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Increased maritime cargo transportation has necessitated stricter management of emissions from ships. The primary source of this pollution is fuel combustion, which is influenced by factors such as a ship's added wave resistance. Accurate estimation of this resistance during ship design is crucial for minimizing exhaust emissions. The challenge is that, at the preliminary parametric design stage, only limited geometric data about the ship is available, and the existing methods for estimating added wave resistance cannot be applied. This article presents the application of artificial neural network (ANN) ensembles for estimating added wave resistance based on dimensionless design parameters available at the preliminary design stage, such as the length-to-breadth ratio (L/B), breadth-to-draught ratio (B/T), length-to-draught ratio (L/T), block coefficient (CB), and the Froude number (Fn). Four different ANN ensembles are developed to predict this resistance using both complete sets of design characteristics (i.e., L/B, B/T, CB, and Fn) and incomplete sets, such as L/B, CB, and Fn; B/T, CB, and Fn; and L/T, CB, and Fn. This approach allows for the consideration of CO2 emissions at the parametric design stage when only limited ship dimensions are known. An example in this article demonstrates that minor modifications to typical container ship designs can significantly reduce added wave resistance, resulting in a daily reduction of up to 2.55 tons of CO2 emissions. This reduction is equivalent to the emissions produced by 778 cars per day, highlighting the environmental benefits of optimizing ship design. [ABSTRACT FROM AUTHOR]

There are two main areas in which the Internet of Ships (IoS) can help: firstly, the production stage, in all its phases, from material bids to manufacture, and secondly, the operation of the ship. Intelligent ship management requires a lot of information, as does the shipbuilding process. In these two phases of the ship's life cycle, IoS acts as a key to the keyhole. IoS tools include sensors, process information and real-time decision-making, fog computing, or delegated processes in the cloud. The key point to address this challenge is the design phase. Getting the design process right will help in both areas, reducing costs and making agile use of technology to achieve a highly efficient and optimal outcome. But this raises a lot of new questions that need to be addressed: At what stage should we start adding control sensors? Which sensors are best suited to our solution? Is there anything that offers more than simple identification? As we begin the process of answering all these questions, we realize that a Computer Aided Design (CAD) tool, as well as Artificial Intelligence (AI), mixed in a single tool, could significantly help in all these processes. AI combined with specialized CAD tools can enhance the sensitization phases in the shipbuilding process to improve results throughout the ship's life cycle. This is the base of the framework developed in this paper. [ABSTRACT FROM AUTHOR]

The shipping industry significantly influences global greenhouse gas emissions through a predominant fossil fuel-based fleet. Regulating bodies are continuously developing rules to reduce the shipping carbon footprint. Adopting low-carbon fuels is considered a step toward achieving the Paris Agreement's goals; however, it represents a significant paradigm shift in ship design. This work aims to illustrate a methodology for the feasibility assessment of alternative-fuelled vessels considering technical, environmental, and economic perspectives. The technical feasibility focuses on ship propulsion, fuel system safety, and design parameters. The environmental impact evaluation is based on the Tank-to-Wake and the Well-to-Wake approaches. The cost assessment is performed by estimating capital and operational expenditures, considering only the modifications required by the new fuel. The methodology addresses new-building and retrofit solutions, and can be used as a decision support tool for selecting the best strategy. A key output of the methodology is the cargo emission footprint, expressed in equivalent carbon dioxide per cargo unit. Using a handysize bulk carrier as a case study, this work points out the effects of using methanol as an alternative fuel, highlighting its impact on market and transport strategies in a sector evolving towards Eco-Delivery services. [ABSTRACT FROM AUTHOR]

Recently, the International Maritime Organization (IMO) introduced an initial strategy aiming to reduce and ultimately achieve net-zero greenhouse gas emissions by 2050. While various research projects on retrofitting have been conducted, there is a noticeable gap in detailed studies concerning emission reduction through liquefied natural gas (LNG) dual-fuel retrofit options. This study assesses the feasibility and environmental impacts of applying LNG dual-fuel retrofit to a 9196 gross tonnage training ship. It explores replacement scenarios of 20 %, 30 %, and 40 % LNG incorporation using life cycle assessment. Additionally, the study employs a life cycle assessment methodology to compare the global warming potential against both the life cycle assessment database and engine emission factors. Over 35 d of operation at a normal continuous rating of 85 % power load, replacing 20 %, 30 %, and 40 % of fuel with LNG resulted in a reduction of global warming potential by approximately 23.1 %, 32.7 %, and 42.3 %, respectively. These results indicate that LNG replacement cases significantly lower emissions related to global warming potential compared to conventional marine diesel oil (MDO) operations, with greater reductions observed at higher replacement percentages. Further investigation revealed significant differences between the results derived from the life cycle assessment database and engine emission factors. However, statistical analyses indicated that both sources exhibit a consistent trend, with p-values in all power load cases exceeding 0.05, indicating no significant interaction term. Despite notable differences, the utilization of life cycle assessment offers high reliability and ease of use, serving as a solid foundation for decision-making regarding sustainable options.

