A decision-making solution to ship flagging out via administrative maritime strategies

The choice of flag is one of the main strategic/critical decisions for shipowners in the initial stage of maritime enterprises. On the other hand, flagging out has a great influence on the prestige and economic benefits for traditional maritime countries. To address this issue, this paper proposes a Multiple Criteria Decision Making (MCDM) approach using a Primarily Strategic Action Plan (PSAP) in a short-run period and a Secondary Strategic Action Plan (SSAP) for a long-term perspective. The case is demonstrated with respect to the flagging out issue in Turkish shipping fleet. It measures the decision-making tendencies of shipowners using Turkish National Shipping Registry (TNSR), Turkish International Shipping Registry (TISR), and Open Registries (ORs) as potential shipping registry alternatives. The model outcomes originally contribute to Turkish maritime policy, especially in terms of strengthening and reinforcing of TNSR procedures.     

Analysis of Characteristics of the Dynamic Flow-Density Relation and its Application to Traffic Flow Models

Abstract

Online traffic flow modeling is of increasing importance due to intelligent transport systems and technologies. The flow-density relation plays an important role in traffic flow modeling and provides a basic way to illustrate traffic flow behavior under different traffic flow and traffic density conditions. Until now the research effort has focused mainly on the shape of the relation. The time series of the relation has not been identified clearly, even though the time series of the relation reflects the upstream/downstream traffic conditions and should be considered in the traffic flow modeling. In this paper, the dynamic flow-density relation is identified based on the classification of traffic states and is quantified employing fuzzy logic. The quantified dynamic flow-density relation builds the basis for online application of a macroscopic traffic flow model. The new approach to online modeling of traffic flow applying the dynamic flow-density relation alleviates parameter calibration problems stemming from the static flow-density relation.     

A comparative study of aggregate and disaggregate gravity models using Seoul metropolitan subway trip data

Abstract

Existing origin constrained and doubly constrained gravity models have not been compared, theoretically or empirically, in terms of their forecasting power. Due to the newly advanced technology of intelligent transport systems, the expanded data presently available have made various models more comparable in terms of forecasting power. This paper uses archived automatic passenger counting (APC) data for urban rail in the Seoul metropolitan area. The APC data contains information about each trip's origin, destination, ticket type, fare, and distance on a daily basis. The objective of this paper is to compare the goodness-of-fit of aggregate and disaggregate gravity modeling using these data. A Hyman aggregate gravity model is used as the aggregate model without the spatial effect. The disaggregate model adopts a multinomial logit as the destination choice model with the spatial effect. In general, while the formulation of aggregate and disaggregate gravity model models are similar, the calibration and parameter estimation methods of the two models are different. As a result, this empirical study demonstrates that the variation in goodness-of-fit and forecasting power largely depends on the estimation method and selected variables. The forecasting power of the disaggregate modeling approach outperforms that of the aggregate model. This paper further confirms that spatial arrangement plays important roles in gravity modeling.     

A structural equation model of activity participation and travel behavior using longitudinal data

Abstract

This paper presents a dynamic structural equation model (SEM) that explicitly addresses complicated causal relationships among socio-demographics, activity participation, and travel behavior. The model assumes that activity participation and travel patterns in the current year are affected by those in previous years. Using the longitudinal dataset collected from Puget sound transportation panel ‘wave 3’ and ‘wave 4,’ these assumptions are tested with suggested SEMs. Within each wave, the model is structured to have a three-level causal relationship that describes interactions among endogenous variables under time-budget constraints. The resulting coefficients representing the activity durations indicate that people tend to allocate their time according to the importance and the obligation of the activity level. Results from the dynamic SEM confirm the fact that people's current activity and travel behavior do have effects on those in the future. The resulting model also shows that activity participation and travel behavior in ‘wave 3’ are closely related to those in ‘wave 4.’ These explicit explanations of relationships among variables could provide important perspectives in the activity-based approach which becomes recognized as a better analytical tool for the transportation planning and policy making process.     

Ultimate strength assessment of a tanker hull based on experimentally developed master curves

A geometrically similar scaling was made from small-scale specimen to full-scale stiffened panels and then their collapse behaviour is investigated. It is considered that the stiffened panel compressive ultimate strength test was designed according to geometrical scaling laws so that the output of the test could be used as representative of the stiffened panels of the compressive zone of a tanker hull subjected to vertical bending moment. The ultimate strength of a tanker hull is analysed by a FE analysis using the experimentally developed master stress-strain curves which are obtained by the beam tension test and the compressive test of the stiffened panel, and are then compared with the result achieved by the progressive collapse method.     

