This article examines the potential implications of using iron powder as an alternative fuel on the design and performance of container ships. Iron powder is a relatively new alternative energy carrier and one in which little research has been done into the application on-board vessels as part of the maritime energy transition. The key benefits of iron powder are that it is a circular energy carrier and the combustion process emits no greenhouse gases. Transitioning to iron powder is expected to have far reaching implications for the design and performance of ships. Thus, this paper aims to perform the first study assessing the potential of this concept applied to container ships. To do so, a preliminary design space was explored with a custom parametric design model developed to generate preliminary designs of iron fuelled container ships as a function of the operational profile. Using this parametric design model, it was identified that iron fuelled container ships are weight limited, unlike conventionally fuelled container vessels. Furthermore, iron fuelled container ships are best suited for short voyages at low cruising speed. For these voyages, it was concluded that iron fuelled ships are economically feasible; however, other alternative marine fuels are likely more profitable than iron due to the low efficiency of iron fuelled ships and the high cost of iron per unit energy.

Objective: This study investigates the implementation of the waterborne platooning transport concept in two of the largest European inland navigation corridors, the Rhine and the Danube region. Each region has different geo-economic and environmental features. These features are compared, and their effects on implementing a waterborne platooning transport concept are studied. The waterborne platooning concept, referred to as the Vessel Train, aims to reduce crew cost by automating the navigation tasks and moving the navigational responsibility to the leading vessel of the platoon, which is fully manned. Methods: The implementation of the Vessel Train is assessed by making use of a developed model, which allows the assessment of the concept's viability by comparing the annual cost per transported ton of a reference vessel that sails individually to a vessel that sails as a part of a VT on the same route. Results: The results conclude that the application of waterborne platooning on the Rhine is more promising than on the Danube. The low wages hamper the implementation of the concept on the Danube in the region, the low traffic density on the waterway, and the common use of large push tows instead of self-propelled vessels. Implications for research: As determined in the analysis for the Rhine case, a reduction in transport cost would make waterborne transport more attractive. However, other factors, such as the further integration of the VT in the overall supply chain, play a role in the successful implementation of this IWT transport concept. Applying the VT concept in the Danube case requires more potential cargo flows, which can be obtained by adding push convoys into the vessel train. This way of transport is more numerous on the Danube than self-propelled vessels. Both of these aspects should be studied further.

Over the next few years, digitalization and automation are expected to be key drivers for maritime transport innovation to be key drivers for maritime transportation innovation. This revolutionary shift in the shipping industry will heavily impact the reliability of the machinery which is intended to be operated remotely with minimum support from humans. Despite a large amount of research into autonomous navigation and control systems in maritime transportation, the evaluation of unattended engine rooms has received very little attention. For autonomous vessels to be effective during their unmanned mission, it is essential for the engine room understand its health condition and self-manage performance. The unattended machinery plant (UMP) should be resilient enough to have the ability to survive and recover from unexpected perturbations, disruptions, and operational degradations. Otherwise, the system may require unplanned maintenance or the operation will stop. Therefore, the UMP must continue its operation without human intervention and safely return the ship to port. This paper aims to develop a machine learning-based model to predict an UMP's performance and estimate how long the engine room can operate without human assistance. A Random Process Tree is used to model failures in the unattended components, while a Hierarchical Bayesian Inference is adopted to facilitate the prediction of unknown parameters in the process. A probabilistic Bayesian Network developed and evaluated the dependent relationship between active and standby components to assess the effect of redundant units in the performance of unattended machinery. The present framework will provide helpful additional information to evaluate the associate uncertainties and predict the untoward events that put the engine room at risk. The results highlight the model's ability to predict the UMP's trusted operation period and evaluate an unattended engine room's resilience. A real case study of a merchant vessel used for short sea shipping in European waters is considered to demonstrate the model's application.

Autonomous ships have become a topic of interest for an increasing number of researchers over the last few years. Most of the research that is being performed focuses on autonomous navigation. An important driver for this research is the belief that autonomous navigation will increase safety at sea. In order to evaluate the possible safety benefit of autonomous navigation, it is essential to have an understanding of the risk associated with navigation-related accidents. In this paper, a monetary quantification of the risk associated with navigation-related accidents will be presented, to support designers in determining the acceptable costs of an autonomous navigation system.. It is the intention to provide order-of-magnitude figures for the annual risk for different ship types and sizes. Although it is acknowledged that the analysis comes with uncertainties, the results provide an overview contribution that different damage cases make to the overall risk per year, associated with navigation-related accidents. It is found that the annual risk can be expected to be between €1.5 billion and €2.5 billion, or a €45k to €75k risk per vessel per year. Consequently, the maximum annual safety benefit of autonomous navigation is equal to this figure if autonomous navigation will be able to prevent all navigation-related accidents.

