Development of a modified independent parallel reactions kinetic model and comparison with the distributed activation energy model for the pyrolysis of a wide variety of biomass fuels

Predicting Pyrolysis of a Wide Variety of Petroleum Coke Using an Independent Parallel Reaction Model and a Backpropagation Neural Network

In this work, the pyrolysis behavior and gaseous products of petroleum coke were investigated by nonisothermal thermogravimetric analysis (TGA) and thermogravimetry-mass spectrometry (TG-MS). Then, the pyrolysis kinetics of six kinds of petroleum coke (Fushun (FS), Fuyu (FY), Wuhan (WH), Zhenhai (ZH), Qilu (QL), and Shijiazhuang (SJZ)) were determined by an independent parallel reaction (IPR) model, and the kinetic parameters (activation energy and preexponential factor) were obtained. In addition, an efficient backpropagation neural network (BPNN) was developed to predict the thermal data of six kinds of petroleum coke. The BPNN-predicted thermal data were used to calculate the kinetic parameters based on the IPR model, and the results were compared with the ones calculated using experimental data. The results showed that the pyrolysis process of six kinds of petroleum coke was divided into three stages, of which stage II (250-900 °C) had the significant mass loss, corresponding to the devolatilization of petroleum coke. MS fragmented ion intensity analysis indicated that the main pyrolysis products were methane CH _x (m/z = 13, 14, 15, and 16), aliphatic hydrocarbon C₃H₅, H₂, CO, CO₂, and H₂O. The thermal data predicted by the IPR, BPNN, and BPNN-IPR (BPNN combined with IPR) models were in good agreement with the experimental data. Most importantly, it was concluded that the BPNN-predicted data can be further applied to calculate the kinetic parameters using the IPR kinetic model.

Thermal Debinding Kinetics of Gelcast Ceramic Parts via a Modified Independent Parallel Reaction Model in Comparison with the Multiple Normally Distributed Activation Energy Model

This work aims to provide useful insights into the thermal debinding kinetics of gelcast ceramic parts, especially for debinding kinetics prediction involving heat preservation. Debinding experiments were conducted in a differential thermogravimetric analyzer at five heating rates (5, 8, 10, 15, and 20 °C/min) in the temperature range of 35-900 °C under an air atmosphere. The conversion (α) and pyrolysis rate (dα/dT) data were simulated using a modified independent parallel reaction (IPR) model and a multiple normally distributed activation energy model (M-DAEM). Their validity was assessed and compared by checking the agreement between the experimental results and the prediction capability. The results showed that both the modified IPR model and M-DAEM had high predictability for thermal debinding kinetics under linear heating conditions. The fitting quality parameters (Fit) were less than 1.406 and 1.01%, respectively. The activation energies (E _i , i = 1, 2, 3, 4, and 5) calculated by the M-DAEM ranged from 153.312 to 217.171 kJ/mol. The relationships between E _i of pseudo components 1 to 5 calculated by the modified IPR model were a function of the conversion rate. The E _i values were E ₁(α) = 116.750 + 11.153α - 26.772α² + 4.362α³ kJ/mol, E ₂(α) = 139.595 - 66.162α + 75.702α² - 38.041α³ kJ/mol, E ₃(α) = 190.854 + 135.755α - 214.801α² + 116.093α³ kJ/mol, E ₄(α) = 64.068 + 280.086α - 380.270α² + 264.724α³ kJ/mol, and E ₅(α) = 188.257 - 77.086α + 74.129α² - 48.669α³ kJ/mol, respectively. However, it is noteworthy that the α and dα/dT curves predicted by the modified IPR model with a deviation of less than 8% were better than those predicted by the M-DAEM for the linear thermal debinding process with the holding stage. Accordingly, it is believed that the proposed modified IPR model is suitable for describing the thermal debinding kinetics involving the heat preservation of gelcast green parts.

Forest Fuel Drying, Pyrolysis and Ignition Processes during Forest Fire: A Review

Forest ecosystems perform several functions that are necessary for maintaining the integrity of the planet’s ecosystem. Forest fires are thus a significant danger to all living things. Forest fire fighting is a foreground task for modern society. Forest fire prediction is one of the most effective ways to solve this urgent issue. Modern prediction systems need to be developed in order to increase the quality of prediction; therefore, it is necessary to generalize knowledge about the processes occurring during a fire. This article discusses the key features of the processes prior to forest fuel ignition (drying and pyrolysis) and the ignition itself, as well as approaches to their experimental and mathematical modeling.

