Search

During the pyrolysis process, solid fuels decompose at different degradation rates and temperature ranges owing to their complex structure and composition. Therefore, predicting the thermal degradation of a wide range of solid fuels is paramount for understanding the thermal stability of fuels to effectively utilize them. In this study, the proposed artificial neural network (ANN) (NN-5-22-22-2), with three layers and tansig–logsig transfer functions, predicts the thermogravimetry (TG) and the derivative thermogravimetry (DTG) curves based on 24,750 experimental data points as input parameters (six different heating rates, 825 temperature points, and moisture, volatile, and fixed carbon content of five types of samples). In this exploratory study, we applied a nonlinear optimization method, namely the generalized reduced gradient (GRG) algorithm, to determine the activation energy (E) and frequency factor (A) in a nonlinear equation instead of using the conventional slope and intercept method. Five types of rank fuels were calculated using a distributed activation energy model (DAEM) at six heating rates (5, 10, 20, 30, 40, and 50 °C min−1). The results of the highest average correlation factor, low mean square error values, and low normalized mean square error values of the prediction and experimental data were in agreement. Thus, we demonstrated that the GRG algorithm is an appropriate method for analyzing kinetic data. [ABSTRACT FROM AUTHOR]

Recently, ashless pretreatment of lignocellulosic biomass prior to pyrolysis has been used for removing mineral matters to prevent slagging and fouling. The purpose of this study is to fundamentally investigate the pyrolysis characteristics of ashless treated kenaf with torrefaction. The related kinetic parameters and thermal behaviors were examined using non-isothermal thermogravimetric experiments. Thermal degradation experiments were conducted at temperatures ranging from 300 to 900 K at six different heating rates in a N2 environment. Ashless treatment resulted in a slight increase in hemicellulose and cellulose contents with decreasing lignin, whereas torrefaction of ashless kenaf led the hemicellulose to be decomposed more into cellulose and lignin compared to only ashless treatment. The decrease in the devolatilization index (Di) for ashless kenaf (AK) reached approximately 20%, whereas the Di for torrefied ashless kenaf (TAK) increased nearly three times the raw kenaf (RK) value. The distributed activation energy model was used to analyze the kinetics and thermal parameters for pyrolysis. The activation energies of RK, AK, and TAK were estimated as 180.51, 195.32, and 187.15 kJ mol−1, respectively. Thermodynamic parameters (ΔH, ΔG, ΔS) and reaction mechanisms were also compared and evaluated. The results indicated that torrefaction can improve the thermal degradation process of AK and can provide useful information for the development and optimization of thermochemical conversion systems using pretreated kenaf as feedstock. [ABSTRACT FROM AUTHOR]