Abstract
The self-heating and spontaneous ignition process pose a fire risk for industrial biomass piles during storage. Most studies, from theoretical to numerical, pay more attention on the effect of pile size on self-heating and self-ignition, which in essence is due to chemical reactions. However, the effect of ambient humidity on the self-heating and spontaneous ignition process, which is due to physical process of water evaporation and vapor condensation, is not well understood. In fact, fire accidents and the related experimental studies have shown that the sudden increase of ambient humidity would cause the rapid increase of biomass pile temperature, leading to spontaneous ignition. In order to fill this knowledge gap, this work proposed a computational self-heating model, coupling heat and mass transfer process and both the microbial and chemical reactions. The processes of moisture evaporation, transportation and convective exchange of vapor were considered in this model to study the effect of humidity on self-heating process. The model was validated against the full-scale experiments of Zhanjiang Biomass Power Plant firstly. The numerical results show that the sudden increase of ambient humidity can lead to a quick increase of pile temperature due to the condensation process. Spontaneous ignition is highly dependent upon the heat generation evolution of the chemical reaction within the pile. The sudden increase of humidity could speed up the chemical reaction process, leading to a fire. This study helps understand the role of humidity on self-heating process during biomass storage.
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Data Availability
All datas generated or analysed during this study are available from the corresponding author on reasonable request.
Code Availability
The codes used or analysed during the current study are available from the corresponding author on reasonable request.
Abbreviations
- A 1 :
-
Pre-exponential factor (s−1)
- A 2 :
-
Pre-exponential factor (–)
- A 3 :
-
Pre-exponential factor (m3 kg−1 s−1)
- a w :
-
Water activity (–)
- c :
-
Concentration (kg m−3)
- c p :
-
Specific heat capacity (J kg−1 K−1)
- D c :
-
Capillary diffusivity (m2 s−1)
- D eff,g :
-
Vapor diffusion coefficient (m2 s−1)
- E :
-
Activation energy (J mol−1)
- h c :
-
Convective heat transfer coefficient (W m−2 K−1)
- h fg :
-
Latent heat of evaporation (J kg−1)
- h m :
-
Convective mass transfer coefficient (m s−1)
- k :
-
Intrinsic permeability (m2)
- k r :
-
Relative permeability (–)
- k th :
-
Thermal conductivity (W m−1 K−1)
- M :
-
Molar mass (kg mol−1)
- M db :
-
Moisture content (dry basis) (–)
- M wb :
-
Moisture content (wet basis) (–)
- n :
-
Mass flux (kg m−2 s−1)
- p :
-
Pressure (Pa)
- p v,a :
-
Ambient vapor pressure (Pa)
- Q b :
-
Reaction heat of microbial activity (J kg−1)
- Q c :
-
Reaction heat of chemical reaction (J kg−1)
- R evap :
-
Evaporation rate (kg m−3 s−1)
- S :
-
Saturation (–)
- T :
-
Temperature (K)
- V :
-
Volume (m3)
- ρ :
-
Density (kg m−3)
- σ :
-
Moisture content (wet basis) (–)
- φ :
-
Porosity (–)
- μ :
-
Viscosity (Pa s)
- χ :
-
Molar fraction (–)
- 1:
-
Promotion item of microbial activity
- 2:
-
Inhibition item of microbial activity
- 3:
-
Chemical reaction
- a :
-
Air
- eff :
-
Effective
- g :
-
Gas
- o :
-
Oxygen
- s :
-
Solid
- w :
-
Liquid water
- v :
-
Vapor
References
- 1.
Ladanai S, Vinterback J (2009) Global potential of sustainable biomass for energy. Institutionen för energi och teknik, Sveriges lantbruksuniversitet, Uppsala
- 2.
Gupta M, Yang J, Roy C (2003) Specific heat and thermal conductivity of softwood bark and softwood char particles. Fuel 82(8):919–927. https://doi.org/10.1016/S0016-2361(02)00398-8
- 3.
