Hydrodynamic performance of multiple-row slotted breakwaters

This study examines the hydrodynamic performance of multiple-row vertical slotted breakwaters. We developed a mathematical model based on an eigenfunction expansion method and a least squares technique for Stokes second-order waves. The numerical results obtained for limiting cases of double-row and triple-row walls are in good agreement with results of previous studies and experimental results. Comparisons with experimental measurements of the reflection, transmission, and dissipation coefficients (C _R , C _T , and C _E ) for double-row walls show that the proposed mathematical model adequately reproduces most of the important features. We found that for double-row walls, the C _R increases with increasing wave number, kd, and with a decreasing permeable wall part, dm. The C _T follows the opposite trend. The C _E slowly increases with an increasing kd for lower kd values, reaches a maximum, and then decreases again. In addition, an increasing porosity of dm would significantly decrease the C _R , while increasing the C _T . At lower values of kd, a decreasing porosity increases the C _E , but for high values of kd, a decreasing porosity reduces the C _E . The numerical results indicate that, for triple-row walls, the effect of the arrangement of the chamber widths on hydrodynamic characteristics is not significant, except when kd<0.5. Double-row slotted breakwaters may exhibit a good wave-absorbing performance at kd>0.5, where by the horizontal wave force may be smaller than that of a single wall. On the other hand, the difference between double-row and triple-row vertical slotted breakwaters is marginal.     

Panama Canal expansion: fuel economy and logistical risk

Since cargo capacity increases faster than fuel consumption, the significantly larger capacity fleets which will accompany expansion of the Panama Canal will introduce additional fuel economies and cost savings. Enabling larger, more fuel-efficient vessels to carry cargo the entire distance from Asia to US east-coast ports allows vessel operators to realize significant and meaningful savings compared with the alternatives of using smaller Panamax vessels for the whole distance, or sending the cargo over the US land bridge by train or truck. Fuel savings are quantified along with the monetary savings based on various assumptions for the price of fuel. These savings are dramatic and will increase directly with the price of crude petroleum. Finally, microeconomic theory is deployed to determine how cost savings will be distributed between shipping customers and vessel operators.     

Effect of pH on mechanical,physical and tribological properties of electroless Ni-P-Al<Subscript>2</Subscript>O<Subscript>3</Subscript> composite deposits for marine applications

Successful co-deposition of fine particulate matter within an Electroless Nickel-Phosphorous (ENi-P) matrix is dependent on various factors like bath composition, particle compatibility with metallic matrix, bath reactivity (pH), particle size and their distribution. ENi-P deposits incorporating Al₂O₃/Alumina in a disperse phase have varied effects on properties and attributes like surface roughness (Ra), microhardness, wear resistance, corrosion resistance and surface morphology of the deposits obtained. This paper experimentally investigates the effect of alumina (1.55 g/L) on Ra, microhardness, surface morphology, deposition rate, wettability, wear resistance and corrosion resistance of ENi-P-Al₂O₃ composite deposits on mild steel substrates at bath pH 5, 7 and 9. Study reveals that optimum deposit parameters and deposition rates are achieved with bath pH. However, not much study has been undertaken concerning composite deposits obtained from higher bath pH or basic bath. This is attributable to the fact that at higher bath pH or alkaline baths, the bath gets unstable and eventually degrades or decomposes, thereby resulting in sub optimal or poor deposition. Hence, experimental investigations carried out by preparing suitable baths, operating under optimum conditions, and enabling successful composite deposition in acidic and alkaline baths have revealed that there is a significant improvement in the above mentioned properties of the as-deposited composite deposits, as the pH is increased from pH 5 to pH 9. This aspect can therefore be advantageously utilized for preparing various marine components like fasteners, nuts, bolts, washers, pipes, cables, components having relative motion etc.     

Generation of synthetic datasets for discrete choice analysis

Despite the widespread use of synthetic data in discrete choice analysis, little is known about how the methodology used to generate synthetic datasets influences the properties of parameter estimates and the validity of results based on these estimates. That is, there are two potential sources of biases when using synthetic discrete choice data: (1) bias due to the method used to generate the dataset; and, (2) bias due to parameter estimation. The primary objective of this study is to examine bias due to the underlying data generation method. This study compares three methods for generating synthetic datasets and uses design of experiments and analysis of variance methods to investigate the ability to recover estimates for “true” logsum parameters for nested logit models. The method that uses nested logit probabilities to generate the chosen alternative results in unbiased parameter estimates. The method that is based on Gumbel error component approximations reveals that while the error components themselves are unbiased, subtle empirical identification problems can arise when these error components are combined with synthetically generated utility functions. The method that is based on normal error component approximations reveals that all logsum coefficients are biased upwards; the bias dramatically increases for those nests that have a low choice frequency and is most pronounced for those nests with high correlations among alternatives. Based on the results of the analysis, several recommendations for the generation of synthetic datasets for discrete choice analyses are provided.     

A joint flexible econometric model system of household residential location and vehicle fleet composition/usage choices

Modeling the interaction between the built environment and travel behavior is of much interest to transportation planning professionals due to the desire to curb vehicular travel demand through modifications to built environment attributes. However, such models need to take into account self-selection effects in residential location choice, wherein households choose to reside in neighborhoods and built environments that are conducive to their lifestyle preferences and attitudes. This phenomenon, well-recognized in the literature, calls for the specification and estimation of joint models of multi-dimensional land use and travel choice processes. However, the estimation of such model systems that explicitly account for the presence of unobserved factors that jointly impact multiple choice dimensions is extremely complex and computationally intensive. This paper presents a joint GEV-based logit regression model of residential location choice, vehicle count by type choice, and vehicle usage (vehicle miles of travel) using a copula-based framework that facilitates the estimation of joint equations systems with error dependence structures within a simple and flexible closed-form analytic framework. The model system is estimated on a sample derived from the 2000 San Francisco Bay Area Household Travel Survey. Estimation results show that there is significant dependency among the choice dimensions and that self-selection effects cannot be ignored when modeling land use-travel behavior interactions.     

