Ship Operation Research Articles

A deep learning method for the prediction of ship fuel consumption in real operational conditions

In recent years, the European Commission and the International Maritime Organization (IMO) implemented various operational measures and policies to reduce ship fuel consumption and related emissions. The effectiveness of these measures relies upon developing accurate predictive models encompassing the influence of real operational conditions. This paper presents a deep learning method for the prediction of ship fuel consumption. The method utilizes big data analytics from sensors, voyage reporting and hydrometeorological data, comprising of 266 variables made available following sea trials of a Kamsarmax bulk carrier of Laskaridis Shipping Co. Ltd. A variable importance estimation model using a Decision Tree (DT) is used to understand the underlying relationships in the available dataset. Consequently, a deep learning model is developed to understand the influence of sailing speed, heading, displacement/draft, trim, weather, sea conditions, etc. on ship fuel consumption (SFC). This is achieved by incorporating attention mechanism into Bi-directional Long Short-Term Memory (Bi-LSTM) network. The potential of the new method is demonstrated by training data streams corresponding to real ship fuel consumption rates as well as internal and external operational conditions. A comprehensive comparison with existing methods indicates that the Bi-LSTM with attention mechanism presents the best fit when using high frequency data. It is concluded that subject to further testing and validation the method could be used for the development of decision support systems for monitoring environmentally sustainable ship operations.

An overview of seafarers’ engagement and training on energy efficient operation of ships

As the shipping industry contributes significantly to anthropogenic CO2 emissions, it is imperative to take urgent steps to reduce its impact on the environment. This study delves into the pivotal role of seafarers in achieving energy-efficient ship operations, which is crucial for mitigating climate change. In the study, 58 articles spanning a decade are analyzed, and key influencers are identified, including knowledge, awareness, education, rewards, social factors, technology, and barriers to participation. As digital tools are integrated into seafarers' roles in ship operations, comprehensive training initiatives will be necessary. The study underscores the urgent need for tailored seafarers' training programs, integrating interactive tools, and addressing gaps in knowledge and motivation. Moreover, it highlights the transformative impact of digital tools, necessitating the reevaluation of energy-efficient ship practices. Collaborative efforts between stakeholders, especially ship owners, ship managers, and crewmembers, must emphasize financial incentives and regulatory frameworks. Future research should evaluate diverse training methods and seafarers' perspectives, bridging knowledge gaps in energy-efficient ship operations after a decade of IMO regulations. This study equips policymakers, training institutions, and industry stakeholders with insights to enhance seafarers' engagement, thereby fostering energy efficiency and environmentally conscious maritime practices. These efforts are instrumental in promoting energy-efficient ship operations and addressing environmental challenges within the shipping industry.

Comprehensive Assessment of Hull Geometry Influence of a Modernized Ship on Maneuvering Performance and Propulsion System Parameters

The necessity to preserve economic efficiency of cruise ships operation stipulates fleet modernization in order to avoid expenses on ordering and construction of new ships. In this paper an approach based on hull length increase in the process of ship modernization is discussed. The method of evaluation of changes in maneuvering characteristics of ship after modernization is developed taking into account the operational parameters of propulsive electric power plants. The calculations are based on the analysis of transient modes of propulsive power plants operation during the corresponding maneuvers. The parameters influencing the characteristics of ship motion during turning circle are revealed; their significance is estimated, comparative analysis of the effect of ship hull length on maneuvering parameters before and after modernization is carried out. It was shown that in some cases the characteristics of the ship’s controllability and operating parameters of the ship power plant after modernization remain within the permissible limits. The comparative results show that the increase in hull length leads to insignificant deterioration of the main maneuverability characteristics while the electric power plant indicators practically do not deteriorate, which confirms the expediency of such modernization.

