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### Mathematical Simulation of Heat and Mass Transfer During Forest Fuel Pyrolysis Caused by High Temperature from Crown Forest Fire

(*) Corresponding author

DOI: https://doi.org/10.15866/iremos.v13i4.18841

#### Abstract

Pyrolysis (thermal decomposition) is the main stage of a forest fire before forest fuel ignition. The aim of this study is to study the mathematical modeling of heat and mass transfer in a typical forest fuel (birch leaf), taking into account the pyrolysis process caused by crown forest fire. The originality of the research is explained by simulation of heat and mass transfer in birch leaf caused by crown forest fire. The majority of known and published researches have been focused on thermal conditions corresponding to surface forest fires. The implementation of the calculations has been carried out in the RAD Studio software. Differential equations have been solved using the finite difference method. The partial derivatives of the equation are replaced by their finite-difference analogues. As a result, an open system of equations is obtained. For its closure, a difference representation of the boundary conditions is used. The closed system of the linear algebraic equations obtained after these operations is numerically solved by marching method. In order to solve the non-linear effect caused by pyrolysis, the simple iteration method has been used. The key findings of this research are: 1) physical and mathematical models developed to simulate leaf forest fuel pyrolysis caused by crown forest fire; 2) computer program coded using high level programming language; 3) temperature distributions obtained across the leave thickness; 4) dry organic matter fraction obtained depending on different parameters (time and spatial coordinate); 5) induction period calculated for typical conditions of crown forest fire. The obtained results can be used for forest fire danger prediction and assessment.

#### Keywords

Mathematical Simulation; Forest Fire; Pyrolysis; Heat and Mass Transfer; Forest Fuel; High Temperature

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#### References

Tedim F., Xanthopoulos G., Leone V. Chapter 5. Forest Fires in Europe: Facts and Challenges. Wildfire Hazards, Risks and Disasters. 2015. P. 77-99.
https://doi.org/10.1016/b978-0-12-410434-1.00005-1

Brushlinsky N.N, Ahrens M, Sokolov S.V, Wagner P. World fire statistics. International association of fire and rescue services. 2019. No. 24. 68 P.

Al_Janabi S., Al_Shourbaji I., Salman M.A. Assessing the suitability of soft computing approaches for forest ﬁres prediction. Applied Computing and Informatics. 2018. Vol. 14. P. 214–224.
https://doi.org/10.1016/j.aci.2017.09.006

4] Baranovskii N.V., Zakharevich A.V. Conditions and Characteristics of the Ignition of a Typical Vegetable Combustible Material by a Local Energy Source (2016) Journal of Engineering Physics and Thermophysics, 89 (6), pp. 1538-1544.
https://doi.org/10.1007/s10891-016-1524-3

Baranovskiy N.V., Zakharevich A.V., Osotova D.S. Experimental study of pine forest fuel layer ignition by the steel heated particle (2015) EPJ Web of Conferences, 82, article N 01020.
https://doi.org/10.1051/epjconf/20158201020

Schetinsky E.A. Sputnik of the head for extinguishing forest fires. Moscow: VNIILM, 2003, 96 P. (In Russian)

Garcia-Pereza M., Chaala H., Pakdel H., Kretschmer D., Roy C. Characterization of bio-oils in chemical families. Biomass and Bioenergy. Vol. 31. 2007. P. 222-242.
https://doi.org/10.1016/j.biombioe.2006.02.006

Collard F.-X., Blin J. A review on pyrolysis of biomass constituents: Mechanisms and composition of the products obtained from the conversion of cellulose, hemicelluloses and lignin. Renewable and Sustainable Energy Reviews. Vol. 38. 2014. P. 594-608.
https://doi.org/10.1016/j.rser.2014.06.013

Van de Velden M., Baeyens J., Brems A., Janssens B., Dewil R. Fundamentals, kinetics and endothermicity of the biomass pyrolysis reaction. Renewable Energy. Vol. 35. 2010. P. 232-242.
https://doi.org/10.1016/j.renene.2009.04.019

Demirbas A. Mechanisms of liquefaction and pyrolysis reactions of biomass. Energy Conversion and Management. Vol. 41. 2000. P. 633-646.
https://doi.org/10.1016/s0196-8904(99)00130-2

Grishin A.M. Mathematical models of forest fires. Tomsk: Tomsk University Press, 1981. 277 p. (In Russian)

Grishin A. M. Mathematical modeling of forest fire and new methods of fighting them. Russia. Tomsk: Publishing House of the Tomsk State University, 1997. 390 р.

