Prediction and quality control of the melt index during production of high-density polyethylene

In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the 1 ^st -order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. The virtual sensor model developed based on the estimation scheme was combined with the virtual on-line analyzer (VOA) to give a quality control system to be implemented in the actual HDPE plant. From the application of the present control system, significant reduction of transition time and the amount of off-spec during grade changes was achieved     

Hydrogen production in solid electrolyte membrane reactors (SEMRs)

In the present work, the prospects and trends of solid electrolyte membrane reactors (SEMRs) towards hydrogen production, are discussed. Initially, an overview of the principles, the properties and the techniques related to the usage of the SEMRs, are presented. In the following, a literature survey covering earlier and recent developments of the various methods (e.g. reforming or partial oxidation or dehydrogenation of hydrocarbons, steam electrolysis) employed in the SEMRs for the production of hydrogen, is performed. Finally, the current status of this research field is analyzed and future research topics are proposed.     

The effect of ambient temperature on the sensitivity of hot-cathode ionization gauges

We measured the sensitivities of five hot-cathode ionization gauges for ambient laboratory temperatures between 23 and 31 °C. All of the ionization gauges exhibited very similar behavior, and the sensitivity could be adequately modeled with a linear function of temperature. The slopes of the fits were smaller than one would expect due to changes in the calibration chamber number density. The thermal transpiration effect, due to local heating of the gauge structures, can account for this, and a characteristic gauge tube temperature can be inferred from the temperature dependence of the sensitivity. A recent comparison of the high vacuum standards of several National Metrology Institutes (NMIs) was performed over the range of 10⁻⁶-10⁻³ Pa using hot-cathode and spinning rotor gauges as transfer standards. Among the participants, laboratory temperatures varied by as much as 5 °C. It is necessary to know how laboratory temperature affects the sensitivity of the hot-cathode transfer standards (spinning rotor gauges explicitly account for the gas temperature) so that individual laboratory results can be corrected to a common temperature.     

网络协同工作环境中应用共享发言权控制的研究

FloorControl是在大型网络实时交互平台下对共享资源进行控制管理的一项技术。FloorControl的概念分为机制和策略两个部分,协议属于机制,而策略则是具体的控制办法。本文着重介绍了在共享应用中使用FloorControl的技术要点,分析了目前常用的FloorControl协议,并给出了若干具体的FloorControl策略,这些策略的共同作用结果是具有公平、灵活和协同性。     

洞穴——从微中子研究到地下空间规划

微中子研究需要很大很深的洞穴，以便在没有太多宇宙射线噪音的情况下捕获重要事件。大型的自然洞穴往往出现在喀斯特石灰岩地区，少数大型洞穴也会出现在矿区，而民用洞穴则被广泛用作发电站、火车站、仓库及其他用途。应力控制被认为是在洞穴深挖中消除巨大应力的普遍方法。如果能够在大型洞穴使用应力控制方法，我们就可以建造安全的洞室来进行微中子研究；从另一方面来讲，大而浅的洞穴也能解决城市规划的很多问题。     

关于沥青针入度指数

介绍了沥青针入度指数(PI)的由来和计算、使用意义、局限性和分析。     

国内3G网络共享问题之研究

随着国内3G时代的来临，3G网络共享问题越来越受到人们的关注。本文结合国内移动通信的现状，着重分析了3G网络共享的模式及经济效益，论述了3G网络共享的相应策略。     

机电一体化设备控制系统的抗干扰措施

针对用单片机控制机电一体化设备必须解决的抗干扰问题,提出了一些对策,旨在提高控制系统的自适应能力,从而做到可靠运行。     

Controllability of One Spin and Two Interacting Spins

Mathematics of Control, Signals, and Systems - ?We consider the problem of steering control for the systems of one spin ½ particle and two interacting spin ½ particles in an...     

Modeling of Temperature–Frequency Correlation Using Combined Principal Component Analysis and Support Vector Regression Technique

A good understanding of environmental effects on structural modal properties is essential for reliable performance of vibration-based damage diagnosis methods. In this paper, a method of combining principal component analysis (PCA) and support vector regression (SVR) technique is proposed for modeling temperature-caused variability of modal frequencies for structures instrumented with long-term monitoring systems. PCA is first applied to extract principal components from the measured temperatures for dimensionality reduction. The predominant feature vectors in conjunction with the measured modal frequencies are then fed into a support vector algorithm to formulate regression models that may take into account thermal inertia effect. The research is focused on proper selection of the hyperparameters to obtain SVR models with good generalization performance. A grid search method with cross validation and a heuristic method are utilized for determining the optimal values of SVR hyperparameters. The proposed method is compared with the method directly using measurement data to train SVR models and the multivariate linear regression (MLR) method through the use of long-term measurement data from a cable-stayed bridge. It is shown that PCA-compressed features make the training and validation of SVR models more efficient in both model accuracy and computational costs, and the formulated SVR model performs much better than the MLR model in generalization performance. When continuously measured data is available, the SVR model formulated taking into account thermal inertia effect can achieve more accurate prediction than that without considering thermal inertia effect.