A KINETIC MODEL FOR THE PRODUCTION OF LIQUIDS FROM THE FLASH PYROLYSIS OF BIOMASS

A kinetically based prediction model for the production of organic liquids from the flash pyrolysis of biomass is proposed. Wood or other biomass is assumed to be decomposed according to two parallel reactions yielding liquid tar and ( gas + char) The tar is then assumed to further react by secondary homogeneous reactions to form mainly gas as a product

The model provides a very good agreement with the experimental results obtained using a pilot plant fluidized bed pyrolysis reactor

The proposed model is shown to be able to predict the organic liquid yield as a function of the operating parameters of the process, within the optimal conditions for maximizing the tar yields, and the reaction rate constants compare reasonably well with those reported in the literature     

Prediction of Biomass Pyrolysis Mechanisms and Kinetics: Application of the Kalman Filter

In order to predict the pyrolysis mechanisms of four different biomasses (Asbos (Psilocaulon utile), Kraalbos (Galenia africane), Scholtzbos (Pteronia pallens), and palm shell), a novel method called Kalman filter was investigated and the results were compared by regression analysis. Both analyses were applied to five different generalized biomass pyrolysis models consisting of parallel and serial irreversible-reversible reaction steps. The models consisting of reversible reactions in addition to parallel pyrolysis steps demonstrated a better fit with the experimental results. The pyrolysis step from biomass to bio-oil has the highest reaction rates compared with the other pyrolysis steps defined in the models. The Kalman filter is thus defined as a promising filtering and prediction method for the estimation of detailed pyrolysis mechanisms and model parameters, using minimum experimental data.     

Computational fluid dynamics modeling of biomass catalytic fast pyrolysis in bubbling fluidized reactor: Effects of catalyst parameters on process performance

In this study, a computational fluid dynamics mathematical model has been developed for catalytic fast pyrolysis (CFP) of biomass based on multiphase flow, transfer process, and biomass pyrolysis reactions in a bubbling fluidized bed reactor. The multiphase fluid flow, and the inter-phase momentum and energy transfer processes are modeled with Eulerian multiphase formulas, representing the flows of gases and solids (catalyst and biomass) within the reactor. The biomass CFP reactions are described by using a two-stage, semi-global model. Specified secondary tar catalytic cracking process, which considers both intrinsic reaction rates and mass-transfer process, is embedded to the developed model by user-defined function. The model simulation results of pyrolysis product yield and distribution are compared with the experimental data with close agreement. The model is then employed to investigate the effects of structural properties of catalyst, such as specific internal area, average size of active sites, pore diameter, and tortuosity, on products yields and composition. The tar cracking process by the selected catalyst is proposed and the influences of adsorption capability of tar molecule on catalyst surface and external film mass transfer are also analyzed. The developed model can be solved with short computational time and thus it can be employed for further research and engineering designs of the catalytic pyrolysis of carbonaceous materials.     

生物质模化物催化热解制取烯烃和芳香烃

采用愈创木酚作为生物质模型化合物,以ZSM-5为催化剂,在固定床反应器中研究了反应温度、质量空速以及分压对热解产物产率、选择性的影响,并考察了催化剂的积炭情况。结果表明,愈创木酚催化热解的主要产物为酚类,其次是芳香烃。温度对产物分布有显著影响。催化剂适量的积炭有利于提高烯烃和芳香烃的产率。根据愈创木酚催化热解反应产物分布,推测其主要反应为脱除甲氧基形成酚类,进一步芳构化形成芳香烃。本文研究结果为研究生物质催化热解反应机理提供了理论依据。     

Simulation and Modeling of Vegetable Market Wastes Pyrolysis Under Progressive Deactivation Condition

The pyrolysis behaviour of predried vegetable market waste has been investigated using TGA within the temperature range 523 to 923 K under inert atmosphere and a comparison has been made with other lignocellulosic materials in order to point out the difference between the pyrolysis of nearly homogeneous and perfectly mixed heterogeneous biomass. Kinetic parameters of the pyrolysis material have been evaluated from the simulation of the TG data. A reaction mechanism involving two parallel 1^st order reactions evolving gaseous products lumped as volatiles and solid products lumped as char has been proposed for prediction of rate constants as a function of normalized fractional change. Four kinetic models incorporating the effect of deactivation have been used for this purpose. In another attempt, using concentration independent model of solid deactivation, simulation has been carried out to predict concentration time history of the system components as well as quantitative change of rate constants with the propagation of time.     

