双频激电法在某地热勘查中的应用

主要介绍采用双频激电测深对江西某地区地热进行勘查.以视电阻率为主,对不同测深点所测得的数据进行处理、一维反演,结合地质资料,圈定低阻含水层,进一步作出规划,以便降低钻探的成本.     

企业信息化建设探析

进入市场经济迅速发展、企业间竞争日益激烈的当今时代,信息化程度的高低成为体现企业核心竞争力的重要表现形式。企业间的有形竞争逐步演变为企业间软实力的无形竞争。通过利用先进信息技术,构建协同办公交流平台,促使公司内部各个部门之间、公司和外部门户之间能够进行高效的协作和沟通,起到降本增效的作用,同时为公司决策层提供有效的信息保证。     

3维Copula函数在降雨特征多变量频率分析中的应用

鉴于径流数据缺乏且难以长期监测而降雨数据相对完整,通常假定降雨和径流同频率,采用设计降雨进行水文分析计算,但此方法很难真实全面地反映降雨变化特征.为此,提出一种基于3维Copula函数的降雨特征多变量频率分析方法.首先利用降雨强度法将连续的降雨时间序列分割成若干个降雨事件,采用年最大值法取样,统计出表征雨量的特征变量,然后引入3维Copula函数构建降雨特征3变量联合概率模型,并以广州1961~2012年历史降雨数据为例进行分析.结果表明,基于3维Copula函数的多变量分析方法计算简单、可靠性高,可以进行3种不同降雨特征变量的组合分析,得到各种不同量级变量的遭遇概率和条件概率,能够更全面地反映降雨特征并更好地满足水文分析计算需求.     

金属Al电子结构与热力学性质的第一性原理计算

针对金属Al的电子结构与热力学性质,采用基于密度泛函理论的第一性原理以及CASTEP软件进行了理论计算,得到了金属Al的平衡晶格常数、相关弹性系数、电子能带、态密度、声子谱、声子态密度以及相关热力学参数,并对计算结果进行了理论分析.结果表明,金属Al具有明显的导电特性与良好的塑性.金属Al具有3条声学支波色散曲线与一个声子态密度峰.随着温度的增加,熵、焓均增加,而自由能减少.热容量随着温度的增加而迅速增加,当温度达到500 K后,热容量几乎不变,所得结论与物理规律相符合.     

锈蚀损伤混凝土管桩水平承载性状时变分析

为研究锈蚀损伤混凝土管桩的水平承载性状,依据Fick第二定律,建立了氯离子在混凝土管桩中的扩散方程,并结合初始和边界条件,得到扩散方程的解析解.依据厚壁圆筒模型,推导了钢筋混凝土管桩保护层锈胀开裂时的钢筋临界锈蚀深度.基于Faraday定律,对钢筋混凝土管桩保护层锈胀开裂时间进行了预测.并在此基础上,通过引入桩身抗弯刚度折减系数对海洋环境下锈蚀损伤钢筋混凝土管桩的桩身抗弯刚度的衰减规律进行了探讨,进而对海洋环境下锈蚀损伤钢筋混凝土管桩的水平承载性状的时变特性进行了分析.结果表明:海洋环境中氯离子侵蚀引起的钢筋锈蚀对钢筋混凝土管桩的水平承载性状有明显影响.随着暴露时间的延长,桩身抗弯刚度呈非线性衰减,桩身水平位移和桩身负剪力最大值逐渐增大,桩身弯矩逐渐减小.     

斜拉索耦合振动模型及其参数分析

考虑支撑构件对斜拉索参数振动的影响,从整体振动角度研究斜拉索的非线性参数振动特性,提出一个耦合索支撑结构模型.该模型既考虑了斜拉索的几何非线性,也考虑了支撑构件的运动对斜拉索振动的影响.应用多尺度法对该模型进行摄动分析,得到该模型参数振动时的激励频率及稳定区域边界,讨论模型质量比、刚度比和倾角等参数对幅频响应及稳定性的影响.研究表明,索的非线性参数振动特性并不随质量比和刚度比单调递增,而是存在某一临界值,使索的非线性参数振动特性最大化;随着倾斜角度的增加,索的非线性参数振动特性是单调递增.     

规范法土钉轴力计算对比分析

土钉墙支护结构在目前具有很强的现实意义,由于工程设计人员对土钉受力机理的不同理解,从而选择不同的设计规范,得出不同的计算结果.本文以包头某深基坑工程为实例,使用建筑工程现行的3种规范对上部土钉墙支护结构的土钉轴力计算,对比分析这3种规范法计算结果的差异性,并讨论产生差异性的原因,为以后本地区类似工程提供一些计算参考.     

Hydraulic Self Servo Swing Cylinder Structure Optimization and Dynamic Characteristics Analysis Based on Genetic Algorithm

The dynamic characteristics of hydraulic self servo swing cylinder were analyzed according to the hydraulic system natural frequency formula. Based on that, a method of the hydraulic self servo swing cylinder structure optimization based on genetic algorithm was proposed in this paper. By analyzing the four parameters that affect the dynamic characteristics, we had to optimize the structure to obtain as larger the Dm(displacement) as possible under the condition with the purpose of improving the dynamic characteristics of hydraulic self servo swing cylinder. So three state equations were established in this paper. The paper analyzed the effect of the four parameters in hydraulic self servo swing cylinder natural frequency equation and used the genetic algorithm to obtain the optimal solution of structure parameters. The model was simulated by substituting the parameters and initial value to the simulink model. Simulation results show that: using self servo hydraulic swing cylinder natural frequency equation to study its dynamic response characteristics is very effective. Compared with no optimization, the overall system dynamic response speed is significantly improved.     

A Semi-Supervised WLAN Indoor Localization Method Based on 1-Graph Algorithm

For indoor location estimation based on received signal strength (RSS) in wireless local area networks (WLAN), in order to reduce the influence of noise on the positioning accuracy, a large number of RSS should be collected in offline phase. Therefore, collecting training data with positioning information is time consuming which becomes the bottleneck of WLAN indoor localization. In this paper, the traditional semi-supervised learning method based on k-NN and ε-NN graph for reducing collection workload of offline phase are analyzed, and the result shows that the k-NN or ε-NN graph are sensitive to data noise, which limit the performance of semi-supervised learning WLAN indoor localization system. Aiming at the above problem, it proposes a 1-graph-algorithm-based semi-supervised learning (LG-SSL) indoor localization method in which the graph is built by 1-norm algorithm. In our system, it firstly labels the unlabeled data using LG-SSL and labeled data to build the Radio Map in offline training phase, and then uses LG-SSL to estimate user’s location in online phase. Extensive experimental results show that, benefit from the robustness to noise and sparsity of 1-graph, LG-SSL exhibits superior performance by effectively reducing the collection workload in offline phase and improving localization accuracy in online phase.