Chemical Percolation Devolatilization Model Research Articles

CPD model prediction of oil sand pyrolysis based on structural parameters from 13C NMR and FTIR measurements

Here, carbon-13 nuclear magnetic resonance spectroscopy (13C NMR) and Fourier transform infrared spectroscopy (FTIR) techniques were used to study the chemical structure characteristics of oil sand and its pyrolysis oil. The FTIR results showed that the values of the CH2/CH3 ratio, A-factor, and DOC1 of the pyrolysis oil decreased during the pyrolysis process, while the C-factor showed a maximum value with increasing pyrolysis temperature. The 13C NMR results showed that methylides and methylides were mainly contributed to oil production. The aliphatic chain in the pyrolysis oil has little alterations during pyrolysis, while the extent of aromatic ring substitution increases from 0.46 to 0.58. Furthermore, a correlation was obtained between the chemical structure of oil and the pyrolysis product yields of oil sand. Moreover, using chemical structure parameters investigated with FTIR and 13C NMR and kinetic parameters based on the thermogravimetric data, the chemical percolation devolatilization (CPD) model was applied to simulate the pyrolysis of oil sand. The results showed that the simulated results for tar and light gas were in good agreement with the experimental data, while those for char underpredicted the experimental data. Overall, the CPD model can effectively predict the pyrolysis of oil sand.

Numerical investigation on NOx formation of staged oxy-fuel combustion in a 35 MW large pilot boiler

In this study, high-fidelity simulations are conducted on a 35 MW pulverized coal oxy-fuel boiler to investigate NOx formation characteristics under staged oxy-fuel combustion, including both fuel-staged and oxygen-fuel two-way staged modes. Detailed volatile components are considered by using the chemical percolation devolatilization model. A skeletal reaction mechanisms consisting of 35 species developed for fuel-NOx formation under oxy-fuel conditions are employed for the gas phase combustion and NOx modeling. The radiative property models are also optimized for oxy-fuel combustion. The results show that in the fuel-staged mode, a reduction atmosphere is established in the reburning zone to reduce the NOx concentration in the flue gas. A reduction of 5.6% in the average NO concentration at the furnace outlet is observed relative to the baseline oxy-fuel case. Moreover, the application of oxygen-fuel two-way staged combustion leads to a further reduction in NOx formation. The average NO concentration at the furnace outlet is decreased by 17% compared to the baseline oxy-fuel case. Pathway analysis indicates a reduction in the NO formation pathway involving HCN → NCO → NO, while the NO reduction pathway of NO → HCN is enhanced.

Modification of extended chemical percolation devolatilization model for application to low-rank coals

For understanding coal gasification reactions, primary pyrolysis reaction is important as the first stage of the gasification reactions. Recently, the authors developed a primary pyrolysis model to predict tar formation behavior by extending the chemical percolation devolatilization (CPD) model which is often used to predict pyrolysis behavior. The extended CPD (Ex-CPD) model predicts gas and tar components as respective chemical species. Consequently, the secondary tar decomposition behavior can be calculated by elementary step-like reaction models. However, some of the coal structure parameters used in the model contradict the 13C NMR data. That is, the molecular weight of the aromatic ring clusters calculated by the original Ex-CPD decreases with the aromatic index obtained by 13C NMR. In this study, this problem was resolved by modifying the calculation procedure to determine the coal structure parameters. The recalculated aromaticity index agreed with that calculated from the 13C NMR data. The modified Ex-CPD model was validated through comparison with coal gasification experiments using a pressurized drop tube furnace. The calculation results successfully described the trend of light gases, soot, and char yield in the experiments.

