# Numerical simulations of propane pool fires with the EDC / finite rate chemistry approach using global reaction mechanisms

Jeri At Thabari, Georgios Maragkos, Boris Kruljevic, Alexander Snegirev, Youk Moorthamers, Bart Merci

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Jeri At Thabari, Georgios Maragkos, Boris Kruljevic, Alexander Snegirev, Youk Moorthamers, et al.. Numerical simulations of propane pool fires with the EDC / finite rate chemistry approach using global reaction mechanisms. 4th European Symposium on Fire Safety Science ESFSS, Oct 2024, Barcelona, Spain. 10.1088/1742-6596/2885/1/012044. . hal-05230114

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# Numerical simulations of propane pool fires with the EDC / finite rate chemistry approach using global reaction mechanisms

To cite this article: Jeri At Thabari et al 2024 *J. Phys.: Conf. Ser.* **2885** 012044

View the [article online](#) for updates and enhancements.

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# Numerical simulations of propane pool fires with the EDC / finite rate chemistry approach using global reaction mechanisms

Jeri At Thabari<sup>a*</sup>, Georgios Maragkos<sup>a</sup>, Boris Kruljevic<sup>b</sup>, Alexander Snegirev<sup>a</sup>, Youk Moorthamers<sup>a</sup>, Bart Merci<sup>a</sup>

<sup>a</sup>Department of Structural Engineering and Building Materials, Ghent University, Technologiepark 60, B-9052, Belgium

<sup>b</sup>Université Paris-Saclay, CentraleSupélec, Laboratoire EM2C, Gif-sur-Yvette 91190, France

E-mail: jeri.atthabari@ugent.be

**Abstract.** Large-eddy simulations (LES) of propane gaseous pool fires with the eddy dissipation concept (EDC) combustion model, considering finite rate chemistry effects, are presented in this study. Two global (2-step) chemical reaction mechanisms for propane are explored with different grid resolutions. The study aims to investigate the performance of the employed approach towards predicting the flow field, the flame temperature, and the concentration of minor species (carbon monoxide). The selected mechanisms are also studied in mixture fraction space using a 0D CMC code to complement the LES simulations. The results demonstrate minor differences between the two mechanisms for the predicted flame temperature and the resulting flow field. Nevertheless, the production of CO was significantly different between the two mechanisms. In addition, the numerical predictions on coarse grids were strongly grid sensitive and could not accurately resolve the flame dynamics, illustrating the increased grid requirements associated with the use of finite rate chemistry.

## 1. Introduction

Large-eddy simulations (LES) of fire scenarios have become widely used in fire engineering. Fire simulations should ideally be able to simulate complex phenomena such as flame extinction and re-ignition and predict minor chemical species (e.g. CO). The latter is a concern regarding human safety, given its toxicity. To date, the state-of-the-art approach in fire simulations uses infinitely fast chemistry models, where the "mixed is burnt" approach is utilised. However, modelling of flame extinction with these approaches also relies on additional sub-models, e.g., based on a critical flame temperature or Damköhler number-based models. Furthermore, the prediction of minor species with these models is not straightforward since they only use a single-step reaction (i.e., with chemistry not accounted for). On the other hand, numerical simulations that incorporate finite rate chemistry can address the above-mentioned problems.

This study continues our exploratory work in using LES with finite rate chemistry and EDC combustion model [1, 2] in fire simulations. It has been previously reported that including finite rate chemistry can capture the temperature development and extinction phenomena reasonably well when compared to experiments [1]. Nevertheless, the numerical predictions were found to be (significantly) sensitive to the choice of the chemical mechanism. In this study, the focus is

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on assessing the performance of two different global mechanisms for propane combustion in fire-related scenarios. The performance of these reaction mechanisms is first discussed in mixture fraction space. Extending the focus discussion on temperature and flow field predictions, the carbon monoxide (CO) prediction is also included in this study.

## 2. Modelling

### 2.1. 0D-CMC

The conditional moment closure (CMC) approach described in [3], without consideration of any spatial terms, is considered in this study (i.e., Cambridge 0D-CMC [4] approach). The constant radiative fraction is employed for radiation, while the conditional scalar dissipation rate (SDR) is modelled as a bell-shaped function using the Amplitude Moment Closure (AMC) model. For more detailed descriptions of the 0D-CMC approach, the readers are referred to [3].