Model-making has been part of the history of the world as a scaled-down, and often simplified, version of an object. This form of representation has had different functions including validation, creative solution, communication and decoration among others. Models depicting ships are known at an early date from ancient Egypt, although some of those boats had funerary ritual symbolism. More than four millennia later the ship models of the eighteenth century were conceived at a time when naval power was reaching a new chapter offered by technological advancements. Such items, made for shipyards and wealthy patrons, showed details that otherwise would have been missed from the plans and became a physical record of the constructive accomplishment. When other data such as plans are missing, the details from these models are vital to determine the otherwise obscure provenance in the same way as details associated with written or pictorial accounts. The purpose of this paper is to determine the origin of the model SLR0436 stored at the National Maritime Museum's model collection at its Chatham site. The features of the model will be discussed as well as the merits of the different hypotheses, including the historical context. Finally, it proposes that the most credible provenance, given the evidence, is the Vittorio, a ship built in Deptford in 1716 for the Savoyard navy. [ABSTRACT FROM AUTHOR]

While hybrid ship drive systems may offer a large potential, a thorough analysis is needed as it is strongly dependent on the operational profile. The fixing of costs during the early design stage, leads to the necessity of a precise evaluation of the systems efficiency within this phase. Conducting statistic-based calculations can be inadequate due to the time-dependent behavior of the battery. Moreover, idealized temporal data is often utilized for the design of battery supported ships. Therefore, this paper discusses the consequential inaccuracies using statistical or smoothed data. But also examines the potential of an advanced in-house developed statistical approach. For the examination, an internal developed method for dimensioning hybrid ship power systems is used. The paper shows that conducting statistical calculations lead to incorrect modeling of battery behavior, while smoothed power time-series can result in an overestimation of the battery lifetime (up to 21% less charge cycles). [ABSTRACT FROM AUTHOR]

Determining the key characteristics of a ship during the concept and preliminary design phases is a critical and intricate process. In this study, we propose an alternative to traditional empirical methods by introducing a model to estimate the main particulars of diesel-powered Z-Drive harbor tugboats. This prediction is performed to determine the main particulars of tugboats: length, beam, draft, and power concerning the required service speed and bollard pull values, employing Bayesian network and non-linear regression methods. We utilized a dataset comprising 476 samples from 68 distinct diesel-powered Z-Drive harbor tugboat series to construct this model. The case study results demonstrate that the established model accurately predicts the main parameters of a tugboat with the obtained average of mean absolute percentage error values; 6.574% for the Bayesian network and 5.795%, 9.955% for non-linear regression methods. This model, therefore, proves to be a practical and valuable tool for ship designers in determining the main particulars of ships during the concept design stage by reducing revision return possibilities in further stages of ship design. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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ObjectiveAccording to the characteristics of the complex waterways of inland rivers, a DC grid solution based on a multi-energy parallel hybrid green intelligent bulk carrier is proposed. MethodsThe advantages of a DC grid for hybrid power are analyzed and the DC grid propulsion efficiencies of each typical working condition for hybrid power are obtained through power chain calculation. The design characteristics of the DC grid are researched according to the specific requirements for the additional signs of green intelligent ships. The DC power system design schemes focused on protection and safety for real ships are then analyzed.ResultsThe results show that the comprehensive performance of the DC grid propulsion system for multi-energy parallel diesel-electric/gas-electric hybrid ships is superior to that of main engine propulsion systems and full electric propulsion systems. The multi-equipment protection mode and blackout recovery solution can ensure the safe application of the DC grid.ConclusionsThe DC grid can build a flexible energy platform for the highest level of green inland river ships, and provide comprehensive support for the intelligent engine room, intelligent energy efficiency and intelligent integrated platform technology and its applications. The results of this study can provide valuable references for other green intelligent hybrid ships.