Gray BF, Sexton MJ, Halliburton B, Macaskill C (2002) Wetting-induced ignition in cellulosic materials. Fire Saf J 37(5):465–479. https://doi.org/10.1016/S0379-7112(02)00002-4
- 4.
Carras JN, Young BC (1994) Self-heating of coal and related materials: models, application and test methods. Prog Energy Combust Sci 20(1):1–15. https://doi.org/10.1016/0360-1285(94)90004-3
- 5.
Schmal D, Duyzer JH, van Heuven JW (1985) A model for the spontaneous heating of coal. Fuel 64(7):963–972. https://doi.org/10.1016/0016-2361(85)90152-8
- 6.
Arisoy A, Beamish B, Yoruk B (2017) Moisture moderation during coal self-heating. Fuel 210:352–358. https://doi.org/10.1016/j.fuel.2017.08.075
- 7.
Zhang J, Ren T, Liang Y, Wang Z (2016) A review on numerical solutions to self-heating of coal stockpile: mechanism, theoretical basis, and variable study. Fuel 182:80–109. https://doi.org/10.1016/j.fuel.2016.05.087
- 8.
Muthu Kumaran S, Raghavan V, Rangwala AS (2020) A parametric study of spontaneous ignition in large coal stockpiles. Fire Technol 56(3):1013–1038. https://doi.org/10.1007/s10694-019-00917-6
- 9.
Sidhu HS, Nelson MI, Chen XD (2007) A simple spatial model for self-heating compost piles. ANZIAM J 48:16. https://doi.org/10.21914/anziamj.v48i0.86
- 10.
Moraga N, Corvalan F, Escudey M, Arias A, Zambra C (2009) Unsteady 2D coupled heat and mass transfer in porous media with biological and chemical heat generations. Int J Heat Mass Transf 52(25):5841–5848
- 11.
Putranto A, Chen XD (2017) A new model to predict diffusive self-heating during composting incorporating the reaction engineering approach (REA) framework. Bioresour Technol 232:211–221. https://doi.org/10.1016/j.biortech.2017.01.065
- 12.
Luangwilai T, Sidhu HS, Nelson MI (2018) One-dimensional spatial model for self-heating in compost piles: Investigating effects of moisture and air flow. Food Bioprod Process 108:18–26. https://doi.org/10.1016/j.fbp.2017.12.001
- 13.
Ferrero F, Lohrer C, Schmidt BM, Noll M, Malow M (2009) A mathematical model to predict the heating-up of large-scale wood piles. J Loss Prevent Proc 22(4):439–448. http://dx.doi.org/10.1016/j.jlp.2009.02.009
- 14.
Krigstin S, Helmeste C, Jia H, Johnson KE, Wetzel S, Volpe S, Faizal W, Ferrero F (2019) Comparative analysis of bark and woodchip biomass piles for enhancing predictability of self-heating. Fuel 242:699–709. https://doi.org/10.1016/j.fuel.2019.01.056
- 15.
Datta AK (2007) Porous media approaches to studying simultaneous heat and mass transfer in food processes. I: problem formulations. J Food Eng 80(1):80–95. https://doi.org/10.1016/j.jfoodeng.2006.05.013
- 16.
Datta AK (2007) Porous media approaches to studying simultaneous heat and mass transfer in food processes. II: property data and representative results. J Food Eng 80(1):96–110. https://doi.org/10.1016/j.jfoodeng.2006.05.012
- 17.
Shu Y (2016) The research on self-heating and ignition behavior of eucalyptus bark biomass fuels. Dissertation, University of Science and Technology of China
- 18.
Reddy A, Jenkins B, Vander Gheynst J (2009) The critical moisture range for rapid microbial decomposition of rice straw during storage. Trans Asabe 52(2):673–677. https://doi.org/10.13031/2013.26806
- 19.
Fu Z, Koseki H, Iwata Y (2006) Investigation on spontaneous ignition of two kinds of organic material with water. Thermochimica Acta 440(1):68–74. http://dx.doi.org/10.1016/j.tca.2005.10.010
- 20.
