挂篮底模纵梁受力简化计算方法及承重分配系数

以一桥梁施工工程实例为依托,采用有限元软件ANSYS对桥梁悬臂施工中使用的菱形挂篮进行仿真分析.提出3种简化模式计算底模纵梁的承重分配,对比发现将底模纵梁承受的外荷载简化为集中荷载,并分配至挂篮下前后横梁的方法是最优简化计算方法.在此基础上对挂篮底模纵梁承重分配系数进行优化,从而简化了繁琐的挂篮底模纵梁受力分析计算,保证了挂篮结构设计和施工的安全.     

Hierarchal assessment of noise pollution in urban areas – A case study

Noise pollution in urban areas has many harmful effects on the citizens. There are varieties of noise generation sources of which the traffic noise could be a major source. The point which is perhaps less noticed is that sound level is not the only parameter to indicate the extent and intensity of noise pollution. Situation of urban land uses, distribution of population centers and types of passages can deeply affect the concern on this environmental issue but not with a similar ratio. This article presents an overlaying technique to define noise prone areas using all different factors involved. A case study was carried out in the District 14 of Tehran Metropolitan City where there are busy streets and highways. For this purpose, the share of each criterion in noise pollution intensity was determined using Analytical Hierarchy Process (AHP). Afterwards, the map layers were overlaid based upon the relative importance of the criteria to get the final map on which the noise prone areas are specified. The developed method could be used as a tool for indirect estimation of noise pollution by which instead of direct measurement of the equivalent sound level, it would be possible to predict noise susceptible areas considering the most important influential factors.     

STX1(2)型驮背多功能运输车超偏载检测标准

分析了STX₁₍₂)型驮背多功能运输车对既有超偏载检测方法和标准的适应性,提出了该车的超偏载检测方案,明确了公路货车或半挂车超偏载的检测方法及评判标准。     

Closed-form multiclass cell transmission model enhanced with overtaking,lane-changing,and first-in first-out properties

A novel multiclass macroscopic model is proposed in this article. In order to enhance first-in, first-out property (FIFO) and transmission function in the multiclass traffic modeling, a new multiclass cell transmission model with FIFO property (herein called FM-CTM) is extended from its prior multiclass cell transmission model (M-CTM). Also, to enhance its analytical compactness and resultant computational convenience, FM-CTM is formulated in this paper as a set of closed-form matrix equations. The objective is to improve the accuracy of traffic state estimation by enforcing FIFO property when a fast vehicle cannot overtake a slow vehicle due to a limitation of a single-lane road. Moreover, the proposed model takes into account a different priority for vehicles of each class to move forward through congested road conditions, and that makes the flow calculation independent from their free-flow speeds. Some hypothetical and real-world freeway networks with a constant or varying number of lanes are selected to verify FM-CTM by comparing with M-CTM and the conventional CTM. Observed densities of VISSIM and real-world dataset of I-80 are selected to compare with the simulated densities from the three CTMs. The numerical results show that FM-CTM outperforms the other two models by 15% of accuracy measures in most cases. Therefore, the proposed model is expected to be well applicable to the road network with a mixed traffic and varying number of lanes.     

内压载荷下X80管道裂纹应力分布规律研究

为了研究内压作用下管道裂纹应力场分布规律,以含有表面裂纹的X80管道为研究对象,对不同形状、不同方向、不同内压、不同尺寸的含裂纹管道进行仿真分析和实验验证。结果表明:裂纹尖端处应力远大于裂纹中心应力。裂纹形状对应力影响作用较小,随着裂纹方向与管道轴向夹角增大,裂纹尖端应力先增大后减小,随着管道内压、裂纹深度、裂纹长度的增大,裂纹尖端处应力随之线性增大。其中,裂纹长度对裂纹尖端应力的影响小于管道内压和裂纹深度。     

An improved cellular automaton with axis information for microscopic traffic simulation

