大直径盾构管片水平拼装试验方法探究

大直径盾构管片水平拼装试验存在效率低下甚至失败的情况,不能真实全面反映产品尺寸精度。分析其原因除大直径管片体积大、重量大的因素外,主要原因在于现有的试验设备工装简陋、试验方法粗放、规范要求低等。结合当前水平拼装的规范要求,分析现有试验方法存在的不足,对现有拼装设备工装进行改造,制定高标准的、更加严格的工艺措施,创造性地提出在每层管片拼装时增加标高检测的新思路。将新方法应用于南京长江第五大桥夹江隧道工程管片水平拼装试验,结果良好,证明了此试验方法的科学性与有效性。     

Coloured Petri net-based traffic collision avoidance system encounter model for the analysis of potential induced collisions

The Traffic Alert and Collision Avoidance System (TCAS) is a world-wide accepted last-resort means of reducing the probability and frequency of mid-air collisions between aircraft. Unfortunately, it is widely known that in congested airspace, the use of the TCAS may actually lead to induced collisions. Therefore, further research regarding TCAS logic is required. In this paper, an encounter model is formalised to identify all of the potential collision scenarios that can be induced by a resolution advisory that was generated previously by the TCAS without considering the downstream consequences in the surrounding traffic. The existing encounter models focus on checking and validating the potential collisions between trajectories of a specific scenario. In contrast, the innovative approach described in this paper concentrates on quantitative analysis of the different induced collision scenarios that could be reached for a given initial trajectory and a rough specification of the surrounding traffic. This approach provides valuable information at the operational level. Furthermore, the proposed encounter model can be used as a test-bed to evaluate future TCAS logic changes to mitigate potential induced collisions in hot spot volumes. In addition, the encounter model is described by means of the coloured Petri net (CPN) formalism. The resulting state space provides a deep understanding of the cause-and-effect relationship that each TCAS action proposed to avoid an actual collision with a potential new collision in the surrounding traffic. Quantitative simulation results are conducted to validate the proposed encounter model, and the resulting collision scenarios are summarised as valuable information for future Air Traffic Management (ATM) systems.     

LNG船舷侧碰撞损伤场景下的极限强度研究

液化天然气(LNG)船的船体极限强度是衡量其安全性及环境适应性的重要指标。LNG船在受到撞击损伤后的安全性,不仅取决于船体结构的剩余极限强度,还取决于其围护系统中的绝缘箱能否在船体损伤状态下承受结构变形所引起的应力载荷。利用有限元数值仿真技术和ABAQUS软件,建立LNG船液舱围护系统以及舱段的有限元模型,模拟LNG船舷侧受撞击场景。在碰撞损伤基础上,对含有液舱围护系统的LNG船舱段开展极限强度研究,获取LNG船舱段结构的极限承载能力。研究发现在船体达到极限强度状态之前,液舱围护系统不会失效。     

基于模糊理论的船舶复合碰撞危险度计算

基于船舶领域和动界的概念,在船舶碰撞几何原理的基础上,利用模糊规则和模糊综合评价方法,本文提出一种船舶复合碰撞危险度的计算方法.确定最近会遇距离(DCPA)、最近会遇时间(TCPA)、两船距离、相对方位、船速比5个主要因素的隶属度函数,并考虑航行区域状况、能见度情况和船舶的操纵性能等对船舶碰撞危险度的隶属度函数修正.用原始数据对3种不同会遇态势进行仿真和对3种不同碰撞危险度计算结果分析比较,结果表明该方法的有效性.     

一种新的碰撞耗散能快速估算方法及其在船—平台碰撞事故中的应用研究

海洋平台在作业过程中存在遭受船舶碰撞的潜在危险,一旦事故发生将可能导致结构严重损伤从而影响平台的作业安全,因此在平台结构设计阶段需要考虑其抗撞性能.文章以海洋供应船撞击半潜式钻井平台为研究对象,基于碰撞外部动力学理论和DNV规范计算方法,计及平台艏摇运动响应的影响,提出了一种新的耗散能估算方法-DNV`R解析法.以非线性有限元船-平台碰撞数值仿真结果为参考,将该解析法与规范法、Zhang解析法及Liu解析法计算结果进行对比,研究得出:文中所提出的DNV`R解析法弥补了规范法较为保守且仅适用于对心碰撞场景的不足,计算过程简单、便捷,且计算精度与Zhang解析法和Liu解析法基本接近,能够满足船-平台碰撞耗散能快速估算的精度要求.     

