Efficient Ship Operation Research Articles

Advances in Navigability and Mooring

Considerable technological progress has been made in ship handling and mooring in recent years, especially progress generated by the needs imposed by the introduction of ever larger ships. These advancements exploit the economic scale and environmental efficiency of larger vessels, but also present unique challenges, particularly in narrow waterways and harbour approaches. Precise navigation in these environments requires highly accurate hydrographic measurements, high-quality electronic charts, and advanced navigation systems, such as modern electronic chart display and information systems (ECDIS). Safe and efficient port operations also depend on the optimised allocation of port resources and comprehensive queuing strategies. Modern ships are increasingly susceptible to interference with Global Navigation Satellite Systems (GNSS) and Automatic Identification Systems (AIS), necessitating the development of resilient technologies and procedures to ensure navigational safety. In addition, climate change is exacerbating the challenges of ship handling in ports, as larger vessels are particularly vulnerable to sudden gusts of wind and have difficulty maintaining their position in the quay in strong crosswinds. Training and simulation are crucial to overcoming these challenges. Ship-handling simulators are invaluable for training purposes, but development is still needed to accurately simulate tilt and lean effects, especially when ships are sailing in narrow channels with following currents and changing winds. Improving the accuracy of these simulators will improve the preparation of seafarers for real-life conditions and ultimately contribute to safer and more efficient ship operations.

Data-driven model for anti-pitching control of wave-piercing trimaran with stern-flap interceptor in waves

The control of pitching in wave-piercing trimarans helps improve crew comfort and navigation stability, providing a strong guarantee of safe and efficient ship operation. Current research on anti-pitching has mostly focused on control algorithms that use empirical formulas to calculate the stabilising moments directly. Little research has been conducted on appendage modelling. The Reynolds-averaged Navier–Stokes (RANS) method was employed to conduct a series of numerical simulations of waves on a trimaran equipped with a stern-flap interceptor with variable angles of attack. An optimal feature combination was designed by considering the spatial and temporal characteristics, such as the interaction between the stern-flap interceptor and hull, and the memory effect of the flow field. Based on long short-term memory (LSTM), a data-driven model of the stern-flap interceptor oriented towards anti-pitching control was constructed. In addition, the anti-pitching and drag-reduction mechanisms of the stern-flap interceptor were explored. The proposed model, which is oriented towards anti-pitching, establishes the relationship between the angle of attack of the appendage, the ship's attitude, and the stabilising moment applied to the hull. Experiments verified the accuracy and generalisation of the model. This study provides a theoretical basis for designing and developing an anti-pitching control system for wave-piercing trimarans.

Evaluation of Operation Patterns and Ship Needs on the Paciran-Bawean Crossing Route, East Java Province

KMP. Gili Iyang which operates on the Paciran-Bawean route has 2 trips/week with a crossing distance of 80 miles. However, the operation of ships on long distances is not balanced with the ideal number of trips, resulting in a buildup of vehicles and passengers at Paciran Port. Where the time needed to sail is 8 hours. Therefore, this research aims to determine the frequency, number of ships needed and efficient ship operation patterns according to the needs of service users. The analysis in this research includes load factor analysis, passenger and vehicle growth prediction analysis, ship frequency analysis, ship number requirement analysis, and scheduling analysis. From this analysis, it was concluded that the ideal number of ship frequencies on the Paciran-Bawean route is 1 trip/week, and the number of ships that must be operated is 1 ship, and the results of the analysis show that the schedule for ships serving the Paciran-Bawean route is still not yet in accordance. So rescheduling is needed from 2 trips/week to 1 trip/week and forecasting is needed for the next 5 years so that the number of trips is in accordance with the needs of service users, as well as the operation of the KMP. Dharma Kencana on the Paciran- Bawean route so that there is a balance between service users and service providers.

Sailing Towards Sustainability: How Seafarers Embrace New Work Cultures for Energy Efficient Ship Operations in Maritime Industry