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

The 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 <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.     

Modelling of the pyrolysis of biomass particles. Studies on kinetics,thermal and heat transfer effects

The present work provides a rationally-based model to describe the pyrolysis of a single solid particle of biomass. As the phenomena governing the pyrolysis of a biomass particle are both chemical (primary and secondary reactions) and physical (mainly heat transfer phenomena), the presented model couples heat transport with chemical kinetics. The thermal properties included in the model are considered to be linear functions of temperature and conversion, and have been estimated from literature data or by fitting the model with experimental data. The heat of reaction has been found to be represented by two values: one endothermic, which prevails at low conversions and the other exothermic, which prevails at high conversions. Pyrolysis phenomena have been simulated by a scheme consisting of two parallel reactions and a third reaction for the secondary interactions between charcoal and volatiles. The model predictions are in agreement with experimental data regarding temperature and mass-loss histories of biomass particles over a wide range of pyrolysis conditions.     

基于遗传算法-综合计算法的生物质热解气化优化分析

生物质热解气化可实现碳基可再生能源的高效清洁利用。为准确预测生物质热解气化产率分布,贴合生物质热解气化真实转化过程,由生物质热解气化实测数据通过遗传算法（genetic algorithm, GA）对综合计算法模型进行改进,按照综合计算法中热解段和固定碳气化反应段建立Aspen Plus模型。 结果表明：在GA-综合计算法中,稻壳在热解段CO₂的氧为干基氧含量的32.02%,焦油产率为挥发分的8.32%, 平均热解组分误差为8.53%,平均合成气组分误差为5.37%;基于GA-综合计算法的Aspen Plus模型,热解过程组分和气化段固定碳转化率由GA-综合计算法得出,实现了GA-综合计算法和流程模拟的复合, 其合成气模拟值与实验值接近,较好地反映生物质热解气化流程,为生物质热解气化产率分布及流程参数优化提供指导。     

Flash pyrolysis of cellulose pellets submitted to a concentrated radiation: experiments and modelling

The image furnace technology has been applied to the study of the first steps of biomass flash pyrolysis. The experiments performed with small pellets of cellulose show that the reaction primarily passes through the intermediate of short lifetime liquid species (ILC). The quantitative study of the variations of the sample mass loss and of the mass of ILC reveals the existence of a transient period followed by a steady-state regime resulting from an equilibrium between cellulose decomposition into ILC and ILC vaporization. A mathematical model has been solved in parallel. The results agree very well with the experimental measurements and yield additional information on the temperatures of cellulose pyrolysis and of ILC vaporization.     

The influence of temperature on the yields of compounds existing in bio-oils obtained from biomass samples via pyrolysis

The influence of temperature on the compounds existing in liquid products obtained from biomass samples via pyrolysis were examined in relation to the yield and composition of the product bio-oils. The product liquids were analysed by a gas chromatography mass spectrometry combined system. The bio-oils were composed of a range of cyclopentanone, methoxyphenol, acetic acid, methanol, acetone, furfural, phenol, formic acid, levoglucosan, guaiacol and their alkylated phenol derivatives. Thermal depolymerization and decomposition of biomass structural components, such as cellulose, hemicelluloses, lignin form liquids and gas products as well as a solid residue of charcoal. The structural components of the biomass samples mainly affect the pyrolytic degradation products. A reaction mechanism is proposed which describes a possible reaction route for the formation of the characteristic compounds found in the oils. The supercritical water extraction and liquefaction partial reactions also occur during the pyrolysis. Acetic acid is formed in the thermal decomposition of all three main components of biomass. In the pyrolysis reactions of biomass: water is formed by dehydration; acetic acid comes from the elimination of acetyl groups originally linked to the xylose unit; furfural is formed by dehydration of the xylose unit; formic acid proceeds from carboxylic groups of uronic acid; and methanol arises from methoxyl groups of uronic acid     

