A mathematical model of fluidized bed biomass gasification

A mathematical model of biomass gasification in a fluidized bed has been developed. It considers axial variations of concentrations and temperature in the bubble and emulsion phases. The mass balance involves instantaneous oxidation and equilibrium devolatilization of the biomass, kinetics of solid-gas gasification reactions as well as of gaseous phase reactions and interphase mass transfer and gas convection. The energy balance is solved locally for each vertical volume element, and globally on the reactor by iteration on the temperature at the bottom of the bed. Three parameters have been adjusted based on the experimental results: the heat transfer coefficient at the wall, the weighting of the kinetics of the water-gas shift reaction and the fraction of biomass carbon remaining as char after devolatilization. The model is used to simulate a pilot scale (50 kg/h) biomass gasifier, and its predictions compared to experimental measurements. The temperature and gaseous concentrations are estimated with good accuracy for the experiments using a wood feedstock, except for the concentration of hydrogen which is overestimated.     

Characterization of the devolatilization rate of solid fuels in fluidized beds by time‐resolved pressure measurements

The characterization of volatile matter (VM) release from solid fuel particles during fluidized‐bed combustion/gasification is relevant to the assessment of the reactor performance, as devolatilization rate affects in‐bed axial fuel segregation and VM distribution across the reactor. An experimental technique for the characterization of the devolatilization rate of solid fuels in fluidized beds is proposed. It is based on the analysis of the time series of pressure measured in a bench‐scale fluidized‐bed reactor as VM is released from a batch of fuel particles. A remarkable feature of the technique is the possibility to follow fast devolatilization with excellent time‐resolution. A mathematical model of the experiment has been developed to determine the time‐resolved devolatilization rate, the devolatilization time and the volume‐based mean molecular weight of the emitted volatile compounds. Devolatilization kinetics has been characterized for different solid fuels over a broad range of particle sizes. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

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.     

Numerical simulation of 3D fluidized bed biomass gasification based on CPFD

Based on computational particle fluid dynamics (CPFD), a three-dimensional bubbling fluidized bed steam-air mixed gasification numerical model was established, and it was verified with experiment trials. The results show that the simulation and experiment have good consistency. Based on the model, the gas distribution and temperature distribution in the gasifier were studied; meanwhile, the biomass properties (particle size, water content, types) and operating conditions (gasification temperature, bed height) were investigated. The results show that there is an optimal value for the impact of biomass particle size on gasification performance, with an average particle size of 0.6 mm being the best; a higher water content will reduce the output of combustible gas and is not conducive to the gasification reaction. Among the four types of biomass, sawdust gasification has the highest efficiency, the largest combustible gas production, and the highest gas calorific value. Rice husk is second only to sawdust but its carbon conversion rate is higher than that of sawdust; increasing the gasification temperature can increase the proportion of combustible gas and increase gasification efficiency; while the change of initial bed height can change the ratio of H₂/CO. This experiment provides a theoretical reference for biomass steam/air gasification, which is helpful for the selection and processing of biomass raw materials, and also facilitates the amplification and optimization of the gasifier.     

基于CPFD方法的流化床生物质气化数值模拟

基于计算颗粒流体动力学（CPFD）建立了三维鼓泡流化床水蒸气-空气混合气化的数值模型,并进行了模型验证,结果表明模拟和实验具有良好的一致性。在该模型的基础上,研究了气化炉内气体分布以及温度分布;同时探究了生物质属性（颗粒粒径、含水率、种类）以及操作条件（气化温度、床料高度）对气化特性的影响。结果表明,生物质颗粒粒径对气化性能的影响存在一个最优值,平均粒径为0.6 mm是最佳的;较高的含水率会降低可燃气体产量,不利于气化反应的进行;四种生物质中,锯末气化的效率最高、可燃气体产量最大、气体热值最高,稻壳仅次于锯末但其碳转化率高于锯末;提高气化温度可以增加可燃气体的比例、提高气化效率;而初始床层高度的变化可以改变H₂/CO的比例。本实验为生物质水蒸气/空气气化提供了理论参考,有助于生物质原料的选取和处理,也有助于气化炉的放大和优化。     