The digitalisation in the ship design sector is currently applied to the design process itself and is well defined, partially standardised and practically implemented by both independent design companies and the design departments of shipyards. The situation is similar in other sectors of engineering. However, the requirements for the digitalisation of other processes in design and engineering companies have not previously been studied, and the limited financial resources of ship design companies mean that there is a need for research on the digitalisation needs of multidisciplinary ship design companies. The implementation of building information modelling (BIM) solutions is costly for design companies and generates benefits mainly for shipyards and shipowners. The lack of benefits for design companies leads to the hesitation of managers whenever digitalisation is considered; the scope and scale of the digitalisation, as well as the selected software and BIM level, are defined by the shipyard requirements. The participation and support of management in the digitalisation process is one of the key success factors; the expected benefits caused by digitalisation for the organisation will increase the motivation of managers to invest limited resources in digitalisation. There are no data that indicate the processes with a high potential for digitalisation and the scale of expected improvements in ship design companies; therefore, research in this area was performed with a group of project managers from design and engineering companies. The research focused on collecting the opinions and experiences of the managers related to the manual management of resources and comparing the poll results with the conclusions from the enterprise resource planning (ERP) system data analyses. The paper analyses if the digital automation of the resource management process can lead to the substantial improvement of the operations of multi-project, multidisciplinary engineering ship design companies.

Increased maritime cargo transportation has necessitated stricter management of emissions from ships. The primary source of this pollution is fuel combustion, which is influenced by factors such as a ship’s added wave resistance. Accurate estimation of this resistance during ship design is crucial for minimizing exhaust emissions. The challenge is that, at the preliminary parametric design stage, only limited geometric data about the ship is available, and the existing methods for estimating added wave resistance cannot be applied. This article presents the application of artificial neural network (ANN) ensembles for estimating added wave resistance based on dimensionless design parameters available at the preliminary design stage, such as the length-to-breadth ratio (L/B), breadth-to-draught ratio (B/T), length-to-draught ratio (L/T), block coefficient (CB), and the Froude number (Fn). Four different ANN ensembles are developed to predict this resistance using both complete sets of design characteristics (i.e., L/B, B/T, CB, and Fn) and incomplete sets, such as L/B, CB, and Fn; B/T, CB, and Fn; and L/T, CB, and Fn. This approach allows for the consideration of CO2 emissions at the parametric design stage when only limited ship dimensions are known. An example in this article demonstrates that minor modifications to typical container ship designs can significantly reduce added wave resistance, resulting in a daily reduction of up to 2.55 tons of CO2 emissions. This reduction is equivalent to the emissions produced by 778 cars per day, highlighting the environmental benefits of optimizing ship design.

There are two main areas in which the Internet of Ships (IoS) can help: firstly, the production stage, in all its phases, from material bids to manufacture, and secondly, the operation of the ship. Intelligent ship management requires a lot of information, as does the shipbuilding process. In these two phases of the ship’s life cycle, IoS acts as a key to the keyhole. IoS tools include sensors, process information and real-time decision-making, fog computing, or delegated processes in the cloud. The key point to address this challenge is the design phase. Getting the design process right will help in both areas, reducing costs and making agile use of technology to achieve a highly efficient and optimal outcome. But this raises a lot of new questions that need to be addressed: At what stage should we start adding control sensors? Which sensors are best suited to our solution? Is there anything that offers more than simple identification? As we begin the process of answering all these questions, we realize that a Computer Aided Design (CAD) tool, as well as Artificial Intelligence (AI), mixed in a single tool, could significantly help in all these processes. AI combined with specialized CAD tools can enhance the sensitization phases in the shipbuilding process to improve results throughout the ship’s life cycle. This is the base of the framework developed in this paper.

The strengthening of regulations such as EEXI, EEDI, and CII on ship emissions is underway. Despite their application, objective comparisons of ships are hindered by diverse navigation patterns and varying velocity regulations in different seas and ports. Additionally, a lack of basic data impedes comparisons of the optimal design and objective energy efficiency for ships. To address these issues, representative sailing modes, similar to those in the automobile industry, are needed. However, there is no reference for marine applications. This study introduces a methodology for representative sailing modes using the Markov chain. A hundred candidate sailing modes were created, and representative modes were identified through an evaluation equation. All chi-square values for representative sailing modes are within 1%, indicating significant results. This study's findings can aid in designing optimized systems for new vessels and computing authorized fuel efficiency for vessels with diverse sailing patterns. [ABSTRACT FROM AUTHOR]

The timely and precise prediction of flooding progression and its eventual outcome in ships with breached hulls can lead to dramatic improvements in maritime safety through improved guidance for both emergency response and ship design. The traditional approach to assessing damage-induced flooding in both these stages, which also fully complies with statutory rules, is through static calculations. On the other hand, the application of models that simulate the flooding progression and the behaviour of flooded ships from, or close to, first principles allows for increased accuracy of the modelling of the phenomenon. This increase in accuracy can then be used to support advanced design for safety procedures. Furthermore, it can considerably enhance a ship's capability for damage identification and inference-based logic for emergency decision support systems and marine accident response in general. This paper conducts a review of selected state-of-the-art methods, procedures, and case studies in recent years which aimed to model progressive flooding and damage ship behaviour and provide some explanations of fundamentals. Applications related to damage identification, the prediction of outcome/situation awareness, and flooding emergency response are also briefly discussed. The paper concludes with a brief reflection on salient gaps in the context of accelerating the development of these methods and their applicability. [ABSTRACT FROM AUTHOR]

