Figure 6: Experimental and computational smouldering-threshold curves correlating to critical IC and MC [7].

Computational Smouldering Combustion: Predicting the Roles of Moisture and Inert Contents in Peat Wildfires

Xinyan Huang* and Guillermo Rein Department of Mechanical Engineering, Imperial College London, x.huang12@imperial.ac.uk

Smouldering combustion is the slow, low-temperature, flameless burning of porous fuels and is the most persistent combustion [1];

It’s the driving phenomenon of wildfires in peat lands (Fig. 1), like those causing haze episodes in Southeast Asia and Northeast Europe, but poorly understood;

Peat fires contribute to 15% of man-made carbon emissions [2], and yield a large amount of toxic gases, which are harmful to public safety and health [3].

Figure 1: Smouldering peat fires in Indonesia in 2013 (up); diagram of the lateral and in-depth spreads of a smouldering wildfire in a layer of peat (down).

Objective: 1. Based on TG data, develop an effective kinetics

for smouldering combustion of peat, and find kinetic parameters for various peat samples.

2. Develop a computational model to solve the in-depth spread of peat fire with proposed kinetics.

3. Find the smouldering threshold related to the critical moisture and inorganic contents, investigate the influence factors, and compare with experiments in literatures [4,5].

Motivation and Introduction

Computational Model

Frandsen’s two experiments 1. A low-mineral peat moss was mixed with water and clay (minerals) to produced wet modified soil

samples (9×9×4 cm) with specific moisture content (MC) and inorganic content (IC). A coil heater was used for ignition on the top of the sample [4].

2. Natural soil samples (with different natural ICs) at various sites of North America were tested to find the critical MC. A dry peat layer (1 cm) was placed on the top and ignited by a coil heater [5].

After ignition, a smouldering front starts to spread in-depth and a layer of ash is accumulated on the top (Fig. 2). As a first approximation, these experiments can be viewed as 1-D. Hence, we used the open-source code Gpyro [6] to develop the 1-D smouldering combustion of peat [7].

Chemical Kinetics

Smouldering Structure

A Scotland (SC) peat with OC= 98.2% [8] is selected as the base case. 6 condensed-phase species (water, peat, α-Char, β-Char, ash, and clay) and 4 gaseous species (N2, O2, H2O(g), and emission gases) are considered. Thermo-physical properties of all species are adopted from literatures.

5-step kinetic model for smouldering combustion of peat Based on the thermogravity (TG) data of four different peat samples from Scotland (SC), Siberia (SI-A and SI-B), and China (CH), the decomposition schemes with different complexities were investigated [8]. The best kinetics was found to include 1-step drying and 4-step decomposition as

1) Peat ∙ 𝑣𝑤H2O → Peat + 𝑣𝑤H2O (g) (Peat drying) 2) Peat → 𝜈𝛼,𝑝𝑝 α-Char + 𝜈𝑔,𝑝𝑝 Gas (Peat pyrolysis) 3) Peat + 𝜈𝑂2,𝑝𝑝O2 → 𝜈𝛼,𝑝𝑝 β-Char + 𝜈𝑔,𝑝𝑝 Gas (Peat oxidation) 4) β-Char + 𝜈𝑂2,𝛽𝑝O2 → 𝜈𝑎,𝛽𝑝 Ash + 𝜈𝑔,𝛽𝑝 Gas (β-char oxidation) 5) α-Char + 𝜈𝑂2,𝛼𝑝𝑂2 → 𝜈𝑎,𝛼𝑝 Ash + 𝜈𝑔,𝛼𝑝 Gas (α-char oxidation)

Smouldering Threshold

Physically, both water and minerals act as heat sinks to enhance the heat dissipation. Therefore, an compensation effect is expected between MC and IC.

The experimental data of modified samples was fitted as MC = 1.1 − 1.35 IC in [4], and plotted in Fig. 6 along with natural-sample data in [5]. That is, it is not possible to ignite and completely combust a soil sample above this line.

The smouldering-threshold curve of critical IC and MC was solved with kinetic parameters of four different peat samples. The found smouldering-threshold curves are non-linear. The critical curve of SC sample crosses the middle of experimental data scatters, and the corresponding critical curve of SI-A peat (OC = 97.6%) is much lower.

The kinetic parameters (i.e. decomposition chemistry) have a significant influence on smouldering threshold.

o The sensitivity of the smouldering thresholds is investigated by varying three parameters: bulk density of peat (𝜌𝑝= 90-130 kg/m3), solid thermal conductivity of peat (𝑘𝑠,𝑝= 0.8-1.2 W/m-K) and heat of char oxidation (20-30 MJ/kg). All other parameters and ignition protocol are fixed.

o Figure 7 reveals that the range of computed smouldering thresholds covers most experimental data on different peat samples. Computational results show that the smouldering thresholds increase monotonously with the heat of combustion, but decreases with the bulk density and thermal conductivity of peat.

