The ongoing technological development of methanol energy converters (EC) towards decarbonization means that their dimensions and performance characteristics will be continually updated during the lifecycle of vessels currently designed. These advancements influence the ease of EC integration within the general arrangement of the vessel. The decision to switch from an internal combustion engine to a fuel cell or a hybrid configuration depends both (1) the technology adoption costs (i.e. CAPEX, OPEX) of the EC and (2)
on the effect of EC on the actual engine room layout. The state-of-the-art literature has typically addressed these two challenges separately. This study proposes a design method to bridge these two fields by combining the use of (1) Markov decision processes to assess uncertain future methanol EC developments during the vessel lifecycle and (2) a generative probabilistic layout algorithm to quantify the risks associated with the EC systems layout integration. The case study identifies the drivers behind the EC technology choice during the lifecycle of a notional yacht vessel.@en

Intermodality is regarded as one way of achieving more sustainable transport solutions. To make intermodal transport the preferred solution among shippers, it must be attractive according to the concept of generalized transport costs. An extended model for generalized transport costs is developed which includes elements important for comparing maritime transport solutions in the Artic. This framework forms the basis for a principal discussion on the conditions that make one transport solution preferable to another within the context of maritime logistics. This model is then applied to the context of the Northeast Passage to discuss the necessary requirements for making an intermodal transport solution attractive relative to the current main route from Northeast Asia to Northwest Europe through the Suez Canal. Even though intermodality could be preferable in principle, current solutions cannot compete with either Arctic routes using unimodal solutions with high ice-class vessels or with the Suez route. Due to uncertainty and limited empirical evidence, a sensitivity analysis is conducted, focusing on the variables with the greatest impact on the result. Policymakers and stakeholders can consider the findings to improve transport competitiveness via the Northeast Passage.

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Editorial.@en

This research addresses the importance of sustainability in shipping beyond fuel selection, stressing the need for responsible material usage in vessel construction and maintenance. Transitioning to a circular economy is crucial for sustainable waste management in the industry, yet current ship design neglects circularity considerations, prioritising functionality and cost. The research evaluates frameworks such as the butterfly diagram, Cradle-to-Cradle, 10R, and ReSOLVE to integrate circularity into ship design. Combining the 10R framework with the Material Circularity Indicator method, this study offers practical insights for circularity in ship design. Challenges include integrating these methods into standard design processes, which are mitigated by fusing 10R strategies with systems engineering. A case study on wheelhouse redesign demonstrates the effects of this approach, highlighting the importance of supplier collaboration for circularity enhancement.@en

In the fiercely competitive shipbuilding industry, precise cost estimates must be considered as they serve as a critical input for determining market prices effectively and ensuring a small profit for the shipyard. In Western Europe, where most projects are Engineering-To-Order (ETO), cost estimations are extra challenging, due to lack of similarity between projects. On top of this, cost estimations are becoming increasingly difficult in a market confronted by mounting challenges related to safety regulations, cost-effectiveness, and the pressing need to address energy conservation and environmental protection. New technologies introduce changes in nearly all aspects of shipbuilding design and construction. This article conducts a literature review, to present the state-of-the-art methods for estimating man-hours, explicitly focusing on man-hours for shipyard production, excluding overhead costs and challenges the suitability of existing systems for ETO and especially for the changes caused to ships by the energy transition. An indication is given of the practicality of each method as outlined in the literature. A solution direction, incorporating the construction process, is proposed to improve cost estimations for ETO projects in pre-contract phase.

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With space constraints onshore, strong renewable resources available far offshore and growing green hydrogen demand, far offshore green hydrogen production may be an attractive option. To assess this potential, a mixed integer quadratically constraint programming (MIQCP) optimization model was developed to find the cost per kilogram of far offshore green hydrogen in specific scenarios. The design of the far offshore green hydrogen supply chain was optimized with this model for six high potential scenarios in varying locations and the results were analyzed. It was found that far offshore green hydrogen costs are in the same order of magnitude as the costs of its alternatives. Far offshore green hydrogen may be considered marginally competitive with these alternatives from 2035 onwards in the analyzed scenarios when taking into account the considerable advantages of far offshore production, such as avoidance of scarce land usage in crowded areas and certain geopolitical considerations.@en

Inland water vessels are impacted by climate change in two respects. First of all, they will need to convert to low-impact power propulsion and energy (PPE) systems. Secondly, they will need to deal with the impact of climate change, especially longer periods of very low and high water. This paper reviews the multi facet impacts of climate change on inland waterway vessel performance and problems associated with the choice of alternative power energy and propulsion (PPE) system on the vessel’s performance.@en

Accurate cost estimates are essential for staying in business in a competitive shipbuilding industry. With new technologies and the energy transition creating an ever-changing landscape, traditional cost estimation methods based on product specifications can no longer keep pace. The need for improvement especially arises for Engineering-To-Order projects, considering that the profit margins are narrow. The use of process information in the estimation process could increase the reliability and flexibility of these estimations. This article presents a concept that utilizes graph theory to include process information in the cost estimations applied to steel buildings. This concept is specifically suited for the early stages of Engineering-To-Order projects.@en

