Resolution of structure characteristics of AE signals in multiphase flow system—From data to information

This investigation was performed to study the underlying structure characteristics of acoustic emission (AE) signals, which could be helpful not only to understand a relatively complete picture of hydrodynamics in multiphase flow systems, but also to extract the most useful information from the original signals with respect to a particular measurement requirement. However, due to AE signals are made up of emission from many acoustic sources at different scales, the resolution of AE signals is often very complicated and appears to be relatively poorly researched. In this study, the structure characteristics of AE signals measured both in gas–solid fluidized bed and liquid–solid stirred tank were researched in detail by resorting to wavelet transform and rescaled range analysis. A general criterion was proposed to resolve AE signals into three physical‐related characteristic scales, i.e., microscale, mesoscale, and macroscale. Multiscale resolution of AE signals implied that AE signals in microscale represented totally the dynamics of solid phase and could be applied to measure particle‐related properties. Furthermore, based on the structure characteristics of AE signals, useful features related to particles motion were extracted to establish two new prediction models, one for on‐line measurements of particle size distribution (PSD) and average particle size in gas–solid fluidized bed and the other for on‐line measurement of the suspension height in liquid–solid stirred tank. The prediction results indicated that (1) measurements of PSD and average particle size using AE method showed a fairly good agreement with that using sieve method both for laboratory scale and plant scale fluidized beds, and (2) measurements of the suspension height using AE method showed a fairly good agreement with that using visual method. The results thus validated that the extracted features based on analyses of structure characteristics of AE signals were very useful for establishing effective on‐line measurement models with respect to some particular applications. © 2009 American Institute of Chemical Engineers AIChE J, 2009     

声波多尺度分析方法在流化床平均粒径检测上的应用

平均粒径是流化床聚合工艺的重要参数,亟需在环保安全、不侵入流场的条件下,快速准确地检测.流化床声信号与平均粒径相关,可对其进行小波(包)分析,提取尺度和频度特征,构建能量模式,用于粒径判别,其判别能力与尺度相关.可选定适当的尺度,采用特征筛选和Bayes方法建立判别模型,预报性能优良,计算量甚小,适于在线检测.用于聚乙烯实例,效果令人满意.     

Non‐intrusive characterization of particle size changes in fluidized beds using recurrence plots

An on‐line method is developed for monitoring of mean particle size in fluidized beds using pressure fluctuations (PFs) and acoustic emissions (AE) signal by recurrence plot (RP) and recurrence quantification analysis (RQA). PFs and AE signals of a lab‐scale fluidized bed were measured simultaneously at various superficial gas velocities and mean particle sizes. Although the AE signals are often very complicated due to many different acoustic sources in the bed, applying RP analyses showed that small changes in mean particle size can be detected by visual comparison of AE‐RP structures, while this cannot be distinguished by graphical RP analysis of PFs. Moreover, the hydrodynamics of the bed was inspected through RQA analysis of both signals. For this purpose, recurrence rate, determinism, laminarity, average length of diagonal and vertical lines were extracted from RPs showing the effect of an increase in the mean particle size. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3547–3561, 2016     

A CFD‐PBM‐PMLM integrated model for the gas–solid flow fields in fluidized bed polymerization reactors

Although the use of computational fluid dynamics (CFD) model coupled with population balance (CFD‐PBM) is becoming a common approach for simulating gas–solid flows in polydisperse fluidized bed polymerization reactors, a number of issues still remain. One major issue is the absence of modeling the growth of a single polymeric particle. In this work a polymeric multilayer model (PMLM) was applied to describe the growth of a single particle under the intraparticle transfer limitations. The PMLM was solved together with a PBM (i.e. PBM‐PMLM) to predict the dynamic evolution of particle size distribution (PSD). In addition, a CFD model based on the Eulerian‐Eulerian two‐fluid model, coupled with PBM‐PMLM (CFD‐PBM‐PMLM), has been implemented to describe the gas–solid flow field in fluidized bed polymerization reactors. The CFD‐PBM‐PMLM model has been validated by comparing simulation results with some classical experimental data. Five cases including fluid dynamics coupled purely continuous PSD, pure particle growth, pure particle aggregation, pure particle breakage, and flow dynamics coupled with all the above factors were carried out to examine the model. The results showed that the CFD‐PBM‐PMLM model describes well the behavior of the gas–solid flow fields in polydisperse fluidized bed polymerization reactors. The results also showed that the intraparticle mass transfer limitation is an important factor in affecting the reactor flow fields. © 2011 American Institute of Chemical Engineers AIChE J, 58: 1717–1732, 2012     

