氧化石墨烯改性碳纤维复合材料抗冲击行为研究

使用单层纳米氧化石墨烯（NGO）粒子对环氧树脂进行改性处理，采用真空辅助树脂传递模塑成型工艺制备了[±45/0/90]_2S铺层角度下的纯树脂及单层NGO改性碳纤维复合材料（CFRP）层合板。通过落锤冲击试验、超声C扫描检测、冲击后压缩试验等对纯树脂及单层NGO改性CFRP进行实验研究。结果表明，纯树脂及单层NGO改性CFRP在损伤阻抗及损伤容限实验中均存在拐点现象，且拐点出现在相同深度位置，其中纯树脂CFRP拐点位置为0.51 mm，单层NGO改性CFRP拐点位置为0.43 mm；相对于纯树脂CFRP，单层NGO改性CFRP可以显著提高复合材料的抗冲击性能及冲击后的压缩性能；通过对冲击后凹坑深度及凹坑面积进行数据模拟，可以用拟合公式实现对复合材料的损伤预测。     

Development of mobile miniature natural gas liquefiers

With increasing consumption of natural gas (NG), small NG reservoirs, such as coalbed methane and oil field associated gas, have recently drawn significant attention. Owing to their special characteristics (e.g., scattered distribution and small output), small-scale NG liquefiers are highly required. Similarly, the mixed refrigerant cycle (MRC) is suitable for small-scale liquefaction systems due to its moderate complexity and power consumption. In consideration of the above, this paper reviews the development of mobile miniature NG liquefiers in Technical Institute of Physics and Chemistry (TIPC), China. To effectively liquefy the scattered NG and overcome the drawbacks of existing technologies, three main improvements, i.e., low-pressure MRC process driven by oil-lubricated screw compressor, compact cold box with the new designed heat exchangers, and standardized equipment manufacturing and integrated process technology have been made. The development pattern of “rapid cluster application and flexible liquefaction center” has been eventually proposed. The small-scale NG liquefier developed by TIPC has reached a minimum liquefaction power consumption of about 0.35 kW·h/Nm³. It is suitable to exploit small remote gas reserves which can also be used in boil-off gas reliquefaction and distributed peak-shaving of pipe networks.     

Investigation of flame spray synthesized La1-xSrxCoO3 perovskites with promotional catalytic performances on CO oxidation

To enhance the activity of catalysts for CO removal, the perovskite-type catalysts La_1-xSr_xCoO₃ (x = 0, 0.2, 0.4, 0.6, and 0.8) with different Sr²⁺ doping amount were synthesized by flame spray synthesis (FSS) method. The perovskite-type catalyst synthesized by FSS has a much larger specific surface area (SSA) than that prepared by other conventional methods. The SSA of catalyst increases with the increase of Sr²⁺ doping amount and the SSA of La_0.2Sr_0.8CoO₃ reaches 31.65 m²/g. Compared with other conventional methods, FSS method significantly improves the activity of catalyst and makes it close to the performances of catalysts with surface modification. The substitution of La³⁺ by Sr²⁺ promotes the generation of secondary phase Co₃O₄ and SrCO₃. The catalytic activity of La_1-xSr_xCoO₃ increases with the addition of Sr²⁺, which results from the increasing active sites and oxygen vacancies. Interestingly, La_0.4Sr_0.6CoO₃ performs the highest activity for CO oxidation and the CO conversion reaches 50% at 148.6 °C and 90% at 165.9 °C. The oxidation of CO over La_1-xSr_xCoO₃ catalyst may follow a combination of MvK and L-H mechanisms according to the experimental results of H₂-TPR. Moreover, the catalyst exhibits good catalytic activity in consecutive oxidation cycles. In consecutive oxidation experiments with La_0.4Sr_0.6CoO₃, the CO conversion reaches 50% at 168.8 °C and 90% at 197.8 °C in the eighth oxidation cycle. These results prove that FSS method can further improve the activity of catalysts and is suitable for the preparation of efficient catalysts.     

Prediction of process parameters of water-assisted injection molding based on inverse radial basis function neural network

Because of the introduction of new processing parameters in water-assisted injection molding (WAIM), processes control has become more difficult. First, design of experiment (DOE) was carried out by using optimized Latin hypercubes (Opt LHS). On the basis of this, computational fluid dynamics (CFD) method was used to simulate and calculate hollowed core ratios and wall thickness differences of cooling water pipe at different positions. Then inverse radial basis function (RBF) neural network model reflecting the fitting relationship between processing parameters and molding quality was established, and accuracy of the model was detected by cross validation. Finally, expected molding quality was applied to predict processing parameters, and the obtained molding quality under the predicted processing parameters was verified by computer aided engineering (CAE) simulation and experimental methods. The results showed that mean relative precisions of processing parameters such as melt temperature, delay time, short shot size, water pressure, and mold temperature for inverse RBF model were 98.6%, 93.6%, 98.5%, 93.9%, and 97.9%, respectively, which met the accuracy requirements. Furthermore, compared with expected values of hollowed core ratios and wall thickness differences, the average errors of CAE and experiment were 2.3% and 4.9%, respectively.     

