enclosure were not successfully reproduced which show big discrepancies from the experimental observations. It indicates that the effects of the heat transfer mechanisms are significant, and they must be considered in numerical simulations in order to accurately predict the turbulent jet fire in a vented combustion chamber. KEYWORDS: Numerical simulation, jet fire, heat losses, hydrogen combustion, GASFLOW-MPI.

INTRODUCTION

Hydrogen jet fires following an accidental release is one of the important safety issues for hydrogen and fuel cell systems. Many factors could impact the hydrogen jet combustion regimes, internal and external pressure and temperature, such as mixture properties, vent size, geometry and dimensions of the vessel, and ignition locations. Combustion of hydrogen jets in an enclosure with venting has not been systematically studied and is not well understood. Therefore, experiments and numerical investigations have been performed to study the hydrogen jet fire in a vented combustion vessel within the European Hyindoor project. It was found from the experiments [1, 2] that heat losses from the combustion products to the enclosure structures may result in pressure oscillations and formation of very low under-pressures that draws air back into the enclosure from the ambient and leads to re-ignition. In the numerical investigations [3], advanced numerical modelling and simulation techniques have been applied to gain insight into various combustion regimes of indoor hydrogen jet fires. However, some physical phenomena, such as pressure oscillations and re-ignition due to back flowing air, were not captured because the effect of heat losses was not considered. In the present work, effects of various heat transfer mechanisms were studied in hydrogen jet fire with respect to hydrogen safety of indoor facilities. The main purpose of this paper is to further reveal and better understand Proceedings of the Eighth International Seminar on Fire and Explosion Hazards (ISFEH8), pp. 669-678 Edited by Chao J., Liu N. A., Molkov V., Sunderland P., Tamanini F. and Torero J. Published by USTC Press ISBN:978-7-312-04104-4 DOI:10.20285/c.sklfs.8thISFEH.067

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the importance of heat losses [4] to the combustion regimes and pressure peak and decay phenomena in an indoor hydrogen jet fire.

EXPERIMENTAL FACILITY

The experimental facility is built inside the test-chamber at the Hydrogen Test Center HYKA at KIT that has a volume of approximately 160 m3. The facility itself mainly consists of a cubic enclosure with inner dimensions of 1 m × 0.96 m × 0.98 m (H × W × D), as shown in Fig. 1. It is made of Aluminum profile rails that are covered with two transparent and four solid plates. Solid Aluminum plates with a thickness of 10 mm are mounted at the top, bottom, front and rear side of the enclosure, while the transparent ones (dual composite of 0.005 m fire-protection glass (Pyran) and 0.015 m of Plexiglas (Makrolon)) are on the left and right side. S1 is the location of the pressure and temperature sensors. They are located at the center of the top wall and the height is 1 m which means the sensor is attached to the wall.

The front plate is used to provide different vent openings in the corresponding experiments designated WP4. The front plate design allows horizontal venting of 0.03 m × 0.30 m located at the central upper position in experiment WP4-036, as illustrated in Fig. 2. A tube nozzle with 0.005 m internal diameter was located in the center of the bottom metal plate 0.1 m above the internal plate surface. Hydrogen was released at the mass flow rate of 0.5486 g/s and injection velocity 300 m/s. In order to avoid hydrogen accumulation and hydrogen explosion risks inside the HYKA Test-Chamber, hydrogen was stopped at 41 s in the experiment WP4-036. The ignition source was 0.02 m above the nozzle orifice and at 0.01 m from the centerline to provide the most efficient ignition of released hydrogen. The spark plug igniter started operating just before hydrogen release so that there is little time for unburned hydrogen accumulation.

Figure 1. Sketch, pressure and temperature sensors

locations and materials of the test enclosure (unit: mm). Figure 2. Front plate with horizontal vent (300 mm × 30 mm) at the top.

NUMERICAL SIMULATIONS

Solver and numerical models

The 3-D parallel CFD code GASFLOW-MPI [5] was used in this study. It is a best-estimate analytical tool for predicting transport, mixing, and combustion of hydrogen and other gases in nuclear reactor containments and other facility buildings. It is a finite-volume code based on proven computational fluid dynamics methodology that solves the compressible Navier-Stokes equations for three-dimensional volumes in Cartesian or cylindrical coordinates. The ICED-ALE numerical methodology

S1 S2

S3

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has been applied for solutions of the Navier-Stokes equations applicable to supersonic flows to the incompressible limit [6].