It is imperative to take proactive measures in light of the escalating concerns about greenhouse gas (GHG) emissions of international shipping. The GHG study conducted by the International Maritime Organization (IMO) indicates that the sector accounted for 2.2% and 2.89 % of emissions in 2012 and 2018, respectively. As a result, IMO has endorsed strategies to reduce ship-induced emissions to 50% by 2050 and net zero emissions by 2100. For reducing carbon emissions, regulations such as the Energy Efficiency Design Index (EEDI) and Ship Energy Efficiency Management Plan (SEEMP) were implemented a decade ago. We collected data from 104 seafarers in 24 countries using purposive sampling, exploring how the energy-efficient operation of ships transforms their work cultures onboard ships. The majority of seafarers in our study agreed that energy-efficient ship operation has changed seafarers' working cultures over the last decade. Seafarers have adopted a variety of energy efficiency (EE) practices, including meticulous record-keeping of fuel consumption and adherence to Planned Maintenance Systems. As well as preparing for Port State Control (PSC) inspections, they follow energy-saving measures prescribed by the SEEMP. In addition to engine maintenance, energy-saving practices, accurate reporting and recording of EE-related data, and efficient power usage, they provide just-in-time arrival, crew training, energy-efficient lighting, environmental awareness, and slow steaming to minimize fuel consumption. The majority of seafarers implemented SEEMP successfully and met the company's objectives, but they did not receive any form of recognition or financial incentives. Although SEEMP can help shipping companies gain financial benefits and preserve the environment, seafarers do not receive tangible rewards or appreciation for implementing it. Only one-fourth of seafarers were rewarded with incentives, bonuses, formal recognition, or trophies. This study holds significant implications for policymakers, offering insight into seafarers' adaptation to energy-efficient ship operations and advocating for integrating Industry 4.0 technologies for EE regulations compliance by reducing seafarers' workloads and improving data accuracy.

Comparative analysis of the manoeuvrability performance for a 9000 tdw chemical/oil tanker

The concept of manoeuvrability is very important for efficient ship operation but also in ship safety. The aim of this paper is to test and perform a comparative analysis of manoeuvrability performance of a 9000 tdw chemical/oil tanker. The comparative analysis has been performed between the results obtained based from two software’s, namely PHP and MPP, but also between the results obtained in the sea trials with the output data from MPP. In this way it will be shown the differences (if any) in terms of manoeuvrability., and if the two used platforms are effective for providing preliminary determination of performances of manoeuvrability.

A Numerical Study on the Hydrodynamic Performance of a Tanker in Bow Sea Conditions Depending on Restraint Conditions

The importance of accurate ship performance estimation is increasing for efficient ship operation. Ship performance has been evaluated through model tests in the past, but there are limitations in terms of facilities and costs. With the spread of high-performance computers, the method of evaluating the performance of a ship by numerical analysis, especially computational fluid dynamics (CFD), has become common. There have been many numerical studies on added resistance under various wave conditions for many years, showing a high reliability. Meanwhile, most of the studies were conducted under conditions where the degree of freedom (DOF) of the ship was limited due to computational complexity. In this study, we tried to compare the added resistance performance and fluid dynamics of S-VLCC with 6 DOFs in the regular wave conditions. One of the methods for utilizing the 6 DOFs is the soft-mooring system, which allows springs to be attached to the bow and stern to recover the non-restoring force of the hull. The second method considers the free-running condition. The virtual disk is used for the self-propulsion of the ship, and the rudder can be rotated to maintain its course. The propeller rotation speed and rudder angle are controlled through PID control. The bow wave (ψ = 180°) and oblique wave (ψ = 150°, 120°) conditions were considered, and various regular wave conditions from short to long wavelengths were regarded. The effects of restraint conditions on the added resistance and motion response amplitude operator (RAO), according to each wave condition, were compared. As a result, there was a difference in the roll motion for each restraint condition, and the y-direction force and yaw moment generated on the hull were compared to analyze the cause. In addition, we observed the change in flow characteristics by comparing the streamlines around the hull and the nominal wake on the propeller plane.

Component Criticality Analysis for Improved Ship Machinery Reliability

Redundancy in ship systems is provided to ensure operational resilience through equipment backups, which ensure system availability and offline repairs of machinery. The electric power generation system of ships provides the most utility of all systems; hence, it is provided with a good level of standby units to ensure reliable operations. Nonetheless, the occurrence of undesired blackouts is common onboard ships and portends a serious danger to ship security and safety. Therefore, understanding the contributing factors affecting system reliability through component criticality analysis is essential to ensuring a more robust maintenance and support platform for efficient ship operations. In this regard, a hybrid reliability and fault detection analysis using DFTA and ANN was conducted to establish component criticality and related fault conditions. A case study was conducted on a ship power generation system consisting of four marine diesel power generation plants onboard an Offshore Patrol Vessel (OPV). Results from the reliability analysis indicate an overall low system reliability of less than 70 percent within the first 24 of the 78 operational months. Component criticality-using reliability importance measures obtained through DFTA was used to identify all components with more than a 40 percent contribution to subsystem failure. Additionally, machine learning was used to aid the reliability analysis through feature engineering and fault identification using Artificial Neural Network classification. The ANN has identified a failure pattern threshold at about 200 kva, which can be attributed to overheating, hence establishing a link between component failure and generator performance.