Ship design is a years-long process that requires balancing complex design trade-offs to create a ship that is efficient and effective. Finding new ways to improve the ship design process could lead to significant cost savings in the time and effort required to design a ship, as well as cost savings in the procurement and operation of a ship. One promising technology is generative artificial intelligence, which has been shown to reduce design cycle times and create novel, high-performing designs. In a literature review, generative artificial intelligence was shown to generate ship hulls; however, ship design is particularly difficult, as the hull of a ship requires the consideration of many objectives. This paper presents a study on the generation of parametric ship hull designs using a parametric diffusion model that considers multiple objectives and constraints for hulls. This denoising diffusion probabilistic model (DDPM) generates the tabular parametric design vectors of a ship hull, which are then constructed into a point cloud and mesh for performance evaluation. In addition to a tabular DDPM, this paper details adding guidance to improve the quality of the generated parametric ship hull designs. By leveraging a classifier to guide sample generation, the DDPM produced feasible parametric ship hulls that maintained the coverage of the initial training dataset of ship hulls with a 99.5% rate, a 149× improvement over random sampling of the design vector parameters across the design space. Parametric ship hulls produced using performance guidance saw an average 91.4% reduction in wave drag coefficients and an average 47.9× relative increase in the total displaced volume of the hulls compared to the mean performance of the hulls in the training dataset. The use of a DDPM to generate parametric ship hulls can reduce design times by generating high-performing hull designs for future analysis. These generated hulls have low drag and high volume, which can reduce the cost of operating a ship and increase its potential to generate revenue. [ABSTRACT FROM AUTHOR]

In shipbuilding, the design and construction processes often involve repetitive tasks and the need for consistent structural elements across various vessels. This research paper presents the implementation of Template Oriented Modeling (TOM), an in-house developed CAD feature that offers an innovative solution to address these challenges. TOM introduces automation and efficiency by streamlining the ship design and construction processes. By utilizing predefined templates and dynamic parameters, TOM significantly reduces the need for manual repetition, resulting in time savings and increased productivity. This paper focuses on the issue of repetitive manual work in shipbuilding and highlights TOM as a transformative approach to overcome this challenge. The motivations, benefits, and innovations associated with TOM are thoroughly examined, emphasizing its potential to revolutionize the shipbuilding industry. We presented a fully functional example demonstrating the effectiveness of TOM in achieving streamlinedworkflows and improved design consistency. [ABSTRACT FROM AUTHOR]

This paper delves into the technical aspects and viability of integrating artificial intelligence (AI) and knowledge-based engineering (KBE) tools in practical design. The goal is to digitally embed the hands-on expertise and technical boundaries set by seasoned professionals during intricate engineering and preparatory phases. We showcase how AI/KBE tools might emulate human cognitive processes to make well-informed choices. The article also probes the prospective economic and modernization repercussions of this innovation. Our findings suggest that such an integration is feasible and can amplify the decision-making efficacy and advance the sophistication of CAD/CAM systems in the shipbuilding realm. Furthermore, this investigation underscores the promising future of AI/KBE tools in ship design and advocates for continued exploration and innovation in this sector to fully harness its advantages. [ABSTRACT FROM AUTHOR]

Maritime transport accounts for around 3% of global anthropogenic greenhouse gas (GHG) emissions (Well-to-Wake). These GHG emissions must be reduced by at least 50% in absolute values by 2050 to contribute to the ambitions of the Paris Agreement signed in 2015. Switching to zero-carbon fuels made from renewable sources (hydro, wind, or solar) is seen by many as the most promising option to deliver the desired GHG reductions. However, renewable energy is a scarce resource that gives a much larger GHG reduction spent within other sectors. This study explores how to reach the IMO 2050 GHG targets exclusively through energy efficiency measures. The results indicate that by combining wind-assisted ship propulsion (WASP) with a slender hull form, fuel consumption and GHG emissions can be reduced by 30-35%, at a negative abatement cost for speeds exceeding 8 knots. Where the cost saving increases with the speed because at higher speeds, the fuel accounts for a higher share of the total cost, which implies that the cost saving goes from zero at 8 knots, to 5% reduction at 11 knots average speed to 14% reduction of total cost with 15 knots average speed. In comparison, GHG reductions through zero-carbon fuels will increase transport costs by 50-200%. [ABSTRACT FROM AUTHOR]

This article discusses an early seventeenth-century draught of an 18-gun ship, which the author believes was drawn by Phineas Pett himself. This is based on handwriting comparisons, dating evidence within the draught, dimensions and armament of the ship possibly portrayed, and a possible explanation of why an English draught is now in the Danish archives. [ABSTRACT FROM AUTHOR]