To achieve a modal shift towards waterborne transport and to deal with the shortage of crewmembers, a platooning concept called the “Vessel Train” is explored for the inland navigation sector. A Vessel Train consists of a lead and various follower vessels. The lead vessel is fully manned and takes over the navigational and situational awareness responsibilities for the follower vessels. This leading action benefits the followers through increasing the vessels’ productivity and enabling crew cost savings. This article investigates the viability of the concept for the lower Rhine region, by presenting a cost model that compares the Vessel Train conditions to the current sailing conditions. This model is used to assess a case study where lead vessels operate on a liner service between Antwerp and Duisburg. Economically viable cases for the concepts’ early-stage application and fully matured implementation are identified, and boundary conditions are presented. The viable conditions vary depending on the vessel type and the operating regime of the reference vessel. A fully matured VT implementation requires a minimum of 26 participants, whereas an early-stage implementation requires 40 participants. The early-stage implementation additionally includes a minimum distance of 200 km to be spent sailing in the VT and the distance sailed in the VT has to amount to a minimum of 50% of the entire trip.

A good mesh is a prerequisite for achieving reliable results from Computational Fluid Dynamics (CFD) calculations. Mesh properties include mesh types, computational domain sizes, and node distributions. However, in literature, we found no clear consensus about what these properties should be. In this article, we performed a case study on ship rudders to determine what the suitable mesh properties are for airfoil-shaped profiles. A classic NACA 0012 profile is chosen as an example, and commercial packages ANSYS ICEM are applied for meshing with an ANSYS Fluent solver. With a strategy in consideration of relationships among different mesh properties, a comprehensive parametric investigation is conducted to study the impacts of these properties on the accuracy of rudder hydrodynamic coefficients obtained by CFD methods. The step-by-step study outputs recommended Reynolds numbers, domain sizes, and near-and far-field node distributions for mesh types with distinct topology structures, i.e., C-mesh, O-mesh, H-mesh, and Hybrid-mesh. Specifically, the study shows that a critical Reynolds number is needed for the perspective of efficiency, while a domain extending 60 times of the chord length enables the boundary effects to be negligible. As for node distributions, the near-field nodes should be treated carefully, compared with those in the far-field. After that, corresponding mesh properties for different calculation objectives are illustrated in detail based on the characteristics of mesh types mentioned above. With the proposed strategy for mesh refinements, impacts of different mesh properties on rudder hydrodynamics are clarified and recommended settings are applicable for other airfoil-shaped profiles such as wind turbines and marine propellers.

Autonomous and unmanned shipping are currently hot topics in the maritime industry. However, there are many different views on how the ultimate goal of an unmanned, autonomous ship will be reached. On any given ship, a large range of tasks is performed every day, each of which need to be replaced in such a way that no human presence is required on board. In this article, different possible combinations of tasks to be replaced are explored systematically, leading to an overview of the most beneficial combinations of tasks to replace together and a logical sequence in which to replace them. This leads to a plausible implementation path from low-manned ships towards fully unmanned autonomous ships.

Maritime Autonomous Surface Ships have received a significant amount of attention in recent projects. They promise a reduction in marine accidents and mitigation of human errors. Most of the ongoing research effort is directed toward autonomous navigation and cybersecurity. However, the importance of a machinery plant in the engine room that can operate reliably without human attendance is hardly investigated. To prevent failures in such systems and extend the interval between required human interventions, it is essential to improve their reliability. This paper aims to present a systematic approach to evaluate the reliability of an autonomous system under the influence of uncertain disruptions and to predict failure rates of unattended machinery plants. A Multinomial Process Tree is used to model failures in the main failure-sensitive components. Hierarchical Bayesian Inference is adopted to facilitate the prediction of frequencies of disruptive events and estimate the entire system's failure rate. The outcome of this research enables design strategies to improve the reliability of autonomous ships and prevent Fatal Technical Failure during the operation. This allows assessing whether a given machinery plant is sufficiently reliable to be used on unmanned ships. A case study is considered to demonstrate the application of the presented method.

The advent of autonomous ships that are unmanned or low-manned will reduce the number of people at risk at sea. Even when autonomous navigation does not reduce the number of accidents, this means that safety at sea will increase. In fact, increased safety is one of the primary perceived drivers for autonomous shipping, although this safety increase has not yet been quantified in academic literature. In this article a statistical analysis is performed to determine the distribution of human casualties and lost ships over accident types, ship types and ship sizes. Subsequently, based on several scenarios for the implementation of autonomous ships, a quantification of the estimated reduction in loss of life and loss of ships is provided. It is concluded that the implementation of autonomy on small cargo ships with a length below 120 m will have the largest safety benefit, since these ships account for the majority recorded ship losses and lives lost.

While successful trials for autonomously navigating ships have been conducted, commercially available unmanned cargo ships are currently unavailable. However, there are many solutions available that will allow for low-manned ship concepts long before fully unmanned ships are possible. There are many drivers for low-manned and unmanned shipping, ranging from availability of workforce, to increased safety to economic. This article investigates the economic viability of several low-manned ship concepts as well as the unmanned ship concept for a short sea container vessel. The operating cost of these concepts are compared to those of a conventional vessel. That way, an assessment can be made on the economic viability. The results show that the low-manned concepts investigated in this article are worthwhile for the ship owner, as some savings can be achieved. The economic viability of the unmanned concept is dependent on the chosen type of propulsion.

