Comparison of Microbubble and Air Layer Injection with Porous Media for Drag Reduction on a Self-propelled Barge Ship Model

Ship resistance issues are related to fuel economy, speed, and cost efficiency. Air lubrication is a promising technique for lowering hull frictional resistance as it is supposed to modify the energy in the turbulent boundary layer and thereby reduce hull friction. In this paper, the objective is to identify the optimum type of air lubrication using microbubble drag reduction (MBDR) and air layer drag reduction (ALDR) techniques to reduce the resistance of a 56-m Indonesian self-propelled barge (SPB). A model with the following dimensions was constructed: length L?=?2000 mm, breadth B?=?521.60 mm, and draft T?=?52.50 mm. The ship model was towed using standard towing tank experimental parameters. The speed was varied over the Froude number range 0.11–0.31. The air layer flow rate was varied at 80, 85, and 90 standard liters per minute (SLPM) and the microbubble injection coefficient over the range 0.20–0.60. The results show that the ship model using the air layer had the highest drag reduction up to a maximum of 90%. Based on the characteristics of the SPB, which operates at low speed, the optimum air lubrication type to reduce resistance in this instance is ALDR.     

Law and Characteristics Analysis of Domestic Tunnel Construction Accidents from 2006 to 2016北大核心CSCD

With the rapid development of tunnel construction in China, strengthening statistical studies of domestic tunnel construction accidents is of great significance in order to understand the safety status of tunnel construction and the development trends of tunnel construction accidents and for exploring the direction of future scientific re-search. There were 89 tunnel construction accidents in China (not including subway tunnels or municipal tunnels)from 2006 to 2016. The characteristics of these accidents are analyzed in terms of time distribution, spatial distribu-tion, grade and type of accident according to the statistics by means of line charts, bar charts and pie charts. Corre-sponding prevention and control recommendations are put forward considering the factors such as year, month, work-ing day, time period, region, location, grade and type. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

Exploring stability and change in transport systems: combining Delphi and system dynamics approaches

Transport is a vast and complex socio-technical system, and despite a clear need to reduce dependence on fossil fuels due to undesirable environmental impacts, it is largely locked into business-as-usual. Systems approaches are a useful way to help make sense of multiple competing influences which may be simultaneously driving change and supporting the status quo. This paper applies qualitative system dynamics modelling to help interpret the results of a Delphi study into global transport transitions, involving 22 international experts in various aspects of transport. The main contribution of the paper is its exploration of the use of system dynamics (SD) modelling to interpret the Delphi findings. SD modelling was used to reveal and elucidate the causal arguments put forward by the expert panel about the factors driving business-as-usual, the factors creating barriers to more sustainable transport systems, and the drivers of change. The SD model is used to explore and expose the key causal patterns at play, and how these interact to both support and hinder change. The resulting model shows the complex, interdependent dynamics involved in supporting the status quo. Even at the relatively high level of analysis reported here, the model is useful in revealing interdependencies between parts of the system, where change in one part may well have knock-on effects elsewhere in the system. In particular the model reveals the strong reinforcing loops that act to minimise the impact of change drivers and thus retain the dominance of automobility. The result is a system that is highly dependent on the continued existence of key reinforcements such as policies that subsidise fossil fuels. From a methodological perspective, the outcomes of the Delphi study provided a rich source of qualitative material which was highly suitable for developing a system dynamics model.     

Symbolic transport choice across national cultures: theoretical considerations for research design

A recently empirically isolated latent variable in transport choice is symbolism, which examines what people believe their transport choices say to others about them and how they are judged in a social context. Whilst it is well established that symbolism differs vertically across different socio-economic groups within a country, very little work has been done on how symbolism in transport may differ between similar individuals across nations as a function of national cultural values, and how this may manifest itself in transport choices. If significant differences were to be found then this could have impacts for transport policy formulation and transfer. This paper explores and discusses these issues and concludes that the initial goal of any research into symbolic transport choices across cultures is theoretical fertility, and this is best achieved by adopting Lakatosian research programmes, using theory-driven thematic analysis to develop theoretical models for testing.     

Does the choice model method and/or the data matter?