This paper presents a semi analytic time domain method for the analysis of the symmetric hydroelastic response of a container ship subject to slamming and green water loads. An Impulse Response Function (IRF) is adopted for the calculation of radiation, diffraction and wave excitation forces. Local hydrodynamic forces associated with green water on decks and slamming loads are respectively modelled by the Buchner's Dam Break Model and a Generalised Wagner Model. The structural responses are captured by Euler-Bernoulli beam theory and solved by the modal superposition method. The Duhamel Integral technique is used to evaluate the dynamic response. A parametric study demonstrates how external forces may affect the global wave induced vertical bending moments and shear forces. Numerical simulations are compared against a hybrid method that combines computational fluid dynamics, boundary element and finite element methods for low to medium frequency induced dynamic response. It is concluded that the proposed semi analytic methodology is fast and accurate and may be useful at concept ship design stage. [ABSTRACT FROM AUTHOR]

In rough seas, ships may be subject to wave-induced slamming loads. Thus, modelling of fluid and structural mechanics, and their dynamic interactions can help with the evaluation of fluid actions and the prediction of wave-induced loads for use in ship design. In this paper a partitioned two-way coupled CFD-FEA fluid–structure interaction (FSI) method is used to study the water entry of flat plates with different impact velocities and wedges with different deadrise angles. Results show that when flexible plate dynamics prevail, at relatively low to medium impact velocity a negative correlation between the nondimensional pressure and water entry velocities is evident near plate centre areas. A steady correlation exists when only stiff plate dynamics prevail. Pressure differences between stiff and flexible wedges become evident at small deadrise angles. The similarity of the pressure distribution during water impingement of ideally stiff wedge structures is not valid when structural flexibility prevails. [ABSTRACT FROM AUTHOR]

The maritime industry is displaying notable interest in the adoption of cutting-edge technologies within the scope of Industry 4.0, aiming to digitalize both companies and processes. At the core of data science lies machine learning, which serves as the focal point of this article. This study seeks to accomplish two main objectives: firstly, an exploration of various machine learning algorithms, and subsequently, the application of these techniques to analyze predictions within the propulsion system of a 9500 TEU container ship. The outcomes of the study reveal that utilizing distinct machine learning algorithms for predicting braking performance yields a lower mean square error (MSE) when compared to the discrepancy introduced by the J. Mau formula, as evident in the container ship database. The selection of propulsion engines was based on predictions for a 9500 TEU container ship. Similarly, promising outcomes were achieved in predicting propeller diameter in comparison to conventional methods. Thus, these predictions can also effectively guide the appropriate choice of propeller diameter. [ABSTRACT FROM AUTHOR]

The shipping industry significantly influences global greenhouse gas emissions through a predominant fossil fuel-based fleet. Regulating bodies are continuously developing rules to reduce the shipping carbon footprint. Adopting low-carbon fuels is considered a step toward achieving the Paris Agreement’s goals; however, it represents a significant paradigm shift in ship design. This work aims to illustrate a methodology for the feasibility assessment of alternative-fuelled vessels considering technical, environmental, and economic perspectives. The technical feasibility focuses on ship propulsion, fuel system safety, and design parameters. The environmental impact evaluation is based on the Tank-to-Wake and the Well-to-Wake approaches. The cost assessment is performed by estimating capital and operational expenditures, considering only the modifications required by the new fuel. The methodology addresses new-building and retrofit solutions, and can be used as a decision support tool for selecting the best strategy. A key output of the methodology is the cargo emission footprint, expressed in equivalent carbon dioxide per cargo unit. Using a handysize bulk carrier as a case study, this work points out the effects of using methanol as an alternative fuel, highlighting its impact on market and transport strategies in a sector evolving towards Eco-Delivery services.

Determining the key characteristics of a ship during the concept and preliminary design phases is a critical and intricate process. In this study, we propose an alternative to traditional empirical methods by introducing a model to estimate the main particulars of diesel-powered Z-Drive harbor tugboats. This prediction is performed to determine the main particulars of tugboats: length, beam, draft, and power concerning the required service speed and bollard pull values, employing Bayesian network and non-linear regression methods. We utilized a dataset comprising 476 samples from 68 distinct diesel-powered Z-Drive harbor tugboat series to construct this model. The case study results demonstrate that the established model accurately predicts the main parameters of a tugboat with the obtained average of mean absolute percentage error values; 6.574% for the Bayesian network and 5.795%, 9.955% for non-linear regression methods. This model, therefore, proves to be a practical and valuable tool for ship designers in determining the main particulars of ships during the concept design stage by reducing revision return possibilities in further stages of ship design.

