Influence of turbulence closure models on the vortical flow field around a submarine body undergoing steady drift

Manoeuvring underwater vehicles experience complex three-dimensional flow. Features include stagnation and boundary layer separation along a convex surface. The resulting free vortex sheet rolls up to form a pair of streamwise body vortices. The track and strength of the body vortex pair results in a nonlinear increase in lift as body incidence increases. Consequently, accurate capture of the body vortex pair is essential if the flow field around a manoeuvring submarine and the resulting hydrodynamic loading is to be correctly found. This work highlights the importance of both grid convergence and turbulence closure models (TCMs) to the strength and path of the crossflow-induced body vortices experienced by the DOR submarine model at an incidence angle of 15°. Five TCMs are considered; Spalart–Allmaras, k-ε, k-ω, shear stress transport, and the SSG Reynolds stress model. The SSG Reynolds stress model shows potential improvements in predicting both the path and strength of the body vortex over standard one- and two-equation TCMs based on an eddy viscosity approach.     

High‐speed rail cost recovery time based on an integer optimization model

With increasing gasoline prices, electric high‐speed rail (HSR) systems represent one means to mitigate overexposure to volatile prices. However, additional research is needed related to funding this infrastructure. In this paper, we develop a new integer optimization model to address this problem and use a hypothetical case study to demonstrate the approach. The objective of the approach is to minimize the time period in which the cost of HSR construction and operation can be recovered. This is an iterative process based on an integer optimization model, whose objective function is to determine the optimum recovery time (ORT), by setting the HSR ticket price and frequency. Embedded in the optimization model is a multinomial logit model for calculating the demand for HSR as a function of these decision variables, thus capturing the effects of level of service on market share. In particular, the optimization model accounts for the role of different types of subsidies toward HSR construction (one‐time subsidies at construction, annual subsidies, and subsidies depending on frequency). This method can also help determine whether an HSR system should be built or how much subsidy should be provided given a fixed expected cost recovery time. By integrating the logit model into the objective function evaluation, the effects of ticket price and service frequency on service demand can be directly captured. Copyright © 2014 John Wiley & Sons, Ltd.     

Collecting longitudinal data from freight operators: survey design and implementation ideas and challenges

Freight transport research has generally been limited by a lack of data of the breadth and quality available for passenger transport, particularly in terms of behavioural data. This paper discusses the survey design and implementation of a survey intended to collect longitudinal behavioural data on the responses of freight transport firms to environmental policies. The design of the survey is centred around a hypothetical scenario where respondents are asked how they would complete a given freight task within common constraints. One of the key components of the survey design is a dynamic component intended to simulate the changing business environment. The paper illustrates the many challenges in getting complex freight related surveys in the field.     

Policy implementation of multi-modal (shared) mobility: review of a supply-demand value proposition canvas

ABSTRACT

Urban mobility options have increased in recent years, assisted by the widespread availability of smart device software apps, geo-positioning technology, and convenient electronic financial transactions. Multi-modal shared mobility consists of public transit systems and shared mobilities that support first/last mile travel, denoting the capability of Mobility as a Service (MaaS), and to stimulate additional non-private car travel demand. This paper reviews the supply and demand sides of implementation of multi-modal shared mobility. It found that an abundance of shared modes of car, bike, and e-scooter that are linked to public transport, can improve transport accessibility to meet specific public preferences, reduce social inequality, and minimise dilemmas from the demand side. This study introduces government policy innovations and other supporting system to improve the implementation of multi-modal shared mobility. Government policies play a key role in supporting shared mobility and technology development. However, governments do not have much information about new products such as shared mobility, which creates difficulties in subsidising multi-modal shared mobility services and potentially leads to policy failures around shared mobility schemes. This study suggests that policy entrepreneurship in collaboration with other partners, policy innovation, and the notions of merit goods and second-best policymaking can enable policy initiatives towards multi-modal shared mobility and provide supporting arguments if policies encounter failures. Implementing multi-modal shared mobility requires a collaborative partnership for a paradigm shift: service providers and government must jointly set a merit-based business model, with the support of organisations to achieve improved infrastructure provision, and smart technology applications. The findings will assist the community, business providers and government policymakers to promote multi-modal shared mobility as a pathway towards more efficient, environmentally sustainable, and socially responsive mobility solutions.     

The Smeed Report 50 years on: a role for the workplace parking levy?

Fifty years ago, Reuben Smeed chaired a study and produced a Report on the Economic and Technical Possibilities of Road Pricing. This report was to consider different methods of charging, including road pricing, to see if different pricing methods could reduce the problems associated with congestion as opposed to the traditional methods in place such as fuel tax. Since that time, various attempts have been made to introduce road pricing schemes but with only modest success so far. By contrast parking policies, a second-best alternative to road pricing, have been extensively used by local authorities as a means of managing congestion. The effectiveness of such policies, however, has been limited by an increase in the proportion of privately owned non-residential parking which is not under the control of local authorities. The aim of this paper is to present the results of an early-stage, post-implementation study of the Nottingham Workplace Parking Levy (WPL) – a measure that charges employers for the number of parking spaces they provide for their staff. Particular emphasis is placed on why a WPL was seen as being favourable compared to a road pricing alternative. The reason for this was that it could be introduced in a shorter time frame and at a lower cost, thus making it a lower risk option when compared with road pricing.     