Characterization of flow regime transition and particle motion using acoustic emission measurement in a gas‐solid fluidized bed

Particle motion is a major determinant of the dynamical performance of a fluidized bed. It plays an important role in determining and optimizing the complex correlation of fluidization condition between particle‐particle and particle‐environment in a system. A passive acoustic emission (AE) technique is applied to monitor, characterize, and control the fluidization condition of polyethylene particles in a gas‐solid fluidized bed. Experimental results show that AE signals are very sensitive to the particle movements by analyzing energy distribution, which can help to understand the status of the system. The AE energy temporal analysis is further used to identify the transition of flow regimes. Moreover, the activity of particle motion can be quantitatively determined by using a combination of granular temperature and AE spatial energy analysis. This work provides valuable insights into the dynamic behavior of particles in a gas‐solid fluidized bed based on AE technique. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

Monitoring the fluidized bed reactor for polyethylene polymerization based on fibre optic acoustic emission sensor

This paper presents applications of a new class of fibre optic acoustic emission (FOAE) sensor to monitor the operation of fluidized bed reactors used in polyethylene production. Specifically, the sensor was implemented to detect undesired, abnormal phenomena related to particle agglomeration, wall sheeting, fine overflow, and variations in the superficial gas velocity. The experiments were executed using a fluidized bed cold model setup for polyethylene powders with average particle sizes of 250, 1000, and 2000 μm. The results demonstrated that the presence of agglomerated particles in the fluidized bed reactor increases the kurtosis of the acoustic emission (AE) signal. Furthermore, the overflow of small particles can be detected by mounting the FOAE sensor below the gas distributor plate and monitoring an increase in the root mean square (RMS) of the AE signal. The AE signal RMS increased with the rising superficial gas velocity. Besides, forming a sheet layer on the reactor wall decreased the AE signal RMS. The proposed sensor's main benefits are its simple design, rapid response to abnormal conditions in the fluidized bed reactor, immunity against electromagnetic noise, high-temperature resistance, and safety in hazardous areas.     

基于小波包分析和K-OPLS的集成方法在颗粒粒径分布检测中的应用

颗粒粒径分布的实时在线检测对于调控气固流化床中颗粒的流化特性具有重要意义。基于混料均匀设计法安排实验,以声发射(AE)技术为检测手段,结合小波包分析,提出采用K-OPLS方法构建颗粒粒径分布的声信号预测模型,定量描述小波包能量特征与颗粒粒径分布的非线性变化规律。实验结果显示,留一交叉验证法的均方根误差(RMSE)仅为0.063,表明基于K-OPLS的颗粒粒径分布声信号预测模型能准确测量气固流化床中颗粒的粒径分布,具有良好的工业应用前景。     

气固流化床中声发生机理及在工业装置中的应用

利用声测量技术,结合频谱分析,建立了颗粒碰撞的声波频率模型,可定量描述声波主频随颗粒粒径、弹性模量和密度的变化规律.通过改变流化颗粒的粒径、弹性模量参数和密度,发现声波主频与频率模型计算值之间的最大偏差为8.3%,说明声波主频可以代表颗粒在壁面的碰撞频率.讨论了热态和冷态条件下声波主频之间变化规律,通过对弹性模量参数的校正,声测量技术可以用于预测工业装置中物料的平均粒径变化,并将该模型应用于线性低密度聚乙烯、高密度聚乙烯和双峰聚乙烯工业生产装置中的平均粒径测量,发现与传统的取样筛分方法所得测量结果十分接近.同时,发现当系统产生聚合物颗粒结块时,声波主频将急剧降低,声波频谱的能量分布将明显集中增大,这可作为判断流化床稳定运行的一个判据.     