### 2.2. LES

The CFD solver FireFOAM, included in OpenFOAM v1912, is used here. The dynamic Smagorinsky model is applied to model sub-grid scale (sgs) turbulence, with the model parameters calculated based on a dynamic procedure [5]. Combustion is modelled considering the EDC model [6], previously reported and evaluated in [1], while radiation is modelled based on the constant radiative fraction approach. The choice for the latter aims to avoid any significant discrepancies in the model predictions that can often arise from radiation modelling when the radiative fraction is not correctly predicted in the simulations. Soot modelling is not considered to avoid added uncertainties. Nevertheless, its effect is already implicitly accounted for in the considered experimental value for the radiative fraction of propane. The two considered global mechanisms are listed in Table 1 (cm, s, mol, and cal/mol). A detailed mechanism, UCSD mechanism [7], which consists of 57 species and 268 reactions, is also employed as a reference solution. It is important to note that this detailed mechanism is not considered in the LES simulations of this study due to the high computational costs associated with its use (i.e., only tested in CMC-0D).

<table><caption>Table 1: Global reaction mechanisms for C₃H₈ used in the LES simulations.</caption><thead><tr><th>Name</th><th>No.</th><th>Reactions</th><th>Ref.</th></tr></thead><tbody><tr><td rowspan="2">WD</td><td>1</td><td>C<sub>3</sub>H<sub>8</sub> + 3.5O<sub>2</sub> → 3CO + 4H<sub>2</sub>O<br>r<sub>1</sub> = 1.0 × 10<sup>12</sup> exp(-3.0 × 10<sup>4</sup>/RT) [C<sub>3</sub>H<sub>8</sub>]<sup>0.1</sup> [O<sub>2</sub>]<sup>1.65</sup></td><td>[8]</td></tr><tr><td>2</td><td>CO + 0.5O<sub>2</sub> ↔ CO<sub>2</sub><br>r<sub>2f</sub> = 10<sup>14.6</sup> exp(-4.0 × 10<sup>4</sup>/RT) [CO]<sup>1</sup> [H<sub>2</sub>O]<sup>0.5</sup> [O<sub>2</sub>]<sup>0.25</sup><br>r<sub>2b</sub> = 5 × 10<sup>8</sup> exp(-4.0 × 10<sup>4</sup>/RT) [CO<sub>2</sub>]<sup>1</sup></td><td></td></tr><tr><td rowspan="2">BE</td><td>1</td><td>C<sub>3</sub>H<sub>8</sub> + 3.5O<sub>2</sub> → 3CO + 4H<sub>2</sub>O<br>r<sub>1</sub> = 5.82 × 10<sup>12</sup> exp(-3.4 × 10<sup>4</sup>/RT) [C<sub>3</sub>H<sub>8</sub>]<sup>0.8</sup> [O<sub>2</sub>]<sup>0.86</sup></td><td>[9]</td></tr><tr><td>2</td><td>CO + 0.5O<sub>2</sub> ↔ CO<sub>2</sub><br>r<sub>2</sub> = 2.0 × 10<sup>9</sup> exp(-1.2 × 10<sup>4</sup>/RT)</td><td></td></tr></tbody></table>

## 3. Test case and Numerical Set-up

This study selects the NIST propane pool fire experiments (21 kW and 34 kW) [10] as validation test cases. They involve a 37 cm diameter gaseous burner in a well-ventilated and quiescent
environment. The reported radiative fractions for the two scenarios were 0.23 (21 kW) and 0.3 (34 kW). A more detailed description of the experimental set-up is found in [10].

A cylindrical computational domain with a diameter of 3 m and a height of 2.32 m is used to model the case. Three different grid sizes are utilised, namely 4 cm, 2 cm, and 1 cm. Uniform meshes are used for the 4 and 2 cm grid size cases, while a local refinement is used for the 1 cm grid case (applied in a 2 m height x 2 m diameter region above the burner). These grid sizes correspond to the plume resolution index (PRI), defined as $D^*/\Delta$, values in the range of 5 - 25. Hence, only the finest grid size used in the present study (1 cm) is considered sufficiently small to resolve the fire plume dynamics reasonably well. The study employs second-order schemes for time and spatial discretisation. As previously reported in [1], a flame anchoring strategy, by fixing the temperature in the first row of cells, just above the burner, to be above the autoignition temperature of the fuel (set to 900 K here) is needed to establish a burning flame. This approach is prone to further improvement and will be further explored in future research.

# 4. Results

## 4.1. 0D-CMC results

Fig. 1 presents the simulation results of the selected mechanisms in a mixture fraction space, $Z$, for two different radiative fractions (i.e., 0.23 and 0.3). Simulations have been performed for three different values of the maximum scalar dissipation rate (SDR), namely, 0.05, 0.1 and 0.2 $s^{-1}$ (i.e., values representative of typical fire simulations). The overall trend for all the results was similar. Hence, only results for $0.1 s^{-1}$ are shown here.