Modeling of Metalized Food Packaging Plastics Pyrolysis Kinetics Using an Independent Parallel Reactions Kinetic Model

Recently, a pyrolysis process has been adapted as an emerging technology to convert metalized food packaging plastics waste (MFPWs) into energy products with a high economic benefit. In order to upscale this technology, the knowledge of the pyrolysis kinetic of MFPWs is needed and studying these parameters using free methods is not sufficient to describe the last stages of pyrolysis. For a better understanding of MFPWs pyrolysis kinetics, independent parallel reactions (IPR) kinetic model and its modification model (MIPR) were used in the present research to describe the kinetic parameters of MFPWs pyrolysis at different heating rates (5-30 °C min-1). The IPR and MIPR models were built according to thermogravimetric (TG)-Fourier-transform infrared spectroscopy (FTIR)-gas chromatography-mass spectrometry (GC-MS) results of three different types of MFPWs (coffee, chips, and chocolate) and their mixture. The accuracy of the developed kinetic models was evaluated by comparing the conformity of the DTG experimental results to the data calculated using IPR and MIPR models. The results showed that the dependence of the pre-exponential factor on the heating rate (as in the case of MIPR model) led to better conformity results with high predictability of kinetic parameters with an average deviation of 2.35% (with an improvement of 73%, when compared to the IPR model). Additionally, the values of activation energy and pre-exponential factor were calculated using the MIPR model and estimated at 294 kJ mol-1 and 5.77 × 1017 kJ mol-1 (for the mixed MFPW sample), respectively. Finally, GC-MS results illustrated that pentane (13.8%) and 2,4-dimethyl-1-heptene isopropylcyclobutane (44.31%) represent the main compounds in the released volatile products at the maximum decomposition temperature.

Assessment of the thermal decomposition kinetics of empty fruit bunch, kernel shell and their blend

In this work, were studied the thermal and kinetic characteristics of the palm kernel shell (PKS) and empty fruit bunch (EFB) from the African oil palm. Experiments in the inert atmosphere were carried out in a thermogravimetric analyzer. In the kinetic analysis were applied the one-step reaction through iso-conversion methods, mechanism of independent parallel reactions (MIPR), and mechanism of consecutive reactions (MCR). The one-step reaction mechanism overestimated the thermal decomposition of all samples; however, the best was the EFB. The MIPR showed to be representative of the thermal decomposition of all samples, and the proposed correlations between the pre-exponential factor and the heating rate improved the accuracy of the model. The MCR analysis showed that using the same kinetic parameters applied in the MIPR does not affect reliability. Finally, as a conclusion, blending PKS with EFB increase 5% heating value and decrease 50% ash content.

Catalytic performance of potassium in lignocellulosic biomass pyrolysis based on an optimized three-parallel distributed activation energy model

The pyrolysis kinetics of extractive tobacco stem and pretreated samples with different KCl impregnation ratios were investigated by the thermogravimetric experiment and an optimized three-parallel distributed activation energy model (DAEM). The significant fitting deviation for the cellulose pyrolysis and the unrealistic partial fitting curve for the hemicellulose pyrolysis were mitigated during the optimization process by applying the Avrami-Erofeev-DAEM and reducing the latent interferences. The optimized parameters with good fitting qualities (about 2%) were obtained. Furthermore, based on the experimental results (changes in reaction intensity and temperature), model calculations (differences in reaction order, activation energy, volatiles fraction, etc.), and the maximum residual error analysis (with a high catalytic reaction rate) regarding different KCl-to-biomass ratios, it was found that KCl kinetically promoted the hemicellulose pyrolysis, which can be utilized as the theoretical support for the industrial application.

Co-pyrolysis kinetics of sewage sludge and bagasse using multiple normal distributed activation energy model (M-DAEM)

In this study, the kinetic models of bagasse, sewage sludge and their mixture were established by the multiple normal distributed activation energy model. Blending with sewage sludge, the initial temperature declined from 437 K to 418 K. The pyrolytic species could be divided into five categories, including analogous hemicelluloses I, hemicelluloses II, cellulose, lignin and bio-char. In these species, the average activation energies and the deviations situated at reasonable ranges of 166.4673-323.7261 kJ/mol and 0.1063-35.2973 kJ/mol, respectively, which were conformed to the references. The kinetic models were well matched to experimental data, and the R² were greater than 99.999%y. In the local sensitivity analysis, the distributed average activation energy had stronger effect on the robustness than other kinetic parameters. And the content of pyrolytic species determined which series of kinetic parameters were more important.

Thermodynamic modeling of small scale biomass gasifiers: Development and assessment of the ''Multi-Box'' approach

Modeling can be a powerful tool for designing and optimizing gasification systems. Modeling applications for small scale/fixed bed biomass gasifiers have been interesting due to their increased commercial practices. Fixed bed gasifiers are characterized by a wide range of operational conditions and are multi-zoned processes. The reactants are distributed in different phases and the products from each zone influence the following process steps and thus the composition of the final products. The present study aims to improve the conventional 'Black-Box' thermodynamic modeling by means of developing multiple intermediate 'boxes' that calculate two phase (solid-vapor) equilibriums in small scale gasifiers. Therefore the model is named ''Multi-Box''. Experimental data from a small scale gasifier have been used for the validation of the model. The returned results are significantly closer with the actual case study measurements in comparison to single-stage thermodynamic modeling.