Numerical and experimental study of stern flaps impact on resistance and propulsion of high–speed displacement ships

This study investigates hydrodynamic interactions between a high-speed displacement ship and various stern flap configurations. It combines towing tank model tests and advanced Computational Fluid Dynamics (CFD) simulations to explore hydrodynamics and energy-saving potential. Sixteen flap combinations were tested across Froude numbers (Fn) from 0.198 to 0.452 to understand post-installation hydrodynamics and energy-saving potential. The alignment between model tests and CFD simulations reinforces the potential of stern flaps to enhance efficiency and environmental friendliness in high-speed displacement vessels with transom sterns. CFD enhanced visualisation of flow, pressure, and other hydrodynamic parameters. The study reveals that the stern flaps reduce resistance and effective power, saving energy across all the combinations. However, the effectiveness of the flaps is limited at lower speeds (Fn < 0.198), where increasing flap angles incur higher resistance penalties. The greatest decrease in resistance is noted when the Froude number (Fn) is at 0.367, with a subsequent reduction after that. Stern flaps influence trim, sinkage, and hydrodynamic length, reducing wave-making resistance without increasing friction. Increased wake fraction and reduced thrust deduction enhance propulsion efficiency, while stern flaps suppress waves, lowering overall resistance. A reduction of effective power by 6% was observed in the present study. This research provides valuable insights into stern flap hydrodynamics and energy-saving potential, guiding ship design and operation.

Передумови розвитку судноплавства України

The article provides coverage of possible approaches to the formation of economically attractive conditions for the operation of ships after the victory, which today is the main goal of the economic science of the maritime industry. In this regard, the main task of the publication is the implementation of strategic goals in shipping, the need to ensure the competitive advantages of Ukraine's foreign trade and the efficiency of work on the global freight market. In addition to the size of the total deadweight, the article provides approaches to establishing an economically feasible number of fleet units that will meet the conditions for achieving the lowest risk of the probability of loss-free operation of each shipping company. This is due to the fact that there is an optimal number of ships in which the losses incurred by one ship are compensated by the profit received by another fleet. The conclusions provide recommendations for the development of shipping in Ukraine.

JUSTIFICATION OF THE CONCEPT OF SAFETY-ORIENTED SHIP OPERATIONS DURING CARGO TRANSPORTATION

Abstract. The article examines topical issues of maritime transportation safety in the context of modern transport production processes. A comprehensive analysis of the key factors affecting the safety of navigation is carried out, and a structured system for classifying these factors is developed. The main categories of safety, including technical, navigational, technological and environmental safety, are considered, and the role of the human factor in ensuring the safety of navigation is determined. Comprehensive research methods were applied, including the analysis of literature sources, statistical data, case studies and expert opinions. The result of the work is a developed system of concepts for ensuring safety in maritime transport, which can contribute to improving safety and reliability in this area. Objective. The purpose of the article is to conduct a comprehensive analysis of shipping safety issues in the context of modern transport production processes. The paper aims to thoroughly consider the key factors affecting the safety of maritime transportation and to provide a structured system for classifying these factors. Additionally, the article identifies the main safety categories and considers the role of the human factor in ensuring all aspects of shipping safety. As a result, a general approach to shipping safety is formulated, which takes into account all the necessary aspects and methods of ensuring safety in the process of maritime transportation. Research methods. This article uses a comprehensive research method, including the analysis of literary sources and scientific publications, the analysis of statistical data on incidents in maritime shipping, and also uses case studies and expert assessments. Additionally, the method of modeling situations that could potentially affect shipping safety was used. All these methods were used for a comprehensive review and classification of factors affecting safety and the development of a system of concepts for ensuring safety in maritime transportation. Results. As a result of the study, a comprehensive system of concepts for ensuring safety in maritime transportation was developed. It includes four main types of safety: technical, navigational, technological and environmental. Each of these aspects of safety has been analyzed in detail and classified depending on the stages of the shipping production process. Scientific novelty. The novelty of this article lies in the development of an approach to comprehensive analysis and security in maritime transportation, which can contribute to improving safety and reliability in this industry. Practical significance. The developed comprehensive system of concepts for ensuring safety during maritime transportation provides specific recommendations and methods for ensuring safety at various stages of ship operation, including cargo transportation and other ship operations.

PTSD Among Refugee Rescue Workers: Effects of Compassion Satisfaction and Fatigue on Burnout

Exposure to traumatic life events can affect workers’ prevalence to post-traumatic stress disorder (PTSD) and quality of life. A cross-sectional study was conducted among 126 volunteers and 33 professional rescue workers in the Open Arms rescue ship operating in the Aegean Sea to analyze the effects of stress exposure on the professional quality of life. Volunteers presented more compassion satisfaction and less burnout than professionals. In terms of gender, women showed more secondary traumatic stress and intrusion than men. Finally, burnout can be explained by age, compassion satisfaction, and secondary traumatic-stress. These results show the necessity of tailored interventions for the people who work in trauma contexts.

