物流分布对板翅式制氢反应器性能的影响

建立了板翅式制氢反应器中的三维数学模型,并采用此模型对反应器内部的温度分布进行了数值计算,并且和实验结果相结合,对不同方式的燃烧气流分布的效果进行分析。计算和分析结果均表明:燃烧气流分布均匀与否对反应器性能的影响较大,通过改进气体分布可以有效地改善反应器内部的温度分布及反应性能。     

数字成像颗粒分析仪在聚乙烯粉料测试中的应用

采用CAMSIZER数字成像颗粒分析仪对聚乙烯粉料样品的粒度分布进行了测试,考察了测试结果的重复性,并对该仪器在粒度分布测试同时获得颗粒球形度数据和颗粒照片的功能进行了验证。结果表明,粒度分布测试自动化程度高,结果重复性较好,与筛分法比较,工作量大大降低,但测试速度有待提高;在进行粒度分布测试的同时,可获得颗粒的球形度数据和颗粒投影照片。     

喷嘴入口位置对气化炉流场影响的实验研究

为了考察气化炉炉侧喷嘴入口位置对炉内流场和颗粒浓度分布的影响规律,在新型水煤浆气化炉冷模三维实验台上进行了大量的实验研究,并与数值模拟计算结果进行了对比,结果表明,当喷嘴距气化炉顶部0.9 m时,气化炉炉内流场分布最合理,颗粒浓度分布最均匀;实验测试结果和数值模拟计算结果非常接近,进一步验证了数值模拟计算结果的准确性.实验测试结果为气化炉的设计和运行提供了参考.     

丁二烯/苯乙烯阴离子连续溶液共聚反应模型化研究

针对n_BuLi引发剂引发的丁二烯／苯乙烯阴离子连续溶液共聚反应,结合共聚机理与反应器操作模式,建立了完全混合全混流模式下共聚单体转化率及分子量分布模型,并借助共聚单体转化率实验结果,对共聚单体转化率模型进行参数估计,求得了4个链增长速率常数。在此基础上,进行了分子量分布模型的模拟计算,并将模拟结果与共聚物分子量分布的实测结果进行了比较。研究结果表明,建立的模型能较为满意地描述丁二烯／苯乙烯阴离子连续溶液共聚反应的单体转化率和分子量分布。     

泡载分离器的研究——泡载分离器内微气泡的分布规律

利用H_2O-CO_2体系,对溶气法产生气泡的分布规律进行考察。实验结果发现,微气泡的分布呈非对称拖尾分布。从气液传质、能量转换和气泡动力学的角度,对气泡形成饥理进行分析。提出了描述气泡拖尾分布的Γ函数分布,并讨论其分布函数中参数m的物理意义。     

三种聚丙烯粉料粒度分布测试方法比较

分别采用CAMSIZER数字成像颗粒分析仪、机械振动筛和手工筛对两类聚丙烯粉料样品的粒度分布进行了测试,对3种方法获得的数据进行了分析比较。结果表明,用CAMSIZER数字成像颗粒分析仪进行聚丙烯粉料粒度分布测试,结果重复性较好;用该方法获得的粒度分布数据以体积百分数表示,与机械振动筛分和手工筛分获得的以质量百分数表示的粒度分布数据比较,存在明显差别。     

闪蒸干燥器气相流场的模拟研究

针对目前旋流闪蒸干燥器的气相流场存在的一些问题,应用FLUENT6．0软件进行模拟,对平底、带叶片的旋流闪蒸干燥器的气相流场分布进行数值模拟和实验研究。并用实验数据对模拟结果进行了验证,取得了很好的一致性。同时,针对带气体分布器的闪蒸干燥器进行了模拟研究,分别对圆管形、圆锥形、方管形分布器进行模拟分析。结果表明,方管形干燥器能够使切向速度分布更加均匀,从而提高干燥能力。     

数字成像颗粒分析仪在聚丙烯粉料测试中的应用

为考察CAMSIZER数字成像颗粒分析仪用于聚丙烯粉料测试的可行性，采用CAMSIZER数字成像颗粒分析仪对聚丙烯粉料样品的粒度分布进行了测试，考察了测试结果的重复性，并对该仪器在粒度分布测试同时获得颗粒球形度数据和颗粒照片的功能进行了验证。结果表明：粒度分布测试自动化程度高，测试速度快，结果重复性好，与筛分法比较，工作量大大降低；在进行粒度分布测试的同时，可获得颗粒的球形度数据和颗粒投影照片。     