The Eddy Dissipation Model (EDM) [7] is based on the assumption that combustion occurs at small scales, where mixing occurs on a molecular level and the rate is assumed to be proportional to the inverse turbulent time scale. It was developed from the original eddy break-up model, the most significant difference being that the EDM model accounts for the fact that the reaction rate cannot occur unless both fuel and oxidizer mix on a molecular scale at a sufficient temperature. This is accomplished by relating the reaction rate to the limiting species. In GASFLOW-MPI, the model is formulated as follows:

2 2

2

O H O

1 2min , , ,1H

Y YS B Y B

kξ

ερ ρ

φ φ=

+

(1)

where B1 = 4.0 and B2 = 0.5 are model constants, and φ is the equivalence ratio. The convective heat transfer between the gas mixture and solid structures, such as walls, ceiling, floor, or internal structures, is given by

( ),conv ,I s s sS h A T T= − (2)

where Ts is the structure surface temperature, T is the gas temperature, hs is the heat-transfer coefficient between the gas mixture and the internal structures, and As is the cell face area for walls or the exposed area for internal structures in a computational cell. The thermal boundary layer is taken into account by using a modified Reynolds analogy formulation which is simplified and combined with a Chilton-Colburn empirical analogy between the momentum and thermal boundary layers to obtain the heat transfer coefficient hs:

23 ,s

s pc

h C P ruτ −

= ⋅ (3)

where τs is the wall shear stress, uc is the cell-centered average velocity, Cp is the specific heat capacity and Pr is the Prandtl number.

The energy resulting from the steam condensation or evaporation on the structural wall surface is calculated as

( ) ( )

( ) ( )2 2

2 2

H o ,saturation H o

,cond/vap

H o ,saturation H o

,max

d s s s

s

d s s

h A I Tq

h A I T

ρ ρ

ρ ρ

− = −

, (4)

where 2H oI (T) is the specific internal energy of the water vapor in the computational cell adjacent

to the wall, and 2H oI (Ts) is the specific internal energy of the liquid water film that is on the surface.

2H oρ is the water vapor density in the gas mixture. The mass transfer coefficient, hd, then can be expressed in terms of the heat transfer coefficient, hs, as

, (5)

by making use of a Chilton-Colburn empirical analogy between heat and mass transfer.

Thermal radiation from combustion products can play an important role in the overall processes of combustion and heat transfer. A computationally efficient thermal radiation transport model has been developed in GASFLOW-MPI. In the absence of photon scattering and the assumption that the gas is in local thermodynamic equilibrium, the radiation-transport equation for a gray gas can be given as

23

23

sd

p

h SchC Prρ

−

−=

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( ) ( ) ( )4, , , ,1 , ,

πii

E r t E r t Tl E r tc t x

Ω Ω ασα Ω

∂ ∂+ = − +

∂ ∂, (6)

where α is the absorption coefficient, c is the speed of light, σ is the Stefan-Boltzmann constant, T is the temperature of the gas, E(r, Ω, t) is the specific radiation intensity which is a function of the position vector r and the directional vector Ω and the time t, and the liʼs are the direction cosines of the vector Ω with respect to the coordinate directions xi. The equation can be approximated by a set of differential equations by means of the “differential” approximation method. The proper coupling between the fluid and thermal radiation transport equations is then provided as

( ) ( ) ( )4 rcI uI p u q Q aT Ut

ρ ρλ

∂+ ∇⋅ = − ∇⋅ −∇⋅ + − −

∂, (7)

Ur is the radiation energy density which is given as,

( )1 , , drU E r tc Ω Ω Ω= ∫ . (8)

Geometrical model and computational grid

The combustion chamber is located inside a larger computational domain which uses a “coarse” mesh (52 × 27 × 37), a “medium” mesh (66 × 32 × 70) and a “fine” mesh (84 × 32 × 82) shown in Fig. 3. The meshes are locally refined. In this paper, we will only show the simulation results with the “fine” mesh. Exploiting the symmetry of the problem, only half of the geometry was used in the simulations. The ranges of the coordinates in the fine mesh are: X(−1.5 m, 0.6 m), Y(0.0 m, 0.65 m) and Z(− 0.1 m, 1.1 m), and the total number of cells is 220416. The location of the injection pipe at the center of the bottom wall is (0.0 m, 0.0 m, 0.0 m) and the length of the pipe is 0.1 m. The width and height of the vented enclosure are 0.98 m and 1.0 m. The half depth of the box is 0.48 m. The ignition source is located at 0.02 m above the orifice and 0.01 m from the pipe centreline.

