对台湾海峡隧道通行方式与施工方案的探讨

针对台湾海峡通道隧道与桥梁方案通行方式存在差异及施工技术更为复杂的问题,对通行电动汽车的可能性和隧道布置方案进行探讨,对台湾海峡隧道TBM施工的通风、运输、设备可靠性及工期控制等关键制约因素进行分析,认为从技术可靠、工期可控的原则出发,有必要布置人工岛对隧道施工段落进行分割。对人工岛的功能、结构方案提出了设想,对今后的研究工作提出了建议。     

Hydrodynamic inline force prediction on vertical cylinders: a comparative study of neural network and its adaptive wavelets (wavenets)

The design of the neural network model and its adaptive wavelets (wavelet networks and wavenets) was used to estimate the wave-induced hydrodynamic inline force acting on a vertical cylinder. The data used to calibrate and validate the models were obtained from an experiment. In the brain, wavelet neural networks (WNNs) use wavelets to activate their hidden layers of neurons. In WNNs, both the position and dilation of the wavelets are optimized along with the weights. In one special approach to this kind of network construction, the position and dilation of the wavelets are fixed and only the weights of the network are optimized. In the present study, the neural network procedure and the above mentioned approach were employed to design a WNN, a so-called wavenet, using feed-forward neural network topology and its training method. Then, a comparison of these two methods was made. Numerical results demonstrate that both networks are capable of predicting hydrodynamic inline force. Furthermore, the combination of the neural network concept and the wavelet theory i.e. wavenet provides a more robust tool rather than standard feed-forward neural network, considering its more appropriate ability to predict any other data which the network had not experienced before. The results of this study can contribute to reducing the errors in future efforts to predict hydrodynamic inline force using WNNs, and thus improve the reliability of that prediction in comparison to the ANN and other methods. Therefore, this method can be applied to relevant engineering projects with satisfactory results.     

Sound scattering from rough bubbly ocean surface based on modified sea surface acoustic simulator and consideration of various incident angles and sub-surface bubbles’ radii

The aim of the present study is to improve the capabilities and precision of a recently introduced Sea Surface Acoustic Simulator (SSAS) developed based on optimization of the Helmholtz–Kirchhoff–Fresnel (HKF) method. The improved acoustic simulator, hereby known as the Modified SSAS (MSSAS), is capable of determining sound scattering from the sea surface and includes an extended Hall–Novarini model and optimized HKF method. The extended Hall–Novarini model is used for considering the effects of sub-surface bubbles over a wider range of radii of sub-surface bubbles compared to the previous SSAS version. Furthermore, MSSAS has the capability of making a three-dimensional simulation of scattered sound from the rough bubbly sea surface with less error than that of the Critical Sea Tests (CST) experiments. Also, it presents scattered pressure levels from the rough bubbly sea surface based on various incident angles of sound. Wind speed, frequency, incident angle, and pressure level of the sound source are considered as input data, and scattered pressure levels and scattering coefficients are provided. Finally, different parametric studies were conducted on wind speeds, frequencies, and incident angles to indicate that MSSAS is quite capable of simulating sound scattering from the rough bubbly sea surface, according to the scattering mechanisms determined by Ogden and Erskine. Therefore, it is concluded that MSSAS is valid for both scattering mechanisms and the transition region between them that are defined by Ogden and Erskine.     

Dynamic network equilibrium for daily activity-trip chains of heterogeneous travelers: application to large-scale networks