Over the coming decades, maritime transportation will transition from fossil hydrocarbon fuels to hydrogen, ammonia, and synthetic hydrocarbon fuels produced using renewable electricity as the primary energy source. In this context, a shipowner needs to identify a cost-efficient plan for the adoption of alternative fuels and onboard energy conversion system retrofits. This paper presents a multiperiod decision model for the selection of energy system components under increasingly stringent CO2 emissions regulations and cost forecasts over a multidecade planning horizon. The model considers the choice of newbuild architecture, timing of retrofits, component sizes, and allocation of fuels to converters with the objective of minimizing total cost of ownership (TCO). The decision problem is formulated as a discrete time multiperiod mixed-integer linear program. The application of the model is numerically illustrated for a Baltic Sea roll-on/roll-off ferry. The main findings are: (i) modifying the energy system with retrofits obtains 43% lower TCO compared to fuel switching alone; (ii) batteries contribute to 23% lower TCO; (iii) optimal component installation period can be shorter than their maximum lifetime; (iv) running an engine with hydrogen is favored over fuel cells and (v) hybrid propulsion is the key future-proofing design choice for short sea vessels. [ABSTRACT FROM AUTHOR]

Development of autonomous vessels is expected to create a paradigm shift in how warfare is conducted. Therefore, there is need to explore the possibilities and limitations in developing integrated systems for defence at sea to support innovation. Fleet modelling can analyse functions and other design options such as autonomous platform’s and evaluate their added effect in naval operations. However, due to the complexity of naval operations, it is not feasible to create a tool that covers all aspects needed to mimic reality. This study, from the perspective of naval tactics, investigate the value of a tool that analyses potential fleet architectures including autonomous platforms. The study identifies that the tool creates relevant mental models for future naval fleets by identifying feasible fleet compositions. However, the proposed fleet combinations are only tested against a limited set of tactical needs and can only be seen as a starting point for development. [ABSTRACT FROM AUTHOR]

Defects such as voids in composite materials often degrade the mechanical properties of laminates. Even if these materials are manufactured based on the design requirements, there is a possibility of instability occurring in these composite structures. In this study, several prototypes were developed based on changes in composite ship design conditions (glass fiber weight fraction and fabric combination type) using a hand lay-up approach. The fabrication quality was quantitatively defined using the burn-off test, and statistical analysis was performed. A combination of chopped strand mat and woven roving material laminates possessed relatively less void content in the entire glass content (Gc) region (30–70 wt%) compared to a chopped strand mat single-material laminate. The effect was more pronounced in the high-Gc region (50–70 wt%) than that in the normal-Gc region (30–50 wt%). The composite hull plate can be designed seamlessly according to changes in fabrication quality. To ensure safety, the thickness of the laminate must be greater than that specified in the ISO standards, regardless of the combination type in the normal-Gc region. As a result of the void content considered, the flexural strength in the single laminate decreased by 15.02%. Furthermore, 3.33% of the flexural strength calculation decreased in the combined laminate compared to that in the ISO rules. Thus, a single CSM material can be designed to be thicker than a combined-material laminate with the same Gc, while considering the void content on the mechanical properties. [ABSTRACT FROM AUTHOR]

This paper explores the design and feasibility of a 200-passenger, 30- to 40-knot emission-free ferry as a potential variant of the traditionally powered Coastal Cruiser 200 ferry currently operating in the Chinese Pearl River Delta. The Pearl River Delta is one of China's most densely urbanized regions and faces numerous social, health, and economic issues due to air pollution. In addition, globally, there are no currently-operating zero-emission ferries that, at minimum, sail at 30 knots and carry 200 passengers. To assess the feasibility of the new ferry, a two step approach was followed. First, an evaluation of efficiency improving measures, energy carriers, and propulsion systems was performed to assess the tradeoffs and identify early design choices. Second, to quantify the most technically feasible design, a technical parametric model was developed specifically for this case study. Results showed that the ferry is technically feasible using batteries, compressed hydrogen fuel cells, or liquid hydrogen fuel cells; however, each has its distinct advantages and disadvantages which influence the potential final viability. Despite the regional focus of the case study, results are applicable to all ferries with similar design requirements. [ABSTRACT FROM AUTHOR]

The importance of comfort during transfer and stationing becomes a key performance parameter for large yacht design, on the same level as propulsive issues. Such a matter extends questions in terms of form and service demand to the motion behaviour of the unit in waves. Relevant studies refer to outdated hull forms not specific to modern large yachts. In this study, five hull forms with different bow concepts represent the most common design solutions for yachts at constant draught and displacement. The preliminary ranking on the effect of alternative bows on comfort requires the definition of internationally accepted comfort standards. Here, the AWI 22834 guidelines for large yachts provide the service and environmental conditions and criteria for the comfort analysis, being the only reference specific to yachts. The calculations employ a strip-theory-based numerical model to provide results of easy understanding for designers during the early design stage. The obtained ranking among the design solutions on a reference large yacht favours the option nested with a bulb, contradicting the expectations in favour of a vertical bow concept. The discussion and conclusions provide a way forward for additional analyses and investigations aimed at proposing suitable multicriterial design guidelines for large yachts. However, the results also show the unsuitability of AWI environmental and encounter conditions for hull form ranking. [ABSTRACT FROM AUTHOR]