In recent years, a significant amount of research has been conducted on autonomous ships. Since it is assumed that these ships will sail with a significantly reduced crew or even without people on board, the design of the ship needs reconsideration. The absence of people on board and the associated safety measures could result in a more efficient design, but amendments in the existing regulatory framework will be needed. In this article, we will focus on potential changes in the Convention for Safety Of Life At Sea (SOLAS) and in particular on the Required Subdivision Index. The index gives a requirement for the allowed probability of sinking when a ship is damaged due to collision. The evaluation is performed by using the principle of equivalent safety, which will ensure that unmanned ships will be at least as safe as manned ships. If the crew is no longer present, the consequences of an incident will be less severe, since the probability of casualties is no longer present. Consequently, a lower subdivision index might be accepted for unmanned autonomous ships. In this article, the damage stability-related level of risk of a manned ship will be derived by means of a risk analysis. Thereafter, the subdivision index for unmanned ships, which ensures an equivalent safety level to similar manned ships, is established for three individual ships. The assessment shows that a reduction in the subdivision index is allowed for unmanned ships and that the reduction will be largest for smaller ships.

Recently, autonomous ships have gotten a lot more attention both in the media and in research. However, very little research has focussed on the effects of automation on the size of the crew. This paper analyses the effects of added automation on the required size and composition of the crew on a 750 TEU short sea container vessel. A Crew Analysis Algorithm is used to determine the cheapest crew composition to perform the tasks required to operate a ship. Using this algorithm, two potential automation options are investigated: automating the navigation tasks and automating the mooring tasks. Automating the navigation tasks decreases the required crew size in the normal sailing and arrival & departure phases by 3 and 1 crew members, respectively. The loading & unloading phase is unaffected. Automating the mooring tasks reduces the required crew in the arrival & departure phase to 2. It is concluded that since individual automation options do not affect the crew requirements for all travel phases, their effect on crew reduction is limited unless several options are combined. However, with a change in task assignment and different training of crew members, a reduction of the required number of crew members is possible.

Prolonged periods of drought affect river discharges and cause water levels and available water depth to drop for extended periods of time. Low water depth has a major impact on the loading capacity of inland ships, and as a consequence on the transport capacity of the overall waterborne supply chain. Individual ship owners have detailed knowledge on how much the draught of their ship and the associated cargo weight should be reduced to adapt to low water. These parameters are even adjusted as a function of environmental circumstances (e.g. composition of the riverbed) and type of cargo. This detailed knowledge is, however, not accessible at an aggregated level to assess the effects on the overall transport capacity of an inland waterway transport network. Based on a range of field observations and information collected from individual ships, this article introduces a general model to define the effect of low water constraints on the deadweight and payload of inland ships, for which only the type, length, and beam of the vessel serve as mandatory input. Availability of a general model of the capacity reducing effect of lowered water depth is important for the design and operation of robust transport chains on the one hand, and for the optimisation of fairway maintenance and long-term infrastructure development on the other.

The conventional extrapolation of ship resistance from model tests to full scale presumes that the coefficient of wave-making resistance (C_w) depends on the Froude number only. This leads to the assumption that C_w of a ship is identical to C_w of its scaled model. However, this assumption is challenged in shallow water due to viscous effects, which are represented by the Reynolds number (Re). In this study, different scales (different Re) of the Wigley hull and the KCS hull are used to investigate the scale effects on C_w numerically. After verification and validation, systematic computations are performed for both ships and their scaled models in various shallow-water conditions. Based on the results, significantly larger values of C_w are found for the KCS at model scale in very shallow water, suggesting that the conventional extrapolation has to be reconsidered. Additionally, this study reveals the relationship between the changes in frictional resistance coefficient (C_f) and the changes in C_w caused by shallow water, which benefits the prediction of shallow water effects on C_w. Finally, use of a larger ship model, where the Re is also higher, is recommended for resistance tests in shallow water to reduce scale effects on C_w.

The potential to implement the concept of waterborne platooning in the European short sea transportation system is currently being explored. In the concept, a platoon is referred to as a “Vessel Train” (VT). A VT is composed of a fully manned lead vessel and a number of follower vessels. The lead vessel takes over the navigational and situational awareness responsibilities for the follower vessels (FVs). This enables automation of the navigational tasks on these follower vessels, which in turn leads to a potential reduction in crew size and associated cost. This paper describes the economic viability of the VT concept. It is applied to a short sea case study in which a fully matured system and an early implementation stage are mimicked. The assessment shows that viability is strongly influenced by the number of crew members removed from the FVs and the departure intervals of consecutive trains. It concludes that while economically viable cases can indeed be identified, the benefits created by this VT implementation are present but not very large. This is making it questionable if a successful application of the concept can be achieved given the risk and uncertainty surrounding the individual parameters.