The current sea margin estimate applied in early ship design, commonly assumed 15-20% extra installed engine power, is not based on calculations, but has nonetheless become an industry standard. These sea margin estimations, applied in early ship design, are insufficiently accurate. This paper evaluates if a data driven approach is suitable to more accurately predict the sea margin in early ship design. Using operational data this method considers the whole operational profile of the vessel not limited to design or calm water conditions. A case study is performed where a data driven model is trained to make power predictions, subsequently this trained model is used to make calm water predictions. This proof of concept illustrates the potential of proposed method to be utilised for sea margin estimations in early ship design.@en

The energy transition from fossil fuels to sustainable alternatives makes the design of future-proof ships even more important. In the design phase of a ship, it is uncertain how many and which fuels it will use in the future due to many external factors. In fact, a ship typically sails for decades, increasing the likelihood that it will use different fuels during its lifetime. Pipe route design is expensive and time-consuming, mainly done by hand. Motivated by this, in previous research, we have proposed a mathematical optimization framework for automatic pipe routing under uncertainty of the energy transition. In this paper, we build on the state-of-the-art by implementing design constraints in mathematical models based on discussions with maritime design experts. Additionally, we apply these models to realistic, complex situations of a commercial ship design company. Our experiments show that location-dependent installation costs, which reflect reality, increase the usefulness of stochastic optimization compared to deterministic and robust optimization. Additionally, to prepare for a possible transition to more sustainable fuels, we recommend installing suitable pipes near the engine room upfront to prevent expensive retrofits in the future.@en

Within the maritime transport sector, data and information have the potential to change the way we work for the betterness. Increasingly shipping companies are generating, storing and reporting data, on their position, their engines, their products and their emissions. As a result, data is sometimes referred to as the new gold and people often protect it in the same way. However, unlike gold, data has actually more value when it is shared and used in collaboration with others. [...]@en

Shipowners need to prepare for low-emission fuel alternatives to meet the IMO 2050 goals. This is a complex problem due to conflicting objectives and a high degree of uncertainty. To help navigate this problem, this paper investigates how methods that take uncertainty into account, like robust optimization and stochastic optimization, could be used to address uncertainty while taking into account multiple objectives. Robust optimization incorporates uncertainty using a scalable measure of conservativeness, while stochastic programming adds an expected value to the objective function that represents uncertain scenarios. The methods are compared by applying them to the same dataset for a Supramax bulk carrier and taking fuel prices and market-based measures as uncertain factors. It is found that both offer important insights into the impact of uncertainty, which is an improvement when compared to deterministic optimization, that does not take uncertainty into account. From a practical standpoint, both methods show that methanol and LNG ships allow a cheap but large reduction in emissions through the use of biofuels. More importantly, even though there are limitations due to the parameter range assumptions, ignoring uncertainty with respect to future fuels is worse as a starting point for discussions.@en

Many fuels are currently considered for reducing the emissions in shipping; Methanol, LNG, Ammonia, Nuclear, Biodiesel, etc. However, Bio-ethanol is not considered at all.This research looked into all aspects of ethanol in a comparison with its most closely related alternative methanol. Using a similar approach as found in earlier comparisons. Though updating the data as well as the application ot vessels relevant for the Dutch ship owners. This research identified that 2nd generation bio-ethanol would in price be close to 2nd generation bio-methanol, but with several technical advantages. Furthermore the bio-ethanol production capacity is far larger than that of any of the other alternative fuels for shipping and with the ongoing electrification of cars, this capacity will most likely be looking for a new market in the future, putting pressure on the price. Hence the report calls for further investigations and reconsiderations of bio-ethanol as a marine fuel. @en

Several measures have been developed to prevent emissions from inland water transportation. However, it is challenging to weigh all the aspects to identify the pathway that will ultimately result in zero-emission inland shipping. A data-driven virtual representation of the inland shipping system can be used to evaluate zero-emission strategies, effectiveness of policies and technologies, and consequences of their implementation. This multi-level digital twin can realistically represent the system with all relevant components, which needs to be validated using real-world data. Subsequently, future scenarios can be imposed on the digital twin, and the proposed intervention measures can be applied, based on which their efficiency can be assessed together with the inland shipping sector. This study discusses the essential aspects of designing a digital twin for an IWT. Three aspects are considered essential: individual ships, logistics chains, and infrastructure. As these research topics span various scales, ranging from a single vessel to an entire infrastructure network, an agent-based approach is suitable for forming the basis of the digital twin. Consequently, potential interventions can be considered, ranging from the application of new technologies to individual vessels to policy measures implemented for an entire shipping corridor or various bunker infrastructure strategies in the network. Additionally, the impact of the implemented interventions can be evaluated at any desired scale, ranging from the individual ship level and its emissions to the network level and aggregated emissions in an entire area, or the impact on the logistics chain.@en

With the current curriculum developed and implemented in phases since 2013, it is time to evaluate and review the BSc curriculum. For this revision, the success and issues of the previous revision, the changes in our field and society, and the recent insights from educational studies are all reviewed to form the basis of this update. Current developments, like energy and autonomy transitions in the sector, as well as extra attention to learning processes and socialization, as a result of COVID-19, are all reviewed. The goals and vision will be discussed as well as current trends in the industry, science and education sciences. This will form the basis for a curriculum revision, followed by a comparison with related education to verify that a sound basis continues to exist. In the discussion, relevant considerations for Maritime Education, in general, will be drawn from this experience to support others in their updates.

