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1.
This article presents a comprehensive review of numerical methods and models for interface resolving simulations of multiphase flows in microfluidics and micro process engineering. The focus of the paper is on continuum methods where it covers the three common approaches in the sharp interface limit, namely the volume-of-fluid method with interface reconstruction, the level set method and the front tracking method, as well as methods with finite interface thickness such as color-function based methods and the phase-field method. Variants of the mesoscopic lattice Boltzmann method for two-fluid flows are also discussed, as well as various hybrid approaches. The mathematical foundation of each method is given and its specific advantages and limitations are highlighted. For continuum methods, the coupling of the interface evolution equation with the single-field Navier–Stokes equations and related issues are discussed. Methods and models for surface tension forces, contact lines, heat and mass transfer and phase change are presented. In the second part of this article applications of the methods in microfluidics and micro process engineering are reviewed, including flow hydrodynamics (separated and segmented flow, bubble and drop formation, breakup and coalescence), heat and mass transfer (with and without chemical reactions), mixing and dispersion, Marangoni flows and surfactants, and boiling.  相似文献   

2.
Detecting flaws and intruders with visual data analysis   总被引:1,自引:0,他引:1  
The task of sifting through large amounts of data to find useful information spawned the field of data mining. Most data mining approaches are based on machine-learning techniques, numerical analysis, or statistical modeling. They use human interaction and visualization only minimally. Such automatic methods can miss some important features of the data. Incorporating human perception into the data mining process through interactive visualization can help us better understand the complex behaviors of computer network systems. This article describes visual-analytics-based solutions and outlines a visual exploration process for log analysis. Three log-file analysis applications demonstrate our approach's effectiveness in discovering flaws and intruders in network systems.  相似文献   

3.
基于GMM的多工况过程监测方法   总被引:1,自引:0,他引:1  
传统基于主元分析的故障检测方法大多假设工业过程只运行在1个稳定工况,数据服从单一的高斯分布。若这些方法直接用于多工况过程则将会产生大量的误检。为此,本文提出了1种基于高斯混合模型的多工况过程监测方法。首先利用PCA变换对过程数据集进行降维,在主元空间建立高斯混合模型对过程数据进行聚类,自动获取工况数和相关分布特性。然后对每个工况建立主元分析(principal component analysis,PCA)模型来描述整个运行过程数据分布的统计特性。最后在过程监测中,根据监测样本属于各个工况的概率构造综合统计量,实现对多工况过程的故障检测。TE过程的仿真结果表明,本文提出的方法与传统的PCA方法相比,能自动获取工况和精确估计各个工况的统计特性,从而能更准确及时地检测出多工况过程的各种故障。  相似文献   

4.
Exploring process data   总被引:2,自引:0,他引:2  
With the growth of computer usage at all levels in the process industries, the volume of available data has also grown enormously, sometimes to levels that render analysis difficult. Most of this data may be characterized as historical in the sense that it was not collected on the basis of experiments designed to test specific statistical hypotheses. Consequently, the resulting datasets are likely to contain unexpected features (e.g. outliers from various sources, unsuspected correlations between variables, etc.). This observation is important for two reasons: first, these data anomalies can completely negate the results obtained by standard analysis procedures, particularly those based on squared error criteria (a large class that includes many SPC and chemometrics techniques). Secondly and sometimes more importantly, an understanding of these data anomalies may lead to extremely valuable insights. For both of these reasons, it is important to approach the analysis of large historical datasets with the initial objective of uncovering and understanding their gross structure and character. This paper presents a brief survey of some simple procedures that have been found to be particularly useful at this preliminary stage of analysis.  相似文献   

5.
化学工程中的计算流体力学   总被引:3,自引:7,他引:3  
本文评述了计算流体力学在化学化工研究和开发中的重要地位,介绍了各种模拟方法研究的现状、存在的困难和一些发展中的前沿领域。与传统应用领域相比,化学工程领域主要面对的是复杂多相流体系统及流动、传递和反应相耦合的过程,基于单尺度统计平均的传统连续介质方法已很难满足对产品结构和过程工艺精确设计的要求,而多尺度方法与粒子方法的结合是一条有效的途径。它通过对复杂系统满足的稳定性条件的分析以及对复杂界面和间断性的合理描述实现跨尺度关联的模拟,从而量化介观结构与行为、建立准确的宏观模型。这种结合无论是对湍流、汽液或气固多相流等传统的难题,还是对微流动、生物流、聚合物流动、颗粒流及散料力学等前沿领域,都带来了新的可能性,也将为化学化工领域的研发工作提供更有力的手段。  相似文献   

6.
本文将化学计量学方法引入土壤肥料研究,以一组紫色花生土理化性状数据作为样本,用因子分析法研究了土壤理化性状关系,用人工神经元网络的BP算法研究土壤理化性状与供肥能力的关系,所得结果表明化学计量学完全可以成为土壤肥料研究的强有力工具。  相似文献   

7.
The increasing performance demands on controlled chemical operations, coupled with the lack of appropriate measurement technology, motivates the need for nonlinear inferential control approaches. In this article, an overview of nonlinear inferential control approaches is presented, with an emphasis on the estimation component of the algorithm and logical extensions of the linear theory. Applications of the algorithms to process applications are reviewed, and new theoretical and application results are presented.  相似文献   

8.
Mining large amounts of unstructured data for extracting meaningful, accurate, and actionable information, is at the core of a variety of research disciplines including computer science, mathematical and statistical modelling, as well as knowledge engineering. In particular, the ability to model complex scenarios based on unstructured datasets is an important step towards an integrated and accurate knowledge extraction approach. This would provide a significant insight in any decision making process driven by Big Data analysis activities. However, there are multiple challenges that need to be fully addressed in order to achieve this, especially when large and unstructured data sets are considered.In this article we propose and analyse a novel method to extract and build fragments of Bayesian networks (BNs) from unstructured large data sources. The results of our analysis show the potential of our approach, and highlight its accuracy and efficiency. More specifically, when compared with existing approaches, our method addresses specific challenges posed by the automated extraction of BNs with extensive applications to unstructured and highly dynamic data sources.The aim of this work is to advance the current state-of-the-art approaches to the automated extraction of BNs from unstructured datasets, which provide a versatile and powerful modelling framework to facilitate knowledge discovery in complex decision scenarios.  相似文献   

9.
《Control Engineering Practice》2007,15(10):1196-1206
This article reviews advances in detection and diagnosis of plant-wide control system disturbances in chemical processes and discusses new directions that look promising for the future. Causes of plant-wide disturbances include non-linear limit cycles in control loops, controller interactions and tuning problems. The diagnosis of non-linearity, especially when due to valve stiction, has been an active area. Detection of controller interactions and disturbances due to plant structure remain open issues, however, and will need new approaches. For the future, the linkage of data-driven analysis with a qualitative model of the process is an exciting prospect. Finally, the paper offers some brief comments about emerging applications.  相似文献   

10.
化工过程控制混杂系统及其Petri网描述   总被引:4,自引:1,他引:4  
强调混杂系统的分析,研究了一类化工过程控制系统的混杂系统特性,建立了由过程层、监控层和调度层组成的混杂系统多层混合模型结构。论文分别讨论了各层混杂系统的模型形式,特别对过程控制层混杂系统模型进行了详细的描述。引入Petri网作为描述化工过程控制混杂系统的方法,以化工溶剂回收过程为例,建立了基于混合Petri网的过程控制层的模型。论文的工作为深入研究化工过程控制混杂系统奠定了基础。  相似文献   

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