Details of numerical simulation

A finite volume methodology was used based on a staggered Cartesian grid. The second order Van-Leer MUSCL scheme was used for the discretization of the advection terms to minimize the numerical diffusion. The time step is automatically adapted according to prescribed error bands and the maximum desired Courant-Friedrichs-Lewy (CFL) number was set equal to 0.85. A non-slip boundary condition was applied to the walls of the combustion chamber, and a symmetrical boundary condition was imposed at the central cut of the combustion chamber. A constant pressure boundary condition was used for the top surface of the computational domain which allows the outflow of the hot combustion products. The standard κ-ε turbulence model was used. The convergence criteria for linear solvers of pressure and thermal radiation equations are 1.0e − 6.

Hydrogen is released at the velocity of 300 m/s and the temperature of 259.2 K. The pressure of the released hydrogen is 0.996614 bar. The initial pressure and temperature of air in the whole computational domain are 0.996614 bar and 298.53 K. The air is initially stagnant. The top, bottom, front and rear walls are made of Aluminum (AMg3) which has the thickness of 10 mm, while the left and right side transparent walls are dual composite of 0.005 m fire-protection glass (Pyran) and 0.015 m of Plexiglas (Makrolon).

CALCULATION RESULTS

To test and demonstrate GASFLOW-MPIʼs combustion capability we have purposely selected a very demanding experiment. The experiment WP4-036, an under-ventilated case, shows flame self-

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extinction and then self-reignition after fresh oxygen is drawn back into the combustion facility due to the under-pressurization caused by heat losses in the chamber. Self-reignition is a result of fresh air mixing with the hot hydrogen and contacting hot surfaces of the combustion chamber. Two cases, as shown in Table 1, are studied: Case 1 invokes heat (convection and radiation) transfer and condensation mass transfer, and Case 2, for comparison purposes, is simply an “adiabatic” simulation. The adiabatic case will not demonstrate self-reignition inside the chamber because there is neither fresh air inflow due to under-pressure caused by heat losses nor hot-spots on the combustion chamber walls. Case 2 clearly shows the importance of heat and mass transfer effects when compared to Case 1 and the experiments.

Table 1. Details of the simulation cases.

Cases Mass flow rate (g/s)

Release velocity (m/s)

Computational grid

Hydrogen stops at (s) Heat transfer

1 0.5486 300 Fine 41 Convective, thermal radiation, steam condensation

2 0.5486 300 Fine 41 Adiabatic

Simulation results with heat transfer

As shown in Fig. 4, the maximum measured over-pressure of 0.32631 kPa was recorded at 0.25 s. In order to focus on the comparison with the experimental data, we eliminated the information up to 0.25 s, and plotted maximum over-pressure peak of the numerical results beginning at 0.25 s. The computed magnitude of the over-pressure peak is 0.31428 kPa, which gives a relative error of around 3.7%. The pressure is seen to decay quickly to the ambient pressure in roughly 10 s due to the heat losses to chamber walls and gas outflowing through the venting hole. The calculated rate of pressure decay agrees well with the experimental data.

As the burning hydrogen jet continues flowing into the chamber, we see in Fig. 5 that heat losses increase at higher rates until 41 s, and then the rates start to decay. During 10 ~ 41 s, the pressure at the sensor S1 is nearly constant and slightly higher than the ambient value because the fire in the chamber is well ventilated and the pressure is the stagnation pressure which considers the dynamic pressure of the H2 jet. However, upon termination of the hydrogen jet at 41 s, the chamber pressure drops below the ambient value and with condensation continuing at the smaller rate, air is drawn from the ambient back into the combustion chamber. The relative contribution of various heat transfer mechanisms is shown in Fig. 6. Until 80 s, the percentage of integral heat losses due to convective heat transfer, thermal radiation and steam condensation are roughly 70%, 15% and 15%.

