A Comparative Study on Fatigue Damage using a Wave Load Sequence Model

Despite that ships get the approval of classification societies and structural members are designed to survive random environmental conditions for twenty or twenty-five years, fatigue crack damage still occurs. Nowadays, the operation based on weather routing programs has become important, not only to avoid adverse sea conditions that can cause damage, time loss or significant speed reduction but also to improve the crew safety. In this paper, S-N based fatigue assessment of a welded joint in an ocean going is performed. It is assumed that the ship sails following a planned route and a route based on weather conditions. Short sea sequences are generated by a storm model called “4G Storm Model”, proposed by one of the co-authors (De Gracia et al., 2017). Stress histories are generated considering the stochastical nature of the wave direction variation. Cumulative fatigue damage is performed following a classification society rule. Based on these results, the effect of ship routing and headings model on the S-N fatigue assessment is discussed. Keywords: Weather routing, fatigue, cumulative damage, storm model, wave sequence model

Predicting Destinations by Nearest Neighbor Search on Training Vessel Routes

The DEBS Grand Challenge 2018 is set in the context of maritime route prediction. Vessel routes are modeled as streams of Automatic Identification System (AIS) data points selected from real-world tracking data. The challenge requires to correctly estimate the destination ports and arrival times of vessel trips, as early as possible. Our proposed solution partitions the training vessel routes by reported destination port and uses a nearest neighbor search to find the training routes that are closer to the query AIS point. Particular improvements have been included as well, such as a way to avoid changing the predicted ports frequently within one query route and automating the parameters tuning by the use of a genetic algorithm. This leads to significant improvements on the final score

Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application

Understanding how container routing stands to be impacted by different scenarios of liner shipping network perturbations such as natural disasters or new major infrastructure developments is of key importance for decision-making in the liner shipping industry. The variety of actors and processes within modern supply chains and the complexity of their relationships have previously led to the development of simulation-based models, whose application has been largely compromised by their dependency on extensive and often confidential sets of data. This study proposes the application of optimisation techniques less dependent on complex data sets in order to develop a quantitative framework to assess the impacts of disruptive events on liner shipping networks. We provide a categorization of liner network perturbations, differentiating between systemic and external and formulate a container assignment model that minimises routing costs extending previous implementations to allow feasible solutions when routing capacity is reduced below transport demand. We develop a base case network for the Southeast Asia to Europe liner shipping trade and review of accidents related to port disruptions for two scenarios of seismic and political conflict hazards. Numerical results identify alternative routing paths and costs in the aftermath of port disruptions scenarios and suggest higher vulnerability of intra-regional connectivity

A model of the vessel traffic process

A model of the total vessel traffic control process that includes the functioning of the human operator (HO) is presented. The vessel traffic services (VTSs) are modeled in their possible role of monitor, conflict detector, and advisor for the total vessel traffic system. The model assumes a number of ships, with a given planned route, in a given confined area. The navigation of each ship is based on a planned route, which is updated by information about the visual scene, instruments, and the VTS. Both normal operation and collision avoidance are modeled. The model is implemented in a C program. Typical traffic situations have been simulated to showing the ability of the model to address realistic vessel traffic scenarios. The model can answer questions related to safety and efficiency, the effect of HO functioning, information necessary to perform tasks, communication between ships and VTS, the optimization of procedures, automation of the total vessel traffic process, et

Automatic collision avoidance of ships

One of the key elements in automatic simulation of ship manoeuvring in confined waterways is route finding and collision avoidance. This paper presents a new practical method of automatic trajectory planning and collision avoidance based on an artificial potential field and speed vector. Collision prevention regulations and international navigational rules have been incorporated into the algorithm. The algorithm is fairly straightforward and simple to implement, but has been shown to be effective in finding safe paths for all ships concerned in complex situations. The method has been applied to some typical test cases and the results are very encouraging

Mixed Data and Classification of Transit Stops

An analysis of the characteristics and behavior of individual bus stops can reveal clusters of similar stops, which can be of use in making routing and scheduling decisions, as well as determining what facilities to provide at each stop. This paper provides an exploratory analysis, including several possible clustering results, of a dataset provided by the Regional Transit Service of Rochester, NY. The dataset describes ridership on public buses, recording the time, location, and number of entering and exiting passengers each time a bus stops. A description of the overall behavior of bus ridership is followed by a stop-level analysis. We compare multiple measures of stop similarity, based on location, route information, and ridership volume over time

Model of large scale man-machine systems with an application to vessel traffic control

Mathematical models are discussed to deal with complex large-scale man-machine systems such as vessel (air, road) traffic and process control systems. Only interrelationships between subsystems are assumed. Each subsystem is controlled by a corresponding human operator (HO). Because of the interaction between subsystems, the HO has to estimate the state of all relevant subsystems and the relationships between them, based on which he can decide and react. This nonlinear filter problem is solved by means of both a linearized Kalman filter and an extended Kalman filter (in case state references are unknown and have to be estimated). The general model structure is applied to the concrete problem of vessel traffic control. In addition to the control of each ship, this involves collision avoidance between ship

MONALISA 2.0 and the sea traffic management - a concept creating the need for new maritime information standards and software solutions

Postprint (published version