Naval hydrodynamics typically focus on reducing ship resistance, which can be achieved by incorporating a bulbous bow. This feature is commonly used in the merchant fleet and smaller vessels, such as fishing boats, to minimize wave-making resistance. However, it is important to note that the use of a bulbous bow may not always be necessary or effective in all ship designs. In some cases, fishing ship designs may include a bulbous bow that is not optimized due to the use of procedures and methods intended for larger merchant ships or based on past experience. This study examines the effect of different bow designs, including the bulbous bow, on ship resistance in calm water, with a focus on a typical Argentinian trawler fishing vessel. The objective of this research is to assess the hydrodynamics of various designs for a particular ship by modifying its vessel lines. Firstly, the bulbous bow is removed, and then the reduction in ship resistance achieved by the bulbous bow under different load conditions and speeds is evaluated by comparing the vessel with and without the bulbous bow. The numerical analysis is performed using OpenFOAM, and the results are validated through towing tank experiments. This research indicates that the performance of the bulbous bow varies under different conditions. Therefore, it is recommended to conduct an initial study and a full evaluation of the design and operation alternatives.

The strengthening of regulations such as EEXI, EEDI, and CII on ship emissions is underway. Despite their application, objective comparisons of ships are hindered by diverse navigation patterns and varying velocity regulations in different seas and ports. Additionally, a lack of basic data impedes comparisons of the optimal design and objective energy efficiency for ships. To address these issues, representative sailing modes, similar to those in the automobile industry, are needed. However, there is no reference for marine applications. This study introduces a methodology for representative sailing modes using the Markov chain. A hundred candidate sailing modes were created, and representative modes were identified through an evaluation equation. All chi-square values for representative sailing modes are within 1%, indicating significant results. This study’s findings can aid in designing optimized systems for new vessels and computing authorized fuel efficiency for vessels with diverse sailing patterns.

The dependence of the fishermen on the use of fossil fuels is still very high at and has not decreased until now. The increased price of fuel and reduced availability of fossil fuels makes fishermen struggling in their fishing activities. IMO (International Maritime Organization) noted that around 277 × 106 of fuel are consumed by ships with fossil fuels. According to an emission study conducted by IMO in 2012, 961 × 106 of CO2 accounting for 2.5 % of total global emissions. This study aims to reduce exhaust emissions by vessel from fossil fuels by making the ship into a hybrid (Diesel-Pv). By making the ship a hybrid with solar panels, it will save fuel consumption. The trozzi method approach is used to evaluate the exhaust emissions. The results obtained from changing the configuration to a hybrid, the emission that is issued can be reduced by around 57 % and save the fuel 19.6 %.

The timely and precise prediction of flooding progression and its eventual outcome in ships with breached hulls can lead to dramatic improvements in maritime safety through improved guidance for both emergency response and ship design. The traditional approach to assessing damage-induced flooding in both these stages, which also fully complies with statutory rules, is through static calculations. On the other hand, the application of models that simulate the flooding progression and the behaviour of flooded ships from, or close to, first principles allows for increased accuracy of the modelling of the phenomenon. This increase in accuracy can then be used to support advanced design for safety procedures. Furthermore, it can considerably enhance a ship’s capability for damage identification and inference-based logic for emergency decision support systems and marine accident response in general. This paper conducts a review of selected state-of-the-art methods, procedures, and case studies in recent years which aimed to model progressive flooding and damage ship behaviour and provide some explanations of fundamentals. Applications related to damage identification, the prediction of outcome/situation awareness, and flooding emergency response are also briefly discussed. The paper concludes with a brief reflection on salient gaps in the context of accelerating the development of these methods and their applicability.

3D modeling techniques have grown increasingly prevalent in a variety of disciplines, including cultural heritage and ship design. The methodology used in the 3D reconstruction of a traditional Greek boat with the Trechadiri hull type named “Aghia Varvara” is presented in this study. The original boat was built in 1925 and is characterized as a modern cultural heritage monument by the Greek Ministry of Culture. The digital reconstruction of the boat is explained in detail, including 3D laser scanning and computer aided geometric design (CAGD), as well as the description of the 3D printing process. The boat’s 3D digital model has been used for the enrichment of the NAVS Project’s digital library, demonstrating the unique geometrical, typological, and cultural characteristics of Greek traditional shipbuilding, a living craft which listed on Greece’s National Inventory of Intangible Cultural Heritage.