Modified network kinetic model for coal pyrolysis with high-value products and low carbon emissions

Pyrolysis is a clean and efficient technology for the conversion of low-rank coal. Its key product is tar with high value. The complex composition of tar limits its further effective utilization. Although most kinetic models can provide the final distribution of three-phase products in coal pyrolysis, an effective prediction method for the specific composition of tar and gas has not yet been developed. Most numerical models serve to improve the total yield of volatile matter and cannot provide theoretical guidance for the improvement of tar quality or the reduction of carbon emission. Based on the basic assumptions of the CPD (Chemical Percolation Devolatilization) model for product molecules structure and generation mechanism, this paper proposed a more sophisticated method for dividing tar composition, which can achieve the division of light, medium, and heavy fractions of tar components according to boiling point. Light gas composition could be obtained with the combination of FG(Functional Group) submodel. The influence of pyrolysis final temperature, heating rate, and environmental pressure was explored for the yield and distribution of products of 18 coals. The simulation results showed that the total yield of tar was affected by both coal structure characteristics and operating parameters. Under conditions favorable for evaporation, such as low pressure and high temperature, the total yield of tar was positively correlated with the average aromatic core size in coal. Under other conditions, tar release was limited by its volatility. Coal with larger average aromatic core size corresponded to less tar yield instead. The pressure in the operating parameters had the most significant influence on the total yield of tar. The heavy fractions of tar are more sensitive to changes in operational parameters, making working conditions that increase the total yield of tar reduce tar quality. The overall carbon emission of pyrolysis is <1 kg CO2/kg tar, which is far lower than the 2–4 kg CO2/kg tar and 3–9 kg CO2/kg tar of direct and indirect liquefaction processes. Under the conditions of sufficient insulation time and no consideration of secondary reactions, the carbon emission of pyrolysis only depended on the content of carboxyl groups in the precursor functional groups. Therefore, the carbon emission intensity decreased with the increase of coal rank. For the optimization for total tar yield and tar quality, 1 atm pressure and 723–923 K temperature was optimal for low rank coals, while low temperature and heating rate with 10–20 atm pressure or high temperature and heating rate with 45–50 atm pressure were optimal for medium rank coals. For the optimization of light tar yield and tar quality, 6–9 atm pressure was optimal for low-rank coals, and 1–3 atm pressure was optimal for medium-rank coals.

Kinetic Modeling of the Devolatilization of Pulverized Coal, Poplar Wood, and Their Blends in a Thermogravimetric Analyzer and a Flat Flame Reactor.

Devolatilization kinetics of coal, poplar wood, and blends containing 10 and 20 wt % of biomass were characterized. Measurements were carried out under inert atmosphere with heating rates between 10 K min-1 and ∼106 K s-1 using a thermogravimetric analyzer (TGA) and a flat flame reactor (FFR). Measured data were simulated using the chemical percolation devolatilization (CPD) model and a global kinetic scheme based on two competitive reactions integrating a refined differential reaction model. The CPD model failed to simulate TGA results but reproduced FFR data relatively well. As for the global model, selecting kinetic parameters from the literature turned out to lead to unsuitable predictions. Fitted values of the activation energies Ea,i, pre-exponential factors Ai, mass stoichiometric coefficients Yi, and the reaction model factor n were therefore inferred using a genetic algorithm-based optimization procedure, leading to obtain an excellent agreement between simulated and measured data. The assessed Ea,i values were found to be lower for wood than for coal, which is consistent with the higher energy required to break the strong C-C bonds holding the highly cross-linked aromatic structures of coal. Besides, blending coal with 20 wt % of wood induced a decrease of Ea,i values, which went from 99.79 to 86.1 kJ mol-1 and from 186.72 to 171.57 kJ mol-1 for the first and second reactions prevailing at low and high temperatures, respectively. Finally, the fact that the activation energy of the first devolatilization reaction was found to be lower with the blend containing 20% of wood than for wood illustrated the probable existence of synergies, as also exemplified by the characteristic devolatilization times for blended samples, which were found to be relatively similar to and even lower than that of wood.