<figure><img src="image_5.png" /><figcaption>Figure 1: Predicted temperature (left) and CO concentration (right) in mixture fraction space from the 0D-CMC simulations.</figcaption></figure>

The temperature results with the two global mechanisms (WD and BE) are very similar in mixture fraction space, both predicting higher temperatures in the fuel-rich side (i.e., $Z > Z_{st}$) when compared to the detailed mechanism (UCSD). As expected, lower temperatures are obtained as the radiative fraction increases since more heat is lost due to radiation. Rapid growth in CO is predicted by all mechanisms right after stoichiometry, with the concentrations reaching their maximum values and decreasing to zero in fuel-rich conditions. Both the UCSD (detailed) and BE (global) mechanisms appear to be sensitive to the value of the prescribed radiative fraction, hence the predicted flame temperatures (which mainly deviate between the different mechanisms around stoichiometry). On the other hand, this sensitivity is less pronounced for
the WD (global) mechanism, which could potentially be linked to the fact that the CO oxidation reaction for this mechanism does not solely depend on temperature (as is the case with the other mechanisms) but on chemical composition as well (see Table 1). Similar differences are also seen in the LES simulations, which will be discussed later.

## 4.2. LES Results

<figure><img src="image_6.png" /><figcaption>Figure 2: Average temperature (top row) and axial velocity (bottom row), as a function of grid size, with different mechanisms for an HRR of 21 kW (left column) and 34 kW (right column).</figcaption></figure>

The predicted flame temperatures and axial velocities from the LES simulations on the centerline (i.e., along $z^* = z/D^*$ where $D^*$ is the characteristic fire diameter), as a function of grid size, for different HRRs and reaction mechanisms are presented in Fig. 2. The model predictions exhibit a strong grid dependency, regardless of the choice of the chemical mechanism. This is more pronounced in the lower HRR case and stems from the fact that the flames are (significantly) under-resolved with grid sizes of 4 cm and 2 cm. The PRI for the 21 kW pool fire scenario was on the order of 5 (4 cm) - 10 (2 cm), while the equivalent values for the 34 kW case were 6 (4 cm) - 12 (2 cm). These values are on the lower end of suggested values reported in the literature (i.e., 10 - 20 based on fire plume results reported in [11] with fast chemistry) to be sufficient for accurately resolving the fire plume dynamics. Given the even more restrictive required grid resolutions associated with the use of finite rate chemistry, it is not surprising that the coarse grid simulations in the lower HRR cases do not perform well. The coarser grid (4 cm and 2 cm) simulations failed to accurately reproduce the expected heat release rate (i.e., due to low reaction rates, some fuel did not react and escaped the computational domain). Depending
on the mechanism, there was an under-prediction of the HRR on the order of 17-30% on the 4 cm grid and approximately 6-10% on the 2 cm grid size. Similar findings were also previously reported in [1] using finite rate chemistry. For this reason, evaluation of the predictions with the employed reaction mechanisms on the coarse grid sizes is not strictly appropriate. Overall, the best predictions are obtained with the finest grid size considered in the simulations (1 cm). The BE mechanism gives slightly higher temperatures than the WD mechanism, similar to what was previously observed from the CMC-0D simulations around stoichiometry (see Fig. 1). The model predictions can follow the experimental trends (e.g., rapid increase of temperature and axial velocity near the burner and subsequent decrease further downstream in the plume region). Nevertheless, discrepancies also exist in all the different parts of the flame, i.e., an over-prediction of the flame temperatures in the intermittent and plume regions (with subsequent over-predictions in the plume velocities). These discrepancies are due to a lack of sufficient turbulence near the burner, predicting a more laminar-like flame structure, which leads to high axial velocities due to strong buoyancy forces. The use of even finer grid resolution (somewhat prohibitive in terms of computational cost in this case) is expected to lead to a more turbulent flame, which would break up closer to the burner and lead to a decrease in both the flame temperatures and axial velocities in the intermittent/plume regions.