A molecular kinetic model for heavy gas oil catalytic pyrolysis to light olefins

Petroleum catalytic pyrolysis to light olefin technology has received wide-ranging research interest in the refining industry. This work built a molecular kinetic model for the catalytic pyrolysis of a heavy gas oil from bitumen synthetic crude oil (SCO) to light olefins. A feedstock compositional model was constructed containing 1311 molecules using bulk properties information. A variety of reaction rules was summarized and digitized, and from which, a reaction network involving 2631 substances and 6793 reactions was generated via a reaction network autogeneration algorithm. The reaction network for the catalytic pyrolysis was transformed into reaction rate equations. Systematical pilot-scale catalytic pyrolysis experiments were carried out, which were used to regress the molecular kinetic model parameters. The tuned model is able to predict the product yield and molecular distribution. Moreover, a range of sensitivity analysis was performed, revealing the dependence of light olefins yields on the reaction conditions.     

Influence of Operating Conditions for Fast Pyrolysis and Pyrolysis Oil Production in a Conical Spouted‐Bed Reactor

Fast pyrolysis experiments of larch sawdust were conducted in a conical spouted‐bed reactor to study the influences of reaction temperature, inlet gas velocity, feeding rate, and particle size on the product yield and pyrolysis oil quality. For the first time, the optimal conditions were determined for various pyrolysis operations of such reactor to increase the yield and quality of pyrolysis oil. The results demonstrate that the biomass particle size, reaction temperature, biomass feeding rate, and inlet gas velocity all affected the quality and yield of the pyrolysis oil, in this order.     

Kinetics of reactions involved in pvrolvsis of cellulose II. The modified kilzer-bioid model

At temperatures below 300°C, it has been shown that the pyrolysis of cellulose can be modeled in terms of a modified Kilzer-Broido ((K-B) Model. According to this model, cellulose decomposes via two competitive reactions, a dehydration reaction to form anhydrocellulose and a depolymerization reaction to form levoglucosan. Anhydrocellulose later decomposes to chars and gaseous products via two competitive reactions. Arrhenius parameters and a technique of estimating empirical constants from experimental data for the K-B type reactions are presented. Comparison of the ability of the modified K-B model and the three reaction model to predict weight loss, product yields and heat pretreated results are also made.     

生物质流化床快速裂解模型

研究了流化床内的生物质快速裂解模型,其特点是考虑了原料粒子在下部密相区和上部稀相区的不同反应历程.模型的计算结果表明,原料粒子和产物气体在反应器内的停留时间有较大的区别,其变化情况对裂解产物的分布有很大影响.由该模型得到的计算结果能和实验值很好吻合,表明它能较好地描述流化床反应器内生物质快速裂解的反应过程.结合计算数据对影响裂解结果的一些因素进行了分析.     

A numerical study on biomass fast pyrolysis process: A comparison between full lumped modeling and hybrid modeling combined with CFD

This study focuses on process modeling and simulation of a biomass fast pyrolysis system. For the simulation of the biomass fast pyrolysis process, two types of simulation models were developed: lumped model and hybrid model. Employing the above models, the effect of reaction temperature on reaction rate and final product yields were analyzed. It was found that the hybrid model exhibited a peculiar characteristic of displaying multiphase reacting flow occurring in fluidized bed. This behavior of hybrid model could have attributed for the difference in product yields of the models (hybrid and lumped). For the yields of the tar and NCG, hybrid model prediction was very consistent with the experimental results than the lumped model. However, for char yield, the results of both the lumped model and the hybrid model were close to that of experimental results.     