Transient numerical simulation of heat recovery coke oven based on chemical percolation devolatilization model

ABSTRACT The actual coking engineering challenge is changed into a numerical simulation calculation problem due to the difficulty in monitoring the parameters of the heat recovery coke furnace. The release law of coal volatiles is calculated using the chemical percolation devolatilization (CPD) model in this study. To explore the distribution properties of the temperature field and flow field in the furnace as well as the burning condition of the surface of the coal cake, the user-defined function (UDF) is coupled with the porous medium model, and the transient condition simulation is carried out. The accuracy of the model is verified by comparing the temperature values at different times with the actual parameters. According to the calculations, the fuel burns more fully when the equivalency ratio is close to 1, and that the flame propagation speed increases with combustion temperature. When the bulk density is 1100 kg/m3 and the air input velocity is 13.3 m/s, the reaction lasts for 15 hours and the emission of volatiles is very minimal, resulting in a poor combustion reaction. The coal cake surface’s major temperature range is 1200 K to 1400 K after 30 hours of reaction time, which is beneficial to accelerate the maturation of coke. The coal cake surface’s temperature distribution at 45 and 60 hours is lower than that of the coke. Additionally, an increase in air and flame propagation velocity can strengthen furnace disturbance, enhance the temperature and velocity distribution uniformity, hasten coke ripening, and enhance coke quality.

Three-dimensional Numerical Simulation of Entrained-Flow Gasifier and Influence of Coal Distribution at the Inlet

The research object in this paper is an industrial HTL gasifier in a plant. A three-dimensional model is built. The chemical percolation devolatilization (CPD) model is used to calculate the pyrolysis reaction. Considering the gas diffusion in the inner pores of the particle and the evolution of pore structure, the random pore model (RPM) was used to simulate the chemical reaction on the particle surface, and the gasification reaction kinetic parameter of char was measured by high-pressure thermogravimetry analysis. The slag model was constructed to describe the formation process and distribution of slag. Through the coupling of the above models, a simulation method that combines several submodels for the entrained flow gasifier is built, and the results from simulation are in good agreement with the industrial data. Furthermore, the effect of the uniformity of pulverized coal injection was analyzed by this method. The simulation results reflect that the asymmetric feed of coal will affect gas-solid mixing and reduce carbon conversion, and it leads to a higher local wall temperature and a lower ratio of crude slag to fine slag.

Particle-scale heat and mass transfer processes during the pyrolysis of millimeter-sized lignite particles with solid heat carriers

• Devolatilization kinetics is coupled with the heat and mass transfer processes. • Evolution of pore structure in coal pyrolysis with solid heat carrier is included. • Multi-physical fields inside a lignite particle during pyrolysis is elaborated. • The intraparticle mass transfer mechanism influences the secondary reaction. The study of mesoscale solid fuel pyrolysis behavior is a key bridge between the microscopic reaction kinetics and macroscopic multiphase reaction flow in a reactor. In this work, a one-dimensional nonstationary model was developed in spherical coordinate system for the pyrolysis of millimeter-scale lignite particles with solid heat carriers, in which a modified multistep kinetic model (MSM) was coupled with a series of correlative transient heat and mass conservation equations in conjunction with the dusty gas model (DGM). The MSM for coal pyrolysis was modified by adding a set of kinetic equations of pseudo-elementary secondary reactions, making the kinetic model comparable to the Chemical Percolation Devolatilization model in terms of accuracy. In addition, a semiempirical submodel for the evolution of pore structure parameters (porosity, pore size, and permeability) was incorporated to obtain the precise mechanism of volatile species transport in the porous coal matrix. The modified MSM and pore evolution submodel were validated against literature data. The coupling effects between intraparticle transport processes and transient devolatilization kinetics were investigated. It was concluded that notable multiphysical fields (pressure, concentration, and velocity) emerged within lignite particles during pyrolysis, governed by the heating history. In addition, it should be noted that the direction and mechanism of volatiles transfer within porous lignite particles varied during pyrolysis, which can significantly affect secondary reactions. Flow reversal and shifts in the dominant mass transfer mode influenced the secondary reaction pathway, in addition to the impact of volatiles flow velocity on the reaction degree.