The experiment shows three self-reignition events at around 41~50 s. These three self-reignition events, although not very energetic, are due to the air inflow with pockets of hydrogen-oxygen self-ignition when contacting wall hot-spots. As shown in Fig. 4, the self-ignition events were captured in GASFLOW-MPI simulations, although the maximum pressures were under-predicted. After approximately 50 s, combustion events are finished as most of the hydrogen has been consumed and the chamber pressure approaches to the ambient value. One observes that the condensation mass flow rates given in Fig.7 approach zero shortly after the three self-ignition events and the chamber temperatures shown in Fig. 8 are nearly ambient. It should be noted that the S1 temperature sensor is attached to the wall in the experiments. During 0~41 s, the measured temperature increases and decreases slower than the calculated temperature where the sensor used in the numerical simulation is located in the gas cell. It also explains those three temperature peaks during 41-50 s. The temperature sensor in the experiment could not capture the sudden temperature increases due to the re-ignitions which show some inconsistencies to the measured pressure signal in Fig. 4. The weak

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temperature peaks were predicted in the numerical simulation. However, the magnitude is lower than

the experimental data. It should be noted that the different nature of the two sensors- namely a

thermocouple attached to the Al-wall and a calculated gas temperature - makes it difficult to compare

the absolute temperature values. However, it is remarkable that the occurrence of re-ignitions and the

timing of the re-ignition events were predicted by GASFLOW-MPI very well.

-10 0 10 20 30 40 50 60 70 80

-0.1

0.0

0.1

0.2

0.3

0.4

S1 (Case 1, GASFLOW-MPI)

Experimental data (Kuznetsov, 2014)

pre

ssu

re (

kP

a)

time (s) Figure 3. Computational domain with fine mesh

(84 × 32 × 82).

Figure 4. Comparison of over-pressure at the

sensor S1 between experimental data and

numerical results of Case 1.

0 20 40 60 800

200

400

600

800

1000

1200

1400

1600

1800

he

at lo

sse

s to

th

e w

alls

(kJ)

time (s)

steam condensation

convective heat transfer

thermal radiation

0 10 20 30 40 50 60 70 80

0

20

40

60

80

100

steam condensation

thermal radiation

pe

rce

nt (%

)

time (s)

steam condensation (case 1, GASFLOW-MPI)

thermal radiation (case 1, GASFLOW-MPI)

convective heat transfer (case 1, GASFLOW-MPI)

convective heat transfer

Figure 5. Calculated heat losses to the enclosure

walls of Case 1.

Figure 6. Relative contribution of various heat

transfer mechanisms to heat losses of Case 1.

0 10 20 30 40 50 60 70 800.0

4.0x10-4

8.0x10-4

1.2x10-3

1.6x10-3

2.0x10-3

2.4x10-3

2.8x10-3

3.2x10-3

3.6x10-3

4.0x10-3

ste

am

co

nd

en

sa

tio

n r

ate

(kg

/s)

time (s)

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

co

nd

en

se

d s

tea

m m

ass (

kg

)

-10 0 10 20 30 40 50 60 70 80-100

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

tem

pe

ratu

re (

oC

)

time (s)

S1 (Case 1, GASFLOW-MPI)

S1, Experimental data (Kuznetsov, 2014)

Figure 7. Calculated steam condensation rate and

total mass of condensed steam of Case 1.

Figure 8. Comparison of temperature at the sensor

S1 between experimental data and numerical

results of Case 1.

Figs. 9-12 show the calculated 3D temperature iso-surfaces in Case 1 at 10 s, 35 s, 45 s and 60 s,

respectively. The strong hydrogen jet is well depicted in Figs. 8 and 9 while the former Figure at

10 s shows the combusting jet with temperatures near 2000 K. From Fig. 10 at 45 s, during the self

re-ignition phase, we gain an idea of the low energetic combustion event (low temperature around

600 K) and its source on the left hand vertical wall. Note that the plume is deflected away by the

Front wall

Injection nozzle

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inflowing air at the upper left corner of the chamber, as shown in Fig.11. At 60 s (Fig. 12) the chamber is cooled to ~350 K due to the heat losses.

Figure 9. Calculated temperature iso-surfaces of Case 1 at 10 s.

Figure 10. Calculated temperature iso-surfaces of Case 1 at 35 s.

Figure 11. Calculated temperature iso-surfaces of

Case 1 at 45 s. Figure 12. Calculated temperature iso-surfaces of

Case 1 at 60 s.

Adiabatic simulation

In case 2, we repeat the identical geometry with vent and hydrogen jet conditions as in case 1 except that we disable all heat and mass transfer mechanisms. As expected, one observes higher pressures and higher temperatures in this adiabatic case. As illustrated in Fig. 13, in case 2 the pressure peak at S1 reaches up to 0.5 kPa and the pressure in the chamber decreases only due to the gas mixtures outflow through the venting hole. Therefore, we see higher pressure compared to the experimental data and results of case 1. From 20-41 s, the pressure decreases to the ambient pressure indicating a well ventilation with much less energetic hydrogen combustion. The temperature at S1 is heated up to 2600 K without heat losses being modelled. And the temperature keeps constant at more than 1300 K after 41 s, as shown in Fig. 14. Both pressure and temperature are significantly over-predicted in the adiabatic simulation of Case 2.

