Transit technology investment and selection under urban population volatility: A real option perspective

This paper addresses transit technology investment issues under urban population volatility using a real option approach. Two important problems are investigated: which transit technology should be selected and when should it be introduced. A real option model is proposed to incorporate explicitly the effects of transit technology investment on urban spatial structure in terms of households’ residential location choices and housing market. The trigger population thresholds for investing in a transit technology project and for shifting from a transit technology to another are explored analytically. Comparative static analyses of the urban system and transit technology investment are also carried out. It was found that (i) transit technology investment can induce urban sprawl; (ii) ignoring the effects of transit technology investment on urban spatial equilibrium can lead to a late investment; and (iii) there is a significant difference in the trigger population thresholds for transit technology shift estimated by the net present value approach and the real option approach.     

Voyage-based statistical fuel consumption models of ocean-going container ships in Korea

ABSTRACT

Accurately estimating fuel consumption of ships is crucial for shipping companies, port authorities, and environmental protection agencies. The bottom-up approach is becoming increasingly popular because it can estimate ship fuel consumption by accounting for ship activity conditions, such as changes in voyage speed, time, and distance; however, its use is still limited when estimating ship fuel consumption. Ship-specific information, such as the daily fuel consumption rate for main and auxiliary engines for every vessel, is expensive to gather, and generally not collected from private shipping companies. To address this research gap, we develop simplified and composite ship fuel consumption models for ocean-going container ships by size using a regression model. To estimate the fuel consumption models for container ships, we rely on ship activity data, including average speed and sailing time, distance, and actual fuel consumption for main and auxiliary engines. This information is obtained from a major container shipping company in Korea. We estimate and validate the parameters associated with fuel consumption for five different container ship sizes, all of which are smaller than the Post-Panamax container ship (15,000 TEU and above).     

Fluid-structure interaction and stress analysis of a floating wind turbine

In this paper, we describe a method to investigate the fluid-structure interaction of a floating wind turbine and to analyze the global deformations and the corresponding stresses with a detailed finite element model. To solve the fluid-structure interaction problem, a partitioned approach is chosen. The in-house C++ library comana, which was developed to solve multi-physic problems by coupling existing solvers, is extended to couple the fluid solver panMARE and the structural solver ANSYS. The significance of the interaction of structural deformations and the fluid loads is pointed out for the rotor of the wind turbine. In order to enable the use of a detailed finite element model in the fluid-structure interaction simulation, a model reduction method is applied in ANSYS. As a result, an efficient stress analysis can be performed under consideration of the fluid-structure interaction.     

某越野车车架拓扑优化设计

拓扑优化技术能在给定的设计空间内寻求最佳的材料分布。根据某越野车车架的实际尺寸建立其三维拓扑优化设计空间,以车架质量分数为约束条件,车架柔度最小为目标函数,对车架的弯曲工况进行了单工况拓扑优化设计,并针对这一工况选择不同的优化参数进行了多次优化计算,得到了一组相似的拓扑结构,分析并选择合适的拓扑优化参数。应用得到的拓扑优化参数,基于折衷规划的多目标拓扑优化设计方法,针对汽车使用情况选择合适的工况权重因子,对车架进行了3种工况下的多目标拓扑优化设计研究。     

基于过程方法的高职“机械制造工艺”课程教学过程的构建与实施

根据过程方法的内容要求,将高职"机械制造工艺"课程教学过程的构建与实施分为四个步骤,即课程教学目标与教学要求的确定,课程教学内容、方法、资源的选择和确定,课程考核内容与方法的选取,课程教学记录要求的确定,并对课程教学过程的构建与实施结果进行监控与改进。     

湘江土谷塘航电枢纽车江坝址通航水流条件分析

采用delft 3d技术,建立了湘江土谷塘车江坝址河段二维正交曲线水流数学模型.计算中,首先采用天然实测资料对模型进行率定,通过有关参数调整,使数值计算成果与天然实测资料达到精度要求.利用率定好的模型,模拟了湘江土谷塘航电枢纽车江坝址河段9种典型泄流方式的水流情况,分析了各泄流方式的河道流速分布特征,给出了引航道口门区...     

