半潜式钻井平台用钢DH36安定行为试验研究

为了给半潜式钻井平台的安全性和寿命评价提供可靠试验依据,在室温下对半潜式钻井平台用钢DH36钢进行了考虑加载波形、加载速率和应力比影响的多工况单轴棘轮安定试验。结果表明:循环硬化速率随循环周次的增加快速下降,在低于某一值的循环应力作用下,应变将最终趋于棘轮饱和状态;正弦应力波比三角波更快地趋于安定,采用较低的加载速率可以加速材料趋向饱和棘轮状态;峰值应力固定不变时,棘轮应变对应力比历史无明显的记忆性;波形和加载速率对饱和棘轮应变的影响有限,饱和棘轮应变随着应力峰值的增加而增大。     

Within day rescheduling microsimulation combined with macrosimulated traffic

The concept of rescheduling is essential to activity-based modeling in order to calculate effects of both unexpected incidents and adaptation of individuals to traffic demand management measures. When collaboration between individuals is involved or timetable based public transportation modes are chosen, rescheduling becomes complex. This paper describes a new framework to investigate algorithms for rescheduling at a large scale. The framework allows to explicitly model the information flow between traffic information services and travelers. It combines macroscopic traffic assignment with microscopic simulation of agents adapting their schedules. Perception filtering is introduced to allow for traveler specific interpretation of perceived macroscopic data and for information going unnoticed; perception filters feed person specific short term predictions about the environment required for schedule adaptation. Individuals are assumed to maximize schedule utility. Initial agendas are created by the FEATHERS activity-based schedule generator for mutually independent individuals using an undisturbed loaded transportation network. The new framework allows both actor behavior and external phenomena to influence the transportation network state; individuals interpret the state changes via perception filtering and start adapting their schedules, again affecting the network via updated traffic demand. The first rescheduling mechanism that has been investigated uses marginal utility that monotonically decreases with activity duration and a monotonically converging relaxation algorithm to efficiently determine the new activity timing. The current framework implementation is aimed to support re-timing, re-location and activity re-sequencing; re-routing at the level of the individual however, requires microscopic travel simulation.     

Modeling the behavioral determinants of travel behavior: An application of latent transition analysis

This paper applies the relatively new method of latent class transition analysis to explore the notion that qualitative differences in travel behavior patterns are substantively meaningful and therefore relevant from explanatory point of view. For example, because the bicycle may function as an important access and egress mode, a car user who also (occasionally) uses the bicycle may be more likely to switch to a public transit profile than someone who only uses the car. Data from the Dutch mobility panel are used to inductively reveal travel behavior patterns and model transitions in these patterns over time. Additionally, the effects of seven exogenous variables, including two important life events (i.e. moving house and changing jobs), on cluster membership and the transition probabilities are assessed. The results show that multiple-mode users compared to single-mode users are more likely to switch from one behavioral profile to another. In addition, age, the residential environment, moving house and changing jobs have strong influences on the transition probabilities between the revealed behavioral patterns over time.     

Using automated walking gait analysis for the identification of pedestrian attributes

Collecting microscopic pedestrian behavior and characteristics data is important for optimizing the design of pedestrian facilities for safety, efficiency, and comfortability. This paper provides a framework for the automated classification of pedestrian attributes such as age and gender based on information extracted from their walking gait behavior. The framework extends earlier work on the automated analysis of gait parameters to include analysis of the gait acceleration data which can enable the quantification of the variability, rhythmic pattern and stability of pedestrian’s gait. In this framework, computer vision techniques are used for the automatic detection and tracking of pedestrians in an open environment resulting in pedestrian trajectories and the speed and acceleration dynamic profiles. A collection of gait features are then derived from those dynamic profiles and used for the classification of pedestrian attributes. The gait features include conventional gait parameters such as gait length and frequency and dynamic parameters related to gait variations and stability measures. Two different techniques are used for the classification: a supervised k-Nearest Neighbors (k-NN) algorithm and a newly developed semi-supervised spectral clustering. The classification framework is demonstrated with two case studies from Vancouver, British Columbia and Oakland, California. The results show the superiority of features sets including gait variations and stability measures over features relying only on conventional gait parameters. For gender, correct classification rates (CCR) of 80% and 94% were achieved for the Vancouver and Oakland case studies, respectively. The classification accuracy for gender was higher in the Oakland case which only considered pedestrians walking alone. Pedestrian age classification resulted in a CCR of 90% for the Oakland case study.     