Moreover, there is no self re-ignition as the hydrogen combustion consumes all available oxygen without the possibility of under-pressurizing the chamber to resupply air from the ambient. This is clearly shown when the hydrogen jet is turned off at 41 s and the chamber pressure drops to the ambient values without any indication of decreasing below the ambient value. As the blue curve

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shows in Fig. 13, the pressure is lower than the ambient pressure during 41-53 s in the simulation with heat transfer (case 1).

-10 0 10 20 30 40 50 60 70 80-0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6 S1 (Case 1, heat transfer, GASFLOW-MPI) Experimental data (Kuznetsov, 2014) S1 (Case 2, adiabatic, GASFLOW-MPI)

pres

sure

(kPa

)

time (s)Time (s)

Pres

sure

(kPa

)

-10 0 10 20 30 40 50 60 70 80-0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6 S1 (Case 1, heat transfer, GASFLOW-MPI) Experimental data (Kuznetsov, 2014) S1 (Case 2, adiabatic, GASFLOW-MPI)

pres

sure

(kPa

)

time (s)Time (s)

Pres

sure

(kPa

)

0 10 20 30 40 50 60 70 800

500

1000

1500

2000

2500 S1 (Case 1, heat transfer, GASFLOW-MPI) S1, Experimental data (Kuznetsov, 2014) S1 (Case 2, adiabatic, GASFLOW-MPI)

tem

pera

ture

(o C)

time (s)

Tem

pera

ture

()

Time (s)

0 10 20 30 40 50 60 70 800

500

1000

1500

2000

2500 S1 (Case 1, heat transfer, GASFLOW-MPI) S1, Experimental data (Kuznetsov, 2014) S1 (Case 2, adiabatic, GASFLOW-MPI)

tem

pera

ture

(o C)

time (s)

Tem

pera

ture

()

Time (s)

Figure 13. Comparisons of over-pressure between experiments and numerical results of Case 1 and

Case 2.

Figure 14. Comparisons of temperature at sensor location S1 between experiments and numerical

results of Case 1 and Case 2.

The 3D temperature iso-surfaces in the chamber are presented in Figs. 15-20 (10 s, 15 s, 25 s, 35 s, 45 s, and 60 s, respectively) provide conclusive information for this adiabatic simulation. The burning jet quenches at approximately 15 s where maximum temperatures around 2600 K are computed and the strong thermal plume exiting the chamber at the upper left corner is shown. By 25 s (Fig. 17), the burning jet is much cooler compared to the jet surroundings > 2000 K. All oxygen has been consumed and the cold hydrogen jet now entrains hot nitrogen and combustion products to increase from its inflowing value to the mixed value. The thermal plume exiting the chamber is only present because the hydrogen jet is still active to 41 s, but it is very weak and cools quickly to the entrainment of ambient air. At 35 s in Fig. 18, an external flame is observed. Since oxygen inside the chamber is almost consumed at 35 s, hot hydrogen accumulates. When the hot H2-N2-H2O gas mix with the fresh air near the vent, hydrogen starts to burn. In the absence of any heat and mass transfer mechanisms, the chamber sits in a mostly steady-state configuration after the hydrogen jet is terminated at 41 s as is shown in Figs. 14, 19-20. Since the temperature of gas mixtures inside the chamber is still higher than 1500 K in the adiabatic simulation (Case 2), very weak reaction can be observed in the area close to the venting hole due to the diffusion of fresh air and hot hydrogen gas mixtures.

CONCLUSIONS

The CFD GASFLOW-MPI code with the κ-ε turbulence model and EDM combustion model was used to perform a detailed simulation of the Hyindoor (www.hyindoor.eu) WP4-036 test. This experiment involved the vented ignition and deflagration of a vertical sonic jet (constant mass flow rate of 0.5486 g/s at 259.2 K from a 5 mm diameter tube) into a volume with inner dimensions of 1 m × 0.96 m × 0.98 m (H × W × D). The effects of heat and mass transfer to chamber walls were studied in Cases 1 and 2. This study serves as an integral test for the following model validation:

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Z

XY

Z

XY

Y

Z

XY

Z

X Figure 15. Calculated temperature iso-surfaces for

Case 2 (adiabatic simulation) at 10 s. Figure 16. Calculated temperature iso-surfaces

for Case 2 (adiabatic simulation) at 15 s.

