> For the complete documentation index, see [llms.txt](https://docs.gasflow-mpi.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.gasflow-mpi.com/7.-ongoing-development-and-enhancements/7.1.-combustion-modeling/7.1.7.-jet-flame-modeling.md).
# 7.1.7. Jet Flame Modeling
## 7.1.7.1. Introduction
**Version:** GASFLOW-MPI 2.1 Revision 4860 (March 30, 2025) or a more recent revision.
**Fuel Type:** We currently support hydrogen and methane as fuel types. However, new fuel types can be easily implemented to meet user requirements.
When using the Eddy Dissipation model, the combustion is assumed to be infinitely fast, which means the fuel and oxidizer react instantaneously as soon as they are mixed, without any delay. This simplification can lead to inaccuracies in situations where the combustion process is controlled by the chemical kinetics, rather than the turbulent mixing. For example, if the ignition is delayed by 0.3 seconds in the example bove, the Eddy Dissipation model would predict the mixtures to be burned immediately as soon as the ignition starts. However, this may not be an accurate representation of the actual combustion behavior, especially for cases with significant ignition delay or slow chemical reactions. For example, it may overpredict the pressure due to the very fast combustion.
To address this limitation, a better approach is to combine the finite-rate chemical kinetics model with the Eddy Dissipation model. This hybrid approach can more accurately capture the combustion process when the chemical kinetics dominate the overall behavior, such as in transient simulations.
On the other hand, for steady-state simulations of jet flames, the combustion is often dominated by the turbulent mixing rather than the chemical kinetics. In such cases, the Eddy Dissipation model alone may be sufficient, as the infinite-rate combustion assumption would be a reasonable approximation.
## 7.1.7.2. Key input parameters for jet fire modeling
### 1) Input parameter to activate jet fire modeling
Activate the Eddy-Dissipation/Finite-Rate (ED/FR) for hydrogen jet flame modeling
{% hint style="info" %}
iburn = 3, ; Activate the ED-FR model for hydrogen jet flame modeling
iburn3\_ed = 1, ; Activate the reaction rate calculated by EDM
iburn3\_fr = 1, ; Activate the reaction rate calculated by finite rate
iburn1\_forev = 1, ; One-step forward reaction for H2-O2 combustion
iburn1\_freqfact\_for = 5.0e+12, ; Frequency factor
iburn1\_tact\_for = 9.375e+3, ; Activation temperature (Ea/R)
iburn1\_n\_for = 0, ; Temperature exponentional factor
{% endhint %}
Ignition starts at 0.0 s and the duration is 0.01 s.
{% hint style="info" %}
burndef(1:10,1) = 30, 34, 1, 2, 4, 5, 1, 2000, 0, 0.01, ; Ignitor
{% endhint %}
Activate the Eddy Dissipation model for methane jet flame modeling
{% hint style="info" %}
iburn = 7, ; Activate the ED-FR model for hydrogen jet flame modeling
iburn7\_fr = 1,; Activate FR model. Must be 1 for premixed combustions.
iburn7\_ed = 1, ; Activate EDM
ireastep = 1, ; One-step global CH4-O2 combustion
ich4reaopt = 1,
{% endhint %}
Ignition starts at 0.0 s and the duration is 0.01 s.
{% hint style="info" %}
burndef(1:10,1) = 4, 5, 1, 2, 20, 24, 1, 2000, 0, 0.01, ; Ignitor
{% endhint %}
### 2) Input parameter for gas species
Gas spieces for hydrogen jet flame
{% hint style="info" %}
mat = 'h2', 'o2', 'n2', 'h2o', ; gas spieces for hydrogen jet flame
{% endhint %}
Gas spieces for methane jet flame
{% hint style="info" %}
mat = 'ch4', 'o2', 'n2', 'h2o', 'co2', ; gas spieces for methane jet flame
{% endhint %}
### 3) Input parameters for turbulence modeling
Turbulence model as well as mass/momentum/energy diffusion must be switched on in jet flame simulations.
{% hint style="info" %}
tmodel = 'ke', ; turbulence model
idiffmom = 1, ; momentum diffusion (0: off | 1: on; must be 1 if tmodel /= 'none')
idiffme = 1, ; mass and energy diffusion (0: off | 1: on)
{% endhint %}
Because the simulation results of the jet flame are sensitive to the initial and boundary conditions of the turbulence model, it is important for the user to choose appropriate values for epsval and tkeval according to the specific conditions of their simulation. In the example below, the initial turbulence conditions (0 s) in the entire computational domain is set up in turbdef(1:12,1), and the turbulent boundary conditions (0-9999 s) at the jet nozzle is given by turbdef(1:12,2).
{% hint style="info" %}
```
turbdef(1:12,1) = 1, 'im1', 1, 'jm1', 1, 'km1', 1, 1, 1, 0, 0.0, 0.0,
turbdef(1:12,2) = 3, 3, 1, 2, 21, 23, 1, 2, 2, 0, 0.0, 9999.0,
tkeval = 100.0, 1.5e5,
epsval = 1000.0, 1.0e5,
```
{% endhint %}
### 4) Input parameters for numerical control
{% hint style="info" %}
```
cflnum = 0.25, ; CFL number for advection
cfldiff = 0.25, ; CFL number for diffusion
ifvl = 1, ; advection scheme (0: donor cell | 1: van Leer)
```
{% endhint %}
It is recommended to limit the CFL (Courant-Friedrichs-Lewy) numbers for advection (**cflnum**) and diffusion (**cfldiff**) to around 0.25 to ensure numerical stability. The user can set these values between 0 and 1. Using a bigger CFL number will result in a larger time step, which can reduce the overall simulation time. However, this approach must be applied with caution, as excessively high CFL numbers can also lead to numerical instability in the simulation. The user should increase the CFL values gradually and monitor the simulation closely for any signs of instability, such as diverging results or unphysical oscillations.
## 7.1.7.3. Input example
This example demonstrates how to set up GASFLOW-MPI to model vertical and horizontal CH4-air jet flames. The user will need to refine the mesh and set appropriate initial and boundary conditions for their specific application.