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The resource constrained project scheduling problem with a flexible project structure and consumption and production of resources, involves making a selection of activities and scheduling these activities in order to minimize the makespan, subject to precedence and resource constraints. Since finding a feasible selection of activities is NP-hard, we introduce the concept of group graphs and restrict ourselves to instances with an acyclic group graph. For these instances, which represent many practical cases, we show how to make a feasible selection of activities in polynomial time and use this concept to schedule the selected activities using a hybrid differential evolution algorithm. We compare this algorithm with an algorithm from the literature on special cases of instances without consumption and production of resources, and show that our algorithm creates solutions of higher quality. Furthermore, to compare general instances, we develop an ant colony optimization algorithm that performs slightly better on special cases than the algorithm from literature and show that the hybrid differential evolution algorithm outperforms the ant colony optimization algorithm on general instances.

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To integrate and assist the system and automation design phases of complex marine vessels, this paper proposes a two-level semantically enhanced scheme. At the design level, the system components are described and automatically connected by a developed graph-making tool using semantic 'knowledge'. Decisions regarding the system selection are made based on certain Quality of Service Criteria (QoS) and enforced in the final semantic database using a dedicated cognitive agent. The automation level leverages the selected systems semantic information with that of the associated automation components and reuses the graph-making tool to update the connection graph. The resulting knowledge-graph is then used to 'reason' for the creation of feasible closed-loop control architectures while a cognitive agent determines which closed-loop architecture to use based on various QoS criteria. The chosen closed-loop architecture can then change in an online manner during the vessel operation in case that system reconfiguration is required either due to malfunctioning components, or aiming to satisfy mission's goals. The applicability and efficiency of the proposed method are shown using a case study for marine propulsion.

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In search of a way to bring back the positive aspects of an internship into the curriculum, TU Delft identified serious games as a potential solution. The literature studied showed that games could increase motivation and understanding, leading to improve knowledge retention. This paper has brought these insights together in a framework identifying the benefits that contribute to knowledge retention but also the requirements and risks for the application of serious games to be addressed. These insights were used to explain the success of a longstanding business game course for advanced students first. Next was the development of a virtual reality practice in a first-year course to replace the lost internship. In this case, knowledge retention was improved significantly, albeit only by 5%. Furthermore, in light of the developed framework, the VR simulation is a more balanced approach with fewer risks compared to the more extensive master course.

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Piping systems are common in many architectures and designing such systems is often a complex task. Design automation of piping systems is therefore a universal research subject. Nonetheless, these piping systems are often still designed by hand as a result of their complexity. Consequently, costs associated with piping design are high, especially for large-scale architectures like ships and chemical plants. The goal of automatic pipe routing is to reduce the design time and associated costs of a piping system by automating the routing of these pipes. This survey provides an overview of the current state of automatic pipe routing literature to assist researchers and practitioners to further the study of automatic pipe routing. This is done by pinpointing and explaining the most important obstacles that stand in the way of making a full-scale automatic pipe routing method. The barriers that are analyzed are related to both model representation and optimization complexity. Finally, a synthesis table of research papers on automatic pipe routing is provided based on the handling of the aforementioned barriers and other general features of automatic pipe routing methodology. The survey concludes by discussing directions for further research.

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The adoption of alternative energy carriers is one of the key ways to meet the increasingly stricter emission regulations faced by shipping vessels from the international maritime organisation (IMO) and European Commission. To support this objective, this study examines the challenges and uncertainties associated with implementing a methanol power propulsion and energy (PPE) system on the design of a vessel. This paper argues that new fuels, such as methanol, should be treated as disruptive innovations due, in part, to the uncertainties surrounding their implementation. Their integration causes challenges regarding systems selection, layout design, and maintaining strict safety measures. In the case of methanol, current research treats the fuel as a system conversion based on diesel fuel. This paper provides a review of the state-of-the-art on the design of methanol fuelled vessels, and identifies a research gap related to the need for a new suitable design method for the design of ships integrating future alternatively fuelled PPE systems. A design approach inspired by model-based systems engineering integrating uncertainty modelling is proposed to examine the influence of uncertainty on the design of the vessels. The impact of uncertainty on the design is investigated through a case study of a simplified engine room layout utilizing a genetic algorithm to produce layouts for variable PPE systems dimensions within a Monte Carlo simulation.@en