Numerical simulation of entrained flow gasification based on properties and kinetic characteristics of pulverized coal particles

Gasification kinetic parameters of coal char based on the random pore (RPM) model are obtained with CO2 and H2O using a high-pressure thermogravimetry analysis (TGA) under atmospheric pressure and 4.0 MPa pressure, considering the influence of internal diffusion and particle structure varying with carbon conversion. The Chemical Percolation Devolatilization (CPD) model is used to modify the actual volatile content. Through the coupling of the gasification kinetic reaction model, a comprehensive numerical simulation method of the entrained flow gasification process is established. This method is used to simulate the typical gasifier of HTL (a gasification technology of Changzheng Engineering Co.) in an industrial plant. The research shows that the intrinsic reaction parameters obtained by TGA under high pressure can give a more reasonable reaction state of coal char particles in the gasifier than that measured under atmospheric pressure, and the simulation results are in good agreement with the industrial data. In addition, HTL adopts a single top-fired burner and multi-channel swirling feed type. The particles are entrained and mixed with swirling oxygen, and the combustion reaction is completed quickly in the upper part of the gasifier. In contrast, the gasification reactions are relatively slow and mostly dominate in the recirculation zone and pipe flow zone, leading to high carbon conversion.

Toba-CPD: An Extended Chemical Percolation Devolatilization Model for Tobacco Pyrolysis.

Tobacco features chemical compositions different from that of raw lignocellulosic biomass. Currently, the performance of network models, like Bio-Chemical Percolation Devolatilization (Bio-CPD), on tobacco pyrolysis is unclear, and only global kinetics have been proposed for tobacco devolatilization, which does not have the versatility for a wide range of heating conditions and tobacco types. To address this issue, the present work first assessed the performance of the Bio-CPD model on tobacco pyrolysis through an a priori study, which showed large deviations. Afterward, an extended Chemical Percolation Devolatilization model for tobacco pyrolysis (Toba-CPD) was developed by modifying the kinetic parameters using a grid-search optimization strategy. The process of grid-search optimization strategy is based on the kinetic parameters of the Bio-CPD model and modified with experimental results of 11 tobacco types under a wide range of heating rates. Finally, the performance of Toba-CPD was measured with experimental results which were not used during parameters optimization. Results demonstrated that the Toba-CPD models could well reproduce the pyrolysis of various tobacco types under a wide range of heating rates (R2 > 0.957).

Effects of Moisture on the Ignition and Combustion Characteristics of Lignite Particles: Modeling and Experimental Study.

The influence of the moisture content on the ignition and combustion characteristics of lignite single particles was studied using an ignition model of single coal particles with moisture and experimental investigations in a visual drop tube furnace under the temperature of 1300 K. The moisture content and the lignite particle size were varied within the ranges of 0–20% and 75–250 μm, respectively. The images of the combustion process illustrated that higher moisture content caused a significant ignition delay. The probability of homogeneous ignition was greatest when the particle size was 125–150 μm and the moisture content was 5%. An ignition model was employed to explain the mechanism of the influence of moisture content on the ignition and combustion characteristics, which embedded the chemical percolation devolatilization model to increase the accuracy of predictions. The predicted results show that there was an overlap in the release of moisture and volatile matter from the lignite particle during the combustion at a high heating rate. The devolatilization rate increases with the increase of moisture, which explains the increase in the probability of homogeneous ignition and fragmentation. Both particle size and moisture content have two-sided effects on the ignition mode, which causes the complexity and irregularity of the ignition mode of particles with moisture.

Simulation analysis of biomass pyrolysis based on the improved chemical percolation devolatilization model with chain reaction dynamics

AbstractThe complex composition and molecular structure of biomass lead to more complex and diversified chemical reactions in the pyrolysis. According to the structural characteristics of the reactants, this article simplifies the pyrolysis process and extends the research focus from the micro‐molecular elementary reactions to the macro reaction kinetics. The wheat straw is chosen as the investigated biomass, and the promoted chemical percolation devolatilization with modified pseudo‐grid and chain reaction kinetics pyrolysis models were constructed for predicting the pyrolysis characteristics. Under the condition of slow pyrolysis, by calculating the average difference between the collected calculated values and the corresponding experimental values, the prediction errors of bio‐char, bio‐oil, and gas production are in a reasonable range of &lt;10%. Moreover, the reliability of the model is verified by comparing with the experimental thermogravimetric curve, which shows that the model could well predict the mass loss, product distribution, and component characteristics, and provides a reasonable prediction for the pyrolysis of biomass. However, the simplifications and assumptions about the model also lead to some deviations of the predicted values, which should be considered and improved in future research.