Liu H., Wang C. Pyrolysis characteristics and kinetic modeling of Artemisia apiacea by thermogravimetric analysis. Journal of Thermal Analysis and Calorimetry. 2018. Vol. 131. P. 1783–1792.
https://doi.org/10.1007/s10973-017-6599-3

Wadhwani R., Sutherland D., Moinuddin K.A.M., Joseph P. Kinetics of pyrolysis of litter materials from pine and eucalyptus forests. Journal of Thermal Analysis and Calorimetry. 2017. Vol. 130. P. 2035–2040.
https://doi.org/10.1007/s10973-017-6512-0

Mishra G., Kumar J., Bhaskar T. Kinetic studies on the pyrolysis of pinewood. Bioresource Technology. Vol. 182. 2015. P. 282-288.
https://doi.org/10.1016/j.biortech.2015.01.087

Reina J., Velo E., Puigjaner L. Kinetic Study of the Pyrolysis of Waste Wood. Ind. Eng. Chem. Res. 1998. Vol. 37. P. 4290-4295.
https://doi.org/10.1021/ie980083g

Slopiecka K., Bartocci P., Fantozzi F. Thermogravimetric analysis and kinetic study of poplar wood pyrolysis. Applied Energy. Vol. 97. 2012. P. 491-497.
https://doi.org/10.1016/j.apenergy.2011.12.056

Bartoli P., Simeoni A., Biteau H., Torero J.L., Santoni P.A. Determination of the main parameters influencing forest fuel combustion dynamics. Fire Safety Journal. Vol. 46. 2011. P. 27-33.
https://doi.org/10.1016/j.firesaf.2010.05.002

Thomas J.C., Hadden R.M., Simeoni A. Experimental investigation of the impact of oxygen flux on the burning dynamics of forest fuel bed. Fire Safety Journal. Vol. 91. 2017. P. 855-863.
https://doi.org/10.1016/j.firesaf.2017.03.086

McAllister S. Critical mass flux for flaming ignition of wet wood. Fire Safety Journal. Vol. 61. 2013. P. 200-206.
https://doi.org/10.1016/j.firesaf.2013.09.002

Kuznetsov, G., Strizhak, P., Volkov, R., & Zhdanova, A. (2017). Amount of Water Sufficient to Suppress Thermal Decomposition of Forest Fuel. Journal of Mechanics, 33(5), 703-711.
https://doi.org/10.1017/jmech.2017.13

Antonov D.V., Volkov R.S., Voitkov I.S., Zhdanova A.O., Kuznetsov G.V. (2018) Influence of Special Additives in a Water Aerosol on the Suppression of a Forest Fire with it. Journal of Engineering Physics and Thermophysics, Vol. 91. P. 1250-1259.
https://doi.org/10.1007/s10891-018-1855-3

Hameed S., Sharma A., Pareek V., Wu H., Yu Y. A review on biomass pyrolysis models: Kinetic, network and mechanistic models. Biomass and Bioenergy. Vol. 123. 2019. P. 104-122.
https://doi.org/10.1016/j.biombioe.2019.02.008

Zhang M., Geng Z., Yu Y. Density functional theory (DFT) study on the dehydration of cellulose. Energy Fuels. Vol. 25. 2011. P. 2664–2670.
https://doi.org/10.1021/ef101619e

Zhang M., Geng Z., Yu Y. Density Functional Theory (DFT) study on the pyrolysis of cellulose: the pyran ring breaking mechanism. Comput. Theor. Chem. Vol. 1067. 2015. P. 13–23.
https://doi.org/10.1016/j.comptc.2015.05.001

Mettler M.S., Mushrif S.H., Paulsen A.D., Javadekar A.D., Vlachos D.G., Dauenhauer P.J. Revealing pyrolysis chemistry for biofuels production: conversion of cellulose to furans and small oxygenates. Energy Environ. Sci. Vol. 5. 2012. P.
https://doi.org/10.1039/c1ee02743c

Agarwal V., Dauenhauer P.J., Huber G.W., Auerbach S.M. Ab initio dynamics of cellulose pyrolysis: nascent decomposition pathways at 327 and 600 °C. J. Am. Chem. Soc. Vol. 134. 2012. P.
https://doi.org/10.1021/ja305135u

Lu Q., Hu B., Zhang Z.X., Wu Y.T., Cui M.S., Liu D.J., Dong C.Q., Yang Y.P. Mechanism of cellulose fast pyrolysis: the role of characteristic chain ends and dehydrated units. Combustion and Flame. Vol. 198. 2018. P. 267-277.
https://doi.org/10.1016/j.combustflame.2018.09.025

Solomon P.R., Hamblen D.G., Carangelo R.M., Serio M.A., Deshpande G.V. General model of coal devolatilization. Energy Fuels. 1988. Vol. 2. P. 405-422.
https://doi.org/10.1021/ef00010a006

Niksa S. Predicting the rapid devolatilization of diverse forms of biomass with bio-flashchain. Proceedings of the Combustion Institute. Vol. 28. 2000. P. 2727-2733.
https://doi.org/10.1016/s0082-0784(00)80693-1

Vizzini G., Bardi A., Biagini E., Falcitelli M., Tognotti L. Prediction Of Rapid Biomass Devolatilization Yields With An Upgraded Version Of The BioCPD Model. Combustion Institute Italian section. 2008. P.

