Numerical analysis of a new model for the processes of the one-dimensional case of metal crystallization

The numerical analysis of a new model of metal crystallization is performed. The novelty of the model, which has recently appeared in publications, consists in modeling that is simultaneously carried out at several scale levels, from micro-to macroscales. Although experimental studies of metal crystallization revealed many details of metal crystallization, there is no comprehensive theoretical view on this phenomenon. In the model employed in this work, the space of the crystallizing alloy is assumed to be a porous medium, in which the disturbance propagation is described by Biot’s type of equations. The formation of crystal nuclei is described by a modified Cahn-Hilliard equation. A numerical scheme is constructed and its convergence is demonstrated. It is shown that various crystallization modes can be set by varying the parameters. We intend to investigate a multidimensional variant in our subsequent research, using multiprocessor computer complexes.     

煮糖结晶过程的动态矩阵控制研究

由于煮糖结晶过程本身受干扰的因素比较多，如糖浆的锤度、糖浆杂质、真空度以及温度的变化都会影响蔗糖结晶过程，非线性比较强。因此一般的控制策略（比如常规PID）难以凑效，根据煮糖结晶过程的物料平衡、能量平衡和生产过程的各种物性参数的机理解析关系（如晶体生长分散）建立描述被控对象的模型，并以该模型作为预测模型对煮糖结晶过程实施动态矩阵控制（DMC）．仿真结果表明该控制算法对煮糖过程的控制是有效的。     

间歇结晶过程模型和动态优化研究的进展

间歇结晶过程是一种重要的分离过程单元操作,由于机理的复杂性以及动态特性使得该过程的数学模型研究非常具有挑战性。本文从间歇结晶过程建模和动态模拟、动态优化、模型辨识以及鲁棒优化与控制等方面,介绍了间歇结晶过程数学模型的研究进展,评述了其中的关键问题和求解技术。指出对结晶过程的机理进一步深入认识,开发数值稳定、精度更高的求解算法是间歇结晶过程数学模型研究的基础。全局优化效果较好的进化算法和模型预测控制理论在结晶过程动态优化和质量控制中的应用是今后的研究方向。     

间歇结晶过程建模和动态模拟

间歇结晶过程广泛应用于精细化工、医药、生物等过程,该过程的模拟将对产品质量和过程控制具有重要作用。本文建立了间歇结晶过程数学模型。该模型是一个包含双曲型偏微分方程(粒数衡算方程)及微分-积分方程的复杂方程组,其较强的非线性使得难以求得解析解。本文用数值方法计算了粒数密度分布函数、过饱和度、成核与生长速率等重要的过程参数,定义并计算了过程的产品质量评价指数。定量模拟了晶种对结晶过程的影响,以及结晶过程中成核和生长的竞争关系,同时,对上述现象和规律进行了理论分析。     

Soft-sensor for industrial sugar crystallization: On-line mass of crystals,concentration and purity measurement

This paper deals with the design of a model-based soft-sensor to improve the process monitoring and control in industrial sugar crystallization. This soft-sensor is based on an original model dedicated to the last stage of crystallization, avoiding the solving of the population balance. Additional information like the mass of crystals in the solution, the concentration of dissolved sucrose and the purity are relevant to improve the manufacturing process. As these physicochemical properties are not measurable on-line, a model based soft-sensor is developed. The effectiveness of the soft sensor is demonstrated using real plant data from an industrial crystallization process.     

烧碱蒸发结晶中氯化钠传质多相流模拟研究

由于烧碱蒸发结晶中氯化钠的结晶是非常复杂的多相传热传质过程,能否使晶粒合理分布以过滤除去是氯碱工业提高产品质量的瓶颈。因此本文对四效逆流蒸发分布器中氯化钠结晶过程进行了研究,将多相流理论应用于氯化钠工业结晶过程,以微元衡算为基础,引入碰撞因子,建立了氯化钠湍流传质模型,并用工厂生产数据对模型进行了验证,结果与生产实际吻合较好。该模型不但可用来优化烧碱生产过程中氯化钠晶粒的分布,指导工业结晶生产,而且可直接预测晶体生长特性。     

JITL-based concentration control for semi-batch pH-shift reactive crystallization of l-glutamic acid

Although concentration control (C-control) strategy has been shown to give effective and robust control performance for batch cooling and semi-batch antisolvent crystallizations in recent years, no research work was reported concerning the potential application of conventional C-control for the more challenging semi-batch pH-shift reactive crystallization that is common in the process industries. To this end, this paper presents detailed analysis to find out that it is not feasible to apply the C-control to semi-batch pH-shift reactive crystallization. To circumvent this problem, a variant of C-control strategy by incorporating the Just-in-Time Learning (JITL) method to cope with strong process nonlinearity inherent in the pH-shift reactive crystallization is developed in this paper. Simulation results are presented to illustrate the proposed design and a comparison with conventional optimal control is made.     