The determination method of the ignition modes of single coal particle with a transient coal ignition and combustion model

A transient model for the ignition and combustion of a quiescent coal particle was developed by coupling the mass, energy and species governing equations between the particle phase and the gas phase. The ignition delay times of single coal particle were calculated by using the transient ignition and combustion model with Kobayashi-Sarofim devolatilization model and Chemical Percolation Devolatilization (CPD) model, respectively. The predicted results were compared with the experimental data to further validate better performance of CPD model. The new ignition criteria of single coal particle were proposed to determine the onset of the ignition and subsequently to define the ignition modes of single coal particle by comparing the magnitude of typical ignition time scales, including the start time and the end time of devolatilization, homogeneous ignition delay time and the heterogeneous ignition delay time based on the thermal explosion theory (TET). The ignition modes map of single coal particle under various ambient oxygen molar fractions (O2 = 0–100%) and gas temperatures (Tg = 800–2000 K) was firstly depicted by using the transient ignition and combustion model with the new ignition criteria. The ignition modes of single coal particle transferred from homogeneous gas-phase ignition (GI) to homo-heterogeneous ignition (GI-HI) when the ambient oxygen molar fraction was increased from 5% to 21% under Tg = 1340 K condition, and then they transformed into hetero-homogeneous ignition (HI-GI) and heterogeneous ignition of coal (HI-coal) when the ambient oxygen molar fraction was further increased to 40% and 70%, respectively. Moreover, the simulated results showed that the critical oxygen molar fraction XO2,cr for the transition of ignition mode from homogeneous to heterogeneous ignition was 15% for the particle size of 50 μm, XO2,cr = 20% for the particle size of 100 μm, and XO2,cr = 30% for the particle size of 200 μm, respectively. The critical parameters for the transition of ignition mode of single coal particle were quantitatively determined to give a deep understanding on coal particle ignition process and to provide the guidance for improving the combustion performance of coal particles.

Improved CPD model coupled with lattice vacancy evolution

The development of CFD (Computational Fluid Dynamics) technology needs more extensive process adaptability of coal pyrolysis models. Some modified CPD (Chemical Percolation Devolatilization) models may have extended the application, but problems still exist: this paper presents further improvements and experimental verification. On the one hand, the improvements cover the integration of cross-linking process with the lattice structure, as well as an updating of the kinetic calculation; i.e., creating directed graphs Gchar and Gtar for modeling char and tar structures, counting node/edge properties for producing macroscopic lattice features, solving traditional DAEM (Distribution Activation Energy Model) for calculating bridge kinetic processes, and tracking the influence of evaporation on the lattice network vacancy. On the other hand, the verification shows that the proposed model can reasonably predict the pyrolysis data of Ill6 and Zap coal under both fast and slow conditions simultaneously. In order to save computational cost and facilitate practical application, an ANN (Artificial Neural Network) is trained. At last, some future work includes optimization of kinetic parameters and modeling of real lattices.

Kinetic modelling of pyrolysis of cellulose using CPD model: effect of salt

In this work, effect of salt on cellulose pyrolysis behaviour using chemical percolation devolatilization (CPD) model has been investigated. The distributed activation energy model (DAEM) has been used to determine the kinetics of pure and NaCl-loaded cellulose pyrolysis in a thermogravimetric analyser (TGA). A number of these experiments were performed for a range of heating rates (5–100 °C min−1) and for different concentrations of NaCl in cellulose (0.25–2 mass/%) which showed a pronounced effect of salt on the primary pyrolysis reactions of cellulose. These data were then used in a two-component DAEM to calculate the kinetic parameters for the chemical percolation devolatilization model (CPD) for both pure and NaCl-loaded cellulose. The optimized kinetic parameters for the pure and NaCl-loaded cellulose were used in the CPD model, and the product yield was predicted. The CPD predictions showed that the fraction of gases and char in the pyrolysis products increased in the presence of salt. The amount of char for pure cellulose was 6.97% which increased to 16.4% in the presence of 0.25% NaCl. The amount of gases produced as a result of pure cellulose pyrolysis was 9.63% and this amount increased with addition of NaCl to 22.85% and then further increases with an increase in NaCl concentration. Amount of tar produced for pure cellulose was 83.4%, and this amount reduced to 60.7% with addition of 0.25% NaCl. The presence of NaCl accelerates cellulose decomposition and favours the formation of gases and char.