CFD simulation and experiments of dynamic parameters in gas–solid fluidized bed

Particle and bubble motion plays an important role in determining the hydrodynamic characteristics of a fluidized system. The dynamic parameters of a fluidized bed are reflection of the complex correlation between particle–particle and particle–bubble in a system. A two-dimensional Eulerian–Eulerian model integrating the kinetic theory of granular flow is used to simulate the bubble and linear low density polyethylene (LLDPE) particle dynamic behavior in a gas–solid fluidized bed. The simulated method is validated by pressure fluctuation experiment. The computed vertical turbulent energy spectrum of particles is applied to identify the particle motion intensity and the inhomogeneity of turbulent energy dissipation. The energy spectrum captures the Levy–Kolmogorov law in inertial range at high frequency. Furthermore, the flatness factors of wavelet decomposition coefficients of particle fluctuation velocity are for the first time introduced to analyze the intermittence caused by coherent structures in the flow field. The results show that the intermittence in dissipation range is much stronger than that in energy-containing and inertial range, and reinforces rapidly as the radial distance and the bed height increase. Moreover, the acoustic emission (AE) energy is found to be able to indicate the flow regimes. By combing granular temperature and AE energy, the relationship between the spatial distribution of granular temperature and the flow regimes is established. To get more detail of bubble motion behavior, the power spectrum of voidage fluctuation is analyzed. This work provides valuable insights into the dynamic characteristics and the flow field information of a gas–solid fluidized bed by CFD simulation.     

A computational model for predicting particle size distribution and performance of fluidized bed polypropylene reactor

Gas phase polymerization of propylene is one of the most widely accepted and commercially used processes for manufacturing of polypropylene. The present work describes a comprehensive mathematical model for simulating fluidized bed polypropylene reactors. Unlike previously published models, the present model simultaneously predicts both polymer properties as well as particle size distribution. A generalized framework of a dynamic model based on mixing cell approach and detailed polymerization kinetics coupled with population balance model for particle size distribution (PSD) is developed. Need for coupling the reaction engineering model with population balance models is demonstrated. The coupled model was then used to understand influence of operating parameters on polymer properties and particle size distribution. The model is also used to understand the effects of multiple active sites and reaction kinetics on macroscopic variables. The developed framework is useful for simulating multi-monomer, multi-site Ziegler-Natta type olefin fluidized bed polymerization reactors.     

烯烃聚合流化床反应器内动结块的声发射检测

烯烃聚合流化床反应器近分布板区域的动结块是分布板堵塞的诱因,严重影响流化床的正常操作,甚至引发事故。本文在冷模实验装置中,使用声发射技术对近分布板区域的动结块进行检测,分别对比了正常流化、加入丝状结块和加入块状结块时近分布板区域声信号能量和频谱的差异。实验发现,与正常流化时相比,加入结块使得声信号能量下降,且加入块状结块时声信号能量下降更为显著;加入结块后声信号频谱的低频部分（0~20 kHz）和高频部分（70~150 kHz）均出现不同程度的降低,且高频部分下降比低频部分更为显著,块状结块导致的下降比丝状结块更为显著。实验结果表明,声发射技术可以用于流化床反应器内近分布板区域动结块的检测。     

