Evaluating determinants of attractiveness and their cause-effect relationships for container ports in Taiwan: users’ perspectives

The attractiveness of ports is usually a pre-requisite and necessary condition for ports to achieve competitiveness, as well as the springboard to explore the competitive advantages of ports. To determine whether a port is competitive, it is necessary to explore whether it boasts certain factors that make the port attractive to users. The main purpose of this article is to apply the Analytic Hierarchy Process (AHP) method and the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique to evaluate key determinants of attractiveness and their cause/effect relationships for container ports in Taiwan. The empirical results showed that: (1) Top six determinates of attractiveness for container ports are ‘ample cargo sources,’ ‘favorable port charges,’ ‘dense ship network and routes,’ ‘low transshipment costs,’ ‘efficient wharf operations,’ and ‘adequate wharfs and back-line land,’ respectively. (2) Among the above six determinants of attractiveness, ‘ample cargo sources’ is the cause determinant. Three determinants of port attractiveness, ‘favorable port charges,’ ‘dense ship network and routes,’ ‘low transshipment costs,’ which are the effect determinants. They are affected by the determinants of attractiveness of ‘ample cargo sources’. In addition, this study discusses the above findings and expects to provide the study results to Taiwan’s port authorities for reference.     

Analysis of volatility in driving regimes extracted from basic safety messages transmitted between connected vehicles

Driving volatility captures the extent of speed variations when a vehicle is being driven. Extreme longitudinal variations signify hard acceleration or braking. Warnings and alerts given to drivers can reduce such volatility potentially improving safety, energy use, and emissions. This study develops a fundamental understanding of instantaneous driving decisions, needed for hazard anticipation and notification systems, and distinguishes normal from anomalous driving. In this study, driving task is divided into distinct yet unobserved regimes. The research issue is to characterize and quantify these regimes in typical driving cycles and the associated volatility of each regime, explore when the regimes change and the key correlates associated with each regime. Using Basic Safety Message (BSM) data from the Safety Pilot Model Deployment in Ann Arbor, Michigan, two- and three-regime Dynamic Markov switching models are estimated for several trips undertaken on various roadway types. While thousands of instrumented vehicles with vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication systems are being tested, nearly 1.4 million records of BSMs, from 184 trips undertaken by 71 instrumented vehicles are analyzed in this study. Then even more detailed analysis of 43 randomly chosen trips (N = 714,340 BSM records) that were undertaken on various roadway types is conducted. The results indicate that acceleration and deceleration are two distinct regimes, and as compared to acceleration, drivers decelerate at higher rates, and braking is significantly more volatile than acceleration. Different correlations of the two regimes with instantaneous driving contexts are explored. With a more generic three-regime model specification, the results reveal high-rate acceleration, high-rate deceleration, and cruise/constant as the three distinct regimes that characterize a typical driving cycle. Moreover, given in a high-rate regime, drivers’ on-average tend to decelerate at a higher rate than their rate of acceleration. Importantly, compared to cruise/constant regime, drivers’ instantaneous driving decisions are more volatile both in “high-rate” acceleration as well as “high-rate” deceleration regime. The study contributes to analyzing volatility in short-term driving decisions, and how changes in driving regimes can be mapped to a combination of local traffic states surrounding the vehicle.     

考虑移步需求的无桩型共享单车动态调度研究

共享单车系统自发的不均衡性导致单车数量分布与用户需求分布之间产生偏移，降低了系统服务能力，需要调度实现再平衡. 现有动态调度算法缺乏考虑起点车辆供给不足，用户在出行过程中“再次”取车的移步需求，难以准确识别用户真实的出行需求分布，降低了调度效果. 本文提出以用户出行选择行为为下层，以调度车辆路径规划为上层的双层规划模型框架，设计结合仿真系统的启发式求解算法. 算例场景基于上海市虹口、杨浦区共享单车历史出行数据搭建，并进行网格化处理. 算例结果表明，模型能有效识别移步需求，提高共享单车的供需匹配能力. 针对各类调度资源配置情况，共享单车的供需匹配率提升18.07%~ 19.89%，提高了共享单车系统的管理效率.     