注射压缩成型的CAE三维模拟分析

以透明的楔形导光板为分析实例,采用真实三维CAE模流分析技术对注射压缩成型过程进行了模拟,直观预测了楔形导光板的充填压力分布、残余应力分布、熔体流动前沿处的温度分布以及缩痕分布等结果,并与传统注射成型的分析结果进行了详细的比较和分析。结果表明:与传统注射成型相比,注射压缩成型在加工过程中压力较低且分布较为均匀、残余应力更低、温度分布更加均匀,而缩痕分布则相差不大,因此更有可能成型出更好品质的透明制品,为实际的注射压缩成型模具设计及工艺参数设置提供了可靠的参考依据。     

泰勒反应器中流体流动及停留时间分布研究

以水为介质对泰勒反应器中的流动状况和停留时间及其分布(RTD)进行了研究,并应用计算流体力学(CFD)技术对反应器进行了流场模拟和RTD计算。结果表明,在实验范围内,泰勒反应器中停留时间分布受内筒转速、轴向流动速率等因素影响,基于流体力学计算结果与实验结果基本相当。     

Predictive control of particlesize distribution of crystallization process using deep learning based image analysis

The challenges to regulate the particle-size distribution (PSD) stem from on-line measurement of the full distribution and the distributed nature of crystallization process. In this article, a novel nonlinear model predictive control method of PSD for crystallization process is proposed. Radial basis function neural network is adopted to approximate the PSD such that the population balance model with distributed nature can be transformed into the ordinary differential equation (ODE) models. Data driven nonlinear prediction model of the crystallization process is then constructed from the input and output data and further be used in the proposed nonlinear model predictive control algorithm. A deep learning based image analysis technology is developed for online measurement of the PSD. The proposed PSD control method is experimentally implemented on a jacketed batch crystallizer. The results of crystallization experiments demonstrate the effectiveness of the proposed control method.     

基于两相模型的聚合物流动诱导结晶数值模拟

基于两相流动诱导结晶模型,采用谱方法分别计算无定形相的构象张量分布函数和半晶相的取向张量分布函数,进而根据Avrami方程和晶核成核速率与第一法向应力差的关系计算成核速率和结晶度。预测剪切对体系结晶速度的影响,并模拟了活化晶核数目和晶体取向的演化。计算结果表明,剪切对聚合物的结晶动力学性能有显著的影响,但是剪切对聚合物结晶的加速作用不是无限制的,随着剪切强度的增加,对结晶加速作用会变得不再明显。     

Entropic analysis of a batch-crystallization process

The analysis of crystallization processes considering an entropic perspective is the primary purpose of this paper. Although the modeling of crystallization processes is well established in the literature, the entropic representation of these processes still needs to be studied. The modeling considering the second law of thermodynamics was investigated, which resulted in a model that represents the entropy production rate of a batch-crystallization process. The results indicate that the entropy production of the batch cooling crystallization is related to the variability of the crystal size distribution. The model of the entropy production rate could be used as a restriction criterion for multi-objective optimization of the cooling temperature profile of a batch crystallizer to improve the quality of the crystal size distribution of the final product.     

头孢氨苄连续结晶研究及应用

头孢氨苄的传统生产方法多为间歇结晶,存在效率低、能耗高等弊端。为节约能耗、提高生产效率、缩短工时、降低成本,针对头孢氨苄等电点结晶的特点,本文设计了两级连续结晶工艺。采用单因素法系统研究了头孢氨苄水溶液初始浓度、停留时间、搅拌速率、结晶终点pH、晶种策略等因素对头孢氨苄连续结晶过程产品的收率、晶习及粒度分布的影响。单因素实验结果显示头孢氨苄水溶液质量分数为14%、最佳停留时间为12min、结晶终点pH控制在4.8附近、晶种添加量为5%时其产品收率、粒度分布均达到了理想的效果。该工艺能将结晶过程的过饱和度有效地控制在介稳区内,避免了爆发成核。与间歇结晶相比,两级连续结晶工艺的工时缩短30%。产品晶习完整,粒度分布均匀,收率可以达到96%。目前该工艺已成功实现单条生产线规模为500t/a的产业化应用。     

Investigation on the structure and crystallization behavior of controlled-rheology polypropylene with different stereo-defect distribution

Understanding concerning the influence of peroxide degradation on the stereo-defect distribution and related crystallization kinetics of controlled-rheology polypropylene are of great importance. In this study, two iPP samples (PP-A, PP-B) with similar molecular weights and average isotacticities, but different stereo-defect distributions and their degradation productions after the addition of dicumyl peroxide (DCP) were prepared. Their melt flow indexes (MFI), stereo-defect distributions, crystallization behaviors and kinetics were studied using MFI measurement, differential scanning calorimetry, wide-angle X-ray diffraction, non-isothermal crystallization kinetics and successive self-nucleation and annealing fractionation. The results showed that as the content of DCP increased, the MFI, the crystallization temperature and crystallization rate of PP increased gradually, the crystallization peak width became narrower, and the crystallite size decreased. Meanwhile, the addition of DCP greatly restrained the formation of thick lamellae and narrowed its stereo-defect distribution [meso-sequence length (MSL) distribution]. On the other hand, results showed that PP resins with different stereo-defect distribution have similar MFI variations after degradation. PP-A (whose stereo-defect distribution was less uniform than PP-B) and its degradation products still possess higher crystallization rate, stronger crystallizability, smaller crystallite size and higher fractions of long MSL, compared with their counterparts of PP-B.     

