结构分割转换工法在地下空间开发中的应用及设想

为了更加快速、安全、高效地完成城市地下空间开发,以结构分割转换工法（CC工法）为研究内容,从工法内涵、工程实践和应用推广3个角度展开研究。首先,基于ＣＣ工法的最新研究成果,从结构分割、建造方案及节点处理3个方面详细介绍CC工法的核心内容;然后,结合工程实践对该工法进行验证性研究,重点比较跨中设缝与柱顶设缝方案的优缺点,介绍该工程地下结构分割、转换的过程,最终证实CC工法建造地下空间的合理性、灵活性及适用性;最后,进行CC工法在富水地层中应用的可行性研究,通过对CC工法与明挖法、暗挖法、型钢混凝土、地面预制装配式结构等技术进行结合应用研究,得出在特定的工程条件下,CC工法也具有与其他先进工法结合应用的价值。     

Railway reforms: do they influence operating efficiency?

This paper considers railway operations in 23 European countries during 1995–2001, where a series of reform initiatives were launched by the European Commission, and analyses whether these reform initiatives improved the efficiency of the railway systems. Efficiency is measured using Multi-directional Efficiency Analysis, which enables investigation of how railway reforms affect the inefficiencies of specific cost drivers. The main findings are that the reform initiatives generally improve technical efficiency but potentially differently for different cost drivers. Specifically, the paper provides empirical evidence that accounting separation is important for improving the efficiency in the use of both material and staff costs, whereas other reforms only influenced one of these factors.

船舶非线性横摇运动数值模拟研究

非线性大角横摇运动是危害船舶安全的重要因素,也是船舶水动力学关注的热点及难点问题。文章采用CFD方法,对某型驱逐舰船模在不同波长规则波中横浪航行时的横摇运动进行了数值模拟。通过与水池实验比对,数值仿真得到的稳定横摇幅值与实验值的误差在10%左右。同时,数值模拟证实了非线性横摇的两种典型特征—“多值”及“跳跃”现象。数值模拟结果表明,CFD方法可作为研究船舶非线性横摇运动的有效手段。     

长洲三线船闸人字门原型调试研究

为保证长洲三线船闸的正常安全运行,同时更好地积累大型船闸人字门运行经验,对长洲三线船闸人字门启闭特性进行原型观测与调试。结果表明：平水调试阶段,人字门系统运行平稳,启门力远小于启闭机额定容量,说明启闭设备设计合理;运行调试初期,闸室存在较严重的超灌（泄）现象,人字门活塞杆受压较大,可能超过启闭机的额定油压,易使液压杆受损;采用集控自动程序运行后,超灌（泄）现象得到较大改善,人字门活塞杆受力在正常允许范围内。证明原型观测与调试是保证实际工程安全运行的有效手段。     

一种ATS系统自动化测试工具的设计与实现

列车自动监控系统(ATS)是车载信号系统中的重要组成部分.本文提出一种ATS系统的非侵入式自动化测试工具,模拟测试人员真实测试的整个流程,可配置的测试脚本更具有灵活性,可以实现不同的测试需求;采用基于计算机视觉与光学字符识别的信息提取方式,使测试流程可以完全模拟真人测试;通过验证状态机的结果,简化了测试验证流程.该工具...     

新巴拿马型散货船系泊系统推荐布置

针对巴拿马运河扩建后,通航运河的散货船增多,前期建造的散货船由于系泊系统不合要求,不能通过运河的情况,根据巴拿马运河管理局2021年颁布的航运通告对系泊系统的布置要求,对某改造及新造两系列散货船,依次从艏、舯、艉部给出系泊系统的推荐布置,运营结果表明,船舶系泊系统布置方案满足相关规则及船东要求.     