Connectivity analysis of the global shipping network by eigenvalue decomposition

ABSTRACT

Maritime shipping necessitates flexible and cost-effective port access worldwide through the global shipping network. This paper presents an efficient method to identify major port communities, and analyses the network connectivity of the global shipping network based on community structure. The global shipping network is represented by a signless Laplacian matrix which can be decomposed to generate its eigenvectors and corresponding eigenvalues. The largest gaps between the eigenvalues were then used to determine the optimal number of communities within the network. The eigenvalue decomposition method offers the advantage of detecting port communities without relying on a priori assumption about the number of communities and the size of each community. By applying this method to a dataset collected from seven world leading liner shipping companies, we found that the ports are clustered into three communities in the global container shipping network, which is consistent with the major container trade routes. The sparse linkages between port communities indicate where access is relatively poor.     

一种新型在线长输管道管体检测技术

文中介绍一种以磁应力为原理的检测技术,即磁力断层摄影检测技术.该技术是一种非接触式的被动检测技术,可以检测出长输管道管体各类型缺陷.首先简单阐述了检测原理,其次详细说明了执行一次检测的全流程工作步骤,以及各步骤的工作内容,然后简要介绍了其独特的经验性计算MAOP和剩余寿命的公式,接着以实际试点检测工作为例,说明了该技术的可行性,最后指明了该技术的优缺点.     

Probabilistic multi-aircraft conflict detection approach for trajectory-based operation

Conflict detection (CD) is one of the key functions used to ensure air transport safety and efficiency. In trajectory-based operation (TBO), aircraft are provided with more flexibility in en route trajectory planning and more responsibility for self-separation. The high flexibility in trajectory planning enables random changes in pilot intent, thus increasing the uncertainty in trajectory prediction and CD. This study proposes a novel probabilistic CD approach for TBO in which the uncertainty of pilot intent is taken into account by quantifying the aircraft reachable domain constrained by the flight plan. First, a probabilistic model for aircraft trajectory prediction is developed using the truncated Brownian bridge method. Based on this model, a novel conflict probability estimation method is developed. Finally, the performance of the proposed probabilistic CD approach is demonstrated through an illustrative air traffic scenario.     

内河航道桥梁船撞时船体最大变形量研究

目前在桥梁船撞防护的专项设计或船撞力专题研究中,对船舶撞击力的研究和桥梁在船舶撞击作用下的响应关注较多,而对船体最大变形量的研究较少。基于ANSYSLS-DYNA软件,对4种不同载质量的内河代表船舶在3种航速、2种碰撞角度下撞击4种墩型的船撞工况进行数值模拟,提取船体最大变形量,并分析船体最大变形量与船舶载质量、撞击速度、桥墩类型及撞击角度的关联性,同时与经验公式做对比。研究结果表明,撞击速度及撞击角度是船体最大变形量的主要控制因素,桥墩类型与之关系不明显。     

Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics

With the increasing prevalence of geo-enabled mobile phone applications, researchers can collect mobility data at a relatively high spatial and temporal resolution. Such data, however, lack semantic information such as the interaction of individuals with the transportation modes available. On the other hand, traditional mobility surveys provide detailed snapshots of the relation between socio-demographic characteristics and choice of transportation modes. Transportation mode detection is currently approached using features such as speed, acceleration and direction either on their own or in combination with GIS data. Combining such information with socio-demographic characteristics of travellers has the potential of offering a richer modelling framework that could facilitate better transportation mode detection using variables such as age and disability. In this paper, we explore the possibility to include both elements of the environment and individual characteristics of travellers in the task of transportation mode detection. Using dynamic Bayesian Networks, we model the transition matrix to account for such auxiliary data by using an informative Dirichlet prior constructed using data from traditional mobility surveys. Results have shown that it is possible to achieve comparable accuracy with the most widely used classification algorithms while having a rich modelling framework, even in the case of sparse mobility data.