超长大直径钻孔灌注桩桩端承载力研究

阐述了超长大直径钻孔灌注桩桩端承载力的影响因素,包括施工工艺、深度效应和尺寸效应等。分析和对比了目前国内常用的各规范所采用的计算方法。文中算例的计算结果表明,对于同等条件的桩,各规范的计算结果相差较大。采用自平衡试桩法获得了几个重大工程的超长大直径钻孔灌注桩的桩端承载力的实测值。将工程实例的测试结果与各规范的计算结果进行对比,证实了目前规范的计算方法不尽合理。目前各规范中桩端承载力的计算方法是在针对小直径的中短桩的研究基础上建立的。如今,大型桥梁工程中普遍采用超长大直径钻孔灌注桩的情况下,对其桩端承载力的计算应当进行相应的调整,使设计更为合理。     

高速风洞引射式进排气动力模拟试验研究

为了测定具有埋入式进气道的某航弹发动机进排气对航弹的气动影响量 ,采用引射式动力模拟器在FL 7高速风洞 ,首次在国内成功地进行了高速风洞进排气动力模拟试验。试验模型缩比为 1∶1 0 ,M =0 .7,P0j/P∞ =2 .62 ,Cφ=0 .79。试验结果表明 ,有动力后XD,CL,CD增加 ,Cma减少。试验表明在高速风洞中对于小尺寸的试验模型 ,采用引射式动力模拟器开展进排气动力模拟试验是一种简便适用的好方法     

Banach空间中算子余弦函数的一个特征

本文主要研究Ｂａｎａｃｈ空间中算子余弦函数与二阶无阻尼方程的Ｃａｕｃｈｙ问题之间的某些关系,借助于此类Ｃａｕｃｈｙ问题的解的存在性与唯一性,给出算子余弦函数无穷小生成元的不同于Ｈｉｌｅ－Ｙｏｓｉｄａ型特征的另一个特征。     

超声速流中激波/湍流附面层干扰数值模拟

采用修正的B／L湍流模型以及多块结构化网格求解了二维N-S方程。分别对超声速流和高超声速流中的激波／湍流附面层干扰进行了数值研究。本文首先研究了进口马赫数为2．96的超声速流。计算结果准确预测了入射斜激波在平直壁面引起湍流附面层分离的流动特征：分离点的反射激波、分离包引起的膨胀扇以及再附点的反射激波。计算的壁面压力分布与实验值吻合较好，计算的分离区长度与实验值比较有一定误差。本文还对进口马赫数为9．22的高超声速流中压缩角引起的激波／湍流附面层干扰进行了数值研究。计算结果与实验结果吻合较好。     

用电离层特性参量提取等效风场信息

导出了利用中低纬电离层特性参量获取电离层F层峰区高度上等效风场（包含电场和风场信息在内）的基本方程，并尝试用该方法从电离层特性参量（峰高和临频）提取等效风场信息，利用武汉站DGS-256电离层数字测高仪数据及由美国Massachusetts Lowell大学最新版的剖面反演程序换算得到F层峰高，获得了武汉地区夏季至日点附近，冬季至日点附近，冬季地磁特别宁静的九天和冬季平均等效风场的初步特征，并利用Fejer经验电场模式计算冬季电场引起的垂直漂移，估计电场和风场对武汉地区的垂直等效风场的贡献大小，结果表明：等效风场呈现出白天与夜晚幅度和方向的差异。至日点附近冬季与夏季白天的幅度差异以及明显的凌晨凹陷现象；平均情况下，垂直等效风场幅度和方向的变化主要是由中性风引起，受电场的影响不大。     

基于脑电功率谱密度的作业人员脑力负荷评估方法

脑力负荷状态的准确识别对减少因作业人员无效脑力负荷导致的人因事故具有重要意义。针对人-机系统中作业人员脑力负荷客观评估问题开展了基于MATB-Ⅱ平台的3种不同脑力负荷水平下的航空情境实验，记录16名被试的NASA任务负荷指数（NASA-TLX）量表数据和脑电（EEG）信号，提出了一种基于脑电功率谱密度（PSD）和支持向量机（SVM）的个体脑力负荷评估方法。结果表明：随着实验设计脑力负荷水平增加，被试的主观脑力负荷得分显著提高（p<0.001），这表明该实验任务设计较好地诱发了低负荷、中负荷和高负荷情境。在此基础上，通过网格搜索法确定个体脑力负荷评估模型的统一优化参数，惩罚系数取3 000，核函数参数取0.000 1，模型测试正确率达到0.966 5±0.029 8，宏平均的受试者工作特征曲线下的面积（Macro-AUC）达到0.991 0±0.011 4。本文为作业人员脑力负荷状态的客观和准确评估提供了一种新的办法，为后期作业人员脑力负荷状态的实时判别提供模型基础。     

旅游者出游激励理论探讨

从期望理论的视角审视旅游者的决策过程,主要借鉴维克托.弗鲁姆(Victor H. Vroom)期望理论的相关原理,初步搭建了旅游者出游激励理论的基本框架,解决了旅游者决策依据问题。通过旅游感知效价、旅游感知成本等全新概念的引入和一系列调查问卷的设计,最终得出了出游激励力的完整表达式并有以下阶段性结论:(1)信息准备是旅游感知效价、旅游期望值2、旅游感知成本的直接来源;(2)旅游感知效价、旅游期望值2、旅游感知成本对旅游者做出决策至关重要;(3)出游激励力是旅游者最终做出决策的惟一依据。     

A general calculation method to specify center-of-buoyancy for the stratospheric airship with multiple gas cells

As the lighter-than-air (LTA) flight vehicle, the stratospheric airship is a desirable platform to provide communication and surveillance services. During the ascent from sea-level to the mission altitude, the volume of the lifting gas may change significantly, which will result in the change of the center-of-buoyancy (CB). A general calculation method is developed to specify CB for the stratospheric airship with a double-ellipsoid hull and an arbitrary number of the gas cells. The cross-section-integral (CSI) method is used as a basic calculation scenario to specify CB. Considering the complexity in determining the boundary between the helium and air in the gas cell, a searching algorithm is put forward and the specification of CB can be conducted by the iterative calculation. As an important application, the stable condition of the pitch angle is analyzed when the change of CB is involved. Under different initial configurations, the stable pitch angle of the stratospheric airship during the ascent is specified and compared, which shows the advantages of the multi-gas-cell configuration. The results of this paper may provide an important reference for the engineering application of the stratospheric airship.     

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.