高强碳纤维束丝拉伸性能测试影响因素的研究

研究了3K,6K和12K碳纤维束丝拉伸性能测试过程中的一些影响因素,包括与样品制备相关的胶液浓度、胶液种类、张力、环境湿度以及测试时的拉伸速率。研究结果表明,碳纤维的拉伸性能测试与样品制备及测试过程中的实验条件有很大关系。胶液浓度较低时（〈25％）,纤维拉伸强度比正常值偏低。比较了环氧6101和环氧648两种树脂作胶液的情况,前者得到的碳纤维拉伸强度更高。样品固化时施加合适的张力可得到较高的拉伸性能。另外,样品制备时,随着相对湿度的增加,测得的碳纤维拉伸强度逐渐降低。随拉伸速率的增加,碳纤维的拉伸模量逐渐增加。     

The risk early-warning of gas hazard in coal mine based on Rough Set-neural network

This article proposed the risk early-warning model of gas hazard based on Rough Set and neural network. The attribute quantity was reduced by Rough Set, the main characteristic attributes were withdrawn, the complexity of neural network system and the computing time was reduced, as well. Because of fault-tolerant ability, parallel processing ability, anti-jamming ability and processing non-linear problem ability of neural network system, the methods of Rough Set and neural network were combined. The examples research indicate： applying Rough Set and BP neural network to the gas hazard risk early-warning coal mines in coal mine, the BPNN structure is greatly simplified, the network computation quantity is reduced and the convergence rate is speed up.     

Research on prediction for coal and gas outburst based on Matlab neural network toolbox and its application

In order to predict the danger of coal and gas outburst in mine coal layer correctly, on the basis of the VLBP and LMBP algorithm in Matlab neural network toolbox, one kind of modified BP neural network was put forth to speed up the network convergence speed in this paper. Firstly, according to the characteristics of coal and gas outburst, five key influencing factors such as excavation depth, pressure of gas, and geologic destroy degree were selected as the judging indexes of coal and gas outburst. Secondly, the prediction model for coal and gas outburst was built. Finally, it was verified by practical examples. Practical application demonstrates that, on the one hand, the modified BP prediction model based on the Matlab neural network toolbox can overcome the disadvantages of constringency and, on the other hand, it has fast convergence speed and good prediction accuracy. The analysis and computing results show that the computing speed by LMBP algorithm is faster than by VLBP algorithm but needs more memory. And the resuits show that the prediction results are identical with actual results and this model is a very efficient prediction method for mine coal and gas outburst, and has an important practical meaning for the mine production safety. So we conclude that it can be used to predict coal and gas outburst precisely in actual engineering.     

Group Contribution based Flammability Limit Estimation of Hydrocarbon-Inert Gas Mixture

As group contribution method is easy to apply and has a wide application range,current study has developed this model to predict flammability limit of hydrocarb...     

贴附式薄壳混凝土组合防渗新技术的应用

本文结合工程实例,介绍了应用薄壳混凝土结构,并组合土工合成材料对挡水坝进行防渗加固处理的工程措 施,以及良好的经济与社会效益。     

无驱动硅微机械陀螺信号解调的研究

从无驱动硅微机械陀螺的敏感结构原理出发，对它的输出信号特征进行了分析，建立了相应的数学模型，提出使用最小均方差（LMSD）的算法对输出信号进行解调。使用MATLAB的数据处理方法，对仿真转台上得到的波形数据进行数字解调，将得到的结果与实际输入相比较，结果表明采用LMSD算法能够解调出陀螺的俯仰和偏航角速度信号。     

多道脉冲幅度分析器改进研究

分析了多道脉冲幅度分析器忙时间的形成特点,设计出来一套能减小系统忙时间的方案,从而大大地减少由于忙时间造成的脉冲漏计数。同时分析了改进后系统和实际测量时存在误差的主要因素;该方案具有实现有成本小,方便灵活等优点。     

无卷边单分子层WS2纳米片原子结构的高分辨电子显微术研究

本文利用高分辨电子显微术(HRTEM)确定了无卷边的单分子层WS2纳米片的原子结构像.通过对样品不同区域HRTEM像进行傅里叶变换(FFT)分析,得到了各个区域的WS2纳米片的晶体取向,确定了WS2纳米片分子层数分布.根据电子显微像强度与样品层数的线性关系以及WS2纳米片的单分子层数分布模型,确定不同区域WS2纳米片的分子层数.为了进一步定量分析结果的正确性,通过模拟电子显微像在不同碳膜厚度及不同成像条件下WS2纳米片的HRTEM像,也确定了在像衬度上与实验像很好的匹配.     

石墨烯基导热薄膜的研究进展

随着现代技术的发展,散热和导热已成为制约芯片器件小型化和大功率制造业发展的关键问题之一。由于传统的金属导热材料存在密度大和易氧化等问题,近年来以石墨烯基材料为代表的非金属碳基材料逐渐成为国内外的研究热点。本文综述了近年国内外石墨烯导热薄膜的制备方法及最新研究成果,分析讨论了热处理工艺、晶粒尺寸、薄膜密度及杂质原子和缺陷等对石墨烯导热薄膜性能的影响和物理机理,并对该领域的发展趋势进行了展望。     

移动视频业务的自适应资源预留方案

提出了一个拓扑独立且自适应的资源预留方案用以向移动视频业务提供服务品质保证.建议的方案通过研究移动节点累积的运动历史,总结出其运动特点,进而对节点的运动趋势进行预测.基于预测的结果,正在进行的移动视频业务所需的资源在移动节点未来最可能访问的子网中被预留.所提出的方案在向用户提供满意的移动视频业务的同时,保证了网络资源的充分利用,并降低了预留阻塞的可能性.