基于CBM的船舶设备健康管理系统

结合分析基于CBM的船舶设备健康管理系统及其国内外研究现状,设计了系统实施流程、技术和功能架构;通过开展状态监控技术、综合诊断技术以及健康评估技术的研究,进行综合状态评估,实现船舶设备健康管理。最后,从数据采集、状态评估、性能预测和维修决策支持等方面对实现系统的关键技术进行论述。基于CBM的船舶设备健康管理系统实现了对船舶设备健康状态及趋势的实时知悉,并对使用、维修活动的决策提供了辅助支持功能,从而降低设备维修费用,提高船舶设备使用效能。     

长江南京以下12.5m深水航道二期工程安全应急方案研究

安全应急预案对于提高安全事故中的救援能力、减少安全事故带来的损失具有重要的意义。以南京以下12.5m深水航道二期工程为背景,对拟定的安全应急预案进行分析研究,总结出安全应急预案体系包括综合安全应急预案、专项应急预案和现场处置方案,提炼各层次预案对应的事件类型和具体内容,并编制首接责任制下的应急组织机构和应急流程。     

Emission rates of intermodal rail/road and road-only transportation in Europe: A comprehensive simulation study

Intermodal rail/road transportation combines advantages of both modes of transport and is often seen as an effective approach for reducing the environmental impact of freight transportation. This is because it is often expected that rail transportation emits less greenhouse gases than road transportation. However, the actual emissions of both modes of transport depend on various factors like vehicle type, traction type, fuel emission factors, payload utilization, slope profile or traffic conditions. Still, comprehensive experimental results for estimating emission rates from heavy and voluminous goods in large-scale transportation systems are hardly available so far. This study describes an intermodal rail/road network model that covers the majority of European countries. Using this network model, we estimate emission rates with a mesoscopic model within and between the considered countries by conducting a large-scale simulation of road-only transports and intermodal transports. We show that there are high variations of emission rates for both road-only transportation and intermodal rail/road transportation over the different transport relations in Europe. We found that intermodal routing is more eco-friendly than road-only routing for more than 90% of the simulated shipments. Again, this value varies strongly among country pairs.     

Papahānaumokuākea: Integrating Culture in the Design and Management of one of the World's Largest Marine Protected Areas

Papahānaumokuākea Marine National Monument is one of the world's largest marine protected areas and was designated the first mixed conservation site in the United States due to its natural and cultural importance. It is also the world's first cultural seascape, being recognized for its continuing connections to indigenous people. As the westernmost place in the Hawaiian universe, many believe these islands and seas are the pathway that Native Hawaiians travel after death, returning to pō (night; realm of the gods). This intimate kinship has profound implications for contemporary management. Current management emphasizes integration of science, policy, cultural knowledge, traditions, and practices to create successful management strategies appropriate for both natural and cultural resources. This management is based on Native Hawaiian values and practices that incorporate observation and understanding of the natural world, indigenous principles and philosophies, cultural norms, community relationships, and unique epistemologies deeply imbedded in and formed by relationships of people with place. A cornerstone of this effort has been the direct involvement of cultural practitioners in policy, management, education, and research. This biocultural approach has led to more effective management of the monument and serves as a model for conservation around the world.     

Situation analysis forecasting: the case of European maritime clusters

Within the literature concerned with aspects of competitiveness, innovation and strategic management of industrial clusters, the body regarding forecasting of strategic management is still nascent. This work aspires to render a contribution within the domain of strategic management forecasting, through the indicative case of European maritime clusters. For this end, a two-tier model is formulated. A quantitative strengths, weaknesses, opportunities, and threats (SWOT) methodology that derives from the fusion of a quondam situation analysis and crosstabs’ theory is generated. This leads to the utilization of the crosstab’s conditional probabilities as transition probabilities; the latter are called to compile the transition matrix of a Markov chain. Through this methodology, and the successive Markov chain’s transition matrices, strategic forecasts are extracted for a devised European maritime cluster case. This work relinquishes a novel application with respect to strategic management forecasting, that provides a dichotomy of practical interpretations and scenarios for quantitative situation analysis. Thus, it may enable effective real-time decision-making for strategic management and/or policy drafting. The situation analysis forecasting model may find applicability in a plethora of practical and theoretical cases, wherein forecasting may be desirable. It may as well pertain to an intrinsic methodology for situation analysis forecasting of maritime clusters.     