基于数据驱动的卷积神经网络电容层析成像图像重建

针对电容层析成像技术的图像重建问题,提出了基于数据驱动的卷积神经网络图像重建方法。根据气固两相流的流型特点,通过数值模拟的方法随机生成了60000组介质分布图像,并利用有限元法计算了与之对应的电容向量,从而建立了一个“电容向量-介质分布”数据集;然后根据电容层析成像图像重建特点建立了卷积神经网络模型,对数据集中的训练集进行学习和训练,并利用测试集对训练结果进行了验证与评价。在此基础上,对获得的ECT图像重建卷积神经网络模型进行了静态实验和流化床测试实验研究。模拟和实验结果表明：所建立的卷积神经网络能较好地实现ECT图像重建,可直接用于流化床内的颗粒浓度分布测量。     

Identification of thermal zones and population balance modelling of fluidized bed spray granulation

Air temperature measurements in a fluidized bed of glass beads top sprayed with water showed that conditions for particles growth were fulfilled only in the cold wetting zone under the nozzle which size and shape depended on operating conditions (liquid spray rate, nozzle air pressure, air temperature, and particles load). Evolution of the particle size distribution during agglomeration was modelled using population balance and representing the fluidized bed as two perfectly mixed reactors exchanging particles with particle growth only in the one corresponding to the wetting zone. The model was applied to the agglomeration of non-soluble glass beads and soluble maltodextrin particles spraying respectively an acacia gum solution (binder) and water. Among the three adjustable parameters, identified from experimental particle size distributions evolution during glass beads agglomeration, only one describing the kinetics of the size distribution evolution depended on process variables. The model allowed satisfying simulation of the evolution of the particle size distribution during maltodextrin agglomeration.     

A fundamental CFD study of the gas–solid flow field in fluidized bed polymerization reactors

A Eulerian–Eulerian model incorporating the kinetic theory of granular flow was applied to describe the gas–solid two-phase flow in fluidized bed polymerization reactors. The model parameters were examined, and the model was validated by comparing the simulation result with the classical calculated data. The effects of distributor shape, solid particle size, operational gas velocity and feed manner on the flow behavior in the reactor were also investigated numerically. The results show that with the increase of solid particle diameter, the bubble numbers decrease and the bubble size increases, resulting in a smaller bed expansion ratio. Bed expansion ratio increases with increasing the gas inlet velocity. Moreover, the final fluidized qualities are almost the same for the plane distributor case and the triangle distributor case. There exists a tempestuous wiggle from side to side in the bed at the continuous feed manner, which could not be obtained at a batch feed manner.     

Experimental profiles of lateral mixing of feed particles in a three‐dimensional fluidized bed

Solids mixing data of high quality is one of the most crucial steps for quantitative studies, but it is a difficult task to obtain in a fluidized bed especially with a 3D configuration. Therefore a novel sampling technique is developed with bed collapse method, for measuring lateral mixing of feed particles in a 3D fluidized bed. The sampling tool is designed using a “bottom‐to‐top sampling” idea. Its development, configuration and measurement repetition are discussed in detail. The effects of mixing time, fluidizing gas velocity, and particle size of bed material on the tracer distribution are investigated. A quantitative comparison of lateral dispersion coefficient shows that our results agree fairly well with measurements and predictions of correlations for lab‐scale fluidized systems in previous studies. The presented 2D profiles of the lateral mixing can be used to validate fundamental solids mixing models or verifying convenient measurement techniques. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