First-principles and direct design approaches for the control of pharmaceutical crystallization

Crystallization is the main separation and purification process for the manufacturing of drug substances. Not only does crystallization affect the efficiency of downstream operations such as filtering, drying, and formulating, the efficacy of the drug can be dependent on the final crystal form. Advances in simulation and control algorithms and process sensor technologies have enabled the development of systematic first-principles and direct design approaches for the batch control of crystallization processes. These approaches address different challenges associated with pharmaceutical crystallization control. This paper provides an overview of recent technological advances in the in situ control of pharmaceutical crystallization processes. Implementation of the first-principles and direct design approaches are compared, and their relative merits are explained. Areas of future opportunities for application of advanced control strategies in pharmaceutical crystallization are presented.     

Crystallization: a computer program for modeling the crystallization of a magmatic liquid

The program CRYSTALLIZATION provides a means of modeling the evolution of a liquid (a magma characterized by its chemical composition) during its crystallization into a solid formed of one or more phases. Three crystallization models are considered in this program: equilibrium crystallization, fractionated crystallization, and equilibrium crystallization with periodic fractionations. The program calculates the composition of successive liquids and solids during the crystallization process, according to a certain number of parameters specified by the user (initial) concentration, interval between initial and final liquid fraction, increments of crystallization, number of fractionations and respective quantities, number of phases forming the solid as well as their time intervals of development and their distribution coefficients, and the proportion of each phase in the final solid).     

基于B-P神经网络的非线性预测控制

针对用一般的方法控制糖液的过饱和度很难奏效的问题,运用B-P神经网络构造预测模型,将模拟退火算法的局部搜索与遗传算法的全局搜索相结合。进行在线滚动优化,对煮糖结晶过程中的过饱和度进行预测控制。实际运行结果表明,基于B-P神经网络的预测控制算法响应速度快、控制精度高、鲁棒性强,具有很强的实用性。     

结晶器不同进料位置混合过程的CFD模拟

用CFD模拟和电导率实验研究结晶过程。重点在不同进料位置对结晶过程的影响。CFD模拟采用FLUENT软件研究结晶器内部搅拌混合过程,分析各点的速度变化;电导率实验利用电导率仪测定搅拌过程中各点的电导率变化。CFD模拟顶部进料时收敛时间为0.75 s,底部为0.25 s;电导率实验顶部进料混合时间为40 s,中部为30 s,底部为20 s。模拟结果和实验结果都表明:以底部进料的混合时间为最短。     

Multivariable linearizing control of an industrial sugar crystallization process

This paper illustrates the benefits of a multivariable linearizing control approach applied to an industrial crystallization process. This relevant approach proposes a setpoint tracking for the crystal mass/concentration couple. In this purpose, a model dedicated to last stage crystallization is designed, without consideration of crystal size distribution. The controlled variables, unavailable, are obtained using an extended Luenberger observer. The observer is validated on industrial data and shows good performance in both convergence rate and accuracy. The performance of the proposed linearizing strategy, which application to cane sugar crystallization constitutes a real novelty, is tested via simulation. The good performance in setpoint tracking, even in presence of noise, disturbances and modeling error, allows to consider a significant improvement of the global productivity.     

Process study and optimization for fabrication of poly‐Si thin‐film transistors on plastic substrates

Abstract— A complete poly‐Si thin‐film transistor (TFT) on plastic process has been optimized to produce TFT arrays for active‐matrix displays. We present a detailed study of the poly‐Si crystallization process, a mechanism for protecting the plastic substrate from the pulsed laser used to crystallize the silicon, and a high‐performance low‐temperature gate dielectric film. Poly‐Si grain sizes and the corresponding TFT performance have been measured for a range of excimer‐laser crystallization fluences near the full‐melt threshold, allowing optimization of the laser‐crystallization process. A Bragg reflector stack has been embedded in the plastic coating layers; its effectiveness in protecting the plastic from the excimer‐laser pulse is described. Finally, we describe a plasma pre‐oxidation step, which has been added to a low‐temperature (<100°C) gate dielectric film deposition process to dramatically improve the electrical properties of the gate dielectric. These processes have been integrated into a complete poly‐Si TFT on plastic fabrication process, which produces PMOS TFTs with mobilities of 66 cm² /V‐sec, threshold voltages of ?3.5 V, and off currents of approximately 1 pA per micron of gate width.     

基于结晶过程的分子动理论优化算法

针对分子动理论优化算法(KMTOA)存在易陷入局部最优、寻优精度低等问题,提出一种基于结晶过程的分子动理论优化算法(C-KMTOA)。该算法通过模拟结晶过程设计了一种分离算子,该算子将种群分为最优个体、优秀个体、较差个体三个子群,并通过引导操作使较差个体向优秀个体附近移动、优秀个体向最优个体附近移动,从而使搜索范围快速缩小到最优解附近。实验结果表明,该算法在优化精度、动态性能等方面均优于GA、DE、QPSO和KMTOA。     

Research into models and algorithms of artificial life

This paper deals with methodology and algorithms for artificial life. The paper is organized as follows. First we briefly present the background and general concept of A-life. Then we describe the methodology and problems of A-life, and modeling, coding, and rendering techniques are proposed. Finally we investigate the application of cellular automata for metal crystallization and some aspects of A-life in engineering and computer art.     