Cellular Automaton (CA), an efficient dynamic modeling method that is widely used in traffic engineering, is newly introduced for traffic load modeling. This modeling method significantly addresses the modest traffic loads for long-span bridges. It does, however, require improvement to calculate precise load effects. This paper proposed an improved cellular automaton with axis information, defined as the Multi-axle Single-cell Cellular Automaton (MSCA), for the precise micro-simulation of random traffic loads on bridges. Four main ingredients of lattice, cells’ states, neighborhoods and transition rules are redefined in MSCA to generate microscopic vehicle sequences with detailed vehicle axle positions, user-defined cell sizes and time steps. The simulation methodology of MSCA is then proposed. Finally, MSCA is carefully calibrated and validated using site-specific WIM data. The results indicate: (1) the relative errors (REs) for the traffic parameters, such as volumes, speeds, weights, and headways, from MSCA are basically no more than ±10% of those of WIM data; (2) the load effects of three typical influence lines (ILs) with varied lengths of 50, 200 and 1000 m are also confidently comparable, both of which validate the rationality and precision of MSCA. Furthermore, the accurate vehicle parameters and gaps generated from MSCA can be applied not only for precise traffic loading on infrastructures but also for the accurate estimation of vehicle dynamics and safety. Hence, wide application of MSCA can potentially be expected.     

Methods to reduce dimensionality and identify candidate solutions in multi-objective signal timing problems

Adjusting traffic signal timings is a practical way for agencies to manage urban traffic without the need for significant infrastructure investments. Signal timings are generally selected to minimize the total control delay vehicles experience at an intersection, particularly when the intersection is isolated or undersaturated. However, in practice, there are many other potential objectives that might be considered in signal timing design, including: total passenger delay, pedestrian delays, delay inequity among competing movements, total number of stopping maneuvers, among others. These objectives do not tend to share the same relationships with signal timing plans and some of these objectives may be in direct conflict. The research proposes the use of a new multi-objective optimization (MOO) visualization technique—the mosaic plot—to easily quantify and identify significant tradeoffs between competing objectives using the set of Pareto optimal solutions that are normally provided by MOO algorithms. Using this tool, methods are also proposed to identify and remove potentially redundant or unnecessary objectives that do not have any significant tradeoffs with others in an effort to reduce problem dimensionality. Since MOO procedures will still be needed if more than one objective remains and MOO algorithms generally provide a set of candidate solutions instead of a single final solution, two methods are proposed to rank the set of Pareto optimal solutions based on how well they balance between the competing objectives to provide a final recommendation. These methods rely on converting the objectives to dimensionless values based on the optimal value for each specific objectives, which allows for direct comparison between and weighting of each. The proposed methods are demonstrated using a simple numerical example of an undersaturated intersection where all objectives can be analytically obtained. However, they can be readily applied to other signal timing problems where objectives can be obtained using simulation outputs to help identify the signal timing plan that provides the most reasonable tradeoff between competing objectives.     

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.     

Experimental study and modeling of car-following behavior under high speed situation

To investigate the car-following behavior under high speed driving conditions, we performed a set of 11-car-platoon experiments on Hefei airport highway. The formation and growth of oscillations have been analyzed and compared with that in low speed situations. It was found that there is considerable heterogeneity for the same driver over different runs of the experiment. This intra-driver heterogeneity was quantitatively depicted by a new index and incorporated in an enhanced two-dimensional intelligent driver model. Using both the new high-speed and the previous low-speed experimental data, the new and three existing models were calibrated. Simulation results show that the enhanced model outperforms the three existing car-following models that do not take into account this intra-driver heterogeneity in reproducing the essential features of the traffic in the experiments.     

The symmetric intersection design and traffic control optimization

It is well recognized that the left-turning movement reduces the intersection capacity significantly, because exclusive left turn phases are needed to discharge left turn vehicles only. This paper proposes the concept of Left-Hand Traffic (LHT) arterial, on where vehicles follow left-hand traffic rules as in England and India. The unconventional intersection where a LHT arterial intersects with a Right-Hand Traffic (RHT) arterial is named as symmetric intersection. It is only need three basic signal phases to separate all conflicts at symmetric intersection, while it at least need four signal phases at a conventional intersection. So, compared with the conventional intersection, the symmetric intersection can provide longer green time for the left-turning and the through movement, which can increase the capacity significantly. Through-movement waiting areas (TWAs) can be set at the symmetric intersection effectively, which can increase the capacity and short the cycle length furthermore. And the symmetric intersection is Channelized to improve the safety of TWAs. The Binary-Mixed-Integer-Linear-Programming (BMILP) model is employed to formulate the capacity maximization problem and signal cycle length minimization problem of the symmetric intersection. The BMILP model can be solved by standard branch-and-bound algorithms efficiently and outputs the lane allocation, signal timing decisions, and other decisions. Experiments analysis shows that the symmetric intersection with TWAs can increase the capacity and short the signal cycle length.