CFD Analysis of the Influence of Marine Fouling on the Performance of High-Speed Planning Craft

Marine fouling, such as heavy slime, is the result of algae and other invertebrates settling and growing on the surfaces of planning hulls that are immersed in water. This may result in a range of serious and costly economic problems. The amount of resistance that planning hulls encounter when operating in maritime settings is an important aspect that considerably impacts the performance, energy efficiency, and operational expenses associated with these hulls. Because of this, the focus of this investigation will be on high-speed planning craft ships. In recent years, there has been a rise in the number of instances in which this sort of ship has been used for military, commercial, and recreational purposes. With the use of CFD analysis, the purpose of this study is to conduct an exhaustive investigation into the effect that the surface roughness of heavy slime has on the resistance of planing hulls. The results will be compared to a reference scenario, including a hydrodynamically smooth hull, to determine how much heavy slime affects resistance. According to the findings of this research project, the presence of heavy slime on the surface of a high-speed planing ship had a significant impact on the performance of the ship, particularly on the friction resistance, which saw an increase of up to 65% as a consequence of the presence of the slime. The results of this study will have substantial repercussions for ship designers, naval architects, and operators. The findings will provide them with useful information that will allow them to improve hull designs and devise effective tactics for fouling management.

A coordinated generation and voyage planning optimization scheme for all-electric ships under emission policy

The International Maritime Organization has introduced the concept of Emission Control Area to reduce sulfur emissions from coastal areas. The expensive low-sulfur fuels are required to be used in Emission Control Area, leading to increased sulfide emissions due to bypassing by ship operators. It creates new challenges for navigation and power generation scheduling of all-electric ships. This article presents a new bi-objective joint optimization scheme for ship sailing routes and energy management. It considers emission control strategies to balance the total cost of operation and sulfur dioxide emissions throughout the ship’s voyage. Unlike previous optimization problems with fixed routes and sailing time, the influence of emission policies on the operator’s navigation decisions is considered. The route options and sailing time are treated as variables embedded in the model. In addition, the optimization accuracy is improved by integrating the model into mixed integer linear programming through a modified piecewise linearization model. The results show that the total operating cost for the same route is reduced by 6.05%, and the SO2 emission is 8.36% after integrating the emission policy influencing factor in the model. The effectiveness of the proposed scheme is validated, and the model’s necessity for optimizing ship power generation and voyage within Emission Control Area is also illustrated.

A novel deterministic search-based algorithm for multi-ship collaborative collision avoidance decision-making

Ship collision avoidance is critical to maritime safety, but maritime traffic patterns are becoming increasingly complex as the number of vessels of all types increases. Therefore, how to improve the collision avoidance effectiveness and efficiency of two ships and multiple ships is crucial. This study proposes a comprehensive collaborative collision avoidance framework that takes into account both safety and economic factors. By analyzing ship navigation characteristics, we formulate a new collision avoidance cost function that covers navigation safety and economic benefits. Furthermore, in accordance with the COLREGS guidelines, this paper adopts a deterministic search algorithm to calculate collision avoidance trajectories involving two or more vessels, and uses a proportional integral differential (PID) algorithm to adjust ship maneuvering based on the derived collision avoidance decisions. In parallel, we conducted extensive simulation studies to evaluate encounter scenarios involving two and multiple vessels. Results show that the proposed collaborative collision avoidance framework ensures regulatory compliance and also improves navigation safety and economic efficiency. This algorithm has important reference value for ship operators to formulate and implement effective collision avoidance strategies.