Incorporating human-factors in car-following models: A review of recent developments and research needs

Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams.It is necessary to consider human-factors in CF modeling for a more realistic representation of CF behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of CF models available in the literature, none of these specifically focuses on the human factors in these models.This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area.     

高弯拉强度水泥混凝土早期干缩变形性能研究

主要研究了水泥用量、胶凝材料类型、引气量、砂率等因素对混凝土干缩变形的影响。混凝土试件尺寸采用100 mm×100 mm×515mm,试验在控温控湿箱内进行,通过控温控湿箱的自动调节功能,设定目标温度和湿度过程,湿度按要求自动调节,利用千分表观察试件干湿变形值。湿度变化过程如下:从当前湿度用30 min升到相对湿度99%,恒定180 min,读取初值;用30 min降低湿度到10%,恒定180 min,读取终值;再用30 min升高湿度到99%,恒定180 min,读取初值,如此进行3个循环。试验结果表明:随水泥用量的增加,混凝土早期干缩变形增大;单掺硅灰的混凝土早期干湿变形大,单掺粉煤灰和混掺硅灰与粉煤灰的混凝土差别不大;3 d龄期的混凝土含气量越大,干湿变形也越大;28 d龄期以后,在含气量小于6.8%的情况下,干湿变形随含气量的增加而减小,而当含气量达到10%,干湿变形又呈现增大的趋势。     

新型GFRP组合梁翼缘有效分布宽度分析

利用能量变分法推导出均布线荷载作用下新型GFRP组合梁翼缘有效分布宽度的理论公式,通过有限元数值模拟验证理论公式可靠性。并借鉴传统钢-混凝土组合梁分析方法,对新型GFRP组合梁翼缘有效分布宽度各种影响因素进行了参数分析。     

32 m超低高度混凝土T梁动力性能试验与分析

为了研究开行120km/h货车后既有铁路32m超低高度混凝土T梁的运营状况、安全性和加固对策,选取1孔32m超低高度混凝土T梁进行自振频率、挠度、振幅等主要动力性能测试。结果发现跨中横向振幅超过限值,不能满足120km/h货车运行,需要提高该梁的竖向和横向刚度。     

某飞鸟式拱桥拱座开裂加固后静动载试验与分析

针对某飞鸟式拱桥拱座加固后结构性能进行静动载试验。分析了静载试验中控制位置变形、应变,吊杆轴力等控制指标,观测了拱座裂缝变化情况。并采用模态分析法比较动载试验所确定桥面前两阶振型及频率,对实测加速度及动挠度变化规律与理论结果进行比较,计算确定冲击系数。试验结果分析表明,该桥检测指标均能满足要求,行车性能较好。表明该桥拱座加固效果良好,使用性能比较理想,可适应设计荷载等级的要求。     

桩-土-结构相互作用对大跨度连续刚架钢桁拱桥地震响应影响研究

以广州新光大桥为例,研究软弱分层土、较软分层土、较硬分层土和岩石地基与群桩相互作用下大跨度连续刚架钢桁拱桥动力特性以及地震响应。研究表明在各种地震时程激励下,不同地基土对大跨度连续刚架钢桁拱桥拱肋以及V形刚架的内力和位移影响很大。随着地基土刚度的增加,在横桥向、顺桥向和竖向地震激励下,主拱肋和边拱肋上弦杆、V形刚架靠边跨斜腿轴力基本呈递减趋势,而V形刚架面内和面外弯矩随地基土刚度变化的规律性不强。