生物质快速热解流化床反应器气力进料特性

为探究不同工况下热解流化床反应器的气力进料特性,设计并搭建了流化床反应器气力进料冷态试验装置。生物质原料和床料分别采用落叶松颗粒和石英砂颗粒,通过试验测得了本装置的最小流化速度,研究了流化气速、喷动气速、流量比、初始静床高、石英砂粒径、落叶松粒径对流化床反应器气力进料特性的影响。试验结果表明：流化气速和喷动气速的增加均会提高进料率;流化气使床料流化并为落叶松颗粒提供进料空间,喷动气为落叶松颗粒提供动能,并平衡一部分床层压力;落叶松与石英砂粒径的增加对进料效果不利;流量比在1.9~2.7范围内进料率高且稳定性好。本文构建了生物质、床料与气体的三相流物理及数学模型,开展试验对模型进行验证,结果表明其预测误差为±13%。     

国内外生物质气化设备研究进展

生物质是重要的可再生能源,生物质气化技术在国内外得到了广泛应用。本文综述了国内外固定床、鼓泡流化床、外循环流化床、内循环流化床、双循环流化床的结构。固定床安装简单,但焦油较多;外循环流化床燃烧效率高,但回料装置较难控制;内循环流化床不易结焦、氢含量高且不用考虑返料问题;双流化床结构复杂但焦油量少。将对固定床和流化床进行对比,认为固定床安装简单适合农村地区,流化床应不断改进和完善,更适应工业化生产。     

Devolatilization of large coal particles in fluidized beds

Analysis of devolatilization of predried large coal particles in fluidized beds requires consideration of both the chemical kinetics of coal decomposition and transport processes. Models available either assume the devolatilization particle to be isothermal (whereas it may be shown that, in general, large temperature gradients may exist within the particle) or require extensive numerical integration procedures. This Paper describes a model which permits formulation of analytical and easy-to-use equations for the estimation of the devolatilization history of a large predried coal particle in a fluidized bed. The model predictions are compared with experimental data collected for Mississippi lignite. A correlation is proposed for the estimation of the total devolatilization time. The analytical solutions presented may be used with ease in coupling the devolatilization process to the other phenomena, such as drying and/or combustion of volatiles and residual char, occuring during fluidized bed combustion of coal.     

Agglomeration of biomass fired fluidized bed gasifier and combustor

Agglomeration is a major problem in biomass fired fluidized bed combustors and gasifiers. Mechanism, reduction options and detection techniques of agglomeration are reviewed. Agglomeration may be classified broadly into three types: defluidization induced agglomeration, melt‐induced agglomeration and coating‐induced agglomeration. Sodium and potassium content of the biomass are the major contributors to the agglomeration in biomass fired fluidized beds. Higher temperature, lower fluidizing velocity and coarser bed particles also increase the risk of agglomeration. Alternative bed materials, additives or the co‐combustion of biomass with other fuels can reduce agglomeration potential of a fluidized bed. Two agglomeration detection techniques are discussed: controlled fluidized bed agglomeration and early agglomeration recognition system.     

磁流化床稳定性分析

应用Foscolo的颗粒床模型分析了磁流化床稳定性,得到了磁流化床的稳定判据;根据得到的判据分别对层流和湍流情况分析了磁场对磁流化床稳定性的影响。     

基于Fluent软件的生物质气化模拟研究

基于Fluent软件,建立流化床反应器模型,对生物质-水蒸气气化过程进行模拟,研究温度对生物质气化过程的影响,同时分析碳转化率、气体成分以及气体总产率的变化规律。结果表明:模拟结果与实验数据吻合良好,碳转化率及气体总产率随温度的升高而升高,床层高度对CO、 H₂生成具有较大影响。模拟计算条件下,氢气体积分数高达55%,这说明水蒸气作为气化介质有利于气化过程中产生更多的H₂。Fluent软件能够很好的对生物质气化过程进行模拟,可以作为生物质气化研究的一个重要工具。     