Prakash N., Karunanithi T. Kinetic modeling in biomass pyrolysis - a review. Appl. Sci. Res. Vol. 4. 2008. P. 1627–1636.

Kansa E.J., Perlee H.E., Chaiken R.F. Mathematical model of wood pyrolysis including internal forced convection. Combustion and Flame. Vol. 29. 1977. P. 311-324.
https://doi.org/10.1016/0010-2180(77)90121-3

Radmanesh R., Courbariaux Y., Chaouki J., Guy C. A unified lumped approach in kinetic modeling of biomass pyrolysis. Fuel. Vol. 85. 2006. P. 1211-1220.
https://doi.org/10.1016/j.fuel.2005.11.021

Barneto A.G., Carmona J.A., Martín Alfonso J.E., Serrano R.S. Simulation of the thermogravimetry analysis of three non-wood pulps. Bioresource Technology. Vol. 101. 2010. P. 3220-3229.
https://doi.org/10.1016/j.biortech.2009.12.034

Manyà J.J., Velo E., Puigjaner L. Kinetics of biomass pyrolysis: a reformulated three-parallel-reactions model. Eng. Chem. Res. 2003. Vol. 42. P. 434-441.
https://doi.org/10.1021/ie020218p

Orfão J.J.M., Antunes F.J.A., Figueiredo J.L. Pyrolysis kinetics of lignocellulosic materials—three independent reactions model. Fuel. Vol. 78. 1999. P. 349-358.
https://doi.org/10.1016/s0016-2361(98)00156-2

Chen T., Zhang J., Wu J. Kinetic and energy production analysis of pyrolysis of lignocellulosic biomass using a three-parallel Gaussian reaction model. Bioresource Technology. Vol. 211. 2016. P. 502-508.
https://doi.org/10.1016/j.biortech.2016.03.091

Papari S., Hawboldt K. A review on the pyrolysis of woody biomass to bio-oil: Focus on kinetic models. Renewable and Sustainable Energy Reviews. Vol. 52. 2015. P. 1580–1595.
https://doi.org/10.1016/j.rser.2015.07.191

Thurner F., Mann U. 1981. Kinetic Investigation of Wood Pyrolysis. Industrial and Engineering Chemical Process Design and Development. Vol. 20. P. 482-488.
https://doi.org/10.1021/i200014a015

Chan W.-C.R., Kelbon M., Krieger B.B. Modelling and experimental veriﬁcation of physical and chemical processes during pyrolysis of a large biomass particle. Fuel. 1985. Vol. 64. P. 1505–1513.
https://doi.org/10.1016/0016-2361(85)90364-3

Di Blasi C., Branca C. Kinetics of primary product formation from wood pyrolysis. Ind Eng Chem Res. 2001. Vol. 40. P. 5547–5556.
https://doi.org/10.1021/ie000997e

Wagenaar B.M., Prins W., van Swaaij W.P.M. Flash pyrolysis kinetics of pine wood. Fuel Process Technol. 1993. Vol. 36. P. 291–298.
https://doi.org/10.1016/0378-3820(93)90039-7

Lautenberger C., Fernandez-Pello C. Generalized pyrolysis model for combustible solids. Fire Safety Journal. Vol. 44. 2009. P. 819-839.
https://doi.org/10.1016/j.firesaf.2009.03.011

Staggs J.E.J. Modelling thermal degradation of polymers using single-step first-order kinetics. Fire Safety Journal. Vol. 32. 1999. P. 17-34.
https://doi.org/10.1016/s0379-7112(98)00026-5

Kuo J.T., His C.-L. Pyrolysis and ignition of single wooden spheres heated in high-temperature streams of air. Combustion and Flame. Vol. 142. 2005. P. 401-412.
https://doi.org/10.1016/j.combustflame.2005.04.002

Leach S.V., Rein G., Ellzey J.L., Ezekoye O.A., Torero J.L. Kinetic and fuel property effects on forward smoldering combustion. Combustion and Flame. Vol. 120. 2000. P. 346-358.
https://doi.org/10.1016/s0010-2180(99)00089-9

Samarskii A.A. The theory of difference schemes. New York – Basel. Marcel Dekker, Inc, 2001, 761 P.