Wind-assisted propulsion (WASP) is one of the most promising ship propulsion alternatives that radically reduce greenhouse gas emissions and are available today. Using the example of a RoPax ferry, this study presents the performance potential of WASP systems under realistic weather conditions. Different design alternatives and system layouts are discussed. Further, uncertainties in the performance prediction of WASP systems are analyzed. Included in the analysis are the sail forces as well as the aero- and hydrodynamic interaction effects, i.e., the sail–sail and sail–deck interaction as well as the drift and yaw of the ship. As a result, this study provides guidelines on the most important parameters when designing and modeling a WASP ship. Finally, the study presents an analysis of the expected accuracy of the employed empirical/analytical performance prediction model ShipCLEAN. [ABSTRACT FROM AUTHOR]

In this paper, a method is introduced which enables the forcing of any degrees of freedom in 6 DoFs ship simulator. It is based on the introduction of an extra force in the equation of motion of the ship and on the forcing of the second derivatives of the forced degrees of freedom rather than the forced degrees of freedom themselves. The method is explicit which makes it easy to implement in existing software. Examples of its application to oblique towing tests and forced heading in wind and waves are presented. [ABSTRACT FROM AUTHOR]

Since the introduction of scientific disciplines into the shipbuilding process, there has been a search for optimisation of human and material resources. The current environmental crisis is putting additional pressure on global resource management and special attention to materials sourcing and utilisation. This paper discusses the potential solution for the current lack of effectiveness at early design stages, which are still based on 2D drawings. The industry is demanding a new 3D approach, which implies, first, a change in the procedures, and second, having a suitable CAD/CAM tool for the early generation of a digital mock-up, from which the project is developed throughout all design and production phases, from conceptual design to operation. The proposed solution shown in this paper would improve the general arrangement definition, with the use of CAD for the 3D definition of the compartments and the main equipment positioning; improve the naval architecture calculation; and finally improve the basic/class design stage, with better reuse of data already developed in the general arrangement model and in the definition of a 3D model of structure, with the main equipment positioning, pipes, and electrical equipment already into the model. Intelligent P&I diagrams and single-wire electric diagrams would be used at this stage and connected to the 3D model. Additionally, it will allow for early estimating of materials, weights, and associated processes. This will be further supported by the use of topology to consider design alternatives and produce early information on materials for procurement and production. The cost reduction associated with the definition of the early design stages in 3D has been estimated at around 15% of the overall design and production stages. [ABSTRACT FROM AUTHOR]

Design rules for ships have become more extensive and detailed due to an increase in the sizes of ships. Several variables and equations used in the rules are complex, thereby impeding their review by reviewers due to their voluminosity. In addition, because these rules are constantly revised, professional investigatorsmay miss these changes. To prevent such confusion, a shipping register, which approves ship drawings, constantly automates the search and review processes of the rules. Consequently, this study proposes a method for recognizing variables in documents to review the rules and build relationships between variables. Each component of a document must be accurately identified. The document containing these rules includes different components such as equations, figures, and strings. Because these rules are mainly converted to a portable document format (PDF) for compatibility, it is challenging to extract each component as raw data. This study used a public library to extract elements from the PDF and utilized the positional relationship between the elements to identify the variables. By applying the Levenshtein distance algorithm, which compares the differences between two strings, the document was partitioned following to the table of contents. Hence, the identified variables were indexed into sections of the table of content. Additionally, based on the indexed information, a data structure was proposed to show the equations, definition of variables, and relationships. This study applied it to common structural rules, which are widely used in the shipbuilding industry. The effectiveness of the proposed method was confirmed by achieving the F1 score = 0.93 in variable recognition and intuitively visualizing the relationship between the variables. [ABSTRACT FROM AUTHOR]

The maritime industry is displaying notable interest in the adoption of cutting-edge technologies within the scope of Industry 4.0, aiming to digitalize both companies and processes. At the core of data science lies machine learning, which serves as the focal point of this article. This study seeks to accomplish two main objectives: firstly, an exploration of various machine learning algorithms, and subsequently, the application of these techniques to analyze predictions within the propulsion system of a 9500 TEU container ship. The outcomes of the study reveal that utilizing distinct machine learning algorithms for predicting braking performance yields a lower mean square error (MSE) when compared to the discrepancy introduced by the J. Mau formula, as evident in the container ship database. The selection of propulsion engines was based on predictions for a 9500 TEU container ship. Similarly, promising outcomes were achieved in predicting propeller diameter in comparison to conventional methods. Thus, these predictions can also effectively guide the appropriate choice of propeller diameter.