<figure><img src="image_7.png" /><figcaption>Figure 3: Average CO and CO₂ concentrations on the centerline, as a function of grid size, with different reaction mechanisms for a heat release rate of (a) 21 kW and (b) 34 kW.</figcaption></figure>

Fig. 3 presents the model predictions for the CO and CO₂ concentrations on the centerline, only on the finest grid size (1 cm), with different reaction mechanisms for the 21 kW and 34 kW pool fire scenarios. There is a clear tendency of the WD mechanism to over-predict and the BE mechanism to under-predict the CO concentrations in both scenarios. Conversely, the WD mechanism can predict reasonably well the maximum CO₂ concentration within the flame region (i.e., towards the fuel-rich conditions) but starts to deviate when going further downstream towards the intermittent region (i.e., towards the fuel-lean conditions). The BE mechanism significantly over-predicts CO₂ in all axial locations examined (which aligns with the lack of CO produced since it has been oxidised). It should be stressed at this point that the two considered reaction mechanisms have not been explicitly developed for fire applications. More specifically, the BE mechanism is mainly developed and used for piston combustion [9] (and valid for high pressures) while the second reaction in the WD mechanism was added to partly account for the effects of incomplete conversion to CO₂ and H₂O, and to include qualitatively the sequential nature of the hydrocarbon oxidation. Although the WD mechanism captures the experimental trends qualitatively, to some extent, neither mechanism quantitatively predicts the correct species concentrations. The development of reduced reaction mechanisms
specifically tailored for fire applications is required for this purpose. In addition, the results
from this study demonstrate that a careful reaction mechanism selection is vital when finite-rate
chemistry effects are considered in fire simulations.

**5. Conclusion**

Large-eddy simulations of 37 cm in diameter propane pool fires (21 kW and 34 kW) have been presented in this study. The influence of two different global (two-step) reaction mechanisms has been examined. To complement the LES results, the mechanisms were also evaluated in mixture fraction space using 0D-CMC simulations. The analysis revealed minor differences in the predicted temperatures (i.e., within 10% from the experiments for the 1 cm grid size within the flame region) and flow fields but significant differences in predicted CO and CO₂ concentrations. These differences were attributed to simplifications made in the mechanisms themselves. Furthermore, the mechanisms were developed for applications and conditions which are (significantly) different from the ones found in fire applications. The development of reduced mechanisms specifically optimised for fire applications is required in the future.

**Acknowledgments**

This research is funded by The Research Foundation-Flanders (FWO-Vlaanderen) through
project G023221N.

**References**

[1] J. At Thabari et al. "Numerical study of the impact of the EDC formulation and finite-rate chemistry mechanisms in CFD simulations of fire plumes". In: *Fire Saf. J.* 141 (2023), p. 103950. ISSN: 0379-7112.

[2] J. At Thabari, G. Maragkos, and B. Merci. "Exploratory Study of the Impact of the Turbulence Model on Flame Extinction with an EDM and EDC/Finite-Rate Approach for a Line Burner Configuration". In: *Flow Turbul. Combust.* (2023), pp. 1–14.

[3] B. Kruljevic, I. Stankovic, and B. Merci. "Systematic study of the impact of chemistry and radiation on extinction and carbon monoxide formation at low scalar dissipation rates". In: *Fire Saf. J.* 117 (2020), p. 103212.

[4] Giorgio De Paola. "Conditional moment closure for autoignition in turbulent flows". PhD thesis. University of Cambridge, 2007.

[5] Georgios Maragkos and Bart Merci. "On the use of dynamic turbulence modelling in fire applications". In: *Combust. Flame* 216 (2020), pp. 9–23.

[6] Bjørn F. Magnussen. "The eddy dissipation concept: A bridge between science and technology". In: *ECCOMAS thematic conference on computational combustion*. Vol. 21. Libson, Portugal. 2005, p. 24.

[7] J. C. Prince, C. Treviño, and F. A. Williams. "A reduced reaction mechanism for the combustion of n-butane". In: *Combust. Flame* 175 (2017), pp. 27–33. ISSN: 0010-2180.

[8] F.L. Dryer C.K. Westbrook. "Simplified Reaction Mechanisms for the Oxidation of Hydrocarbon Fuels in Flames". In: *Combust. Sci. Technol.* 27.1-2 (1981), pp. 31–43.

[9] CERFACS. *C3H8/air 2-step mechanism*. URL https://chemistry.cerfacs.fr/en/chemical-database/mechanisms-list/2s-propane-air-mechanism/. 2023; accessed November 2023.

[10] A. Hamins R.L. Falkenstein-Smith K. Sung. "Characterization of Medium-Scale Propane Pool Fires". In: *Fire Technology* (2023), pp. 1–18.

[11] K. McGrattan et al. *Fire Dynamics Simulator, Technical Reference Guide, Volume 3: Validation*. 1018-3. NIST Special Publication. 2024.