Ignition predictions of isolated coal particles by different ignition criteria and devolatilization models

The prediction accuracy of coal ignition characteristics depends on the sub-model selections. A detailed modeling study on the influences of ignition criteria and devolatilization models on the ignition characteristics of isolated coal particles is conducted using a one-dimensional transient ignition model. The assessed ignition criteria include the thermal explosion theory (TET), the transient adiabatic criterion (TAC) and the flammability limit criterion (FLC), while the assessed the devolatilization models include the chemical percolation devolatilization (CPD) one and two competing reaction (TCR) one. Under each combination, the ignition characteristics under different oxygen concentration, particle size, and surrounding temperature are studied. The prediction results are compared with microgravity experimental data obtained from the 3.6 s drop tower in National Microgravity Laboratory Center of China (NMLC). Modeling results reveal that the particle center temperature is more reasonable to be used as the characteristic temperature in the ignition study. When devolatilization process is described by CPD model, for homogenous ignition FLC is more accurate to predict ignition temperature and time than TAC at a higher XO2 and a high Tw, while TAC is more accurate to predict ignition temperature at a large particle size. Using FLC, against TAC, the transient of ignition mode from homogenous to combined happens at a ∼ 80 K higher temperature and ∼ 50 μm larger particle size, while that from combined to heterogenous happens at 250 μm rather than 400 μm. When FLC is used as the ignition criterion, selection of devolatilization model has more notable effect on the prediction of ignition temperature and time. Furthermore, the combination of FLC and CPD is more accurate to predict ignition temperature and time at a higher XO2. Two diagrams are respectively given to guide the selection the ignition criterion and identify the ignition mode at a wide range of conditions. In addition, the mechanisms of the associated discrepancy are discussed.

Modeling Coal Swelling during Pyrolysis at Elevated Pressure by Using a Single Bubble Model: Validation and Application

ABSTRACT Pressurized oxy-coal combustion technologies are attracting more attention of researchers because of their advantages of carbon capture. While the ambient pressure could significantly influence the coal pyrolysis behavior. In this study, Yulin coal was used for the pyrolysis experiment in a pressurized drop tube furnace. Pyrolysis temperature of 1273 K, and pressures of 1, 4, 7, 10 atm were considered. The swelling behavior of produced char was analyzed by the scanning electron microscope (SEM). The char evolution process during pyrolysis at elevated pressure was simulated by a revised single bubble model, in which the volatile releasing rate and yield by residence time can be obtained from the CPD (chemical percolation devolatilization) model. Results show that the revised single bubble model is suitable for predicting the char evolution over a wide range of pressure and heating rate. Optimum pressure is present in the range of 7–15 atm, where the swelling ratio and porosity reach the maximum value. This model can predict the two regimes of coal swelling in varied heating rates, which is more obvious at high pressure. The porosity development by time can also be output, and the variation trends are similar to the swelling ratio.

Numerical investigation and assessment of flamelet-based models for the prediction of pulverized solid fuel homogeneous ignition and combustion