A Critical Review of On-Line Oil Wear Debris Particle Detection Sensors

In the field of marine engineering, the friction and wear experienced by rotating mechanisms are recognized as significant contributors to the failure of marine machinery. In order to enhance the safety and dependability of marine ship operations, the implementation of on-line oil wear debris particle detection sensors enables the on-line monitoring of oil and facilitates the rapid identification of abnormal wear locations. This paper provides a critical review of the recent research progress and development trends in the field of sensors for on-line detection of oil wear debris particles. According to the method of sensor detection, wear debris particle detection sensors can be classified into two distinct categories: electrical and non-electrical sensors. Electrical sensors encompass a range of types, including inductive, capacitive, and resistive sensors. Non-electrical sensors encompass a range of technologies, such as image processing sensors, optical sensors, and ultrasonic sensors. Finally, this review addresses the future research directions for wear debris particle detection sensors in light of the challenging problems currently faced by these sensors.

Hazard Identification of Hydrogen-Based Alternative Fuels Onboard Ships

It is essential to use alternative fuels if we are to reach the emission reduction targets set by the IMO. Hydrogen carriers are classified as zero-emission, while having a higher energy density (including packing factor) than pure hydrogen. They are often considered as safe alternative fuels. The exact definition of what safety entails is often lacking, both for hydrogen carriers as well as for ship safety. The aim of this study is to review the safety of hydrogen carriers from two perspectives, investigating potential connections between the chemical and maritime approaches to safety. This enables a reasoned consideration between safety aspects and other design drivers in ship design and operation. The hydrogen carriers AB, NaBH4, KBH4 and two LOHCs (NEC and DBT) are taken into consideration, together with a couple reference fuels (ammonia, methanol and MDO). After the evaluation of chemical properties related to safety and the scope of the current IMO safety framework, it can be concluded that safety remains a vague and non-explicit concept from both perspectives. Therefore, further research is required to prove the safe application of hydrogen carriers onboard ships.

Selection of auto-carrier loading policy in automobile shipping

Auto-carriers are widely used to ship automobiles by land from origins to destinations. To enable the compact storage of multiple automobiles, auto-carriers are specially designed such that automobiles can only be loaded and unloaded through a common exit of an auto-carrier, which complicates the automobile loading and unloading operations. This study is motivated by the lack of consensus in the automobile shipping literature regarding whether reloading operations should or should not be prohibited while auto-carriers are en-route. The impact of a loading policy on auto-carrier shipping is not well understood in the literature. We thus examine two types of loading policies (namely reloading prohibited versus allowed), and design network-based optimization methods for each resulting policy variant. We then conduct extensive numerical experiments based on the data from the Southeast region of the USA to investigate the impact of a loading policy on automobile shipping operations through a trade-off analysis between solution quality and computational burden. We find that two proposed policy variants when reloading is allowed can achieve a desirable compromise between cost efficiency and computational effort. A full-scale analysis involving 10 auto-carriers with various capacities further confirms that with these policy variants, substantial cost savings are achieved with reasonable computation effort. The research findings from this article are expected to inform the choice of an appropriate auto-carrier loading policy for automobile transportation companies.

OPTIMIZING SUSTAINABLE MATERIAL SELECTION FOR AIR CONDITIONERS IN A SUPPLY CHAIN

In order to cut their carbon footprint and promote environmental sustainability, the majority of businesses have now turned towards sustainable practises in their manufacturing processes and supply networks. The use of sustainable materials has drawn a lot of attention recently as a crucial step in accomplishing these goals. Choosing the material that is most suited for a product can be difficult, despite the fact that there are many sustainable materials available. This study uses machine learning – a random forest algorithm and multi-criteria decision analysis (MCDA) to optimise the use of sustainable materials in supply-chain operations. The study uses machine learning algorithms to analyse data on different sustainable materials, their characteristics and their effects on the environment. The study also investigates how an optimised material selection affects the whole supply chain, including the production, packing and shipping operations. The research offers a complete strategy for reducing the environmental effect of industrial processes by combining approaches from material engineering, supply chain management and machine learning. The novelty of this work resides in its integration of material engineering and machine learning strategies to enhance the supply chain choice of sustainable materials. As a notable example, the study highlights the potential of mycelium as a sustainable material for air conditioner components. Mycelium’s unique properties, such as its biodegradability, lightweight nature and adaptability position it as a promising candidate, enhancing the environmental profile of air conditioners. By incorporating mycelium-based components, manufacturers can significantly reduce carbon emissions, resource consumption and waste generation throughout a product’s lifecycle. This investigation underscores both the viability of mycelium and the broader significance of innovative material choices in reshaping industries towards a more sustainable future. Through such advances, this research not only contributes to the air conditioning sector but also establishes a paradigm for sustainable material adoption with far-reaching positive implications.