重载货车摩擦缓冲器阻抗特性的数值模拟

为预测摩擦缓冲器的实际工作状态,从几何特征和作用原理的角度,建立详细的MT-2型缓冲器理论模型。首先,通过对缓冲器内部各摩擦元件的运动学和静力学分析,推导出缓冲器在准静态下的阻抗特性;其次,引入附加摩擦系数量化各摩擦元件之间动静态摩擦过渡时的黏滞补偿,并模拟出缓冲器在动态下的阻抗特性;最后,利用C80型货车冲击试验数据对该缓冲器的理论模型进行验证。验证结果表明:总体上,数值模拟和现场试验下的缓冲器示功曲线基本吻合,说明模型的正确性;局部上数值模拟中缓冲器从加载Ⅰ阶段过渡至加载Ⅱ阶段的突变现象在冲击试验中表现的并不明显,还有待进一步完善。     

鱼雷定深航行稳定性的分叉分析

鱼雷定深运动方程含有诸多的非线性项，用传统的分析方法对其稳定性进行研究有较大难度。运用非线性科学中的分叉理论，选定鱼雷定深运动方程中的某一流体动力系数扰动值为分叉参数，系统地分析在经典比例微分深度控制系统作用下，鱼雷在退化平衡点处的航行稳定性。利用中心流形定理，推导出系统状态变量解析表达式，对系统 Hopf分叉进行分析，并进行仿真验证。结果表明，流体动力系数变化使定深航行产生 Hopf分叉，并给出了确保鱼雷稳定航行的流体动力参数取值范围。     

基于FLAC软件模拟强夯加固吹填砂地基

基于港区陆域吹填项目,采用FLAC软件建立三维模型,模拟了不同夯能、夯击次数对强夯效果的影响,对强夯前后杨氏模量的变化进行了分析研究。结果表明,表层吹填砂厚度和下卧软土层分布对夯能的大小起着决定作用。对于下卧松散砂层,可适当加大夯击能量和夯击次数(7~8击),增加其处理深度和效果;而对于下卧软黏土层,可以适当减小夯击能量并增加夯击次数,以提高加固效果。夯击之后,表层吹填砂的杨氏模量有较大的提高,从原来的10 MPa提高到20~40 MPa。     

水中悬浮隧道交通荷载模拟方法研究

为研究水中悬浮隧道交通荷载的合理模拟方法以及交通荷载对隧道结构的影响,借鉴铁路、公路交通荷载的模拟方法,综合考虑车辆轮载、路面不平度、行车速度以及外部激励荷载等影响因素的共同作用,提出水中悬浮隧道交通荷载的模拟表达式。通过数值模拟计算,分析悬浮隧道交通荷载的变化特征,并研究不同交通荷载模拟方法对悬浮隧道结构振动位移响应的影响。结果表明:文章提出的交通荷载模拟方法计算结果符合移动振动荷载的波动性和周期性特征。在对结构振动位移响应影响方面,固定均布荷载相当于静载,移动集中荷载和移动振动荷载时的位移变化幅值相对固定均布荷载时的大且影响相似,但移动振动荷载时的振幅稍大,体现了交通荷载中动荷载部分对结构振动位移响应的影响,更适合用来模拟悬浮隧道中的交通荷载。     

强夯置换法处理滨海公路软土路基

结合辽宁省滨海公路庄河市大张至中隈段的土质情况,阐述了强夯处理软土地基的设计方法、施工过程及处理后的地基效果.     

地震作用下钢筋混凝土桥墩抗倒塌性能研究

为研究混凝土桥墩的结构抗震性能,进行了单墩多自由度体系非线性静力推倒分析、非线性动力分析、增量动力分析。分别采用纤维模型中分布塑性铰和集中塑性铰两种建模方法,建立单墩有限元模型,利用Open Sees软件中的Hysteretic滞回模型考虑各种累积损伤的影响。     

沥青玛蹄脂混合料的高温性能影响因素分析

沥青玛蹄脂混合料作为良好的钢桥面铺装层材料,其高温性能一直是关注的焦点,本文基于室内车辙试验研究了其高温性能影响因素,重点分析了荷载和温度、拌合时间及加铺SMA对沥青玛蹄脂混合料的高温性能指标动稳定度的影响规律,为今后玛蹄脂混合料的路用实践提供了借鉴.