Importance of several nonlinear factors on broaching prediction

In order to realize a more quantitative prediction of broaching and capsizing in following and quartering seas, existing mathematical modelling techniques should be upgraded. Therefore, it is necessary to systematically examine all factors relevant to capsizing in following and quartering seas. To this end, we first attempted to examine the prediction accuracy of wave-induced forces by comparing calculations with captive model experiments. As a result, we found that a wave-induced surge force has a certain nonlinearitiy with respect to wave steepness. The nonlinearity of sway–roll coupling with respect to sway velocity was also found, and our numerical result with these nonlinearities improves the prediction accuracy of the critical ship speed of capsizing in following and quartering seas. The importance of the wave effect on propeller thrust was also examined. We found that this effect is not negligibly small and could improve capsizing predictions in heavy following and quartering seas. Finally, we attempted to investigate the importance of nonlinear heel-induced hydrodynamic forces on numerical predictions of capsizing due to broaching. Here, we propose a new procedure for captive model experiments to obtain hydrodynamic forces with various heel angles up to 90°, and data on heel-induced hydrodynamic forces with respect to heel angle in calm water are provided. We then compare the numerical simulations with the nonlinear heel-induced hydrodynamic forces and without them. These time series comparisons show that the effect of nonlinear heel-induced hydrodynamic forces in calm water is not negligibly small for the case of ship capsizing due to broaching.     

Synthesis of experimental designs of maneuvering captive-model tests with a large number of factors

An approach to synthesizing D-optimized experimental designs for an arbitrary number of factors was developed and tested on a third-order polynomial regression model with 5–8 factors. Three options were envisaged for the internal optimization procedure: an exhaustive search, a quasirandom search with the help of the Sobol sequences, and a genetic algorithm. The calculations performed have shown the pronounced superiority of the variant involving a genetic algorithm. Captive-model tests with a catamaran model with varying Froude number, drift angle, rate of yaw, sinkage, trim, and heel are presented as an example of the practical synthesis of the experimental design. The linear regression model constructed is a third-order 5-factor polynomial with respect to all factors except the Froude number. The influence of the latter is accounted for by representing the polynomials regression coefficients as functions of the Froude number represented as a truncated Fourier series with a linear term added.     

A CIP-based method for numerical simulations of violent free-surface flows

A CFD model is proposed for numerical simulations of extremely nonlinear free-surface flows such as wave impact phenomena and violent wave–body interactions. The constrained interpolation profile (CIP) method is adopted as the base scheme for the model. The wave–body interaction is treated as a multiphase problem, which has liquid (water), gas (air), and solid (wave-maker and floating body) phases. The flow is represented by one set of governing equations, which are solved numerically on a nonuniform, staggered Cartesian grid by a finite-difference method. The free surface as well as the body boundary are immersed in the computation domain and captured by different methods. In this article, the proposed numerical model is first described. Then to validate the accuracy and demonstrate the capability, several two-dimensional numerical simulations are presented, and compared with experiments and with computations by other numerical methods. The numerical results show that the present computation model is both robust and accurate for violent free-surface flows.     

Breaking wave at the bow of a fast displacement ship model

We investigated the flow structures under the bow wave generated by a fast displacement ship model (INSEAN model 2340) in the presence of wave breaking. The data acquired were also used for a detailed database for CFD validation. The mean and r.m.s. point-wise values of the wave height were measured by means of a finger probe. The intensity of the breaking wave was taken as the r.m.s value of the wave height. The mean velocity field under the free surface was measured at 0.15 L _PP and 0.2 L _PP downstream of the fore perpendicular by means of a 5-hole Pitot probe. Uncertainty assessment of the wave height and velocity field results was performed following the AIAA Standards S-071-1995. Preliminary CFD results from a RANSE code with a breaking model are shown in comparison with the measured data.     

The implications on willingness to pay of respondents ignoring specific attributes

Individuals processing the information in a stated choice experiment are typically assumed to evaluate each and every attribute offered within and between alternatives, and to choose their most preferred alternative. However, it has always been thought that some attributes are ignored in this process for many reasons, including a coping strategy to handle ones perception of the complexity of the choice task. Nonetheless, analysts typically proceed to estimate discrete choice models as if all attributes have influenced the outcome to some degree. The cognitive processes used to evaluate trade-offs are complex with boundaries often placed on the task to assist the respondent. These boundaries can include prioritising attributes and ignoring specific attributes. In this paper we investigate the implications of bounding the information processing task by attribute elimination through ignoring one or more attributes. Using a sample of car commuters in Sydney we estimate mixed logit models that assume all attributes are candidate contributors, and models that assume certain attributes are ignored, the latter based on supplementary information provided by respondents. We compare the value of travel time savings under the alternative attribute processing regimes. Assuming that all attributes are not ignored and duly processed, leads to estimates of parameters which produce significantly different willingness to pay (WTP) to that obtained when the exclusion rule is invoked.     

