scholarly journals Approximations to the Non-Isothermal Distributed Activation Energy Model for Biomass Pyrolysis Using the Rayleigh Distribution

2017 ◽  
Vol 20 (3) ◽  
pp. 78-84 ◽  
Author(s):  
Alok Dhaundiyal ◽  
Suraj B. Singh
Keyword(s):  
Activation Energy ◽  
Numerical Solutions ◽  
Frequency Factor ◽  
Rayleigh Distribution ◽  
Energy Model ◽  
Biomass Pyrolysis ◽  
Distributed Activation Energy Model ◽  
Scale Parameters ◽  
Thermoanalytical Data

AbstractThis paper deals with the influence of some parameters relevant to biomass pyrolysis on the numerical solutions of the nonisothermalnthorder distributed activation energy model using the Rayleigh distribution. Investigated parameters are the integral upper limit, the frequency factor, the heating rate, the reaction order and the scale parameters of the Rayleigh distribution. The influence of these parameters has been considered for the determination of the kinetic parameters of the non-isothermalnthorder Rayleigh distribution from the experimentally derived thermoanalytical data of biomass pyrolysis.

scholarly journals Asymptotic Approximations to the Non-Isothermal Distributed Activation Energy Model for Bio-Mass Pyrolysis

2017 ◽  
Vol 11 (4) ◽  
pp. 293-301 ◽  
Author(s):  
Alok Dhaundiyal ◽  
Suraj B. Singh
Keyword(s):  
Activation Energy ◽  
Kinetic Parameters ◽  
Gamma Distribution ◽  
Numerical Solutions ◽  
Frequency Factor ◽  
Energy Model ◽  
Erlang Distribution ◽  
Biomass Pyrolysis ◽  
Distributed Activation Energy Model ◽  
Thermoanalytical Data

AbstractThis paper describes the influence of some parameters significant to biomass pyrolysis on the numerical solutions of the non-isothermal nth order distributed activation energy model (DAEM) using the Gamma distribution and discusses the special case for the positive integer value of the scale parameter (λ), i.e. the Erlang distribution. Investigated parameters are the integral upper limit, the frequency factor, the heating rate, the reaction order, and the shape and rate parameters of the Gamma distribution. Influence of these parameters has been considered for the determination of the kinetic parameters of the non-isothermal nth order Gamma distribution from the experimentally derived thermoanalytical data of biomass pyrolysis. Mathematically, the effect of parameters on numerical solution is also used for predicting the behaviour of the unpyrolysized fraction of biomass with respect to temperature. Analysis of the mathematical model is based upon asymptotic expansions, which leads to the systematic methods for efficient way to determine the accurate approximations. The proposed method, therefore, provides a rapid and highly effective way for estimating the kinetic parameters and the distribution of activation energies.

scholarly journals Parametric Study of NTH Order Distributed Activation Energy Model for Isothermal Pyrolysis of Forest Waste Using Gaussian Distribution

2017 ◽  
Vol 20 (1) ◽  
pp. 23-28 ◽  
Author(s):  
Alok Dhaundiyal ◽  
Suraj B. Singh
Keyword(s):  
Activation Energy ◽  
Gaussian Distribution ◽  
Frequency Factor ◽  
Energy Model ◽  
Distributed Activation Energy Model ◽  
Cedrus Deodara ◽  
Upper Limit ◽  
Forest Waste ◽  
Thermoanalytical Data ◽  
Distribution Frequency

Abstract This paper deals with the influence of some factors relevant to isothermal pyrolysis of residual leaves of Cedrus deodara on the asymptotic solution of the non-isothermal nth order distributed activation energy model (DAEM) using Gaussian distribution. Frequency factor, integral upper limit, the reaction order and the variance of Gaussian distribution are the parameters taken under purview of this study. In order to determine the kinetic parameters of the isothermal nth order Gaussian DAEM from thermoanalytical data of loose biomass pyrolysis, the variation of these factors has been considered. The obtained results show that the predicted results for nth order DAEM hold good at upper limit of dE, E∞ = 39 kJ mol-1.