XY

Z

XY

Z

XY

Z

XY

Z

Figure 17. Calculated temperature iso-surfaces for

Case 2 (adiabatic simulation) at 25 s. Figure 18. Calculated temperature iso-surfaces

for Case 2 (adiabatic simulation) at 35 s.

XY

Z

XY

Z

XY

Z

XY

Z

Figure 19. Calculated temperature iso-surfaces for Case 2 (adiabatic simulation) at 45 s.

Figure 20. Calculated temperature iso-surfaces for Case 2 (adiabatic simulation) at 60 s.

1. The Reynolds Averaged Navier-Stokes (RANS) equations coupled with the classical κ-ε turbulence model and reduced chemical kinetics mechanisms;

2. Detailed heat and mass transfer models between combustion products and the chamber walls.

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In Case 1 with heat and mass transfer, the initial pressure peak at ignition and the subsequent pressure decay as the chamber vents and loses heat is well predicted. Hot steam produced by combustion condenses on the cooler chamber walls. Immediately after the jet is terminated, the chamber pressure drops below the ambient value and air is drawn back into the combustion chamber. Three low energy combustion events were observed in Case 1 as the drawn in air mixes with available hydrogen and is self-reignited as the mixture touches wall hot-spots. These low energy combustion events are predicted in the simulation at the correct time, although not as strong as the experimental data. All major physical phenomena, such as hydrogen jet fire, combustion quenching, under-pressure due to heat losses and steam condensation, fresh air inflow and re-ignitions, which occur in the studied jet combustion process were successfully reproduced in the simulation including convection, thermal radiation, and steam condensation. In the adiabatic simulation (Case 2) without heat and mass transfer models, the initial pressure peak, pressure decay and temperature show big discrepancies from the experiments. Temperature inside the chamber is generally much higher since no heat and mass transfer is modelled. We see flame quenching due to the low oxygen concentration. No re-ignition in the chamber is predicted. Instead, an external flame appears outside of the venting hole due to the very hot hydrogen (> 1500 K) in the chamber flowing out to the ambient. In general, the simulation results of Case 2 fail to reproduce the experimentally observed physical phenomena.

As shown in this study, the major physical phenomena of the confined hydrogen jet fire experiment WP4-036 can only be simulated successfully if the heat loss mechanisms are adequately taken into account. The good results obtained with GASFLOW-MPI support the reliability of the applied models. A further more general conclusion from this investigation is that heat losses can have very important implications for confined hydrogen fires and should be taken into account in predictive CFD simulations.

ACKNOWLEDGEMENTS

The authors would like to acknowledge Wolfgang Breitung for the valuable suggestions.

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Jet Fire in a Vented Enclosure, 8th International Seminar on Fire and Explosion Hazards, China, 2016. 2. Anon. Final Report on Analytical, Numerical, and Experimental Studies of Jet Fires, HyIndoor Project

Contract Number: 278534, 2015. 3. Molkov, V., Shentsov, V., Brennan, S., and Makarov, D. Hydrogen Non-Premixed Combustion in Enclosure

with One Vent and Sustained Release: Numerical Experiments, International Journal of Hydrogen Energy, 39(20): 10788-10801, 2014.

4. Xiao, J. J., Travis, J. R., and Kuznetsov, M. Numerical Investigations of Heat Losses to Confinement Structures from Hydrogen-Air Turbulent Flames in ENACCEF Facility, International Journal of Hydrogen Energy, 40(38): 13106-13120, 2015.

5. Xiao, J. J., Travis, J. R., Royl, P., Svishchev, A., Jordan, T., and Breitung, W. PETSC-Based Parallel Semi-Implicit CFD Code GASFLOW-MPI in Application of Hydrogen Safety Analysis in Containment of Nuclear Power Plant, Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method, Nashville, 2015.

6. Xiao, J. J., Travis, J. R., Royl, P., Necker, G., Svishchev, A., and Jordan, T. GASFLOW-MPI: A Scalable Computational Fluid Dynamics Code for Gases, Aerosols and Combustion, Volume 1: Theory and Computational Model (Revision 1.0), KIT Scientific Report Nr.7710, ISBN 978-3-7315-0448-1, KIT Scientific Publishing, January 2016.

7. Magnussen, B. F., and Hjertager, B. H. On Mathematical Modeling of Turbulent Combustion with Special Emphasis on Soot Formation and Combustion, Proceedings of the Combustion Institute, 16(1): 719-729, 1977.