强夯法处治浅层小煤窑采空区

浅层小煤窑采空区给高速公路的建设带来较大困扰,采用强夯法处治工程造价低、治理效果显著、工期短、施工难度小,具有良好的社会及经济效益。     

高速公路动态交通流Elman神经网络模型

为了提高高速公路交通流建模的精度,分析了离散的高速公路动态交通流数学模型,基于Elman网络原理,建立了回归神经网络交通流模型。回归神经网络的输入层、上下文层、隐含层和输出层的节点数目分别选为8、30、30和2,采用Levenberg-Marquardt算法对回归神经网络进行训练,并对一条5路段的高速公路进行仿真。结果表明:回归神经网络平均相对误差为8.683 7×10-5,最大相对误差为4.237 1×10-4,与BP神经网络和RBF神经网络相比较,Elman回归神经网络能更好地逼近交通流数学模型,真实地描述交通流基本特性,能准确地建立动态交通流模型,适应交通状况的变化。     

新型负阶跃动态扭矩校准装置

针对扭矩传感器静态校准无法完全满足实际需要的难题,设计一种新型100 N·m负阶跃动态扭矩校准装置,并阐述该装置的工作原理和关键技术。校准装置由扭矩产生装置、连接系统、制动系统、信号处理控制系统和空气轴承系统组成,利用火工拔销器产生负阶跃动态扭矩,较大程度上降低负阶跃动态扭矩的下降时间,并采用空气轴承的支承方式提高动态扭矩的传递精度。通过对试验数据进行分析和处理,结果表明该装置负阶跃扭矩产生时间低于0.1 ms。不确定度分析结果显示,该装置的扩展不确定度U为4.22%,扩展因子k为2。     

动力定位船舶全速度路径跟踪CB导引自适应闭环控制

针对仅使用槽道推进器提供横向推力的动力定位船舶路径跟踪控制问题,建立慢变环境干扰影响下的非线性船舶数学模型,设计带有自适应干扰补偿的反步控制算法来消除环境干扰的影响。引入平行目标接近(CB)导引算法为跟踪控制生成期望速度矢量信号,通过与所提出的自适应反步控制算法相结合,得到不受船舶驱动特性限制的全速度范围动力定位船舶导引跟踪控制算法,应用李雅普诺夫稳定性理论证明系统跟踪误差渐进收敛到零。仿真结果表明通过调整导引算法参数可以调节船舶跟踪过程表现,并可以得到较好的控制精度。     

船闸闸室结构的船-墙碰撞三维有限元分析

以江苏某重力式船闸闸室结构为例,采用ABAQUS软件建立船舶-闸室结构-土体三维有限元模型,对船舶撞击闸室进行瞬态动力分析,得到不同工况下的撞击力时程曲线和撞击力值等结果。研究结果表明:船舶撞击闸室的法向平均撞击力大小与船舶排水量的12次方、撞击速度的1次方、撞击角度的1次方成线性关系;将软件模拟的船舶法向撞击力数值与依据JTJ 307—2001《船闸水工建筑物设计规范》得到的计算值比较,发现规范公式得到的数值普遍偏小,低估了过闸船舶撞击力的影响。     

FPSO单点系泊系统安装及回接技术

单点系泊系统作为浮式生产储油卸油装置（Floating Production Storage and Offloading,FPSO）的核心组成部分,需在FPSO进入安装现场之前完成安装,随后FPSO进入安装现场进行回接。以我国南海某具体工程项目为背景,全面、系统地介绍FPSO悬链腿单点系泊系统的安装及回接方法,并采用OrcaFlex分析软件对各个施工步骤进行相关的模拟分析。该单点系泊系统的整个安装过程可分为抓地锚安装、下段锚腿铺设、锚腿张紧、上段锚腿铺设、单点浮筒拖航及就位和锚系回接单点浮筒等6个阶段。     

重载情况下船舶及主机加速问题分析

针对目前一些船舶在恶劣海况下遇到的加速问题,以及通过转速禁区时间过长的问题,从螺旋桨匹配和主机内部设计两方面进行原因分析。围绕转速禁区功率裕度,结合相关案例,从轻螺旋桨裕度、转速禁区及MAN主机输出扭矩能力等方面入手,提出改进措施。     

An integrated framework for embedding large-scale dynamic traffic assignment models in advanced traveler information systems

In recent years, increasing attention has been drawn to the development of various applications of intelligent transportation systems (ITS), which are credited with the amelioration of traffic conditions in urban and regional environments. Advanced traveler information systems (ATIS) constitute an important element of ITS by providing potential travelers with information on the network's current performance both en-route and pre-trip. In order to tackle the complexity of such systems, derived from the difficulty of providing real-time estimations of current as well as forecasts of future traffic conditions, a series of models and algorithms have been initiated. This paper proposes the development of an integrated framework for real-time ATIS and presents its application on a large-scale network, that of Thessaloniki, Greece, concluding with a discussion on development and implementation challenges as well as on the advantages and limitations of such an effort.     

Estimation of origin-destination matrices from link counts and sporadic routing data

Estimation of origin-destination (OD) matrices from link count data is a challenging problem because of the highly indeterminate relationship between the observations and the latent route flows. Conversely, estimation is straightforward if we observe the path taken by each vehicle. We consider an intermediate problem of increasing practical importance, in which link count data is supplemented by routing information for a fraction of vehicles on the network. We develop a statistical model for these combined data sources and derive some tractable normal approximations thereof. We examine likelihood-based inference for these normal models under the assumption that the probability of vehicle tracking is known. We show that the likelihood theory can be non-standard because of boundary effects, and provide conditions under which such irregular behaviour will be observed in practice. For regular cases we outline connections with existing generalised least squares methods. We then consider estimation of OD matrices under estimated and/or misspecified models for the probability of vehicle tracking. Theoretical developments are complemented by simulation experiments and an illustrative example using a section of road network from the English city of Leicester.