Efficient missing data imputing for traffic flow by considering temporal and spatial dependence

The missing data problem remains as a difficulty in a diverse variety of transportation applications, e.g. traffic flow prediction and traffic pattern recognition. To solve this problem, numerous algorithms had been proposed in the last decade to impute the missed data. However, few existing studies had fully used the traffic flow information of neighboring detecting points to improve imputing performance. In this paper, probabilistic principle component analysis (PPCA) based imputing method, which had been proven to be one of the most effective imputing methods without using temporal or spatial dependence, is extended to utilize the information of multiple points. We systematically examine the potential benefits of multi-point data fusion and study the possible influence of measurement time lags. Tests indicate that the hidden temporal–spatial dependence is nonlinear and could be better retrieved by kernel probabilistic principle component analysis (KPPCA) based method rather than PPCA method. Comparison proves that imputing errors can be notably reduced, if temporal–spatial dependence has been appropriately considered.     

The visual impact of development in coastal zone areas

Abstract

The focus of this paper is theoretical, as well as methodological. It reviews previous studies of visual impact and reports research by the author on people's evaluation of the appropriateness of different man‐made facilities in different coastal‐area contexts and other environments. In this study, subjects were asked to react to slides developed through the use of landscape models and experimental facilities to simulate the appearance of a building in the landscape, while systematically varying the visual relatedness between the two. Specific interest centered on the variable of congruity vs. contrast between the appearance of the building and its landscape context, manipulated by co‐varying the attributes of color and size to create a five‐point scale of contrast/obtrusiveness. The hypothesis was that judgments of appropriateness, and to a lesser extent judgments of liking, would vary inversely with level of contrast. The role of two further variables, the functional significance of the building in its setting, and the character of the setting itself, was also investigated. The author reviews methodological issues involved where subjects respond to visual stimuli for purposes of judging change in visual quality. These methodological issues include: stimulus‐selection and problems of simulation, choice of response measures, and choice of respondents, and the treatment of individual differences. The author calls for development of standardized scales and indices such as “perceptually‐relevant environmental quality indicators.”     

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership estimates that account for day-to-day demand variations in the near future (e.g., next week, next month). It is one of the most critical tasks in high-speed passenger rail planning, operational decision-making and dynamic operation adjustment. An accurate short-term HSR demand prediction provides a basis for effective rail revenue management. In this paper, a hybrid short-term demand forecasting approach is developed by combining the ensemble empirical mode decomposition (EEMD) and grey support vector machine (GSVM) models. There are three steps in this hybrid forecasting approach: (i) decompose short-term passenger flow data with noises into a number of intrinsic mode functions (IMFs) and a trend term; (ii) predict each IMF using GSVM calibrated by the particle swarm optimization (PSO); (iii) reconstruct the refined IMF components to produce the final predicted daily HSR passenger flow, where the PSO is also applied to achieve the optimal refactoring combination. This innovative hybrid approach is demonstrated with three typical origin–destination pairs along the Wuhan-Guangzhou HSR in China. Mean absolute percentage errors of the EEMD-GSVM predictions using testing sets are 6.7%, 5.1% and 6.5%, respectively, which are much lower than those of two existing forecasting approaches (support vector machine and autoregressive integrated moving average). Application results indicate that the proposed hybrid forecasting approach performs well in terms of prediction accuracy and is especially suitable for short-term HSR passenger flow forecasting.     

Estimates of vertical mixing during a Lagrangian experiment off the Galician coast

An adjoint 1-D model was used to determine vertical diffusivity coefficients from temperature profiles collected within a filament escaping from the Galician coast following an upwelling event. The optimisation scheme ended with relatively high diffusivity values within the thermocline (9×10⁻⁵ m² s⁻¹). Such high values are relevant for biogeochemical exchanges between surface and deep waters in stratified areas.The optimised values were several orders of magnitude higher than the bulk of diffusivity measurements recorded with a free-falling device; however, the optimisation solution was consistent with the arithmetic mean of the measurements in the thermocline (7.7×10⁻⁵ m² s⁻¹), giving more weight to the few largest values. Below the thermocline, the data assimilation method failed because of the three-dimensional nature of the advective field of the upwelling system. Ignoring this advective forcing in the model led to estimates that were two orders of magnitude too high.The results suggest that turbulent mixing is a random process where a few intense events determine the average mixing that drives the long-term evolution of the water column structure. This statistical property is very important when one wants to use instantaneous diffusivity measurements for modelling purposes.