An integrated framework for embedding large-scale dynamic traffic assignment models in advanced traveler information systems

In recent years, increasing attention has been drawn to the development of various applications of intelligent transportation systems (ITS), which are credited with the amelioration of traffic conditions in urban and regional environments. Advanced traveler information systems (ATIS) constitute an important element of ITS by providing potential travelers with information on the network's current performance both en-route and pre-trip. In order to tackle the complexity of such systems, derived from the difficulty of providing real-time estimations of current as well as forecasts of future traffic conditions, a series of models and algorithms have been initiated. This paper proposes the development of an integrated framework for real-time ATIS and presents its application on a large-scale network, that of Thessaloniki, Greece, concluding with a discussion on development and implementation challenges as well as on the advantages and limitations of such an effort.     

基于城市文化生态下的交通系统规划设计思考

本文主要是通过分析城市不同功能的模块的内在属性,探究城市交通系统如何在适应城市文化生态系统的情况下,通过合理的规划设计,实现自身功能的最大化,其次详细的阐述了为何要将城市的文化生态系统融合于如今城市快速发展建设中融合,最后针对城市不同功能模块提出了相应有效的交通规划设计思路。     

Understanding members' carsharing (activity) persistency by using econometric model

Carsharing is an innovative travel alternative that has recently experienced considerable growth and become part of sustainable transportation initiatives. Although carsharing is becoming increasingly a popular alternative transportation mode in North America, it is still an under‐researched area. Current research is aimed at better understanding of the behavior of carsharing users. For every member, a two‐stage approach microsimulates the probability of being active in any month using a binary probit model and given that a particular member is active during a month, the probability of that member using the service multiple times using a random utility‐based model. The model is estimated using empirical data from one of the largest carsharing companies in North America. The model estimates reveal that the activity persistency of members is positively linked to previous behaviors for up to 4 months, and that the influence of previous months weakens over time. It also shows that some attributes of the traveler (gender, age, and language spoken at home) impact his or her behaviors. Copyright © 2010 John Wiley & Sons, Ltd.     

VMT, energy consumption, and GHG emissions forecasting for passenger transportation

Globalization, greenhouse gas emissions and energy concerns, emerging vehicle technologies, and improved statistical modeling capabilities make the present moment an opportune time to revisit aggregate vehicle miles traveled (VMT), energy consumption, and greenhouse gas (GHG) emissions forecasting for passenger transportation. Using panel data for the 48 continental states during the period 1998-2008, the authors develop simultaneous equation models for predicting VMT on different road functional classes and examine how different technological solutions and changes in fuel prices can affect passenger VMT. Moreover, a random coefficient panel data model is developed to estimate the influence of various factors (such as demographics, socioeconomic variables, fuel tax, and capacity) on the total amount of passenger VMT in the United States. To assess the influence of each significant factor on VMT, elasticities are estimated. Further, the authors investigate the effect of different policies governing fuel tax and population density on future energy consumption and GHG emissions. The presented methodology and estimation results can assist transportation planners and policy-makers in determining future energy and transportation infrastructure investment needs.     

Augmented Reality Vehicle system: Left-turn maneuver study

Augmented Reality “AR” is a promising paradigm that can offer users with real-time, high-quality visualization of a wide variety of information. In AR, virtual objects are added to the real-world view in real time. The AR technology can offer a very realistic environment for enhancing drivers’ performance on the road and testing drivers’ ability to react to different road design and traffic operations scenarios. This can be achieved by adding virtual objects (people, vehicles, hazards, and other objects) to the normal view while driving an actual vehicle in a real environment. This paper explores a new Augmented Reality Vehicle “ARV” system and attempts to apply this new concept to a selected traffic engineering application namely the left-turn maneuver at two-way stop-controlled “TWSC” intersection. This TWSC intersection experiment, in addition to testing the feasibility of the application, tries to quantify the size of gaps accepted by different driver’s characteristics (age and gender). The ARV system can be installed in any vehicle where the driver can see the surrounding environment through a Head Mounted Display “HMD” and virtual objects are generated through a computer and added to the scene. These different environments are generated using a well defined set of scenarios. The results from this study supported the feasibility and validity of the proposed ARV system and they showed promise for this system to be used in the field-testing for the safety and operation aspects of transportation research. Results of the left-turn maneuver study revealed that participants accepted gaps in the range of 4.0-9.0 s. This finding implies that all gaps below 4 s are rejected and all gaps above 9 s are likely to be accepted. The mean value of the left-turn time was 4.67 s which is a little bit higher than reported values in the literature (4.0-4.3 s). Older drivers were found to select larger gaps to make left turns than younger drivers. The conservative driving attitude of older drivers indicates the potential presence of reduced driving ability of elderly. Drivers’ characteristics (age and gender) did not significantly affect the left-turn time. Based on the survey questions that were handed to participants, most participants indicated good level of comfort with none or small level of risk while driving the vehicle with the ARV system. None of the participants felt any kind of motion sickness and the participants’ answers indicated a good visibility and realism of the scene with overall good system fidelity.