基于结构导向集总的FCC汽油催化裂解分子尺度动力学模型

利用结构导向集总模型构造烃分子和编制反应网络,并结合Monte Carlo模拟方法,建立了催化裂化（FCC）汽油催化裂解反应的分子尺度动力学模型。结构导向集总模型选用7个分子结构片段表示催化汽油中的分子,生成2000个共计92种烃类分子代表催化汽油原料组成。模型选取催化汽油中含量较多的11种单体烃作为模型化合物研究其催化裂解反应行为,并以此为依据制定反应规则,求取模型所需反应速率常数。模拟结果表明,应用结构导向集总模型和Monte Carlo模拟方法进行催化裂解分子尺度动力学建模是可行的,能对多种反应产物的产率进行预测。模拟值和实验结果符合良好,相对误差基本在10%以内。模型对延长反应时间后的产品收率有一定的预测能力。     

A practical approach for modelling and control of biomass pyrolysis pilot plant with heat recovery from combustion of pyrolysis products

A pilot plant of biomass pyrolysis using pyrolysis products as fuel has been tested and shown to improve energy balance of the process and to be environmentally friendly by avoiding rejection of pyrolysis pollutants fumes into the atmosphere. The high number of parameters involved in a pyrolysis process makes it difficult to specify an optimum procedure for charcoal yield and pyrolysis cycle durability. So the knowledge of the essential parameters which govern the kinetics mechanisms of the biomass thermal decomposition and the combustion of pyrolysis gases is very useful to understand the operating cycle of the plant. In the present study a thermochemical model is developed in order to simulate and control the operating cycle of the system. The effect of the inlet molar air flow rate on the temporal evolution of biomass mass loss rate and temperatures in the different active zones of the pilot plant as well as the determination of the critical inlet molar air flow rate for which accidental runaway of combustion reactions occurs are presented. To avoid this accidental phenomenon a Proportional-Integral-Derived (PID) anticipated regulation is used in order to control temperatures evolution in the different zones of the device and avoid the runaway of combustion reactions.     

生物质快速热解制油试验及流程模拟

使用自主研发的流化床热解反应器对生物质热解制油进行实验研究,通过对不同实验温度450、500、525、550、580、610℃下得到的目标产物进行分析,得到了反应温度对生物油产率的影响规律。实验表明：550℃时,最大液体产率为42.5%（质量）;实验得到的不可冷凝气体的组分以CO、CO₂、CH₄和H₂为主,气相产物产率约为37.7%（质量）。在实验基础上,利用Aspen Plus流程模拟软件,建立了生物质热解制油工艺模拟流程,模拟分析了热解温度对生物油产率的影响,结果表明该模型能准确模拟实际热解过程,具有较好的适用性和可靠性。     

蒙脱石的催化生物质热解特性

以纤维素和橡树叶为研究对象,探索了蒙脱石催化作用下热解产物的变化规律及机理.结果表明:蒙脱石负载促进纤维素向β-消除路径转化,导致活化能增加、DTG(微商热重分析曲线)峰值温度升高和热解速率降低,而对橡树叶的热解过程影响较小;蒙脱石可催化热解液体的2次裂解,使液体产率降低,气体产率增加,而对固体产物产率的影响较小,其中...     

Prediction of bio-oil yield during pyrolysis of lignocellulosic biomass using machine learning algorithms

This work aims to implement and use machine learning algorithms to predict the yield of bio-oil during the pyrolysis of lignocellulosic biomass based on the physicochemical properties and composition of the biomass feed and pyrolysis conditions. The biomass pyrolysis process is influenced by different process parameters, such as pyrolysis temperature, heating rate, composition of biomass, and purge gas flow rate. The inter-relation between the yield of different pyrolysis products and process parameters can be well predicted by using different machine learning algorithms. In this study, different machine learning algorithms, namely, multi-linear regression, gradient boosting, random forest, and decision tree, have been trained on the dataset and the models are compared to identify the optimum method for the determination of bio-oil yield prediction model. Analysis of the results showed the gradient boosting method to possess a regression score of 0.97 and 0.89 for the training and testing sets with root-mean-squared error (RMSE) values of 1.19 and 2.39, respectively, and overcome the problem of overfitting. Therefore, the present study provides an approach to train a generalized machine learning model, which can be employed on large datasets while avoiding the error of overfitting.