Can we reduce car use and, if so, how? A review of available evidence

Transport accounts for nearly a quarter of current energy-related carbon dioxide emissions with car travel constituting more than three quarters of all vehicle kilometres travelled. Interventions to change transport behaviour, and especially to reduce car use, could reduce CO₂ emissions from road transport more quickly than technological measures. It is unclear, however, which interventions are effective in reducing car use and what the likely impact of these interventions would be on CO₂ emissions. A two-stage systematic search was conducted focusing on reviews published since 2000 and primary intervention evaluations referenced therein. Sixty-nine reviews were considered and 47 primary evaluations found. These reported 77 intervention evaluations, including measures of car-use reduction. Evaluations of interventions varied widely in the methods they employed and the outcomes measures they reported. It was not possible to synthesise the findings using meta-analysis. Overall, the evidence base was found to be weak. Only 12 of the 77 evaluations were judged to be methodologically strong, and only half of these found that the intervention being evaluated reduced car use. A number of intervention approaches were identified as potentially effective but, given the small number of methodologically strong studies, it is difficult to draw robust conclusions from current evidence. More methodologically sound research is needed in this area.     

International experience with speed limits during and prior to the energy crisis of 1973–4

This paper presents an artificial neural network (ANN) based method for estimating route travel times between individual locations in an urban traffic network. Fast and accurate estimation of route travel times is required by the vehicle routing and scheduling process involved in many fleet vehicle operation systems such as dial‐a‐ride paratransit, school bus, and private delivery services. The methodology developed in this paper assumes that route travel times are time‐dependent and stochastic and their means and standard deviations need to be estimated. Three feed‐forward neural networks are developed to model the travel time behaviour during different time periods of the day‐the AM peak, the PM peak, and the off‐peak. These models are subsequently trained and tested using data simulated on the road network for the City of Edmonton, Alberta. A comparison of the ANN model with a traditional distance‐based model and a shortest path algorithm is then presented. The practical implication of the ANN method is subsequently demonstrated within a dial‐a‐ride paratransit vehicle routing and scheduling problem. The computational results show that the ANN‐based route travel time estimation model is appropriate, with respect to accuracy and speed, for use in real applications.     

Preoperational ocean forecasting in the southeastern Mediterranean Sea: Implementation and evaluation of the models and selection of the atmospheric forcing

Within the framework of several local and international programs, a quasi-operational ocean-forecasting system for the Southeastern Mediterranean Sea has been established and evaluated through a series of preoperational tests. The Princeton Ocean Model (POM) is used for simulating and predicting the hydrodynamics while the Wave Model (WAM) is used for predicting surface waves. Both models were set up to allow varying resolution and multiple nesting. In addition, POM was set up to be easily relocatable to allow rapid deployment of the model for any region of interest within the Mediterranean Sea. A common requirement for both models is the need for atmospheric forcing. Both models require time varying wind or wind stress. In addition, the hydrodynamic model requires initial conditions as well as time dependent surface heat fluxes, fresh water flux, and lateral boundary conditions at the open boundaries. Several sources of atmospheric forcing have been assessed based on their availability and their impact on the quality of the ocean models' forecasts. The various sources include operational forecast centers, other research centers, as well as running an in-house regional atmospheric model. For surface waves, higher spatial and temporal resolution of the winds plays a central role in improving the forecasts in terms of significant wave height and the timing of various high wave events. For the hydrodynamics, using the predicted wind stress and heat fluxes directly from an atmospheric model can potentially produce short range ocean forecasts that are nearly as good as hindcasts forced with gridded atmospheric analyses. Finally, a high-resolution, nested version of the model has shown to be stable under a variety of forcing conditions and time scales, thus indicating the robustness of the selected nesting strategy. For the southeastern corner of the Mediterranean, at forecast lead times of up to 4 days the high-resolution model shows improved skill over the coarser resolution driving model when compared to satellite derived sea surface temperatures. Most of the error appears to be due to the analysis error inherent in the initial conditions.     

A break-even model for evaluating the cost of container ships waiting times and berth unproductive times in automated quayside operations

The planning, design and development of a container terminal with optimum size and capacity and with a minimum capital cost is fundamentally dependent upon the loading and discharging operations at the quayside. The quayside function of container terminals is dependent basically on the number of berths available to service the incoming container ships. The objective of the container terminals dealing and admitting the ongoing ship calls is to provide immediate berth and loading and discharging services to the container ships with a minimum costly waiting time and a maximum efficiency. Previously terminal planners used to build extra berths to provide service. During the last two decades the terminal operators have adopted automation technologies in loading and discharging operation of the container ships as an alternative to designing extra berths. Ship owners naturally expect least waiting times for their container ships. On the other hand, it is also natural for port operators in a container terminal with costly facilities to see a high berth occupancy and productivity at the quayside. This study uses queuing theory to find a break-even point as a way of evaluating the cost of container ship waiting times and the cost of berth unproductive service times for container terminals aiming to automate their quayside operation. The analysis illustrates that automation devices installed on conventional Quayside Cranes (QSCs) significantly reduce the turnaround time of the container ships calling at the ports. It argues, however, that there should be a balance between the cost of berth unproductive service times and the cost of vessel waiting times. The study introduces a break-even point to be considered as a benchmark for calculating such a balance. The analysis in this study can be used as a decision tool for the operators of container terminals in the medium to small ports to appraise the feasibility of an investment in automation or expansion of the quayside facilities.     

Geography and Coastal Management

This article presents an overview of the relationship between geography and coastal management. It explores the nature of geography as well as the geographical underpinnings of key notions within coastal management, in particular, “coast,” “conflict,” and “integration.” The article considers the integrated coastal management process and tracks the influence of geography on the development of the discipline's theory and practice, as well as its academic infrastructure. The article concludes that although geography both underpins and offers useful insights into coastal management, a challenge remains to explore in greater depth the benefits of applied geographical approaches to the management of coasts.