Percolation phenomenon in connected vehicle network through a multi-agent approach: Mobility benefits and market penetration

This paper presents an integrated multi-agent approach, coupled with percolation theory and network science, to measure the mobility impacts (i.e., mean travel time of the system) of connected vehicle (CVtio) network at varying levels of market penetration rate. We capture the characteristics of a CV network, i.e., node degree distribution, vehicular clustering, and giant component size to verify the existence of percolation phenomenon, and further connect the emergence of mobility benefits to the percolation phase transition in the CV network. We show the percolation phase transition properties to appear in a dynamic CV network with time-correlated link and node dynamics. An analytical framework was developed to evaluate the CV network attributes with varying market penetrations (MP) and connection ranges (CR) to identify percolation phenomenon in a mixed CV and Non-CV environment. In addition, a multi-agent CV simulation platform was created to further measure (1) how varying MPs and CRs affect the network-wide mobility measured by the mean travel time of the network; and (2) when percolation transition occurs in CV network to capture the critical MP and CR. Percolation phenomenon in CV network was further validated with the analytical assessments. The results show that (1) percolation phase transition phenomenon is a function of both market penetration and communication range; (2) percolation phase transitions in both mobility and CV network are highly correlated; (3) the application can reduce the average travel time of the system by up to 20% with reasonable market penetration and communication range; (4) critical market penetration is sensitive to communication range, and vice versa; (5) at least 70% of the CVs on the network are required to show in the same cluster for mobility benefits to appear; and (6) for high levels of MP or CR, a low probability of connectivity (PC) does not dramatically change the mean travel time. These results provide solid supports to create evidence-driven frameworks to guide future CV deployment and CV network analysis.     

An energy-efficient scheduling approach to improve the utilization of regenerative energy for metro systems

Regenerative braking is an energy recovery mechanism that converts the kinetic energy during braking into electricity, also known as regenerative energy. In general, most of the regenerative energy is transmitted backward along the pantograph and fed back into the overhead contact line. To reduce the trains’ energy consumption, this paper develops a scheduling approach to coordinate the arrivals and departures of all trains located in the same electricity supply interval so that the energy regenerated from braking trains can be more effectively utilized to accelerate trains. Firstly, we formulate an integer programming model with real-world speed profiles to minimize the trains’ energy consumption with dwell time control. Secondly, we design a genetic algorithm and an allocation algorithm to find a good solution. Finally, we present numerical examples based on the real-life operation data from the Beijing Metro Yizhuang Line in Beijing, China. The results show that the proposed scheduling approach can reduce energy consumption by 6.97% and save about 1,054,388 CNY (or 169,223 USD) each year in comparison with the current timetable. Compared to the cooperative scheduling (CS) approach, the proposed scheduling approach can improve the utilization of regenerative energy by 36.16% and reduce the total energy consumption by 4.28%.     

Deep subterranean railway system: Acceptability assessment of the public discourse in the Seoul Metropolitan Area of South Korea

The objective of this study is to analyze the public acceptability of deep subterranean railway systems, which will be constructed in the space 40 m below ground level and will be operated at twice the speed of the existing subway system. Although such railway systems have been feasible in terms of construction technologies and economics, public acceptability must be considered for the successful introduction of such a new public infrastructure. Therefore, to perform the analysis of public acceptability, a telephone-based survey was conducted for residents in the vicinity of the planned the deep subterranean railway systems. As a result, about 70% of the respondents answered that they took a neutral or opposing attitude to introducing the deep subterranean railway systems. Awareness of the deep subterranean railway systems has a positive impact on its acceptability. In addition, the acceptability is found to show a negative relationship with environment and inconvenience factors. Based on the analysis results, an affective approach through soft measures such as awareness campaigns and advertisements is recommended to effectively address and mitigate the concerns and issues raised by the public.     

A simple nonparametric car-following model driven by field data

Car-following models are always of great interest of traffic engineers and researchers. In the age of mass data, this paper proposes a nonparametric car-following model driven by field data. Different from most of the existing car-following models, neither driver’s behaviour parameters nor fundamental diagrams are assumed in the data-driven model. The model is proposed based on the simple k-nearest neighbour, which outputs the average of the most similar cases, i.e., the most likely driving behaviour under the current circumstance. The inputs and outputs are selected, and the determination of the only parameter k is introduced. Three simulation scenarios are conducted to test the model. The first scenario is to simulate platoons following real leaders, where traffic waves with constant speed and the detailed trajectories are observed to be consistent with the empirical data. Driver’s rubbernecking behaviour and driving errors are simulated in the second and third scenarios, respectively. The time–space diagrams of the simulated trajectories are presented and explicitly analysed. It is demonstrated that the model is able to well replicate periodic traffic oscillations from the precursor stage to the decay stage. Without making any assumption, the fundamental diagrams for the simulated scenario coincide with the empirical fundamental diagrams. These all validate that the model can well reproduce the traffic characteristics contained by the field data. The nonparametric car-following model exhibits traffic dynamics in a simple and parsimonious manner.