基于逐类组合支持向量机的边坡稳定性预测研究

首次采用逐类组合支持向量机（TCSVM）方法,用于解决边坡稳定性预测的问题。模型是先用支持向量分类机（SVC）对边坡状态进行判识,然后用支持向量回归机（SVR）建立边坡安全系数预测模型,再用建好的模型对未知边坡的稳定性进行判别和安全性系数预测。利用模型对71个边坡实例中的61个进行学习,10个进行检验。结果表明:TCSVM对边坡安全系数的预测结果均优于SVM和PCA-SVM。表明逐类组合支持向量机方法提高了安全性系数预测的准确率,对边坡稳定性研究具有积极意义。     

Magic Formula减振器数值模型的参数识别与虚拟调校

为研究减振器的调校和匹配,需要建立可以完整描述减振器的外特性曲线理论模型。介绍了一种新型减振器模型——Magic Formula减振器数值模型,同时给出了一种有效、精确地模型参数辨识方法。然后将模型参数化,嵌入到7自由度整车Simulink模型中,以整车的动力学性能为优化目标,联合Isight软件,使用多目标优化算法,在C级路面对减振器的阻尼特性进行虚拟调校。优化结果表明,调校后的减振器的阻尼特性能够较明显改善车辆的动力学性能。     

驾驶行为险态辨识方法

为实现险性驾驶行为状态的有效辨识,提出了一套驾驶行为险态辨识方法.以单位时间误操作率为依据,采用自底向上的分段算法实现了行为险态分级,采用因子方差分析,选取听觉感知、动视野、动视力、色觉、暗适应、注意力、判断能力、反应时这8项因子构成驾驶行为状态因子集,构建驾驶行为险态辨识特征向量,然后再对行为状态指标数据予以预先分级的前提下,采用单因子分析法对试验数据予以分析.并设计出BP神经网络行为险态辨识模型,最后进行了实例分析与计算.分析结果表明:反应时、注意力、判断能力3项指标在各分级间差异显著,故可作为驾驶行为险态辨识主因子,行为状态错判误差率为2.5％.     

基于COMSOL的气液两相流空隙率研究

文章利用电阻层析成像技术对管道内的气液两相流进行空隙率研究,并利用多物理场耦合软件COMSOL计算出了截面上单元的灵敏度系数,进而可得到空隙率值。文中还对气液两相流三种典型流型下的测量电压值分布形式进行了模拟,从而可以根据测量电压值的波动情况进行初步的流型辨识。该文提出的方法能够获得气液两相流的空隙率,对两相流体力学的研究以及工程应用都具有较大的价值。     

Coastal Hazards and the Built Environment on Barrier Islands: A Retrospective View of Nags Head n the Late 1990s

This article provides a summary of past disasters, and hazard mitigation initiatives in the state of North Carolina, with a focus on the barrier island of Nags Head. The article also highlights the application of GIS technology to assess (i) the built environment and the extent of development and tax base in the "danger" zones (floods, oceanfront hazard zone, incipient inlets); (ii) the status of pre-Flood Insurance Rate Mapping (FlRM) structures on developed parcels; and (iii) vacant land in relation to current zoning. Findings show that 72% of Nags Head was developed, with close to one-third of the developed parcels within the oceanfront hazard zone. A relatively high percentage of structures built prior to Nags Head's regular participation in the Flood Insurance Rate Mapping (FIRM) program also lie within incipient inlets and VE flood zones. These findings were used as part of Nags Head's ongoing hazard mitigation initiatives.     

Modeling, identification and simulation of DC resistance spot welding process for aluminum alloy 5182

Currently the aluminum alloy resistance spot welding(AA-RSW) has been extensively used for light weight automotive body-in-white manufacturing.However the aluminum alloys such as AA5182 have inferior weldability for forming the joint due to their high reflectiveness to heat and light.Therefore it is necessary to further develop the high performance control strategy and the set-up of a new welding schedule.The welding process identification is the essential issue where the difficulty arises from the fact that the AA-RSW is a nonlinear time-varying uncertain process which couples the thermal,electrical,mechanical and metallurgical dynamics.To understand this complicated physical phenomenon a novel dual-phase M-series pseudo-random electrical pattern is adopted to excite the AA-RSW electrical-thermal process and the thermal response is recorded according to the welding power outputs.Based on the experimental information,the transfer function of an AA-RSW electrical- thermal mechanism is identified,and the optimum model order and parameters are determined.Subsequently a control-oriented DC AA-RSW model is established to explore the welding power control algorithm.The simulated results of the control model show agreement with the experimental data,which validates its feasibility for the corresponding welding control.     

Risk-identification-based hybrid method for estimating the system reliability of existing jacket platforms under fire

This paper proposes a risk-identification-based hybrid method for estimating the system reliability of steel jacket structures under fire.The proposed method starts with risk identification;according to the results of hazard identification and Dow’s fire and explosion index(F&EI) methodology,the most dangerous hazard sources are determined.In term of each equipment layout in steel jacket structures,fire load is imposed and elasto-plastic analysis is performed.According to the deformed state of steel jacket structures,the weakest failure mode of steel jacket structures is identified.In order to know the effect on ultimate bearing capacity of the offshore structural system,a series of elasto-plastic analyses are performed in which single failure element contained in the weakest failure mode is removed from the whole offshore platform structural system.Finally,the failure function of the steel jacket structure is generated and the failure probability of the steel jacket structure system is estimated under fire by genetic algorithm via MATLAB program.     

Application of non-detective techniques in traditional masonry structures

Study on the non-destructive detection techniques and damage identification method is of great importance in protecting and rehabilitating the ancient architectural structure. In order to identify the location and the grade of structural damages, a multi-point microtremor measurement is performed on carved brick screen walls at Songjiang area in Shanghai, and the observed dynamic parameters (natural frequencies and natural modal) are obtained. On the other hand, the dynamic parameters of the original structure are calculated by finite-element-method (FEM). Normalizing the observed and calculated parameters on unified physical quantity, the damages are located by the variation on vibration modal, and the grade of structural damages is quantitatively evaluated by stiffness losses based on the variation on vibration modal.     

基于RFID的道路交通拥堵信息识别模型

为推动交通智能化发展,引入射频自动识别技术获取道路上车辆运行信息,进行基于RFID的车辆信息采集框架设计。然后利用信息融合约简方法计算交通流特征值,最后根据速度、密度、流量三变量建立基于模糊层次分析的道路拥堵评价模型,判定道路交通拥堵级别,并在此基础上提出道路交通拥堵峰值异常和总体评价并行的预警机制。实验分析表明,该模型能够快速准确地确定当前道路的拥堵状态,及时预警拥堵路段,保证道路行车通畅和安全。     

基于行程时间影响的关键路段识别与查找

从路段实际功能出发,提出基于路段与路径行程时间序列的相关性识别关键路段的方法.借鉴蒙特卡洛思想,以真实数据构造10万条随机路径验证该方法的可行性,并识别出对上海市路网行程时间有关键影响的路段集合.以上述集合为参照,利用模糊聚类及迭代累计平方和算法提取路段行程时间序列特征并构造两个新变量,结合基础属性建立二项Logit模型,从而主动查找关键路段.比较该模型与基础模型、随机分类器查找效果表明：基于最大归一化行程时间曲线聚类,其结果对关键路段识别模型的性能有提升效用;行程时间对数差分序列的结构性变点在路网和路段级别均有明显时间聚集特性,虽然其个数与路段关键性无明显关系,但其与常见波动程度指标相关性小,可保留用于描述行程时间波动常发性和聚集性.