Analysis of Collected Data and Establishment of an Abnormal Data Detection Algorithm Using Principal Component Analysis and K-Nearest Neighbors for Predictive Maintenance of Ship Propulsion Engine

Because ships are typically operated for more than 25 years after construction, they can be considered mobile factories that require economic maintenance before being scrapped. Therefore, for stable and efficient ship operation, continuous maintenance systems and processes are required. Ships cannot be operated when defects or failures occur in any of the numerous systems configured in them, and research is urgently needed to apply predictive maintenance to propulsion engines with high maintenance costs using machine learning. Therefore, this study analyzes the operation and control characteristics of the propulsion engine, acquires engine data from the alarm monitoring system of the ship in operation, and then preprocesses the data by constructing a data preprocessing algorithm that incorporates the engine control characteristics. In addition, principal component analysis and K-nearest neighbors were used to check whether preprocessing data were classified based on engine control characteristics, and an algorithm capable of detecting abnormal data was built and verified to lay the foundation for predictive maintenance of ship propulsion engines using machine learning.

Marine route optimization using reinforcement learning approach to reduce fuel consumption and consequently minimize CO2 emissions

To meet the 2050 CO2 targets, the shipping industry which is responsible for about 3% of global CO2 emissions needs to be optimized in several aspects. Obviously, alternative fuels constitute the main measure in this respect. However, relatively high fuel prices in combination with increasing political and economic pressure may raise the need for more efficient ship operation. Ship route optimization can make an indispensable contribution to achieving this goal. In this sense, this paper applies an innovative approach for route optimization using Reinforcement Learning (RL). For this purpose, a generic ship model is first developed using Artificial Neural Networks (ANNs) to predict the fuel consumption of the ship. Moreover, various RL methods, namely Deep Q-Network (DQN), Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO) are applied. The application of RL enables continuous action space and simultaneous optimization of ship speed and heading. DDPG demonstrates the best results as an off-policy and policy gradient method which allows a continuous action space. For example, in the fuel consumption minimization scenario without time limitation, this method can achieve savings of 6.64%. For DQN as a method with discrete action space, this value is 1.07%.

A new power prediction method toward efficient ship design and operation

A new power prediction method toward efficient ship design and operation

Load optimization of central cooling system pumps of a container ship for the slow steaming conditions to enhance the energy efficiency

The implementation of International Maritime Organization regulations for CO2 emission reduction has oriented ships to sail at lower speeds. Speed reduction reduces fuel consumption of ships significantly. In order to perform efficient ship operation, energy demand throughout the whole engine room has to be decreased. The goal of the study is to minimize electrical power consumption during slow steaming operation, hence equivalent fuel consumption and emissions could be decreased. A computational study was carried out in order to clarify potential savings with respect to main engine load. The study quantifies the energy savings in main engine cooling system which has significant potential to reduce electrical power consumption in slow steaming operations. Operational requirements are determined with the help of realistic engine room simulator of a container ship which has waste heat recovery system. The values, obtained from the simulator were verified using the technical manual of a diesel engine, which have similar output power range. The results of calculations show that there is great potential to improve energy efficiency when variable pumps are used. Based on the results, from the main engine cooling system, 60% of electrical power demand reduction can be achieved. The power reduction saved by pumps, decreases considerable amount of marine diesel oil consumption as 296.2 tons where 367.4 tons of fuel needed by diesel generators or oil fired boiler. The reduction in fuel consumption is 80% that the saving in the central cooling system corresponds 948 tons of CO2 emission reduction and $207,300 cost saving.

Exploring the new policy framework of environmental performance management for shipping: a pilot study

Changes in weather patterns are now recorded more and more frequently in various locations of the Earth. Collective action is needed to deal with the challenges of climate change; the maritime industry must contribute its fair share to those activities, aiming to mitigate a risk that can threaten humanity’s own existence. On the positive side, both the European Union (EU) and the International Maritime Organization (IMO) have clear ambitions to reduce greenhouse gas (GHG) emissions from ships that are linked to climate change, and two similar albeit separate regimes have been introduced. EU’s monitoring, reporting, and verification (MRV) regulation of CO2 emissions has already been influencing shipping activities, since the related data collection has started on the 1st of January 2018. The second initiative is the IMO’s data collection system (DCS), which revolves primarily around fuel consumption; the necessary data collection started on the 1st of January 2019. To support an effective environmental performance management framework for the maritime industry, it is necessary to create a robust database that describes all aspects of energy efficient ship operations, with an emphasis on the inventory of CO2 emitted from ships. The analysis at hand examines the challenges in the relevant data collection scheme, with a particular focus on MRV, considering that the specific regulation is already operationalized. An online survey was conducted among maritime professionals in Singapore and Bangladesh to examine the gap between current energy-related regulations/policies and standing operational practices. The findings address the issues relating to shipping operations and certain compliance, institutional and management matters. They also identify the industry’s preparedness for this new policy framework of environmental performance management as well as the impact on existing energy efficiency practices. A very important conclusion derived is that the quality of data collected is crucial for the effective management of emissions related to shipping and the associated fuel consumption.