A stochastic formulation for the description of the crystal size distribution in antisolvent crystallization processes

A stochastic approach to describe the crystal size distribution dynamics in antisolvent based crystal growth processes is here introduced. Fluctuations in the process dynamics are taken into account by embedding a deterministic model into a Fokker‐Planck equation, which describes the evolution in time of the particle size distribution. The deterministic model used in this application is based on the logistic model, which shows to be adequate to suit the dynamics characteristic of the growth process. Validations against experimental data are presented for the NaCl–water–ethanol antisolvent crystallization system in a bench‐scale fed‐batch crystallization unit. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

Synthesis of SAPO-34 templated by diethylamine: Crystallization process and Si distribution in the crystals

The crystallization process of SAPO-34 molecular sieve with Si distribution in the crystals using diethylamine (DEA) as the template was investigated by XRD, SEM, IR, NMR, XRF, XPS and EDS techniques. It was found that the solution-mediated transport mechanism occurred during the crystallization, though the gel transformation cannot be completely excluded in the initial crystallization (t  1 h). Si directly participated in the crystallization in the initial stage and incorporated into the framework of SAPO-34 by SM2 (P substitution by Si) and SM3 (pairs of Al and P substitution by 2Si) mechanisms. XPS analysis revealed the enrichment of Si on the surface of crystals. Based on the experimental results, a model of Si distribution in the crystals was proposed, which described a non-uniform distribution of Si in the crystals, with the increasing content from the core to the surface.     

Effects of short‐chain branches on strain‐induced polymer crystallization

We performed dynamic Monte Carlo simulations of a lattice polymer model to investigate strain‐induced crystallization behaviors of short‐chain branched polymers with variable sequence distributions, branch numbers and lengths, and their blending compositions with linear polymers. The results revealed that the branch density and distribution bring dominant effects. In the blends, there is no phase separation prior to crystallization, except that strain‐enhanced mixing is temporarily hindered by chain folding upon crystallization. Our observations shed lights onto the strain‐induced crystallization of short‐chain branched polymers. © 2018 Society of Chemical Industry     

Investigation of the crystallization behavior of isotactic polypropylene polymerized with different Ziegler‐Natta catalysts

Detailed characterization of the crystallization behavior is important for obtaining better structure property correlations of the isotactic polypropylene (iPP), however, attributed to the complexity in ZN‐iPP polymerization, the relationship between crystallization behavior and the stereo‐defect distribution of iPP is still under debate. In this study, the crystallization kinetics of the primary nucleation, crystal growth and overall crystallization of two iPP samples (PP‐A and PP‐B) with nearly same average isotacticity but different stereo‐defect distribution (the stereo‐defect distribution of PP‐B is more uniform than PP‐A) were investigated. The results of isothermal crystallization kinetics showed that the overall crystallization rate of PP‐A was much higher than that of PP‐B; but the analysis of self‐nucleation isothermal crystallization kinetics and the polarized optical microscopy (POM) observation indicated that the high overall crystallization rate of PP‐A was attributed to the high primary nucleation rate of the resin. The stereo‐defect distribution plays an important role in determining both the nucleation kinetics and crystal grow kinetics, and thus influence the overall crystallization kinetics. A more uniform distribution of stereo‐defects restrains the crystallization rate of iPP, moreover, it has more influence on nucleation kinetics, comparing with the crystal growth. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Comparison of different solubility equations for modeling in cooling crystallization

In this paper we evaluate the sensitivity of using different solubility models on cooling crystallization. Specifically, the cooling crystallization of acetaminophen in ethanol is investigated. Empirical, correlative thermodynamic (namely van Laar, Wilson, and NRTL) and predictive thermodynamic (namely MOSCED, NRTL-SAC, and UNIFAC) models are considered. Equilibrium solubility model prediction determines the predicted supersaturation profile. The different solubility equations are used within a population balance model for prediction of crystal size properties. Incorrect prediction of the supersaturation profile results in incorrect prediction of crystal size distribution. The NRTL model was found to be more accurate at predicting equilibrium solubility and consequently crystal size. After the solubility sensitivity is evaluated, two methods are proposed to make the crystallization model more robust against solubility model errors.