流化床粉煤气体热载体快速热解反应器的计算

在冷态模拟实验和煤热解动力学计算的基础上,对粉煤气体热载体快速热解提升管反应器的高度进行了计算。利用高速摄像粒子测速法结合互相关算法研究了不同气体流量和不同颗粒粒径时固体颗粒在热解提升管中的运动速度,通过求解神府煤热解动力学方程,得到了不同粒径神府煤颗粒热解挥发分析出的时间,从而确定了快速热解提升管反应器的高度。研究结果表明:当气体流量在850 m3/h,粉煤的粒径主要集中在0.7—3.0 mm时,提升管的高度应选择在10.0 m。     

Devolatilization and combustion of large coal particles in a fluidized bed

Devolatilization and combustion of large particles of Eastern Canadian coals (Evans and Minto), 5-50 mm dia., were studied in a bench-scale atmospheric fluidized bed reactor at 1023-1173 K with 0.5 mm sand particles as the bed material. The devolatilization time, mass loss history, changes in proximate volatiles content and C/H mass ratio, and temperature history at the centre of the particle during devolatilization were determined. The mass loss during devolatilization is correlated with the proximate volatiles content of the parent coal. The devolatilization time is correlated with the initial particle diameter by a power-law relation with an exponent of 1.54-1.64. The results show insignificant effect of superficial velocity on devolatilization.     

生物质流化床空气-水蒸气气化模型研究

根据流化床反应器特点,结合生物质气化动力学反应机理,建立了生物质在流化床内气化的等温稳态、一维二相动力学模型。该模型所做的主要假定如下:流化床分为气泡相和乳相,在气泡相和乳相内均存在化学反应,考虑二相内的轴向气体扩散,生物质热解过程瞬时完成,主要考虑焦碳以及CO,CO2,H2,H2O,CH4等在流化床内发生的8个主要化学反应。数学模型属于常微分方程组边值问题,利用数值计算软件M atlab7.0进行编程求解。以木粉为原料,将模型结果与实验结果进行了对比,模拟结果与试验数据符合良好,在一定程度上证明了模型的有效性和可靠性。     

双流化床生物质气化炉研究进展

生物质是重要的清洁可再生能源,双流化床生物质气化技术是将低品位的生物质能转化成高品位氢能的重要途径。本文阐明了双流化床气化过程的基本原理,从燃气中氢气浓度、焦油含量和装置热效率等角度,介绍了双流化床生物质气化技术的早期探索和发展现状,对目前几种典型双流化床生物质气化炉的炉型设计及相关试验研究进行了分析和总结。指出内循环双流化床气化炉结构虽然简单紧凑,但是难以避免气化室和燃烧室之间的气体串混问题;而外循环流化床通过外置返料器很好地解决了气体串混问题。分析了不同气化室优化设计方案对提升燃气品质的理论依据及其优缺点。最后对双流化床生物质气化技术的发展进行了总结和展望,指出双流化床生物质气化制氢具有非常广阔的工业化应用和发展前景。     

Modelling fast pyrolysis of biomass in a fluidized bed reactor

A compartmental one-dimensional model of a fluidized bed pyrolytic converter of biomass is presented. Reference conditions are those of non-catalytic fast pyrolysis of biomass in a shallow fluidized bed with external regeneration of the bed material. The fate of biomass and of the resulting char has been modelled by considering elutriation of biomass and char particles, char attrition as well as bed drain/regeneration. The course of primary and secondary pyrolitic reactions is modelled according to a semi-lumped reaction network using well-established kinetic parameters taken from the literature. A specific focus of the present study is the role of the heterogeneous volatile–char secondary reactions, whose rate has been modelled by borrowing a kinetic expression from the neighbouring area of tar adsorption/decomposition over char. The results of computations highlight the relevance of heterogeneous volatile–char secondary reactions and of the closely associated control of char loading in the bed. The sensitivity of the reactor performance to char elutriation and attrition, to proper management of bed drain/regeneration, and to control of gas phase backmixing is demonstrated. Model results provide useful guidelines for optimal design and control of fluidized bed pyrolyzers and pinpoint future research priorities.     