The opportunity to have seven data sets associated with a stated choice experiment that are very similar in content and design is rare, and provides an opportunity to look in detail at the empirical evidence within and between each data set in the context of a range of discrete choice estimation methods, from multinomial logit to latent class to scale multinomial logit to mixed logit, and the most general model, generalized mixed multinomial logit that accounts for preference and scale heterogeneity. Given the problems associated with data from different countries and time periods, we estimate separate models for each data set, obtaining values of travel time savings that are then updated post estimation to a common dollar for comparative purposes. We also pooled all data sets for a scaled MNL model, treating each data set as a set of three separate utility expressions, but linked to the other data sets through scale heterogeneity. This is not behaviourally appropriate with MNL, latent class or mixed logit. The main question investigated is whether there exists greater synergy in the willingness to pay evidence within model form across data sets compared to across model forms within data sets. The evidence suggests that there is a relatively greater convergence of evidence across the choice models, with the exception of generalized mixed logit, after controlling for data set differences; and there is strong evidence to suggest that differences between data sets do matter.     

Accounting for scale heterogeneity within and between pooled data sources

There is growing interest in incorporating both preference heterogeneity and scale heterogeneity in choice models, as a way of capturing an increasing number of sources of utility amongst a set of alternatives. The extension of mixed logit to incorporate scale heterogeneity in a generalised mixed logit (GMXL) model provides a way to accommodate these sources of influence, observed and unobserved. The small but growing number of applications of the GMXL model have parameterized scale heterogeneity as a single estimate; however it is often the case that analysts pool data from more than one source, be it revealed preference (RP) and stated preference (SP) sources, or multiple SP sources, inducing the potential for differences in the scale factor between the data sources. Existing practice has developed ways of accommodating scale differences between data sources by adopting a scale homogeneity assumption within each data source (e.g., the nested logit trick) that varies between data sources. This paper extends the state of the art by incorporating data-source specific scale differences in scale heterogeneity setting across pooled RP and SP data set. An example of choice amongst RP and SP transport modes (including two ‘new’ SP modes) is used to obtain values of travel time savings that vary significantly between a model that accounts for scale heterogeneity differences within pooled RP and SP data, and the other where differences in scale heterogeneity is also accommodated between RP and SP data.     

Financing public transport systems in Kuala Lumpur,Malaysia: challenges and prospects

Most major cities across the world today are facing an intractable challenge of financing public transport. In Kuala Lumpur for example, public transport services are somewhat poor in part because of the failure of major operators to secure ample funding. Previous funding programs implemented in the city have failed to produce a replicable model for financing public transport. Due to numerous financial problems and the dismal performance of privately owned transport firms, the State has in the recent past emerged as a key source of funding for the public transport sector in Kuala Lumpur. This article argues that, despite the insuperable challenges, prospects for the future funding of public transport in Kuala Lumpur appears to be good. The article also draws lessons from both Tokyo and Hong Kong. In order to address the funding deficit facing the public transport industry in the city it is crucial that more viable strategies and policies such as value capture and public–private sector partnerships are adopted by the urban authorities.

The relationship between instrumental, symbolic and affective factors as predictors of car use: A structural equation modeling approach

Traditionally, urban mobility has been studied from the utilitarian or practical viewpoint, focusing on instrumental motivations and ignoring symbolic and affective aspects that may play a relevant role. The purpose of this work is to analyze from a psychosocial perspective the influence of symbolic, affective, and instrumental motivations on the frequency of car use, taking into account diverse reasons for traveling. From a sample of the Spanish population, participants were 284 people (50.3% female), with a driver’s license, car owners and residents in cities of various sizes, who completed an anonymous questionnaire. The effect of each type of variable was estimated by a structural equation model. Results indicate that people’s affective link with their private vehicle explains 12% of frequency of car use, as a latent variable of different kinds of trips: visiting friends or relatives, going to work or to a study center, going shopping, or to leisure areas. The instrumental advantages associated with cars and thinking that it expresses one’s status predict the affective link with the car. These findings corroborate the relevance of the non-instrumental aspects involved in the selection of the means of transportation.