SYSTEMIC APPROACHES TO RATIONAL MANAGEMENT OF FUNCTIONAL MARINE TECHNICAL SYSTEMS AND COMPLEXES

In the present era, the development of effective and safe management methods for marine technical systems and complexes (MTSC) is gaining particular importance. The article, considering the continuous progress of science and technology, proposes the development of a comprehensiveapproach to the rational management of functional MTSC, integrating scientific strategies, automation, and intelligent systems.The main goal of the research is to create a framework structure of comprehensive measures for managing MTSC in conditions of partial internal and external uncertainty, with a special emphasis on the human factor and ergonomics in management. A deep risk analysis is proposed, including a review of the evolution of risk assessment methods, from intuitive to scientifically substantiated strategies, and the implementation of automated and intelligent systems in the processes of managing MTSC risks.The work focuses on the importance of creating a structural model of information support for MTSC, including the identification of key components focused on risks, studying internal and external factors affecting MTSC, and developing mechanisms for their monitoring and analysis. Significant attention is paid to the development of a scheme for ensuring rational management of MTSC in conditions of partial uncertainty, with an emphasis on creating adaptive management strategies.The importance of developing an intelligent decision-making model for MTSC is emphasized, which includes a detailed analysis of methods for intelligent data analysis specific to ship technical systems, the implementation of machine learning for dynamic ship management, and the development of criteria for management rationality.Finally, the article highlights the need to refine the method for deriving the coefficient of rational management of MTSC, including the development of models of interaction between operators and technical means to optimize interfaces and train operators.Thus, a comprehensive approach to managing MTSC is proposed, integrating scientific strategies,automation, intelligent systems, ergonomics, and considering the importance of the human factor. This approach aims to increase the efficiency, speed, accuracy, and safety of managing MTSC, especially considering the importance of monitoring the actions of ship operators. Keywords:rational management; ship technical systems; automation and intelligent systems; risk management; ergatic aspects; human factor.

Operational Risk Management On The Training Ship Bung Tomo

Risk management plays a crucial role in ensuring the sustainability of an organization's operations. At the Surabaya Navigation Polytechnic, Bung Tomo's training vessel became the backbone for cadets to undergo navigation training. However, it is important to acknowledge that the ship's operational activities are not exempt from potential risks. Therefore, the study aims to identify potential obstacles or issues that may arise in the implementation of risk management at the Tomo Training Ship. This research adopts a qualitative descriptive approach, prioritizing an in-depth understanding of the observed phenomena. Various data collection techniques, such as observations, interviews, and documentation, are used to gain comprehensive insights. The results of this study reveal that the Engine of Tomo's Training Ship faces the highest level of risk. It's related to the fact that the ship hasn't undergone a major dock process since it was officially inaugurated six years ago, causing frequent damage. Therefore, risk management focused on the engine aspects becomes an urgent need to minimize potential interference in ship operations. Precautionary measures, periodic maintenance, and possible risk reduction must be implemented carefully to ensure the safety and reliability of the Tomo Brother's Training Ship during the cadets' sailing training.

Probabilistic analysis of operational ice damage for Polar class vessels using full-scale data