Road Safety Strategies: A Comparative Framework and Case Studies

Abstract

This paper proposes a nine‐component analytical framework for developing, comparing, and evaluating road safety strategies. The nine components are: (1) vision; (2) objectives; (3) targets; (4) action plan; (5) evaluation and monitoring; (6) research and development; (7) quantitative modelling; (8) institutional framework; and (9) funding. While the first four components are essential for the formulation of a road safety strategy, the remaining components are key to its successful implementation. To demonstrate the usefulness of this comparative framework, we examine the road safety strategies of six selected administrations: Australia, California, Great Britain, Japan, New Zealand, and Sweden. In these case studies, we extract and highlight good practices in the formulation and implementation of their road safety strategies. The proposed framework also provides a systematic approach for assessing road safety strategies in other administrations. The evaluation of the six case studies forms a benchmarking platform for the planning, formulation, and implementation of good practices for road safety strategies.     

Calibrating a social-force-based pedestrian walking model based on maximum likelihood estimation

Although various theories have been adopted to develop reliable pedestrian walking models, a limited effort has been made to calibrate them rigorously based on individual trajectories. Most researchers have validated their models by comparing observed and estimated traffic flow parameters such as speed, density, and flow rate, or replaced the validation by visual confirmation of some well-known phenomena such as channelization and platooning. The present study adopted maximum likelihood estimation to calibrate a social-force model based on the observed walking trajectories of pedestrians. The model was assumed to be made up of five components (i.e., inertia, desired direction, leader–follower relationship, collision avoidance, and random error), and their corresponding coefficients represented relative sensitivity. The model also included coefficients for individual-specific characteristics and for a distance-decay relationship between a pedestrian and his/her leaders or colliders. The calibration results varied with the two density levels adopted in the present study. In the case of high density, significant coefficient estimates were found with respect to both the leader–follower relationship and collision avoidance. Collision avoidance did not affect the pedestrian’s walking behavior for the low-density case due to channelization. The distance limit was confirmed, within which a pedestrian is affected by neighbors. At the low-density level, by comparison with women, men were found to more actively follow leaders, and pedestrians walking in a party were found to be less sensitive to the motion of leaders at the high-density level.     

Robust adaptive horizontal vibration isolation of towed seismic streamers

The horizontal vibration of towed seismic streamers is a main reason for efficiency reduction of the seismic survey and tail tangling. A vibration suppression scheme of towed seismic streamers is investigated in this paper. The towed seismic streamer is divided into two spans, a controlled span, i.e., the low tension span, and an uncontrolled span, i.e., the high tension span, by a bird. The system model includes a hyperbolic partial differential equation with variable coefficient describing the towed seismic streamers, and an ordinary differential equation describing the dynamic of bird. Robust based-model knowledge and adaptive controllers, based on the Lyapunov method, are designed to isolate the vibration of towed seismic streamers caused by the course deviations of towing vessel, the variations of towing vessel velocity and the variations of towed seismic streamer density. The robust based-model knowledge and adaptive controllers exponentially and asymptotically drive the span-towed seismic streamer displacement to zero, respectively. A finite difference scheme is used to validate the efficiency of the control law. The proposed controller can isolate effectively the disturbance originated from the towed vessel, and can provide the improved damping but not sacrifice the isolation performance. The adaptive scheme can tolerate the lack of knowledge of some uncertain parameters and can directly execute the online adjustment of the parameters. Meanwhile, the proposed control law is robust and can resist the model uncertainty due to parameter incertitude, model error and unknown disturbance and so on. The control law only includes velocity and slope, while it does not need the displacement which is difficult to measure in the practical operations. Thus it is easy to implement.     

Design of fuzzy controller for direct drive wind turbines

Based on the research results of these years, this paper proposes a design of 3MW direct-driven wind generation inverter, and takes much effort in the control algorithm research and MATLAB simulation. Some wonderful results are obtained. All this may provide the reference for practical application. The fuzzy controllers are designed, based on fuzzy logic control theory, which can perfect control of wind generation system with no mathematic model. Models of permanent magnet synchronous generator (PMSG) and dual pulse width modulation (PWM) converter with their controllers are set by MATLAB/Simulink. In addition, experiments are made on the simulation platform of variable speed constant frequency (VSCF) wind power generation system. The behavior of dual PWM converter is demonstrated by simulations and experiment, and the control strategy is valid and correct.     

Evolutionary algorithms for solving unconstrained multilevel lot-sizing problem with series structure

This paper presents a comparative study of evolutionary algorithms which are considered to be effective in solving the multilevel lot-sizing problem in material requirement planning (MRP) systems. Three evolutionary algorithms (simulated annealing (SA), particle swarm optimization (PSO) and genetic algorithm (GA)) are provided. For evaluating the performances of algorithms, the distribution of total cost (objective function) and the average computational time are compared. As a result, both GA and PSO have better cost performances with lower average total costs and smaller standard deviations. When the scale of the multilevel lot-sizing problem becomes larger, PSO is of a shorter computational time.