A generic energy systems model for efficient ship design and operation

There is an environmentally and economically motivated need to reduce the fuel consumption and air emissions of ships. To achieve a reduction in energy consumption, the energy flow in the entire energy system of a ship must be analysed in both the component, or subsystem, level as well as in a holistic way to capture the interactions between the components. Of the currently available energy consumption monitoring and prediction methods or models, no single model or method can be used to assess the energy efficiency of an arbitrary vessel in both the early design phase and during operation. This study presents a new generic ship energy systems model that can be used for this purpose. This new model has two parts: one for the assessment of a ship’s energy consumption based on an ordinary static power prediction and one for advanced operational analysis, considering hydrodynamic and machinery systems effects. A Panamax tanker vessel was used as the case study vessel to prove the versatility of the model for five example simulations for the design and operation of ships. The examples include variations of the main dimensions, propeller design, engine layout and the operational profile on a North Atlantic route. From the results, different areas with a potential for energy savings were identified.

Achieving energy efficient ship operations under third party management: How do ship management models influence energy efficiency?

Profitable energy saving measures are often not fully implemented in shipping, causing energy efficiency gaps. The paper identifies energy efficiency gaps in ship operations, and explores their causes. Lack of information on energy efficiency, lack of energy training at sea and onshore and lack of time to produce and provide reliable energy efficiency information cause energy efficiency gaps. The paper brings together the energy efficiency and ship management literatures, demonstrating how ship management models influence energy efficiency in ship operations. Achieving energy efficiency in ship operations is particularly challenging under third party ship management. Finally, the paper discusses management implications for shipping companies, which outsource ship management to third parties.

Fuel usage data analysis for efficient shipping operations

There are incentives from maritime regulatory bodies to operate ships more efficiently, driven by the need to reduce CO2 budget.In order to establish more efficient ship operations, fuel consumption across the full operational profile of a vessel is needed. This could be accomplished through a complete characterisation through extensive sea-trials, or interpretation of data from monitoring systems. Results from repeated testing under controlled sea-trial conditions provides high-fidelity data, however, this approach is prohibitively expensive and requires repeating as the condition of the vessel changes with time. Conversely, data monitoring devices are relatively inexpensive, however, the process of analysing data can be complex, particularly when a ship׳s activities are diverse.This paper describes a methodology for associating ship activity with corresponding segments of a data-stream from a commercially available monitoring system. Further analysis is then performed to determine the fuel efficient performance of the ship. The case-study used is a harbour tug, although the approach used is applicable to other ship types, its success on this basis indicates the methodology is robust. To validate the methodology, results from the data analysis are compared to fuel consumption data measured under sea-trial conditions, and are found to be in close agreement.

An artificial neural network based decision support system for energy efficient ship operations

Reducing fuel consumption of ships against volatile fuel prices and greenhouse gas emissions resulted from international shipping are the challenges that the industry faces today. The potential for fuel savings is possible for new builds, as well as for existing ships through increased energy efficiency measures; technical and operational respectively. The limitations of implementing technical measures increase the potential of operational measures for energy efficient ship operations. Ship owners and operators need to rationalise their energy use and produce energy efficient solutions. Reducing the speed of the ship is the most efficient method in terms of fuel economy and environmental impact. The aim of this paper is twofold: (i) predict ship fuel consumption for various operational conditions through an inexact method, Artificial Neural Network ANN; (ii) develop a decision support system (DSS) employing ANN-based fuel prediction model to be used on-board ships on a real time basis for energy efficient ship operations. The fuel prediction model uses operating data – ‘Noon Data’ – which provides information on a ship’s daily fuel consumption. The parameters considered for fuel prediction are ship speed, revolutions per minute (RPM), mean draft, trim, cargo quantity on board, wind and sea effects, in which output data of ANN is fuel consumption. The performance of the ANN is compared with multiple regression analysis (MR), a widely used surface fitting method, and its superiority is confirmed. The developed DSS is exemplified with two scenarios, and it can be concluded that it has a promising potential to provide strategic approach when ship operators have to make their decisions at an operational level considering both the economic and environmental aspects.