The fuzzy crystallization algorithm: a new approach to complexsystems modeling

A new identification method for fuzzy modeling is introduced. Since the method has some analogy with the process of material crystallization in nature, the name of fuzzy crystallization algorithm (FCA) is given to this novel approach. This method accomplishes structure identification and parameter identification at the same time, and possesses the properties of simplicity, flexibility, and high calculation speed. Compared with other modeling strategies, it is easier to construct a model with a specific accuracy. Numerical examples are provided to demonstrate the performance of this approach.     

Data-driven,using design of dynamic experiments,versus model-driven optimization of batch crystallization processes

A new data-driven experimental design methodology, design of dynamic experiments (DoDE), is proposed as a means of developing a response surface model that can be used to effectively optimize batch crystallization processes. This data-driven approach is especially useful for complex processes for which it is difficult or impossible to develop a knowledge-driven model in a timely fashion for the optimization of an industrial process. Design of dynamic experiments [1] generalizes the formulation of time-invariant design variables from design of experiments, allowing for consideration of time-variant design variables in the experimental design. When combined with response surface modeling and an appropriate optimization algorithm, a data-driven optimization methodology is produced, which we call DoDE optimization. The method is used here to determine the optimal cooling rate profile, which integrates to give the optimum temperature profile, for a batch crystallization process. To examine the effectiveness of the DoDE optimization method, the data-driven optimum temperature profile is compared to the optimum temperature profile obtained using a model-based optimization technique for the potassium nitrate–water batch crystallization model developed by Miller and Rawlings [2]. The temperature profiles calculated using DoDE optimization yield response values within a few percent of the true model-based optimum values. A sensitivity analysis is performed on one case study to evaluate the distribution of the response variable from each method in the presence of parameter and initial seed distribution variability. It is demonstrated that there is partial overlap in the distributions when only variability in the model parameters is evaluated and there is substantial overlap when variability is included in both the model and initial seed distribution parameters. From this evidence, it can be concluded that the DoDE optimization method has the potential to be a useful data-driven optimization tool for batch crystallization processes where a first-principles model is not available or cannot be developed due to time and/or cost constraints.     

非晶材料晶化过程温度-电特性测试系统的设计

提出了非晶材料晶化过程温度控制和电阻率测试的总体设计方案,介绍了测试系统的控制算法及硬件和软件设计。在电阻率测试中采用四探针方法,克服了接触电阻和引线电阻的影响;在温度控制中采用了组合自校正算法,满足了调节和跟踪两个方面的要求。试验表明,本测试系统完全满足了非晶材料晶化过程电特性研究的需要。     

PLC专家控制在结晶生产中的应用

针对结晶生产温度控制要求较高且工艺复杂,人工方式难以满足对温度冗长实时精确控制等生产问题,利用PLC为核心,结合变频器技术,通信技术,专家系统理论,根据晶体生产经验设计了基于专家系统原理的PLC控制系统,进而组建功能完善的工业系统控制网络,用于结晶生产。实际生产中表明此种控制方式很好的满足了温度实时精确控制的要求,缩短了生产的复杂流程,大大的提高了生产效率。本文通过该系统在某公司食用糖醇晶体实际生产应用为背景,介绍该系统控制生产的原理,硬件构成以及软件设计。     

Data-driven modeling of product crystal size distribution and optimal input design for batch cooling crystallization processes

In this paper, a novel data-driven model building method is proposed for predicting one-dimensional product crystal size distribution (CSD) or chord length distribution (CLD) of batch cooling crystallization processes, based on only batch run data. The proposed model relating the manipulated variable of cooling rate to the product CSD are constructed by two classes of basis functions, one is the wavelet basis function for reshaping the CSD and the other is the polynomial basis function for weighting the chosen wavelet basis functions to reflect the nonlinear relationship between the input and the density of individual crystal size among the product crystals. Correspondingly, a double-layer least-squares algorithm is established to estimate the model parameters, along with an adaptive strategy to determine the location and number of wavelet basis functions. By introducing an objective function that combines the information entropy of product CSD and the sample deviation of product crystals in each batch with respect to the target crystal size, the optimal input design of cooling rate for the desired product CSD is carried out by using a particle swarm optimization (PSO) algorithm to solve the non-convex optimization problem with the established CSD model. Simulation tests on the hen-egg-white lysozyme crystallization process along with experiments on the L-glutamic acid cooling crystallization process are performed to demonstrate the effectiveness and advantage of the proposed method.