用瑞利波检验高喷防渗墙的施工质量及地层分布特征

本文阐述了瞬态多道瑞利波探测的原理和方法，并将其应用到大堤高喷防渗墙施工质量的检验中，取得一定成效，测试结果与测压管观测结果对比，相互吻合，为类似工程的质量检验提供了一种可采用的检测手段。     

H2O(g)对富氧燃烧超细颗粒物生成特性影响

为实现富氧燃烧技术的广泛推广,对煤粉燃烧在富氧气氛下的颗粒物排放特性进行了研究。在1800 K管式炉内进行煤焦燃烧试验,研究了富氧气氛下H₂O(g)体积分数(0、5%、10%、20%、30%)对煤焦燃烧超细颗粒物的影响;采用荷电低压撞击器(ELPI+)获得超细颗粒物质量和数量浓度粒径分布并进行分析。结果表明,H₂O(g)对超细颗粒物质量浓度和数量浓度粒径分布无影响,但会导致超细颗粒物的峰值波动。超细颗粒物总数量由最小粒径超细颗粒物决定,5种水蒸气浓度下EL?PI+第1级撞击器收集到的超细颗粒物数量占比均超过65%。超细颗粒物总质量由最大粒径超细颗粒物决定,5个水蒸气浓度下ELPI+第7级撞击器收集到的超细颗粒物质量占比均超过94%。低H₂O(g)浓度会抑制超细颗粒物生成,H₂O(g)体积分数为5%时的抑制作用最显著;高H₂O(g)浓度会促进超细颗粒物生成。这是因为一方面H₂O(g)与煤焦发生气化反应,使煤焦颗粒周围产生还原性气氛,促进矿物质还原为单质,进一步促进矿物质蒸发;另一方面气化反应是吸热反应,会降低煤焦颗粒燃烧温度,同时H₂O(g)加入也导致烟气热容增加进一步降低,煤焦燃烧温度抑制煤中矿物质的蒸发,导致超细颗粒物生成减少,是2种作用相互竞争的结果。此外,H₂O(g)的加入使超细颗粒物平均粒径增大,0~5%H₂O(g)时超细颗粒物平均粒径增大最迅速。     

Preparation and application of fluorocarbon polymer/SiO2 hybrid materials,part 1: Preparation and properties of hybrid materials

For this study, we first prepared a fluorocarbon polymer and its hybrid materials. We found that fluorocarbon copolymers can produce hydrogen bonds with SiO₂ to form hybrid materials. We also used thermogravimetric analyzer and tested the thermostabilities of the four products, which were ranked as follows: fluorocarbon copolymer/SiO₂ hybrid material > fluorocarbon polymer/SiO₂ hybrid material > fluorocarbon copolymer > fluorocarbon polymer. In addition, we found that, due to the inorganic SiO₂ used, the number of pores and the specific surface areas of the hybrid materials both increased. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 1140–1145, 2007     

基于DNA遗传算法的CR多载波参数优化

提出了一种基于DNA计算的非支配排序多目标遗传算法(DNA-GA)来对CR多载波传输参数进行优化。该算法通过非支配排序计算个体适应度,结合克隆操作使算法收敛于全局最优,并引入DNA基因级操作,以提高算法的搜索性能,保持种群的多样性。通过在不同服务需求情况下得到的仿真参数结果,证明了DNA-GA可以有效地优化CR传输参数。     

Compact electrostatic levitator for diffraction measurements with a two axis diffractometer and a laboratory x-ray source

A compact electrostatic levitator was developed for the structural analysis of high-temperature liquids by x-ray diffraction methods. The size of the levitator was 200 mm in diameter and 200 mm in height and can be set up on a two axis diffractometer with a laboratory x-ray source, which is very convenient in performing structural measurements of high-temperature liquids. In particular, since the laboratory x-ray source allows a great amount of user time, preliminary or challenging experiments can be performed with trial and error, which prepares and complements synchrotron x-ray experiments. The present small apparatus also provides the advantage of portability and facility of setting. To demonstrate the capability of this electrostatic levitator, the static structure factors of alumina and silicon samples in their liquid phases were successfully measured.     

山东省棉花主要病害的发生现状与防治

山东省棉花病害种类共有１９种，根据其发病部位和时期等特点习惯了分为四大类：苗期病害的发生枯黄萎病，铃部病害和叶部病害，其中危害性最大的是棉花枯萎病和黄萎病。某些年份，立枯病，黑斑病和铃疫病也能引起较大的损失。     

用人工智能中的搜索原理解决迷宫问题

迷宫问题是一个经典的程序设计问题,它要求用计算机编程的方法求解出从迷宫的入口到出口的所有路径。本文采用人工智能中的搜索原理,介绍了求解迷宫问题的基本思想以及实现方法。分析了用C语言编程的思路并给出了详细的程序设计语句,通过调试和运行总结出了一种极为简便、易于理解、易于编程的新方法。     

高炉渣处理综述及螺旋法水渣处理工艺的应用

介绍了高炉渣处理方法。通过对不同高炉水渣处理系统进行分析对比,指出螺旋法水渣处理工艺的优缺点,分析了本工艺应用的现实可能性,介绍了主要的设备和工艺流程布置方案。     

Performance evaluation of fuzzy rule-based classification systems obtained by multi-objective genetic algorithms

In this paper, we examine the classification performance of fuzzy if-then rules selected by a GA-based multi-objective rule selection method. This rule selection method can be applied to high-dimensional pattern classification problems with many continuous attributes by restricting the number of antecedent conditions of each candidate fuzzy if-then rule. As candidate rules, we only use fuzzy if-then rules with a small number of antecedent conditions. Thus it is easy for human users to understand each rule selected by our method. Our rule selection method has two objectives: to minimize the number of selected fuzzy if-then rules and to maximize the number of correctly classified patterns. In our multi-objective fuzzy rule selection problem, there exist several solutions (i.e., several rule sets) called “non-dominated solutions” because two conflicting objectives are considered. In this paper, we examine the performance of our GA-based rule selection method by computer simulations on a real-world pattern classification problem with many continuous attributes. First we examine the classification performance of our method for training patterns by computer simulations. Next we examine the generalization ability for test patterns. We show that a fuzzy rule-based classification system with an appropriate number of rules has high generalization ability.