Data-Driven Analysis for Safe Ship Operation in Ports Using Quantile Regression Based on Generalized Additive Models and Deep Neural Network

Marine accidents in ports can cause loss of human life and property and have negative material and environmental impacts. In South Korea, due to a pier collision accident of a large container ship in Busan New Port of South Korea, the need for safe ship operation guidelines in ports emerged. Therefore, to support quantitative safe ship operation guidelines, ship trajectory data based on automatic information system information have been used. However, because this trajectory information is variable and uncertain due to various situations arising during a ship’s navigation, there is a limit to deriving results through traditional regression analysis. Considering the characteristics of these data, we analyzed ship trajectories through quantile regression using two models based on generalized additive models and neural networks corresponding to deep learning. Among the automatic information system information, the speed over ground, course over ground, and ship’s position were analyzed, and the model was evaluated based on quantile loss. Based on this study, it is possible to suggest safe operation guidelines for the position, speed, and course of the ship. In addition, the results of this work can be further developed as a manual for the in-port-autonomous operation of ships in the future.

Studying reliability of marine pump systems by using technical supervision data

The article describes the analysis of the ship systems’ reliability at the stage of the technical design, which is based on the reliability data of individual system elements and mathematical methods of reliability theory. During the ship operation maintenance deficiencies can lead to the equipment failure, which can be prevented by the methods of instrumental diagnostics of system elements, maintenance repairs regardless of the current technical condition, and classification inspection during the ship operation. Collecting the detailed data on changes in the functional reliability of ship mechanical systems, which could confirm or deny the advantages of each of the existing methods is not enough. There has been carried out collecting, processing and analyzing the actual data on the life cycles of various pumps of ship systems at different stages of service life, as well as beyond the designated service life or operating time. There are examined the general ship systems and auxiliary power units of icebreakers and floating structures. The examined equipment has standard pumps with different capacity and efficiency. Service life, assigned resource (operating time), frequency of repair are taken as the criteria of pump reliability and durability. There have been shown the actual life cycles of pumps in dependence of the service life in years on the operating time in hours; in addition, data on the passage of maintenance repairs, maintenance, inspection of the technical condition, as well as replacement or extension of the service life are plotted on the graphs. It has been inferred that some of the pumps in the ship's systems should be replaced before the full resource was developed, while the performance of the systems as a whole was preserved or restored as a result of repairs; some pumps have exceeded their specified resource, but during the technical inspection their operation was extended, the operability of the systems was also preserved.

LH2 Tanker Design Based on WIT Operating Model and CAPEX as Competitive Advantage

This paper presents the concept and design of a tanker powered by, and carrying, liquid hydrogen (LH2). Beyond the realization of a complete reduction in carbon emissions, the concept is closely related to the authors’ proposal for a rethinking of ship operation with a substitution of Just-in-Time (JIT) by Warehouse-in-Transit (WIT). Ways to fund a LH2 tanker is also reviewed and suggested.

Identification of Shipyard Priorities in a Multi-Criteria Decision-Making Environment through a Transdisciplinary Energy Management Framework: A Real Case Study for a Turkish Shipyard

Ship building, as an energy-intensive sector, produces significant amounts of air emissions, including greenhouse gases. Most research in greenhouse gas reductions from shipping concentrates on the reduction in emissions during the operational phase. However, as emissions during ship operation are reduced, the construction and dismantling phases of ships are becoming increasingly important in the assessment of the life-cycle impact of ships. In this study, priorities for a Turkish shipyard to become energy efficient were identified by means of a semi-structured questionnaire and an interview. This was undertaken using Fuzzy Multi-Criteria Decision-Making methods, including the Fuzzy Analytical Hierarchy Process and Fuzzy Order of Preference by Similarity to Ideal Solution, which are part of a proposed systematic and transdisciplinary Energy Management Framework and System. By applying Multi-Criteria Decision-Making methods, this framework supports the shipyard’s decision makers to make rational and optimized decisions regarding energy sectors within their activities. Applying the framework has significant potential to help achieve good product quality while reducing costs and environmental impacts, and can thereby enhance the sustainability of shipping. Moreover, the framework can boost both business and socio-economic perspectives for the shipyard, and improve its reputation and competitiveness, in alignment with achieving the Nationally Determined Contributions of States under the Paris Agreement.

A method for assessing of ship fuel system failures resulting from fuel changeover imposed by environmental requirements

Environmental regulations instigated the technological and procedural revolution in shipping. One of the challenges has been sulfur emission control areas (SECA) and requirement of fuel changeover. Initially, many reports anticipated that new grades of low sulfur fuels might increase various technical problems in ship operation. This research develops a simple and easy to use method of the failure severity and intensity assessment in relation to fuel changeover. The scale of failure rate in the ship’s fuel system was evaluated qualitatively and quantitively, using developed failure frequency indicator and the time between failure. Based on 77 records of fuel system failures collected on seven ships, it has been found that frequency of failures related to SECA fuel changeover is on average nearly three times higher compared to the rest of sailing time. Their severity did not significantly change, but the structure of failures changed considerably. The method and presented results may help in improvement of ship’s systems design and on-board operational procedures.

Development of Enhanced Two-Time-Scale Model for Simulation of Ship Maneuvering in Ocean Waves

In this study, a modified two-time-scale model is proposed to overcome the limitations of the existing maneuvering analysis model. To this end, not only wave conditions but also all directions of ship operation velocities are considered in estimating wave drift force and moment. Subsequently, the increment of the drift force and moment induced by steady drift and yaw motion of a ship is imposed up to the first derivative of Taylor series expansion. By introducing this bilinear model, the burden of the drift force computation is reduced so that a more realistic and efficient seakeeping-maneuvering coupling analysis can be performed. A turning circle simulation in a regular short wave is carried out using the modified two-time-scale model. Then, the performance is validated by comparing its results with the direct coupling model. Moreover, quantitative improvement of the present numerical scheme and the influence of the operation velocities on ship maneuvering performance are discussed.

Assessing autonomous ship navigation using bridge simulators enhanced by cycle-consistent adversarial networks

The advent of artificial intelligence and deep learning has provided sophisticated functionality for sensor fusion and object detection and classification which have accelerated the development of highly automated and autonomous ships as well as decision support systems for maritime navigation. It is, however, challenging to assess how the implementation of these systems affects the safety of ship operation. We propose to utilize marine training simulators to conduct controlled, repeated experiments allowing us to compare and assess how functionality for autonomous navigation and decision support affects navigation performance and safety. However, although marine training simulators are realistic to human navigators, it cannot be assumed that the simulators are sufficiently realistic for testing the object detection and classification functionality, and hence this functionality cannot be directly implemented in the simulators. We propose to overcome this challenge by utilizing Cycle-Consistent Adversarial Networks (Cycle-GANs) to transform the simulator data before object detection and classification is performed. Once object detection and classification are completed, the result is transferred back to the simulator environment. Based on this result, decision support functionality with realistic accuracy and robustness can be presented and autonomous ships can make decisions and navigate in the simulator environment.