Baranovskiy N., Demikhova A. Mathematical Modeling of Heat Transfer in an Element of Combustible Plant Material When Exposed to Radiation from a Forest Fire. Safety 2019, 5, 56.
https://doi.org/10.3390/safety5030056

Morvan, D.; Accary, G.; Meradji, S.; Frangieh, N.; Bessonov, O. A 3D physical model to study the behavior of vegetation fires at laboratory scale. Fire Saf. J. 2018, 101, 39–52.
https://doi.org/10.1016/j.firesaf.2018.08.011

Baranovskiy, N. V. (2020). Mathematical Simulation of Anthropogenic Load on Forested Territories for Point Source. In N. Baranovskiy (Ed.), Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks (pp. 64-88). Hershey, PA: IGI Global.
https://doi.org/10.4018/978-1-7998-1867-0.ch003

Baranovskiy, N. V. (2020). Predicting Forest Fire Numbers Using Deterministic-Probabilistic Approach. In N. Baranovskiy (Ed.), Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks (pp. 89-100). Hershey, PA: IGI Global.
https://doi.org/10.4018/978-1-7998-1867-0.ch004

Yankovich, E. P., & Yankovich, K. S. (2020). Classification of Territory on Forest Fire Danger Level Using GIS and Remote Sensing. In N. Baranovskiy (Ed.), Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks (pp. 258-267). Hershey, PA: IGI Global.
https://doi.org/10.4018/978-1-7998-1867-0.ch011

Badmaev, N. B., Bazarov, A. V., & Sychev, R. S. (2020). Forest Fire Danger Assessment Using Meteorological Trends: Case Study. In N. Baranovskiy (Ed.), Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks (pp. 183-208). Hershey, PA: IGI Global. doi:10.4018/978-1-7998-1867-0.ch008
https://doi.org/10.4018/978-1-7998-1867-0.ch008

Clarke, H., Gibson, R., Cirulis, B., Bradstock, R.A., & Penman, T.D. (2019). Developing and testing models of the drivers of anthropogenic and lightning-caused wildfire ignitions in south-eastern Australia. Journal of Environmental Management, 235, 34-41.
https://doi.org/10.1016/j.jenvman.2019.01.055

Grishin, A.M., Filkov, A.I. (2011). A deterministic-probabilistic system for predicting forest fire hazard. Fire Safety Journal, 46(1-2), 56-62.
https://doi.org/10.1016/j.firesaf.2010.09.002

Wotton B.M. (2009) Interpreting and using outputs from the Canadian Forest Fire Danger Rating System in research applications // Environmental and Ecological Statistics. Vol. 16. pp. 107-131.
https://doi.org/10.1007/s10651-007-0084-2

Ye J., Wu M., Deng Z., Xu S., Zhou R., Clarke K.C. (2017) Modeling the spatial patterns of human wildfire ignition in Yunnan province, China // Applied Geography, Vol. 89. pp. 150-162.
https://doi.org/10.1016/j.apgeog.2017.09.012

You W., Lin L., Wu L., Ji Z., Yu J., Zhu J., Fan Y., He D. (2017) Geographical information system-based forest fire risk assessment its spatiotemporal variability // Ecological Indicators, Vol. 77. pp. 176-184.
https://doi.org/10.1016/j.ecolind.2017.01.042

Zhang Y.; Lim S.; Sharples J.J. (2016) Modelling spatial patterns of wildfire occurrence in South-Eastern Australia. Geomatics, Natural Hazards and Risk, Vol. 7, pp. 1800 – 1815.
https://doi.org/10.1080/19475705.2016.1155501

Viegas D.X.; Bovio G.; Ferreira A.; Nosenzo A.; Sol, B. (2000) Comparative study of various methods of fire danger evaluation in Southern Europe. International Journal of Wildland Fire, Vol. 10, pp. 235-246.
https://doi.org/10.1071/wf00015

Majlingová A., Sedliak M., Smrecek R. Spatial distribution of surface forest fuel in the Slovak Republic. J. Maps 2018, 14, 368–372.
https://doi.org/10.1080/17445647.2018.1480973

Eskandari S. A new approach for forest fire risk modeling using fuzzy AHP and GIS in Hyrcanian forests of Iran. Arabian J. Geosci. 2017, 10, 190.
https://doi.org/10.1007/s12517-017-2976-2

Qiao C., Wu L., Chen T., Huang Q., Li Z. Study on Forest Fire Spreading Model Based on Remote Sensing and GIS. IOP Conf. Ser. Earth Environ. Sci. 2018, 199, 022017.
https://doi.org/10.1088/1755-1315/199/2/022017

Santi E., Paloscia S., Pettinato S., Fontanelli G., Mura M., Zolli C., Maselli F., Chiesi M., Bottai L., Chirici G. The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas. Remote Sens. Environ. 2017, 200, 63–73.
https://doi.org/10.1016/j.rse.2017.07.038

Baranovsky N.V. The development of application to software origin pro for informational analysis and forecast of forest fire danger caused by thunderstorm activity. Journal of Automation and Information Sciences. 2019. 51 (4). P. 12-23.
https://doi.org/10.1615/jautomatinfscien.v51.i4.20

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