Applications of dynamic network equilibrium models have, mostly, considered the unit of traffic demand either as one-way trip, or as multiple independent trips. However, individuals’ travel patterns typically follow a sequence of trips chained together. In this study we aim at developing a general simulation-based dynamic network equilibrium algorithm for assignment of activity-trip chain demand. The trip chain of each individual trip maker is defined by the departure time at origin, sequence of activity destination locations, including the location of their intermediate destinations and their final destination, and activity duration at each of the intermediate destinations. Spatial and temporal dependency of subsequent trips on each other necessitate time and memory consuming calculations and storage of node-to-node time-dependent least generalized cost path trees, which is not practical for very large metropolitan area networks. We first propose a reformulation of the trip-based demand gap function formulation for the variational inequality formulation of the Bi-criterion Dynamic User Equilibrium (BDUE) problem. Next, we propose a solution algorithm for solving the BDUE problem with daily chain of activity-trips. Implementation of the algorithm for very large networks circumvents the need to store memory-intensive node-to-node time-dependent shortest path trees by implementing a destination-based time-dependent least generalized cost path finding algorithm, while maintaining the spatial and temporal dependency of subsequent trips. Numerical results for a real-world large scale network suggest that recognizing the dependency of multiple trips of a chain, and maintaining the departure time consistency of subsequent trips provide sharper drops in gap values, hence, the convergence could be achieved faster (compared to when trips are considered independent of each other).     

Multiclass fuzzy user equilibrium with endogenous membership functions and risk‐taking behaviors

Over the last decades, several approaches have been proposed in the literature to incorporate users' perceptions of travel costs, their bounded rationality, and risk‐taking behaviors into network equilibrium modeling for traffic assignment problem. While theoretically advanced, these models often suffer from high complexity and computational cost and often involve parameters that are difficult to estimate. This study proposes an alternative approach where users' imprecise perceptions of travel times are endogenously constructed as fuzzy sets based on the probability distributions of random link travel times. Two decision rules are proposed accordingly to account for users' heterogeneous risk‐taking behaviors, that is, optimistic and pessimistic rules. The proposed approach, namely, the multiclass fuzzy user equilibrium, can be formulated as a link‐based variational inequality model. The model can be solved efficiently, and parameters involved can be either easily estimated or treated as factors for calibration against observed traffic flow data. Numerical examples show that the proposed model can be solved efficiently even for a large‐scale network of Mashhad, Iran, with 2538 links and 7157 origin–destination pairs. The example also illustrates the calibration capability of the proposed model, highlighting that the model is able to produce much more accurate flow estimates compared with the Wardropian user equilibrium model. Copyright © 2016 John Wiley & Sons, Ltd.     

Using stop bar detector information to determine turning movement proportions in shared lanes

Turning vehicle volumes at signalized intersections are critical inputs for various transportation studies such as level of service, signal timing, and traffic safety analysis. There are various types of detectors installed at signalized intersections for control and operation. These detectors have the potential of producing volume estimates. However, it is quite a challenge to use such detectors for conducting turning movement counts in shared lanes. The purpose of this paper was to provide three methods to estimate turning movement proportions in shared lanes. These methods are characterized as flow characteristics (FC), volume and queue (VQ) length, and network equilibrium (NE). FC and VQ methods are based on the geometry of an intersection and behavior of drivers. The NE method does not depend on these factors and is purely based on detector counts from the study intersection and the downstream intersection. These methods were tested using regression and genetic programming (GP). It was found that the hourly average error ranged between 4 and 27% using linear regression and 1 to 15% using GP. A general conclusion was that the proposed methods have the potential of being applied to locations where appropriate detectors are installed for obtaining the required data. Copyright © 2016 John Wiley & Sons, Ltd.     

An approximate method for the surge response of the tension leg platform

The solution for the Duffing equation in anonlinear vibration problem is studied in this paper. Clearly,in the case of the perturb parameter being a larger value, thetraditional perturbation method is no longer valid but theHomotopy Perturbation Method （HPM） is applicable usually.HPM is used to solve the weak and strong nonlineardifferential equations for finding the perturbed frequency ofthe response. The obtained frequencies via HPM and theapproximate method have good accordance for weak andstrong nonlinear differential equations. Additionally, thecalculated responses by use of the approximate method arecompared with the responses obtained from the Numericalmethod in the time history of the response and phase plane.The results represent ~ood accordance between them.