Modeling household activity–travel interactions as parallel constrained choices

The daily activity-travel patterns of individuals often include interactions with other household members, which we observe in the form of joint activity participation and shared rides. Explicit representation of joint activity patterns is a widespread deficiency in extant travel forecasting models and remains a relatively under-developed area of travel behavior research. In this paper, we identify several spatially defined tour patterns found in weekday household survey data that describe this form of interpersonal decision-making. Using pairs of household decision makers as our subjects, we develop a structural discrete choice model that predicts the separate, parallel choices of full-day tour patterns by both persons, subject to the higher level constraint imposed by their joint selection of one of several spatial interaction patterns, one of which may be no interaction. We apply this model to the household survey data, drawing inferences from the household and person attributes that prove to be significant predictors of pattern choices, such as commitment to work schedules, auto availability, commuting distance and the presence of children in the household. Parameterization of an importance function in the models shows that in making joint activity-travel decisions significantly greater emphasis is placed on the individual utilities of workers relative to non-workers and on the utilities of women in households with very young children. The model and methods are prototypes for tour-based travel forecasting systems that seek to represent the complex interaction between household members in an integrated model structure.     

An evaluation of web site services in liner shipping in Taiwan

This paper empirically evaluates web site services in the liner shipping industry based on the service requirements of the user firms, i.e., shippers. The results suggest that shippers perceive tracing to be the most important service attribute of a web site, followed by customs response, vessel schedules, and electronic document service. Based on the concept of market segmentation, we employed cluster analysis to classify users (shippers) of web site services provided by liner shipping companies into four segments, namely support and performance services oriented firms, equipment information oriented firms, performance information oriented firms, and transaction services oriented firms. Theoretical and practical implications of the research findings are discussed.     

Refocusing the Modelling of Freight Distribution: Development of an Economic-Based Framework to Evaluate Supply Chain Behaviour in Response to Congestion Charging

The distribution of freight is a major contributor to the levels of traffic congestion in cities. However it is much neglected in the research and planning activities of government, where the focus is disproportionately on passenger vehicle movements. Despite the recent recognition of the contribution of freight transportation to the performance of urban areas under the rubric of city logistics, we see a void in the study of how the stakeholders in the supply chain might cooperate through participation in distribution networks, to reduce the costs associated with traffic congestion. Given that transport costs are typically over 45 of all distribution costs, with congestion a major contributor in the urban setting, the importance of establishing ways in which supply chain partnerships might cooperate to reduce levels of freight vehicle movements has much merit. This paper sets out a framework to investigate how agents in a retail supply chain might interact more effectively to reduce the costs of urban freight distribution. We propose an interactive agency choice method as a way of formalising a framework for studying the preferences of participants in the supply chain to support specific policy initiatives. Such a framework is a powerful way of investigating the behavioural response of each agent to many policies, including congestion pricing, as a way of improving the efficient flow of traffic in cities.     

Does telecommuting reduce vehicle-miles traveled? An aggregate time series analysis for the U.S.

. This study examines the impact of telecommuting on passenger vehicle-miles traveled (VMT) through a multivariate time series analysis of aggregate nationwide data spanning 1966–1999 for all variables except telecommuting, and 1988–1998 for telecommuting. The analysis was conducted in two stages. In the first stage, VMT (1966–1999) was modeled as a function of conventional variables representing economic activity, transportation price, transportation supply and socio-demographics. In the second stage, the residuals of the first stage (1988–1998) were modeled as a function of the number of telecommuters. We also assessed the change in annual VMT per telecommuter as well as VMT per telecommuting occasion, for 1998. The models suggest that telecommuting reduces VMT, with 94% confidence. Together with independent external evidence, the results suggest a reduction in annual VMT on the order of 0.8% or less. Even with impacts that small, when informally compared to similar reductions in VMT due to public transit ridership, telecommuting appears to be far more cost-effective in terms of public sector expenditures.     

Short-Term Prediction of Travel Time using Neural Networks on an Interurban Highway

The main purpose of this study was to investigate the predictability of travel time with a model based on travel time data measured in the field on an interurban highway. Another purpose was to determine whether the forecasts would be accurate enough to implement the model in an actual online travel time information service. The study was carried out on a 28-kilometre-long rural two-lane road section where traffic congestion was a problem during weekend peak hours. The section was equipped with an automatic travel time monitoring and information system. The prediction models were made as feedforward multilayer perceptron neural networks. The main results showed that the majority of the forecasts were close to the actual measured values. Consequently, use of the prediction model would improve the quality of travel time information based directly on the sum of the latest measured travel times.