On the vibrational characteristics of a two-tier scaled container stack

It is estimated that around 10,000 containers are lost during maritime transportation every year, representing an economic loss to the liner industry. Regulations and norms used to calculate values to secure them to the ship’s deck account for static loads only, neglecting more realistic conditions. This paper describes an approach to simulate a two-tier scaled model of a 20-ft ISO freight container and its linking connectors, denominated twist locks, subject to a dynamical load induced by its base. To analyze this problem two methods were employed: a shaking table test and finite-element analysis. Results of this study indicate that the numerical model built to simulate two-tier container stack dynamics is a promising tool for further studies. Moreover, the model is able to predict conditions close to real situations faced by container stacks while stored on deck.     

Study on a procedure for propulsive performance prediction for CRP-POD systems

The experimental procedure to predict the full-scale performance of the CRP-POD propulsion system is studied. In the CRP-POD system, the RPM ratio of the two propellers is not mechanically fixed, in contrast with conventional CRP systems. Therefore the existing procedure for conventional CRP systems is not appropriate for evaluating the performance of each propeller. In this paper, the characteristics of the CRP-POD system, designed for a 9,600 TEU class container carrier, are studied experimentally. Based on this study, a procedure for propulsive performance prediction for CRP-POD propulsion ships is suggested.     

Verification and validation study of URANS simulations for an axial waterjet propelled large high-speed ship

The accurate prediction of waterjet propulsion using computational fluid dynamics (CFD) is of interest for performance analyses of existing waterjet designs as well as for improvement and design optimization of new waterjet propulsion systems for high-speed marine vehicles. The present work is performed for three main purposes: (1) to investigate the capability of a URANS flow solver, CFDSHIP-IOWA, for the accurate simulation of waterjet propelled ships, including waterjet–hull interactions; (2) to carry out detailed verification and validation (V&V) analysis; and (3) to identify optimization opportunities for intake duct shape design. A concentrated effort is applied to V&V work and performance analysis of waterjet propelled simulations which form the focus of this paper. The joint high speed sealift design (JHSS), which is a design concept for very large high-speed ships operating at transit speeds of at least 36 knots using four axial flow waterjets, is selected as the initial geometry for the current work and subsequent optimization study. For self-propelled simulations, the ship accelerates until the resistance equals the prescribed thrust and added tow force, and converges to the self propulsion point (SPP). Quantitative V&V studies are performed on both barehull and waterjet appended designs, with corresponding experimental fluid dynamics (EFD) data from 1/34 scale model testing. Uncertainty assessments are performed on iterative convergence and grid size. As a result, the total resistance coefficient for the barehull case and SPP for the waterjet propelled case are validated at the average uncertainty intervals of 7.0 and 1.1%D, respectively. Predictions of CFD computations capture the general trend of resistance over the speed range of 18–42 knots, and show reasonable agreement with EFD with average errors of 1.8 and 8.0%D for the barehull and waterjet cases, respectively. Furthermore, results show that URANS is able to accurately predict the major propulsion related features such as volume flow rate, inlet wake fraction, and net jet thrust with an accuracy of ~9%D. The flow feature details inside the duct and interference of the exit jets are qualitatively well-predicted as well. It is found that there are significant losses in inlet efficiency over the speed range; hence, one objective for subsequent optimization studies could be maximizing the inlet efficiency. Overall, the V&V work indicates that the present approach is an efficient tool for predicting the performance of waterjet propelled JHSS ships and paves the way for future optimization work. The main objective of the optimization will be reduction of powering requirements by increasing the inlet efficiency through modification of intake duct shape.     

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.     

Reliability of Nanofluid Concentration on the Heat Transfer Augmentation in Engine Radiator

Nanofluids, the fluid suspensions of nanomaterial, became a promising fluid that is invoked when heat transfer increase is required. Using of nanofluids as a coolant in the engine radiators is a crucial topic for the thermal engines manufactrers due to the expected enhancement in the cooling process. In this study, Two nanofluids (Al₂O₃/water and CuO/water) flowing in a flat tube of radiator are investigated numerically to evaluate thermal and flow performance. The resizing process for the radiator is performed by using nanofluid instead of water flow. A significant reduction in the radiator volume is achieved due to marked improvement in the heat transfer performance while, the required pumping power after this reduction in the volume is increased over that needed for base fluid. The normalized heat transfer (heat transfer to the pumping power) is found to be a function of both Reynolds number and nanofluid concentration ratio while the ratio of the normalized heat transfer is found to be dependent only on the nanofluid concentration ratio. These dependencies are formulated as general correlations.