机场陆侧交通设施竖向布局模式研究

轨道交通设施引入机场后使机场陆测交通设施竖向布局设计更加复杂多样。分析了大型机场轨道交通线路走向与航站楼平面布局的关系,在剖析国内外各种实例的基础上,提出机场陆侧交通设施竖向布局模式;对各种模式的优缺点、换乘设施布局、旅客流程组织进行比较分析。     

Experienced travel time prediction for congested freeways

Travel time is an important performance measure for transportation systems, and dissemination of travel time information can help travelers make reliable travel decisions such as route choice or departure time. Since the traffic data collected in real time reflects the past or current conditions on the roadway, a predictive travel time methodology should be used to obtain the information to be disseminated. However, an important part of the literature either uses instantaneous travel time assumption, and sums the travel time of roadway segments at the starting time of the trip, or uses statistical forecasting algorithms to predict the future travel time. This study benefits from the available traffic flow fundamentals (e.g. shockwave analysis and bottleneck identification), and makes use of both historical and real time traffic information to provide travel time prediction. The methodological framework of this approach sequentially includes a bottleneck identification algorithm, clustering of traffic data in traffic regimes with similar characteristics, development of stochastic congestion maps for clustered data and an online congestion search algorithm, which combines historical data analysis and real-time data to predict experienced travel times at the starting time of the trip. The experimental results based on the loop detector data on Californian freeways indicate that the proposed method provides promising travel time predictions under varying traffic conditions.     

Brake light cellular automaton model with advanced randomization for traffic breakdown

Traffic breakdown is one of the most important empirical phenomena in traffic flow theory. Unfortunately, it cannot be simulated by many traffic flow models. In order to clarify its mechanism, the new brake light cellular automaton model has been proposed. Comparing with previous brake light models, three different aspects have been considered: (i) drivers tend to take large decelerations if the time gap is smaller than the safe time gap and the leading vehicle’s brake light is on; (ii) the brake light rule is set according to the reality; (iii) the randomization rule is put forward before the acceleration rule to weaken the impact of brake light on driving behaviors. Analyses show that the new model can explain the mechanism of traffic breakdown and the failures of other brake light models. Simulations confirm that all empirical features of traffic breakdown are successfully reproduced. At last, brake light models are calibrated and validated by the I-80 empirical data provided by NGSIM. Results show that the performance of the new model is the best and models in the three-phase theory are not necessarily better than models in the fundamental diagram approach and vice versa, at least for the brake light models.     

Spectral and time‐frequency analyses of freeway traffic flow

This paper uses spectral and time‐frequency analyses to treat three macroscopic traffic characteristics, namely, time mean speed, volume and occupancy as stochastic processes. Spectral and time‐frequency analyses are performed to characterize power spectral density (PSD), cross‐PSD, autocorrelation and cross‐correlation of these characteristics using TransGuide traffic data collected from four different freeways. It is found that low‐frequency components dominate the PSDs of speed, volume and occupancy at all times. The magnitude of PSDs decreases dramatically as frequency increases and remains almost at a constant level in high‐frequency regimes. A power law is found to exist, which describes the relationship between the frequency and the PSD of traffic characteristics. It is also found that speed can be properly modeled by a narrowband low‐pass stochastic process in a low‐frequency regime and by a nonzero mean white noise in a high‐frequency regime. Strong periodicities and synchronization are both shown in traffic flow. A variety of frequencies can be excited by congestion, and there is no dominant frequency found in stop‐and‐go traffic. Copyright © 2013 John Wiley & Sons, Ltd.     

关于辐流式二沉池设计计算方法的探讨

针对辐流式二沉池设计资料中存在的相关问题,从平面设计要点和竖向设计要点两方面分别对辐流式二沉池中设计流量的选定、沉淀池表面积计算、进出水口、污泥区容积计算,以及有效水深、池边水深和总池高计算等进行了探讨,并对刮(吸)泥设备和配水井的设计要点进行了相关说明.同时结合工程实践,优化平面设计参数和竖向设计参数,合理选择刮(吸)泥设备和配水井等辅助设施,能为相关技术人员提供一定的参考和借鉴意义.     

三叶片节气门进气系统的 CFD 计算和分析

以一款新型三叶片式节气门为主要研究对象，通过发动机台架试验，获得发动机稳态工况下进气歧管三维C FD计算的边界条件，选取不同转速、不同负荷率的12个有代表性的工况点，建立配置传统的单叶片节气门和三叶片节气门的进气歧管网格模型，并进行C FD计算和流场分析。结果表明：发动机处于中、高负荷时，由三叶片节气门产生的进气涡流比单叶片节气门大，且优势随节气门开度的增加而更加明显，但在低转速、小负荷的工况下，配置三叶片节气门的进气歧管内的涡流强度小于单叶片节气门。     

A framework for short-term traffic flow forecasting using the combination of wavelet transformation and artificial neural networks

The main objective of this paper is to develop a framework for short-term traffic flow forecasting models with high accuracy. Due to flow oscillations, the real-time information presented to the drivers through variable message signs, etc., may not be valid by the time the driver reaches the location. On the other hand, not all compartments of the flow signal are of same importance in determining its future state. A model is developed to predict the value of traffic flow in near future (next 5–35?minutes) based on the combination of wavelet transformation and artificial neural networks. This model is called the hybrid WT-ANN. Wavelet transformation is set to denoise the flow signal, i.e., filtering the unimportant fluctuations of the flow signal. Unimportant fluctuations are those that have little or no effect on the future condition of the signal. The neural network is set and trained to use previous data for predicting future flow. To implement the system, traffic data of US-101 were used from Next Generation Simulation (NGSIM). Results show that removing the noises has improved the accuracy of the prediction to a great extent. The model was used to predict the flow in three different locations on the same highway and a different highway in a different country. The model rendered highly reliable predictions. The proposed model predicts the flow of next 5?min on the same location with 2.5% Mean Absolute Percentage Error (MAPE) and of next 35?min with less than 12% MAPE. It predicts the flow on downstream locations for next 5?min with less than 8% MAPE and for the different highway with 2.3% MAPE.     

堆石混凝土砌体施工质量控制研究及实践

结合某沿河滨江路项目中堆石混凝土挡墙工程的现场试验,分别从原材料、工艺流程、试验和检测评定等环节探讨了堆石混凝土挡墙施工质量控制方法.结果表明：高比例含量的大粒径块（卵）石可以降低圬工结构水泥用量,使圬工结构的总释放热量和绝热温升显著降低,并能发挥大颗粒漂石及大块石对混凝土收缩的限制约束作用,抑制裂缝的产生与发展,从而满足施工质量控制要求.     

High-resolution numerical relaxation approximations to second-order macroscopic traffic flow models

A novel numerical approach for the approximation of several, widely applied, macroscopic traffic flow models is presented. A relaxation-type approximation of second-order non-equilibrium models, written in conservation or balance law form, is considered. Using the relaxation approximation, the nonlinear equations are transformed to a semi-linear diagonilizable problem with linear characteristic variables and stiff source terms. To discretize the resulting relaxation system, low- and high-resolution reconstructions in space and implicit–explicit Runge–Kutta time integration schemes are considered. The family of spatial discretizations includes a second-order MUSCL scheme and a fifth-order WENO scheme, and a detailed formulation of the scheme is presented. Emphasis is given on the WENO scheme and its performance for solving the different traffic models. To demonstrate the effectiveness of the proposed approach, extensive numerical tests are performed for the different models. The computations reported here demonstrate the simplicity and versatility of relaxation schemes as solvers for macroscopic traffic flow models.