基于聚类的数据加权优化在犯罪预测中的应用

近年来，我国传统暴力犯罪与成年人犯罪呈下降态势，但是，犯罪案由层出不穷。为有效提升公安实践工作中犯罪预测能力，打击各类违法犯罪事件,本文针对犯罪数据，提出一种新型犯罪预测模型。利用密度聚类分析方法将犯罪数据分类，然后进行数据降维提取关键属性生成特征数据，继而对特征数据进行加权优化并采用机器学习的方式对特征数据进行学习，从而预测犯罪案由。实验结果表明，与传统方法相比，本文方法具有更好的预测效果，为公安实践工作中类似案件的侦破和预防，提供新的路径支撑。     

基于注意力机制与文本信息的用户关系抽取

随着社交媒体的发展,用户之间的关系网络对于社交媒体的分析有很大的帮助。因此,该文主要研究用户好友关系检测。以往的关于用户好友关系抽取的研究主要基于社交媒体上的结构化信息,比如其他好友关系,用户的不同属性等。但是,很多时候用户本身并没有大量的好友信息存在,同时也不一定有很多确定的属性。因此,我们希望基于用户发表的文本信息来对用户关系进行预测。不同于以往的潜在好友推荐算法,该文提出了一种基于注意力机制以及长短时记忆网络(long short-term memory,LSTM)的好友关系预测模型,将好友之间的评论分开处理,通过分析用户之间的评论来判断是否具备一定的好友关系。该模型将好友双方信息拼接后的结果作为输入,并将注意力机制应用于LSTM的输出。实验表明,用户之间的评论对于好友关系预测确实有较大的实际意义,该文提出的模型较之于多个基准系统的效果,取得了明显的提升。在不加入任何其它非文本特征的情况下,实验结果的准确率达到了77%。     

Transformation of the reabsorption characteristics of lignite treated by low and high temperature drying process

Abstract

The reabsorption characteristics of the lignite treated by low and high temperature drying process were addressed in the paper. The information about the moisture form, functional groups, effective water-filled porosities and equilibrium moisture content of the lignite before and after the drying process was investigated using Differential scanning calorimetry (DSC), Fourier transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy and a self-made reabsorption device, respectively. The results show that the low drying temperature (140, 190, 230?°C, 10?min, N₂) has little impact on the effective water-filled porosities of the resulted samples, whereas it has a great influence on the main oxygen-containing functional groups, which amount firstly decreases and then increases with the drying temperature increasing. In the case of the lignite samples dried under high-temperature (600, 700, 800?°C, 30?s, N₂), the amount of the effective water-filled porosity of the sample decreases and the amount of oxygen-containing functional groups increases as the temperature increasing. The reabsorption capability of the high temperature dried sample is much lower than that of the sample treated under low drying temperature. The reabsorption characteristics of the low-temperature dried samples are affected by the amount of the oxygen-containing functional groups, while the effective water-filled porosity is main factor for the lignite samples derived from high temperature drying process. Moreover, the work gives a good evidence that the high-temperature drying process is an effective choose for lignite upgrading.     

基于P波模量的原位胶结充填体强度预测模型研究

原位胶结充填体质量评价通常采用单轴抗压强度作为表征指标,由于在现场工程中无法快速、准确获取充填体的强度值,因此需要建立一种参数易于获取且准确的原位胶结充填体强度预测模型。基于胶结充填体物理力学参数的内在联系,从量纲平衡的角度探索了胶结充填体单轴抗压强度与P波模量的关系。根据C矿和I矿两种原位胶结充填体的密度、P波速度及取芯强度的测试数据,采用线性拟合的方法获得了基于P波模量的原位胶结充填体强度预测模型。通过对C矿和I矿的强度预测模型拟合效果分析可知,P波模量与取芯强度呈正相关性,且拟合效果较好,证明原位胶结充填体强度预测模型精度高,具有很强的实用性。     

多裂纹混凝土等效断裂模型研究

根据混凝土材料断裂过程区存在尺寸效应这一特点,结合混凝土断裂韧度的尺寸效应规律,对混凝土有效裂缝扩展量进行了研究,得到反映尺寸效应规律的有效裂缝扩展量表达式,进而得到与试件尺寸相关的混凝土多裂纹等效断裂模型,使得多裂纹等效断裂模型更符合断裂过程区的尺寸效应规律。同时,通过与在实际工程中已用的其他模型的计算结果相比较,得出此模型比较可靠的结论。     

简化形式的系统EMC预测分析技术概述

本文探讨了系统级简化形式的电磁兼容性预测分析方法，该方法对于只有几对发-收干扰对的系统EMI的预测分析简洁有效，它避免了大系统间繁复的建模与大量的数据采集及其计算工作，从而对于只考虑其结果的系统间的EMC预测分析提高了效率。