A peat is easy to combust with a small bulk density, a low thermal conductivity, and a large heat of combustion.

Conclusions

A 5-step (including drying) heterogeneous kinetics is proposed for smouldering combustion of peat, and the kinetic parameters are inversely found based on TG data.

A multi-physics 1-D model of a reactive porous media is developed with this 5-step kinetics to simulate the small-scale experiments in [4, 5]. The transient temperature, species mass fraction, reaction profiles, and surface regression are studied.

The predicted smouldering thresholds related to the critical MC and IC are nonlinear. A sensitivity analysis shows that the critical content thresholds depend significantly on the kinetic parameters, increases with the heat of combustion, but decreases with bulk density and thermal conductivity of peat.

[1] T. Ohlemiller, Progress in Energy and Combustion Science 11 (1985) 277– 310.

[2] G. Rein, Smouldering Fires and Natural Fuels, Fire Phenomena in the Earth System, Wiley and Sons, 2013.

[3] A. Rappold et al., Environ Health Perspect 119 (2011) 1415–20. [4] W. H. Frandsen, Can. J. of Forest Research 17 (1987)1540–44. [5] W. H. Frandsen, Can. J. of Forest Research 27 (1997) 1471–77. [6] C. Lautenberger et al, Fire Safety J. 44 (2009) 819–39. [7] X. Huang et al. 35th Int. Combustion Symposium (submitted). [8] X. Huang, G. Rein. Combustion and Flame (2014) in press.

References

Acknowledgements The author (XH) was supported by the ME Department at Imperial College London, and Santander Overseas Research Scholarship. The authors thank Prof. H. Chen (USTC) for TG data and valuable discussions.

Figure 2: 1-D computational domain for the smouldering peat fire.

1-D governing equations The details are reported in [6], only the essentials of the model are presented here:

𝜕�̅�𝜕𝜕

= −�̇�𝑓𝑔′′′ (1)

𝜕 �̅�𝑌𝑖𝜕𝜕

= �̇�𝑓𝑖′′′ − �̇�𝑑𝑖′′′ (2)

𝜕(�̅�ℎ�)𝜕𝜕

=𝜕𝜕𝜕

𝑘�𝜕𝜕𝜕𝜕

+ ��̇�𝑠,𝑘′′′

𝐾

𝑘=1

+ � �̇�𝑓𝑖′′′ − �̇�𝑑𝑖′′′ ℎ𝑖

𝑀

𝑖=1

3

𝜕 𝜌𝑔𝜓�

𝜕𝜕+𝜕�̇�′′

𝜕𝜕= �̇�𝑓𝑔′′′ (4)

𝜕 𝜌𝑔𝜓�𝑌𝑖𝜕𝜕

+𝜕(�̇�′′𝑌𝑗)

𝜕𝜕=

𝜕𝜕𝜕

𝜓�𝜌𝑔𝐷𝜕𝑌𝑗𝜕𝜕

+�̇�𝑓𝑗′′′ −�̇�𝑑𝑗′′′ (5)

�̇�′′ = −𝐾�𝜐𝜕𝜕𝜕𝜕

𝑝 = 𝜌𝑔𝑅𝑠𝜕 (6)

Figure 7: Computational smouldering-threshold curves under a combination of ρp, ks,p, and Cαo, varying in a wide range [7].

Ignition A successful ignition and spread is defined if most of the organic matter (> 95%) is consumed. If ignition succeeds, simulations show that the smouldering combustion lasts for 1-2 h, agreeing with experimental observations in [4, 5].

Spread One case (MC = 50% and IC = 30%) is investigated in detail. The peak temperature stabilizes at about 600 ℃ (Fig. 4). Figure 5 shows the evolution of mass, surface regression and mass-loss rate, and the reaction profile at 𝜕 = 20 min.

Figure 5: Simulated evolution of (a) mass of each species condensed species, (b) total mass-loss rate and thickness of fuel bed, and (c) reaction profile at t = 20 min for SC peat with MC = 50% and IC = 30% [7].

Figure 4: Simulated evolution of temperature profiles for SC peat with MC = 50% and IC = 30% [7].

Figure 3: mass-loss rate of SC peat in a TG experiment. Marks: experimental data, and lines: simulations [8]. Table 1: kinetic parameters of SC peat for 5-step chemistry.

where there are two parallel paths: (a) Peat → α-Char → Ash, and (b) Peat → β-Char → Ash.

The kinetic parameters are inversely found through the genetic algorithm (GA), as listed in Table 1. The simulated mass-loss-rate curve with the 5-step kinetics gives an excellent agreement with the corresponding TG experiment. Figure 3 shows an example comparison between simulation and TG experiment for a SC peat.