Release of volatiles from large coal particles in a hot fluidized bed

Coal particles with diameters of 3–11 mm were injected into a small, hot bed of sand fluidized by nitrogen. Volatiles evolution was followed by sampling the exit gas stream and subsequent analysis by gas chromatography. Three Australian coals covering a range of volatile matter were studied and the effects of coal particle size and bed temperature were determined. The yields of gaseous components, char and tar are explained by consideration of the competitive reactions for coal hydrogen and oxygen and secondary reactions of the volatile species within the coal particle. The pore structure developed during devolatilization has a significant effect on the extent of these secondary reactions. It is concluded that heat transfer is the main process controlling the volatilization time in fluidized bed combustors. The time required for heat transfer into the coal particle, determined by calculation and experiment, agrees with the measured volatilization time. Significant factors are external heat transfer to the surface of the particle, internal conduction through the coal substance and radiation through the pores, and the counterflow of volatiles out of the coal particle. For different coals, variations in the volatilization time appear to be caused by the development of different pore structures, which affect radiant heat transfer through the pores.     

Modeling the thermochemical degradation of biomass inside a fast pyrolysis fluidized bed reactor

A fast pyrolysis process in a bubbling fluidized bed has been modeled, thoroughly reproduced and scrutinized with the help of a combined Eulerian/Lagrangian simulation method. The 3‐D model is compared to experimental results from a 100 g/h bubbling fluidized bed pyrolyzer including such variables as particle composition at the outlet and gas/vapor/water yields as a function of fluidization conditions, biomass moisture concentrations, and bed temperatures. Multiprocessor simulations on a high‐end computer have been carried out to enable the tracking of each of the 0.8 million individual discrete sand and biomass particles, making it possible to look at accurate and detailed multiscale information (i.e., any desired particle property, trajectory, particle interaction) over the entire particle life time. The overall thermochemical degradation process of biomass is influenced by local flow and particle properties and, therefore, accurate and detailed modeling reveals unprecedented insight into such complex processes. It has been found, that the superficial fluidization velocity is important while the particle moisture content is less significant for the final bio‐oil yield. © 2011 American Institute of Chemical Engineers AIChE J, 58: 3030–3042, 2012     

Simplified model for calculation of devolatilization in fluidized beds

A devolatilization model based on simplification of the earlier model has been developed for fluidized bed conditions. It is simple and computationally fast enough to be incorporated as a submodel into a CFD code, but accurate enough to be suitable for different fuels including biomass with varying particle size, moisture, reactivity and shape. In this new model, the partial differential equation describing heat and mass transfer inside the particle is approximately converted to two differential equations. Drying is described to take place on a shrinking core and pyrolysis, which can take place simultaneously with drying, is described to take place at a specific “characteristic pyrolysis temperature”. The dependence of this temperature on parameters for the kinetics of pyrolysis, bed temperature and particle size can be determined. The model can be extended to include the case, where pyrolysis is considered to consist of parallel reactions of different components.     

基于LSTM神经网络的流化床干燥器内生物质颗粒湿度预测

生物质作为一种储量丰富、环境友好且易于获取的可再生能源,日渐成为能源研究利用领域的热点。生物质湿度是影响生物质利用效率的关键因素,因此干燥是生物质利用之前的必要步骤。流化床由于其良好的传热传质特性,在干燥过程中得到了广泛的应用。为了实时监测生物质颗粒的干燥过程,利用弧形静电传感器阵列,结合用于时间序列建模的长短期记忆（LSTM）神经网络,实现了流化床干燥器内生物质颗粒湿度的预测。在实验室规模的流化床干燥器上进行了多工况实验获取训练和测试数据,通过模型参数优化确定了LSTM模型。通过与标准循环神经网络（RNN）模型的预测结果的对比表明,LSTM神经网络模型的平均相对误差较小,能够较为准确地预测流化床干燥器内生物质颗粒的湿度。