scholarly journals Analysis of the non Isothermal Distributed Activation Energy Model for Biomass Pyrolysis by Fuzzy Gaussian Distribution

2016 ◽  
Vol 35 (330) ◽  
pp. 32-41 ◽  
Author(s):  
Alok Dhaundiyal ◽  
Suraj B. Singh
Keyword(s):  
Activation Energy ◽  
Gaussian Distribution ◽  
Fuzzy Numbers ◽  
Analytical Data ◽  
Frequency Factor ◽  
Energy Model ◽  
Membership Functions ◽  
Biomass Pyrolysis ◽  
Distributed Activation Energy Model ◽  
Upper Limit

Abstract The main aim of this paper is to fuzzify the kinetic parameters, which have crisp nature, in order to obtain the realistic and accurate results. In the present study, the variance, upper limit of ‘dE’ and the frequency factor are assumed to be fuzzy numbers. The Gaussian distribution is considered as the distribution function, f (E), of Distributed Activation Energy Model (DAEM). The membership and the non-membership functions are evaluated by the trapezoidal fuzzy number. Thermo-analytical data has been found experimentally with the help of TGA/DTG analysis. The approximated solution of DAEM is obtained with the help of asymptotic expansion.

Kinetic analysis of biomass pyrolysis using a double distributed activation energy model

2015 ◽  
Vol 121 (3) ◽  
pp. 1403-1410 ◽  
Author(s):  
Benedetta de Caprariis ◽  
Maria Laura Santarelli ◽  
Marco Scarsella ◽  
Carlos Herce ◽  
Nicola Verdone ◽  
...  
Keyword(s):  
Activation Energy ◽  
Kinetic Analysis ◽  
Energy Model ◽  
Biomass Pyrolysis ◽  
Distributed Activation Energy Model

scholarly journals Thermogravimetric and Kinetic Analysis of Melon (Citrullus colocynthis L.) Seed Husk Using the Distributed Activation Energy Model

2015 ◽  
Vol 15 (1) ◽  
pp. 77-89 ◽  
Author(s):  
Bemgba Bevan Nyakuma
Keyword(s):  
Activation Energy ◽  
Thermal Decomposition ◽  
Kinetic Analysis ◽  
Biomass Conversion ◽  
Clean Energy ◽  
Frequency Factor ◽  
Energy Model ◽  
Distributed Activation Energy Model ◽  
Solid Biofuel ◽  
Seed Husk

Abstract This study seeks to characterize the thermochemical fuel properties of melon seed husk (MSH) as a potential biomass feedstock for clean energy and power generation. It examined the ultimate analysis, proximate analysis, FTIR spectroscopy and thermal decomposition of MSH. Thermogravimetric (TG) analysis was examined at 5, 10, 20 °C/min from 30-800 °C under nitrogen atmosphere. Subsequently, the Distributed Activation Energy Model (DAEM) was applied to determine the activation energy, E, and frequency factor, A. The results revealed that thermal decomposition of MSH occurs in three (3) stages; drying (30-150 °C), devolatization (150-400 °C) and char degradation (400-800 °C). Kinetic analysis revealed that the E values fluctuated from 145.44-300 kJ/mol (Average E = 193 kJ/mol) while A ranged from 2.64 × 1010 to 9.18 × 1020 min-1 (Average E = 9.18 × 1019 min-1) highlighting the complexity of MSH pyrolysis. The fuel characterization and kinetics of MSH showed it is an environmentally friendly solid biofuel for future thermal biomass conversion.

Analysis of coals and biomass pyrolysis using the distributed activation energy model

2009 ◽  
Vol 100 (2) ◽  
pp. 948-952 ◽  
Author(s):  
Zhengqi Li ◽  
Chunlong Liu ◽  
Zhichao Chen ◽  
Juan Qian ◽  
Wei Zhao ◽  
...  
Keyword(s):  
Activation Energy ◽  
Energy Model ◽  
Biomass Pyrolysis ◽  
Distributed Activation Energy Model
Sign in / Sign up

Export Citation Format

Share Document