Scrutinizing individuals’ leisure-shopping travel decisions to appraise activity-based models of travel demand

Activity-based models for modeling individuals’ travel demand have come to a new era in addressing individuals’ and households’ travel behavior on a disaggregate level. Quantitative data are mainly used in this domain to enable a realistic representation of individual choices and a true assessment of the impact of different Travel Demand Management measures. However, qualitative approaches in data collection are believed to be able to capture aspects of individuals’ travel behavior that cannot be obtained using quantitative studies, such as detailed decision making process information. Therefore, qualitative methods may deepen the insight into human’s travel behavior from an agent-based perspective. This paper reports on the application of a qualitative semi-structured interview method, namely the Causal Network Elicitation Technique (CNET), for eliciting individuals’ thoughts regarding fun-shopping related travel decisions, i.e. timing, shopping location and transport mode choices. The CNET protocol encourages participants to think aloud about their considerations when making decisions. These different elicited aspects are linked with causal relationships and thus, individuals’ mental representations of the task at hand are recorded. This protocol is tested in the city centre of Hasselt in Belgium, using 26 young adults as respondents. Response data are used to apply the Association Rules, a fairly common technique in machine learning. Results highlight different interrelated contexts, instruments and values considered when planning a trip. These findings can give feedback to current AB models to raise their behavioral realism and to improve modeling accuracy.     

Catching a ride on the information super-highway: toward an understanding of internet-based carpool formation and use

Fluctuating fuel prices, rising congestion, longer commutes, and related environmental and human health effects have combined to once more draw the interest of governments, commuters, and firms toward the concept of travel demand management (TDM). While TDM is not new, the proliferation of mobile telephony, fixed Internet, and associated applications has created fresh prospects for the implementation of commuter focused TDM strategies. One recent example is Carpool Zone, an on-line carpool-matching tool deployed and managed by the TDM group at Metrolinx, the regional transportation planning agency within Canada’s largest metropolitan region, the Greater Toronto and Hamilton Area. Using data provided by Metrolinx, this paper broadens current thinking on carpool formation and use. The main hypothesis guiding this work is that the carpool formation and use process is sensitive to personal and household characteristics, space, time, travel cost, and workplace TDM policies. Results from a logistic regression analysis suggest that geographical proximity to other users; workplace TDM policies; the scheduling of work; and commuter role preference increase the odds of successfully carpooling. Importantly, findings regarding the positive influence of workplace TDM policies suggest that Internet based TDM tools will likely require critically important investment in human capital at the back-end to ensure program participation.     

Workshop report - System development

The workshop considered system development as a key element of improving the performance of public transport. The main theme was the governance of decision making, design and development of public transport projects. A first main finding is that governance should be improved to keep focus on the original values for which the projects are started. Many projects lose sight of their original aims through the long and often problematic process from inception to operation. A second main finding is that the technological choice, mainly between rubber on tarmac and steel on rails, can be postponed, as both technologies start to overlap in their capacities. A stronger focus on functional needs in the earlier phases of the projects could help. Finally, as the different technologies provide similar options and can be used interchangeably, communicating the service they provide in other ways then through vehicle and infrastructure technology becomes more important.     

Permanent Deformation of Highway Subgrade Soils

Based on a comprehensive review of the literature and preliminary testing performed on a subgrade soil, a testing methodology for repeated load testing was established. This testing protocol was verified using data from subgrade soil. The successful application of this testing protocol on the two subgrade soils proves that it can provide consistent, reliable results. A power model was used to fit the accumulated axial strain over load repetitions with the first hundred cycles excluded from the data set. A number of factors influencing the accumulation of permanent deformation were investigated. The results indicate that confining pressure, load frequency and density are relatively minor contributors to deformation accumulation. Moisture content, deviator stress and first cycle freeze-thaw are major factors governing permanent deformation. The effects of stress history resulting from staged loading are dependent upon the level of applied deviator stress. The interpretation of the rich and consistent deformation data derived from this testing protocol provide valuable insights for transportation engineers relative to the design, construction, operation and maintenance strategy of highway subgrades as well as railway roadbeds.     

Instantaneous 2-D visualization of spray combustion and flame luminosity of GTL and GTL-biodiesel fuel blend under quiescent ambient conditions

An experimental study has been performed on spray combustion and two-dimensional soot concentration in diesel (ULSD), GTL and GTL-biodiesel fuel jets under high-pressure, high-temperature quiescent conditions. Instantaneous images of the fuel jets were obtained with a high-speed camera. It was confirmed that by blending GTL with 20% rapeseed biodiesel, certain fuel properties such as kinematic viscosity, density, surface tension, volatility, lower heating value and others may be designed and improved to be more like those of conventional diesel fuel but with considerable decrease in the amount of sulfur, PAH, cold filter plugging point, etc. The results showed that the spray tip penetration increased and the spray cone angle decreased when 20% biodiesel fuel was added to GTL fuel. Autoignition of the GTL-biodiesel blend occurred slightly earlier than that of diesel fuel. Experiments under high-pressure, high-temperature conditions showed that higher injection pressure induced a lower soot formation rate. The integrated flame luminosity, which serves as an indicator of soot concentration in the fuel jet, was slightly higher for the GTL-biodiesel blend than for pure GTL fuel due to the slightly higher sulfur content of pure biodiesel fuel.