To ensure the safety of maritime operations in polar waters, the IMO enforced the International Code for Ships Operating in Polar Waters (Polar Code) in 2017. To address ice navigation related risks, the Polar Code refers to a set of guidelines known as the Polar Operational Limit Assessment Risk Indexing System (POLARIS). Following POLARIS, operational limits for ice navigation are defined based on the Risk Index Outcome (RIO) value, which takes into account the prevailing ice conditions and the ice class of a ship.Recent studies indicate that the POLARIS guidelines are well-founded. However, no direct relationship between RIO values and the probability of an ice-induced hull structural damage has been established. To enable a more accurate analysis of ice navigation risks, this article addresses this issue by (i) relating measured ice-induced loads to RIO values corresponding to the ice conditions in which the loads were measured, (ii) calculating the load limits for plastic deformation and rupture of the ice belt of hull structures representing different ice classes, and (iii) defining the probability of structural damage for different load limits. The study utilizes long-term full-scale ice load measurements carried out onboard Polar Supply and Research Vessel (PSRV) S.A. Agulhas II in the Antarctic Ocean. The load limits were calculated for ice class standards, PC3, PC4, PC5, PC6, and PC7 in accordance with the Unified Requirements of the International Association of Classification Societies (IACS).On a general level, the results are consistent with earlier findings indicating that the POLARIS guidelines are well-founded. If a ship operates mainly at ‘normal operation’ level, the probability for fracture at hull are at probability levels of 10-3 and 10-4 for ice classes PC3 to PC5. The probability levels for PC6 and PC7 are higher that is possibly a result from conservative load probability distributions. When the portion of operations at ‘special consideration’ level becomes significant, the probability of fracture at the hull increases significantly. However, large ice thicknesses and the largest load magnitudes may be associated with positive RIO values. Some inconsistencies are recognized, and the uncertainty and limitations of the analysis are discussed.

Toward optimized operation of freshwater generator using computer vision, and its economic and environmental benefits

Sufficient quantities of fresh water (FW) must be maintained for the operation of ships and fresh water generators (FWGs), used to produce FW on ships tend to be suboptimal because of work schedules and low-skilled marine crew. Therefore, a system that optimally and automatically operates the discharge valve of an FWG distillate pump by recognizing the FW condition through a sight glass using computer vision technology was developed. Three deep-learning models were trained using videos of FW flowing and filling the sight glass. An optimal model structure was selected in the pre-test phase, which consisted of (i) a test using a camera and a monitor showing the validation videos, and (ii) a test based on data. In the real-test phase, an electrical valve and stepper valve were used as optimization valves, and the flow rates of the fuel oil for the generator engine (G/E) and FW for the FWG were recorded for 10 experimental conditions. The stepper valve operated in a more stable manner than the electrical valve, and its prediction performance with CNN-LSTM was superior. Finally, the economic and environmental impacts were evaluated based on the flow rates of fuel oil for the G/E and FW for the FWG.

Comprehensive evaluation of machine learning models for predicting ship energy consumption based on onboard sensor data

Machine learning models for predicting ship energy consumption are built and their influencing factors are investigated. First, data collected from a real ship is preprocessed. Six machine learning methods are used to establish the prediction models of ship fuel consumption, and the performance of models is evaluated by Mean Absolute Error, Coefficient of Determination and training time. Then, by analysing the correlation and importance of the features, it's studied whether the model established complies with the laws of physics. Finally, the factors affecting the prediction performance of machine learning models are analysed. The results show that Random Forest and Extreme Gradient Boosting are the most suitable algorithms for ship fuel consumption prediction. Data preprocessing, data normalisation, training sample size, model type, ship operating conditions, as well as the thermotechnical parameters of main engine have impact on the prediction performance. In particular, when taking the thermotechnical parameters into consideration, R2 is increased by 0.32%, MAE is reduced by 5.0%.

The enhanced role of canals and route choice due to disruptions in maritime operations

PurposeThis paper focusses on the aftermath of disruptions and the importance of the two largest canals (Suez and Panama), commenting on how during the pandemic the canal fees were lowered. Considering the ongoing efforts to decarbonize shipping, some of the ongoing disruptions will help reach these objectives faster.Design/methodology/approach Following a literature review of route choice in shipping, and a presentation of significant disruptions in recent years, the author deploys a simplified fuel consumption model and conduct case study analyses to compare different routes environmentally and economically.Findings The results explain why at times of low fuel prices as in 2020, canals provided discounts to entice ship operators to keep transiting these, instead of opting for longer routes. Considering the ongoing repercussions of the pandemic in supply chains, as well as the potential introduction of market-based measures in shipping, the value of transiting canals will be much higher in the coming years.Research limitations/implications The main limitation in this work is that the author used the publicly available information on canal tolls, for the different ship types examined.Practical implications The envisioned model is simple, and it can be readily used for any ship and route (port to port) combination available, if ship data are available to researchers.Social implications It is possible that canal tolls will increase, to account for the additional environmental benefits brought to ship operators.Originality/value The methodology is simple and transferable, and the author proposes several interesting research questions for follow-up work.