Li XR, Koseki H, Momota M (2006) Evaluation of danger from fermentation-induced spontaneous ignition of wood chips. J Hazard Mater 135(1–3):15–20. http://dx.doi.org/10.1016/j.jhazmat.2005.11.034
- 21.
Rahimi Borujerdi P, Shotorban B, Mahalingam S, Weise DR (2019) Modeling of water evaporation from a shrinking moist biomass slab subject to heating: Arrhenius approach versus equilibrium approach. Int J Heat Mass Transf 145:118672. https://doi.org/10.1016/j.ijheatmasstransfer.2019.118672
- 22.
Ni H, Datta AK, Torrance KE (1999) Moisture transport in intensive microwave heating of biomaterials: a multiphase porous media model. Int J Heat Mass Transf 42(8):1501–1512. https://doi.org/10.1016/S0017-9310(98)00123-9
- 23.
Stoklosa AM, Lipasek RA, Taylor LS, Mauer LJ (2012) Effects of storage conditions, formulation, and particle size on moisture sorption and flowability of powders: a study of deliquescent ingredient blends. Food Res Int 49(2):783–791. https://doi.org/10.1016/j.foodres.2012.09.034
- 24.
Chen Z (2005) Chemical engineering thermodynamics. Chemical Industry Press, Beijing
- 25.
Halder A, Dhall A, Datta AK (2007) An improved, easily implementable, porous media based model for deep-fat frying: part I: model development and input parameters. Food Bioprod Process 85(3):209–219. https://doi.org/10.1205/fbp07033
- 26.
Halder A, Dhall A, Datta AK (2007) An improved, easily implementable, porous media based model for deep-fat frying: part II: results, validation and sensitivity analysis. Food Bioprod Process 85(3):220–230. https://doi.org/10.1205/fbp07034
- 27.
Zhu H, Gulati T, Datta AK, Huang K (2015) Microwave drying of spheres: coupled electromagnetics-multiphase transport modeling with experimentation. Part I: model development and experimental methodology. Food Bioprod Process 96:314–325. https://doi.org/10.1016/j.fbp.2015.08.003
- 28.
Gulati T, Zhu H, Datta AK, Huang K (2015) Microwave drying of spheres: coupled electromagnetics-multiphase transport modeling with experimentation. Part II: model validation and simulation results. Food Bioprod Process 96:326–337. https://doi.org/10.1016/j.fbp.2015.08.001
- 29.
Fierro V, Miranda JL, Romero C, Andrés JM, Arriaga A, Schmal D (2001) Model predictions and experimental results on self-heating prevention of stockpiled coals. Fuel 80(1):125–134. https://doi.org/10.1016/S0016-2361(00)00062-4
- 30.
Prince DR (2014) Measurement and modeling of fire behavior in leaves and sparse shrubs. Dissertation, Brigham Young University
- 31.
Borujerdi PR, Shotorban B, Mahalingam S (2020) A computational study of burning of vertically oriented leaves with various fuel moisture contents by upward convective heating. Fuel 276:118030. https://doi.org/10.1016/j.fuel.2020.118030
Funding
This work was sponsored by National Key R&D Program of China (No. 2016YFC0800100) and National Natural Science Foundation of China (No. 51576184). HX Chen was supported by Science and Technological Fund of Anhui Province for Outstanding Youth (No 1808085J21) and Fundamental Research Funds for the Central University (WK2320000036 and 2320000042).
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S.F.: Conceptualization, Methodology, Formal analysis, Writing—review & editing, Writing—original draft. H.C.: Supervision, Formal analysis, Writing—review & editing. S.D.W.: Software, Writing—review & editing. H.S.S.: Conceptualization, Writing—review & editing. T.L.: Software, Writing—review & editing. Y.S.: Data Curation.
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Fu, S., Chen, H., Watt, S.D. et al. Numerical Study on Effect of Ambient Humidity Variation on Self-heating and Spontaneous Ignition of the Eucalyptus Bark Pile. Fire Technol (2021). https://doi.org/10.1007/s10694-021-01091-4
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Keywords
- Ambient humidity variation
- Self-heating
- Spontaneous ignition
- Eucalyptus bark
- Moisture
- Numerical model