The homogeneous ignition and volatile combustion of pulverized solid fuel in single-particle and particle group configurations were studied numerically in a laminar flat flame burner. Simulations with increasing particle streams were performed to investigate the influence of the interactions in particle groups on homogeneous ignition and combustion. An extensive set of simulations are conducted considering models with different levels of detail for both the gas-phase and solid fuel chemistry. The reference simulations employ the chemical percolation devolatilization model coupled with a detailed chemistry model for gas-phase reactions. The particle-fluid interactions were modeled with a fully coupled Eulerian-Lagrangian framework. Increased ignition delay times for higher particle streams were successfully validated against available experimental measurements. Furthermore, the transition from single-particle ignition to a conically shaped volatile flame with suppressed reactions near the flame base in particle group combustion was observed in both experiments and simulations. The subsequent detailed investigations revealed that the increased heat transfer to particles and, therefore, lower gas temperature for higher particle number densities together with the local oxygen depletion are the primary reasons for this transition. Based on the reference simulation, different simplified model combinations were assessed. The systematic model reduction investigation started with assessing the fixed volatile composition as a required assumption for flamelet models. Finally, the effects of gas-phase chemistry and different simple devolatilization models on ignition and combustion chemistry were studied. Overall, all model combinations provide reasonable predictions of volatile combustion with minor local deficits in the studied conditions.

Approaches to Biomass Kinetic Modelling: Thermochemical Biomass Conversion Processes

Modeling of biomass pyrolysis kinetics is an essential step towards reactors design for energy production. Determination of the activation energy, frequency factor, and order of the reaction is necessary for the design procedure. Coats and Redfern's work using the TGA data to estimate these parameters was the cornerstone for modeling. There are two significant problems with biomass modeling, the first is the determination of the kinetic triplet (Activation energy, Frequency factor, and the order of reaction), and the second is the quantitative analysis of products distribution. Methods used in modeling are either One-step or Multistep methods. The one-step techniques allow the determination of kinetic triplet but fail to predict the product distribution, whereas multistep processes indicate the product's distribution but challenging to estimate the parameters. Kissinger, Coats, and Redfern, KAS, FWO, Friedman are one-step methods that have been used to estimate the kinetic parameters. In this work, after testing more than 500 data points accessed from different literature sources for coal, oil shale, solid materials, and biomass pyrolysis using one-step global method, it was found that the activation energy generated by KAS or FWO methods are related as in the following equations: 𝐸𝐾𝐴𝑆 = 0.9629 ∗ 𝐸𝐹𝑊𝑂 + 8.85, with R² =0.9945 or 𝐸𝐹𝑊𝑂 = 1.0328 ∗ 𝐸𝐾𝐴𝑆 − 8.0969 with R2= 0.9945. The multistep kinetic models employed the Distributed Activation Energy Model (DAEM) using Gaussian distribution, which suffers from symmetry, other distributions such as Weibull, and logistic has been used. These multistep kinetic models account for parallel/series and complex, primary and secondary biomass reactions by force-fitting the activation energy values. The frequency factor is assumed constant for the whole range of activation energy. Network models have been used to account for heat and mass transfer (diffusional effects), where the one-step and multistep could not account for these limitations. Three network models are available, the Bio-CPD (Chemical Percolation Devolatilization) model, Bio-FLASHCHAIN, and the Bio-FGDVC (Functional Group Depolymerization Vaporization Crosslinking models). These models tried to predict the product distributions of the biomass pyrolysis process

Pyrolysis of a typical low-rank coal: application and modification of the chemical percolation devolatilization model.

The chemical percolation devolatilization (CPD) model can simulate the formation of various products during the coal pyrolysis process and predict the products composition relatively accurately. In this study, the pyrolysis products of a typical low-rank coal were calculated using the CPD model, and several model improvements were proposed by combining the experimental results in a lab-scale pyrolysis system. The chemical structural parameters calculated from the Genetti correlations were verified by adjusting the initial fraction of char bridges (c0) from 0.098 to 0.25. A yield difference (Δftar) was defined in this paper to analyze the consumption of tar fragments in the model, and it was found that the deviations between experiments and calculations resulted from the weak influence of crosslinking. A modification expression was adopted to amplify the tar consumption: , which improved the accuracy of the model on the tar yield with errors of less than ±0.5 wt%. Furthermore, this paper also developed a correlation in an exponential form about gas composition, which attempted to extend the application of the CPD coalification reference mesh for the coal away from interpolation triangles. The improved model by the correlation predicted CH4, CO, and CO2 yields for this typical low-rank coal accurately in most cases. Compared with the original CPD model, the modified model showed better agreement with the experimental results and predicted 71.4% and 88.6% of the data points in this work within ±10% and ±20% errors, respectively.