Demarcation of a new circulating turbulent fluidization regime

Transient flow behaviors in a novel circulating‐turbulent fluidized bed (C‐TFB) were investigated by a multifunctional optical fiber probe, that is capable of simultaneously measuring instantaneous local solids‐volume concentration, velocity and flux in gas‐solid two‐phase suspensions. Microflow behavior distinctions between the gas‐solid suspensions in a turbulent fluidized bed (TFB), conventional circulating fluidized bed (CFB), the bottom region of high‐density circulating fluidized bed (HDCFB), and the newly designed C‐TFB were also intensively studied. The experimental results show that particle‐particle interactions (collisions) dominate the motion of particles in the C‐TFB and TFB, totally different from the interaction mechanism between the gas and solid phases in the conventional CFB and the HDCFB, where the movements of particles are mainly controlled by the gas‐particle interactions (drag forces). In addition, turbulence intensity and frequency in the C‐TFB are significantly greater than those in the TFB at the same superficial gas velocity. As a result, the circulating‐turbulent fluidization is identified as a new flow regime, independent of turbulent fluidization, fast fluidization and dense suspension upflow. The gas‐solid flow in the C‐TFB has its inherent hydrodynamic characteristics, different from those in TFB, CFB and HDCFB reactors. © 2009 American Institute of Chemical Engineers AIChE J, 2009     

Monte Carlo modeling of fluidized bed coating and layering processes

A stochastic modeling approach based on a Monte Carlo method for fluidized bed layering and coating is presented. In this method, the process is described by droplet deposition on the particle surface, droplet drying and the formation of a solid layer due to drying. The model is able to provide information about the coating coverage (fraction of the particle surface covered with coating), the particle‐size distribution, and the layer thickness distribution of single particles. Analytical solutions for simplified test cases are used to validate the model theoretically. The simulation results are compared with experimental data on particle‐size distributions and layer thickness distributions of single particles coated in a lab‐scale fluidized bed. Good agreement between the simulation results and the measured data is observed. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2670–2680, 2016     

Discrete particle simulations of an electric-field enhanced fluidized bed

Reducing the size of gas bubbles can significantly improve the performance of gas-solid fluidized reactors. However, such a control of bubbles is difficult to realize without measures that either use a lot of energy or deteriorate the fluidization behavior. In this paper, we present the results of discrete particle simulations of an electric-field enhanced fluidized bed, and compare these results to experimental data.The simulations show a significant effect on the size of bubbles, both with horizontal and vertical electric-fields applied. When the field strength is increased to values higher than those used in the experiments, the particles are found to form strings in the direction of the electric field. At very high field strengths, defluidization is observed, consistent with the experiments.Through the analysis of the bubble behavior, it is concluded that moderate strength electric fields distribute gas more evenly at the bottom of the bed. As the bubbles rise through the bed, the coalescence rate is lower because of the guiding paths, or resistance, the particles form due to the field. This results in a smaller average bubble size in the higher region of the bed. The simulations presented here show how and why the electric fields reduce bubble size in electric-field enhanced fluidized beds.     

The Bed Expansion and Particle Velocity Analysis in the Swirling Fluidized Bed Combustor (SFBC) Cold Model

Flow visualization and analysis was extensively conducted in a bench‐scale swirling fluidized bed combustor (SFBC) cold model. An advanced laser‐based particle image velocimetry (PIV) system was used to visualize the gas‐particle flow in SFBC cold model. The robust experiment design method was applied to study the bed expansion in the SFBC cold model in relationship with secondary airflow ratio. It was found that the secondary airflow ratio did not affect the bed expansion in the SFBC cold model. Based on the PIV velocity profiles analysis, it was observed that particle velocities increased when secondary airflow ratio is increased. The secondary air was definitely generating the high tangential particle velocity.     

Method to estimate uncertainty associated with parcel size in coarse discrete particle simulation

Coarse grained particle methods significantly reduce the computation cost of large‐scale fluidized bed simulation by lumping many real particles into a computation parcel. This research provides a method to estimate the errors associated with parcel size in large‐scale fluidized bed simulations. This uncertainty is first quantified in small scale domains by comparing results of discrete particle method with that employing coarse parcels of different sizes. Then, this uncertainty is correlated with parcel size and simulation domains consisting of a simple homogeneous cooling system and more complex bubbling and circulating fluidized beds. These correlations allow us to accurately estimate the uncertainty in large‐scale fluidized beds based solely on data obtained in smaller systems. The ability to estimate model‐related uncertainty in larger systems makes this method relevant for industrial applications. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2340–2350, 2018