哈尔滨炼油厂MTBE装置试生产

介绍了哈尔滨炼油厂ＭＴＢＥ装置的工艺路线、新技术的应用及特点；催化剂的装填及应用情况；总结了生产过程中遇到的一系列问题及解决办法；探索了平稳生产的新徐径，以保证装置安全、平稳、长周期运行；同时对反应器操作温度、催化蒸馏塔操作压力、原料中醇烯比等因素对异丁烯转化率及ＭＴＢＥ产品的影响做了简单的总结。     

Issues in nonlinear stochastic grey box identification

Grey box identification refers to the practice of identifying dynamical systems in model structures exploiting partial prior information. This contribution reviews a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes. Issues to be addressed include advantages and costs of introducing stochastics into the model, the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.     

材料研究中系列试样的单标样法 X 射线定量分析

本文提出了用一个标样进行系列试样 X 射线定量相分析的方法.它克服了一般 X 射线定量方法需要混合研磨和手续烦复的缺点以及无标样 X 射线定量方法存在病态方程不易解决的问题.该方法对常规 X 射线定量分析具有普遍的实用性.     

自旋为j的粒子在旋转磁砀中的几何相位

用相干态的方法得到旋转磁场中自旋为j的粒子的态矢量的严格表达式，由此可计算相干态和叠加相干态的Abaronov－Anandan相位（AA相让）．并具有清楚的物理图象．     

Distributed memory systems for simulating artificial neural networks

In executing tasks involving intelligent information processing, the human brain performs better than the digital computer. The human brain derives its power from a large number [O(10¹¹)] of neurons which are interconnected by a dense interconnection network [O(10⁵) connections per neuron]. Artificial neural network (ANN) paradigms adopt the structure of the brain to try to emulate the intelligent information processing methods of the brain. ANN techniques are being employed to solve problems in areas such as pattern recognition, and robotic processing. Simulation of ANNs involves implementation of large number of neurons and a massive interconnection network. In this paper, we discuss various simulation models of ANNs and their implementation on distributed memory systems. Our investigations reveal that communication-efficient networks of distributed memory systems perform better than other topologies in implementing ANNs.     

Effect of Bi and Sr concentrations on the formation of the 2223 phase in Bi-Pb-Sb-Sr-Ca-Cu-O materials, obtained under different conditions of thermal treatment

The superconducting properties and the phase and chemical composition of Bi _x Pb_0.3Sb_0.1Sr _y Ca₂Cu₃O_z (x=1.5, 1.6, and 1.7;y=1.9, 2.0, and 2.1) materials synthesized by one-step and multistep thermal treatments have been investigated. The multistep annealing between 825–875°C promotes the 2223 phase. The change of Bi concentration has little effect on the 2223 phase formation, regardless of the kind of thermal treatment used, but increasing the Sr concentration (y> 2) strongly inhibits this phase. It has also been established that the loss of Pb after synthesis depends on the initial Bi concentration. The loss of Pb decreases when the initial Bi content is lower.     

ADS expert

ADS Expert is an integrated system that (a) provides suggestions about suitable optimization algorithms for a particular structural optimization problem, (b) it offers explanations and guide lines, in the form of hypertext, that refer to the optimization strategy, optimizer and one dimensional search method, (c) it produces the required gradients for the objective function and the constraints using symbolic differentiation, (d) establishes a direct linking with ADS routines and (e) it monitors the evolution of the optimization process. The system can be used as an educational tool for structural optimization and as an efficient integrated system for small to medium size optimization problems for which the objective function and the constraints are given in the form of explicit functions of the design variables. The system is a Windows application and runs quite satisfactorily on PCs.     

An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system.The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence.A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.     

广义频率响应函数的鲁棒建模新方法

针对基于非线性谱分析的故障诊断技术的需要,研究了非线性系统的广义频率响应函数的鲁棒在线建模方 法。首先将次元分析算法应用于Volterra级数模型的辨识,并通过对此算法的修正,得到了一种改进的Volterra系统的鲁 棒辨识算法。对其鲁棒性能进行的分析表明,改进算法的鲁棒抗噪性能被明显提高。在此基础上,提出了一种广义频率响 应函数的两步鲁棒建模新方法。仿真实验表明,该方法具有良好的鲁棒收敛性能,能够有效解决GFRF的在线建模问题。