The impact of port operations on efficient ship operation from both economic and environmental perspectives

Recently, shipping lines have focused on efficient ship operation, which relates to energy efficiency issues in shipping and, particularly, to operational issues such that the minimisation of fuel consumption and resulting greenhouse gas emissions. Efficient ship operation in container lines is closely related to the ship’s time at sea and ship’s time in port. Reduction in port time, thanks to high-quality port operations, allows improvement in the operational efficiency of a liner service by reducing the fuel consumption of a ship at sea and its resulting CO2 emissions. The main goal of this article is to investigate how time in port affects efficient ship operation in terms of operating costs, CO2 emissions and externalities. For this, as a methodology, a simulation based upon system dynamics is introduced. Major finding is that less time in port resulting from the improvement of port operations contributes to efficient ship operation in terms of operating costs, amount of CO2 emissions and external effects in the liner shipping industry. In particular, a sensitivity analysis on efficient ship operation vis-à-vis the quality of port operation shows that bigger ships need to select highly productive calling ports that provide less time in port.

Development of a Spectral Method and a Statistical Wave Model for Crack Propagation Prediction in Ship Structures

As a result of the wide use of high-tensile steel and the imperfect fabrication process in ship construction as well as some uncertainties in ship fatigue design, cracks could be initiated much earlier than expected. The presence of fatigue cracks greatly affects a ship's structural safety and serviceability. To ensure structural safety and perform reliable crack inspection and maintenance planning, it is important to know how fast cracks can grow in ship structures. In the current study, the principles of fracture mechanics are used for crack propagation analysis in ships. By taking into account the special properties of a ship's stress response, an efficient spectral method is proposed and validated for the prediction of crack propagation in ship structures. In this spectral method, structural stresses are assumed to be narrow-band Gaussian processes. Furthermore, for crack inspection and maintenance planning based on crack growth, it is essential to know the wave environments encountered in a ship's future operations. Therefore, a spatiotemporal statistical wave model based on both satellite and buoy measurements is briefly introduced. It is developed to generate wave environments along arbitrary ship routes. Finally, the deck longitudinal stiffener of a 2800TEU containership is used to demonstrate the application of the spectral method and the wave model for the prediction of crack propagation in ships. The route information and operating conditions are taken from full-scale measurements of this ship. In the case study, the scatter of crack propagation associated with the wave environments encountered is also investigated. The results from this investigation indicate possible potentials of crack inspection and maintenance optimization to enable more efficient ship operation.

Development of a Spectral Method and a Statistical Wave Model for Crack Propagation Prediction in Ship Structures

As a result of the wide use of high-tensile steel and the imperfect fabrication process in ship construction as well as some uncertainties in ship fatigue design, cracks could be initiated much earlier than expected. The presence of fatigue cracks greatly affects a ship's structural safety and serviceability. To ensure structural safety and perform reliable crack inspection and maintenance planning, it is important to know how fast cracks can grow in ship structures. In the current study, the principles of fracture mechanics are used for crack propagation analysis in ships. By taking into account the special properties of a ship's stress response, an efficient spectral method is proposed and validated for the prediction of crack propagation in ship structures. In this spectral method, structural stresses are assumed to be narrow-band Gaussian processes. Furthermore, for crack inspection and maintenance planning based on crack growth, it is essential to know the wave environments encountered in a ship's future operations. Therefore, a spatiotemporal statistical wave model based on both satellite and buoy measurements is briefly introduced. It is developed to generate wave environments along arbitrary ship routes. Finally, the deck longitudinal stiffener of a 2800TEU containership is used to demonstrate the application of the spectral method and the wave model for the prediction of crack propagation in ships. The route information and operating conditions are taken from full-scale measurements of this ship. In the case study, the scatter of crack propagation associated with the wave environments encountered is also investigated. The results from this investigation indicate possible potentials of crack inspection and maintenance optimization to enable more efficient ship operation.

Stochastic uncertainty modelling for ship design loads and operational guidance

Understanding and quantification of uncertainties are important attributes for the assessment of the performance, reliability and risk of complex engineering structures and systems. From a naval architecture perspective the consideration of the uncertainties related to ship’s seakeeping responses and wave induced loads is necessary for the assessment of ship design as well as for safe and efficient ship operations. To this end, the efficient processing of large amounts of data and the stochastic load combination by use of available numerical models may assist with the rationalisation of modelling assumptions and support the validation and verification of design and decision making criteria in the context of risk based ship design. This paper presents recent advances in (a) modelling the combined hydrodynamic responses of ship structures using cross-spectral combination methods and (b) in implementing uncertainty models used for the development of modern decision support systems as guidance to ship’s master.