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Asymptotic approximations to the distributed activation energy model for non isothermal pyrolysis of loose biomass using the weibull distribution

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper explains the influence of some relevant parameters to biomass pyrolysis, described by the asymptotic solution of non-isothermal nth order distributed activation energy model using the Weibull distribution. Investigated parameters are the integral range, the frequency factors, heating rate, the reaction order, and the shape, scale and location parameters of the Weibull distribution. These parameters have been used for evaluation of the kinetic parameters of the non-isothermal Weibull DAEM from thermo-analytical data of biomass pyrolysis.
Rocznik
Strony
131--146
Opis fizyczny
Bibliogr. 33 poz., rys., tab.
Twórcy
  • Himgiri Zee University Department of Mechanical Engineering Dehradun, India
autor
  • Pant University of Agriculture and Technology Department of Mathematics Statistics and Computer Science Pantnagar, India
Bibliografia
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  • [5] Galgano A., and Blasi C.D. (2003). Modeling wood degradation by the unreacted-core-shrinking approximation. Ind. Eng. Chem. Res, 42: 2101-2111.
  • [6] Ferdous D, Dalai A.K., Bej S.K. and Thring R.W. (2002). Pyrolysis of lignins: experimental and kinetics studies. Energy Fuels, 16: 1405–1412
  • [7] Brown M.E. (1988). Introduction to Thermal Analysis Techniques and Applications, Chapman and Hall, New York.
  • [8] Gašparoviè, L. Labovsky, J., Markoš, J., and Jelemensk, L. (2012). Calculation of Kinetic Parameters of the Thermal Decomposition of Wood by Distributed Activation Energy Model (DAEM), Chem.Biochem.Eng, 26: 45-53
  • [9] Güne M, and Güne S. (1999). The influences of various parameters on the numerical solution of nonisothermal DAEM equation Thermochim. Acta. 336:93-96
  • [10] Cai J.M., He Fe, and Yao F.S. (2006). Nonisothermal nth order DAEM equation and its parametric study-use in the kinetic analysis of biomass pyrolysis, J. Math. Chem., 42:949–956
  • [11] Anthony D. B. (1974). DSc. t h e s i s, Massachusetts Institute of Technology.
  • [12] Skrdla P.J. and Roberson R.T. (2005). Semiempirical equations for modeling solid-state kinetics based on a Maxwell-Boltzmann distribution of activation energies: applications to a polymorphic transformation under crystallization slurry conditions and to the thermal decomposition of AgMnO4 crystals. J. Phys. Chem. B, 109: 10611- 10619.
  • [13] Weibull W. (1951). A Statistical distribution function of wide applicability. J. Appl. Mech., 18: 293-296.
  • [14] Burnham A. K., Oh M. S., Crawford R. W., and Samoun A. M. (1989). Pyrolysis of Argonne premium coals: activation energy distributions and related chemistry. Energy & Fuels, 3: 42-55.
  • [15] Lakshmanan C. C., and White N. (1994) A new distributed activation energy model using Weibull distribution for the representation of complex kinetics. Energy & Fuels, 8: 1158-1167
  • [16] Meeker W. Q., and Escobar L. A. (1998). Statistical Methods for Reliability Data. John Wiley & Sons, Inc. (US), New York.
  • [17] Abramowitz M., and Stegun I. A. (1964) Handbook of Mathematical Functions. NBS Applied Math Series 55, (nine printing, 1970) U. S. Department of Commerce, Washington DC, p. 257.
  • [18] Jansen J.U., and Machado L.D.B. (2006). Using ordinary differential equations system to solve isoconversional problems in non-isothermal kinetic analysis, J. Therm. Anal. Cal., 87:913-918.
  • [19] Vyazovkin S. (2006).Thermal analysis Anal. Chem., 78: 3875- 3886.
  • [20] Cai J.M., Yao F.S., Yi W.M., and He F.(2006). New temperature integral approximation for nonisothermal kinetics, AIchem J. 52: 1554-1557
  • [21] Cai J.M., and He F.(2006). Letter to the editor. AIChE J., 52 (2006) 2656-2656.
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  • [23] Cai J., Liu, R. (2008). New distributed activation energy model: Numerical solution and application to pyrolysis kinetics of some types of biomass, Bioresource Technology, 99: 2795-2799
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  • [25] McGuinness M.J., Donskoi E., and McElwain D.L.S. (1999). Asymptotic Approximations to the Distributed Activation Energy Model Appl. Math. Lett., 12:27-34.
  • [26] Bender, C.M., and Orszag, S.A. (1978). Advanced Mathematical Methods for Scientists and Engineers, McGraw-Hill.
  • [27] Scott, T. C., Mann R. B., Martinez Ii, and Roberto E. (2006). General Relativity and Quantum Mechanics: Towards a Generalization of the Lambert W Function, AAECC (Applicable Algebra in Engineering, Communication and Computing), 17: 41–47.
  • [28] Scott T. C., Fee G., and Grotendorst J. (2013). Asymptotic series of Generalized Lambert W Function, SIGSAM (ACM Special Interest Group in Symbolic and Algebraic Manipulation), 47: 75–83
  • [29] Scott T. C., Fee, G., Grotendorst, J., and Zhang W.Z. (2014). Numerics of the Generalized Lambert W Function. SIGSAM, 48: 42–56.
  • [30] Howard, J.B., in Chemistry of Coal Utilization, (M.A.Elliott, Ed) Wiley & Sons (1981) Ch. 12.
  • [31] Suuberg, E.M. (1983). Approximate solution technique for nonisothermal, Gaussian distributed activation energy models Combust. Flame 50:243
  • [32] Pitt, G.J. (1962). The kinetics of the evolution of volatile products from coal. Fuel 1:267 (1962).
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9beac3ea-5568-403c-a000-402bf818b6f4
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