A finite element model for flexible pipe armor wire instability

The constructive disposition of metallic and plastic layers confers flexible pipes with high and low axial stiffness respectively when tensile and compressive loads are applied. Under certain conditions typically found during deepwater installation or operation, flexible pipes may be subjected to high axial compression, sometimes accompanied by bending. If not properly designed, the structure may not be able to withstand this loading and fails. From practical experience observed offshore and in laboratory tests two principal mechanisms, which will be discussed in this paper, have been identified regarding the configuration of the armor wires. When the pipe fails by compression the armor wires may exhibit localized lateral or radial deflections, consequently permanent damage is observed in the armor wires with a sudden reduction of the structure’s axial stiffness. The pressure armor may also unlock, thus causing potential fluid leakage.In this work a finite element model is developed to estimate the critical instability load and failure modes. An axi-symmetric model is constructed employing a complex combination of beam and spring elements. For each armor layer only one wire needs to be modeled, hence the computational cost is minimized without compromising the phenomenon characterization. A parametric case study is performed for a typical flexible pipe structure, where the friction coefficient between the wire armors and the external pressure are varied, and the critical instability loads and failure modes are obtained and results are discussed.     

通过形状差异修正模式方法进行的损伤识别试验(英文)

An experimental program was undertaken to test the feasibility to detect the occurrence of structural damage using a modified mode shape difference technique. The vibration response of a steel beam fixed at one end and hinged at the other was obtained for the intact and damage conditions. Modal analysis was performed to extract the frequencies and mode shapes. The method shows a good potential in detection of occurrence and location of damage.     

Income-contingent user preferences in policy evaluation: application and discussion based on multi-agent transport simulations

Standard economic policy evaluation allows the realization of projects if the aggregated economic benefit outweighs their costs. The use of one single aggregated welfare measure for evaluating and ranking projects has often been criticized for many reasons. A major issue is that differentiated effects on individuals or subgroups of the population are not taken into consideration. This leads to the need for transport planning tools that provide additional information for politicians and decision makers. The microscopic multi-agent simulation approach presented in this paper is capable of helping to design better solutions in such situations. In particular, it is shown that the inclusion of individual income in utility calculations allows a better understanding of problems linked to public acceptance. First, individual income-contingent utility functions are estimated based on survey data in order to describe human mobility behavior. Subsequently, using the MATSim framework, the implementation is tested in a test scenario. Furthermore, and going beyond Franklin (2006), it is shown that the approach works in a large-scale real world example. Based on a hypothetical speed increase of public transit, effects on the welfare distribution of the population are discussed. It is shown that the identification of winners and losers seems to be quite robust. However, results indicate that a conversion or aggregation of individual utility changes for welfare analysis is highly dependent on the functional form of the utility functions as well as on the choice of the aggregation procedure.     

A random utility maximization (RUM) based dynamic activity scheduling model: Application in weekend activity scheduling

The paper presents a modeling framework for dynamic activity scheduling. The modeling framework considers random utility maximization (RUM) assumption for its components in order to capture the joint activity type, location and continuous time expenditure choice tradeoffs over the course of the day. The dynamics of activity scheduling process are modeled by considering the history of activity participation as well as changes in time budget availability over the day. For empirical application, the model is estimated for weekend activity scheduling using a dataset (CHASE) collected in Toronto in 2002–2003. The data set classifies activities into nine general categories. For the empirical model of a 24-h weekend activity scheduling, only activity type and time expenditure choices are considered. The estimated empirical model captures many behavioral details and gives a high degree of fit to the observed weekend scheduling patterns. Some examples of such behavioral details are the effects of time of the day on activity type choice for scheduling and on the corresponding time expenditure; the effects of travel time requirements on activity type choice for scheduling and on the corresponding time expenditure, etc. Among many other findings, the empirical model reveals that on the weekend the utility of scheduling Recreational activities for later in the day and over a longer duration of time is high. It also reveals that on the weekend, Social activity scheduling is not affected by travel time requirements, but longer travel time requirements typically lead to longer-duration social activities.     

Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist

A recent survey reported that many commuter-cyclists had enjoyed leisure bicycling on a regular basis prior to becoming a commuter-cyclist. While bicycling for leisure, it is assumed that they considered various factors that led them to consider becoming commuter-cyclists. This study began with the question of how long it would take for a leisure-cyclist to become a commuter-cyclist, and it focused on the time that elapsed between leisure-cyclists transitioning to commuter-cycling. In order to analyze the time frame, it was hypothesized that the probability that a leisure-cyclist would become a commuter-cyclist at a certain time would be conditional on the duration that elapsed from the onset of leisure cycling till that time, which represents the “snowballing” or “inertial” dynamics of duration. A robust methodology, which is known as the “hazard model,” was adopted to accommodate such characteristics of a time period. In addition, various external covariates such as individual-specific characteristics, variables associated with the current or previous commuting mode, supply variables regarding bicycle facilities, and individual latent propensities were adopted to account for the duration of changes that would be generally applicable. As a result, many useful results were derived that could be used in fomenting policies to promote cycling to work. It was found that government should invest in establishing segregated lanes for leisure- and commuter-cyclists. It also turned out that a long distance to work hinders a leisure-cyclist from progressing to commuter-cycling. According to the results, young white-collar workers who live in high-rise apartments and enjoy intensive leisure-cycling in groups, are a good target toward whom promotions for commuter-cycling should be focused. However, an unfortunate development was that, when compared with car-commuters, it was found that transit-commuters are more likely to become commuter-cyclists.     

Quantifying the benefit of responsive pricing and travel information in the stochastic congestion pricing problem

This paper is concerned with roadway pricing amidst the uncertainty which characterizes long-term transportation planning. Uncertainty is considered both on the supply-side (e.g., the effect of incidents on habitual route choice behavior) and on the demand-side (e.g., due to prediction errors in demand forecasting). The framework developed in this paper also allows the benefits of real-time travel information to be compared directly against the benefits of responsive pricing, allowing planning agencies to identify the value of these policy options or contract terms in publicly-operated toll roads. Specifically, six scenarios reflect different combinations of policy options, and correspond to different solution methods for optimal tolls. Demonstrations are provided on both the Sioux falls and Anaheim networks. Results indicate that providing information to drivers implemented alongside responsive tolling may reduce expected total system travel time by over 9%, though more than 8% of the improvement is due to providing information, with the remaining 1% improvement gained from responsive tolling.     

Design and implementation of efficient transit networks: Procedure, case study and validity test

This paper presents and tests a method to design high-performance transit networks. The method produces conceptual plans for geometric idealizations of a particular city that are later adapted to the real conditions. These conceptual plans are generalizations of the hybrid network concept proposed in Daganzo (2010). The best plan for a specific application is chosen via optimization. The objective function is composed of analytic formulae for a concept’s agency cost and user level of service. These formulae include as parameters key demand-side attributes of the city, assumed to be rectangular, and supply-side attributes of the transit technology. They also include as decision variables the system’s line and stop spacings, the degree to which it focuses passenger trips on the city center, and the service headway. These decision variables are sufficient to define an idealized geometric layout of the system and an operating plan. This layout-operating plan is then used as a design target when developing the real, detailed master plan. Ultimately, the latter is simulated to obtain more accurate cost and level of service estimates.This process has been applied to design a high performance bus (HPB) network for Barcelona (Spain). The idealized solution for Barcelona includes 182 km of one-way infrastructure, uses 250 vehicles and costs 42,489 €/h to build and run. These figures only amount to about one third of the agency resources and cost currently used to provide bus service. A detailed design that resembles this target and conforms to the peculiarities of the city is also presented and simulated. The agency cost and user level of service metrics of the simulated system differ from those of the idealized model by less than 10%. Although the designed and simulated HPB systems provide sub-optimal spatial coverage because Barcelona lacks suitable streets, the level of service is good. Simulations suggest that if the proposed system was implemented side-by-side with the current one, it would capture most of the demand.