Vessel Design Research Articles

Exploring Vessels from the Offshore Oil and Gas Industry in Design of Deep-Sea Mining Vessels

_ In this paper, vessels from the offshore oil and gas industry are explored in the conceptual design of value-robust deep-sea mining vessel solutions. The responsive systems comparison method is applied in a case addressing two hypothetical stakeholders: a mining company and a vessel operator. Their value propositions are outlined and pave the ground for important attributes that consolidate into conceptual vessel design solutions. The cost–benefit trade-offs for various design solutions and technology choices are discussed for different future scenarios. The results indicate that complexity drives high CAPEX generation, yielding so-called gold-plated designs. Lower cost mitigation measures should be taken to ensure future missions of a deep-sea mining vessel. The consequences of design choices on commercial considerations are discussed, such as the vessels’ second-hand value in the market and alternative uses. Keywords deep-sea mining; offshore vessels; ship design; technology transfer; cost–benefit; scenario-testing

Influence of Water Cover on the Blast Resistance of Circular Plates

Abstract Explosion containment vessels (ECVs) can effectively limit the range of potential hazards, and improving their blast resistance is an important research topic. Placing ECVs underwater is an excellent and promising method. The effect of water covering on the blast resistance of circular plates was investigated experimentally and numerically in this paper. First, blast experiments of circular water-covered and bare plates were conducted, and strain responses were obtained. The effect of water on the maximum strain as well as the high-level strain crests was investigated based on experimental results. Then, numerical simulations were carried out using ansys/autodyn and validated by experimental results. The displacement and strain response at the center of the circular plate with different water cover heights were analyzed. The experimental and numerical results show that water can effectively reduce the peak dynamic response of the steel plate and increase the vibration period of the steel plate. The center of the circular plate is the most dangerous position under confined blast loading, regardless of whether the plate is covered with water or not. The results from numerical simulations also clearly show that the blast resistance of the steel plate will first be improved and then stable with the increase of the water cover height. The work in this paper can provide a useful reference for the design and protection of explosion containment vessels.

An Investigation into Using CFD for the Estimation of Ship Specific Parameters for the SPICE Model for the Prediction of Sea Spray Icing: Part 2—The Verification of SPICE2 with a Full-Scale Test

A hybrid CFD–ML model for the prediction of sea spray icing, SPICE2, was developed in Part 1 of this study in Deshpande et al., 2024. The SPICE2 model is an extension of the ML model, SPICE, where some of the variables required for icing rate predictions: local wind speed, spray duration, spray period, and spray flux, are computed from CFD simulations. These, along with the air and water temperatures, and the salinity from the metocean data are used for the prediction of icing rates at different locations on a moving vessel. The existing full-scale icing measurements proved to be not detailed enough for the purpose of the verification of sea spray icing prediction models and the verification of the SPICE2 required distribution of sea spray icing data on the vessel surface in addition to the vessel design for simulation. A full-scale sea spray icing test was conducted in 2018 by Sundsbø et al. on a fully enclosed lifeboat equipped for the Goliat field in the Barents Sea. The 3D design of the same lifeboat, together with the corresponding metocean conditions and ship characteristics was used for the simulation of the vessel-specific parameters required for the verification of the icing rate and distribution prediction from the SPICE2 model against the measured distribution of sea spray icing rates on the lifeboat surface. The availability of the 3D model of this lifeboat, in addition to the fact that the icing measurements from this test were detailed enough to attempt a model verification served the purpose of validating the SPICE2 model. The icing rates measured on this lifeboat are used for the full-scale validation of the SPICE2 model that is proposed in Part 1 of this study. It was seen that the icing rates predicted by SPICE2 concurred with 9 of 13 selected locations on the lifeboat. The ones which did not showed very little deviation from the measurements. The icing rate and distribution prediction with SPICE2 were satisfactorily validated against full-scale icing measurements. This is a first attempt in modelling sea spray generation using CFD and further research into CFD for the estimation of spray flux is suggested.

Conceptual design of an autonomous single-container vessel

The growth of maritime shipping is leading to the creation of larger vessels. However, this expansion in size brings with it several challenges, including the development of maritime infrastructure, the potential for growth in third-world countries, and the emission of greenhouse gases. In response to these challenges, this research explores the feasibility of designing an autonomous ship capable of transporting a single standardized 40 ft. container overseas using mainly passive propulsion methods. Using advanced design tools, including CAD software and CFD simulations, as well as conducting a comprehensive analysis of relevant literature, the designs for a hull and sails were developed, and an overview of the potential active control systems required for autonomous operation was provided. The study also performed an initial analysis of strength, stability, and velocity to validate the design choices. The ship proves to adhere to the basic strength and stability requirements while reaching its maximum hull velocity at certain wind speeds. The results of the study indicate that it is possible to design and manufacture a mainly passively propelled ship capable of transporting a 40 ft. standardized container overseas and rethink the logistics at scale.

Learning Harris Hawk Algorithm Based on Signal-to-Noise Ratio

In view of the problem of insufficient population learning and adaptability of the Harris Hawk optimization algorithm, this paper proposes a learning Harris Hawk algorithm based on signal-to-noise ratio, referred to as SLHHO. This algorithm introduces the concept of signal-to-noise ratio to determine the location information of individuals, and designs a coordinated learning strategy that can more reasonably update the location of individuals within the population, and then redesign the escape distance to improve the adaptation and optimization of the algorithm. ability. Using 12 benchmark functions as standards, the performance of this algorithm was tested with variants of the Harris Eagle algorithm and other algorithms, and comparative analysis was conducted in evaluation indicators such as time complexity, diversity, exploration and development, and the results show that SLHHO has strong competitiveness and feasibility. Finally, the practicality of SLHHO was verified in the pressure vessel design problem.

Prediction of Ductile Damage in Composite Material Used in Type IV Hydrogen Tanks by Artificial Neural Network and Machine Learning with Finite Element Modeling Approach

This study investigates the degradation process of composite materials used in high‐pressure hydrogen storage vessels by employing advanced computational techniques. A recurrent neural network, specifically a bidirectional long short‐term memory (Bi‐LSTM) network, is utilized to predict the temporal evolution of ductile damage. The key degradation features are extracted from finite element modeling (FEM) computations using group method of data handling algorithms and treated as time‐series data. Results demonstrate that the Bi‐LSTM network can accurately undergo both elastic and plastic behaviors of the composite under tensile strength. Additionally, traditional machine learning (ML) algorithms such as extreme gradient boosting and random forest are employed to forecast strain degradation, showing promising results. This hybrid approach combining FEM, ML, and deep learning provides a comprehensive method for predicting the degradation of composite materials, offering significant potential for optimizing the design and durability of hydrogen storage vessels.

An efficient weighted slime mould algorithm for engineering optimization

In engineering applications, optimal parameter design is crucial. While Slime Mould Algorithm (SMA) excels in parameter discovery under constrained conditions, it faces challenges in achieving global convergence and avoiding local opsecttimal traps in complex tasks. This paper introduces an enhanced variant of SMA, termed CCHSMA, which integrates a Chaotic Local Search (CLS) mechanism to improve initial population diversity and combines Covariance Matrix Adaptation (CMA) and Harris Hawks Optimization (HHO) strategies to enhance global search efficiency. CCHSMA aims to improve search quality and reduce the likelihood of getting trapped in local optima. We evaluated CCHSMA's effectiveness by benchmarking it against the standard SMA and its variants using 30 CEC2017 test functions, and compared its performance with seven notable meta-heuristic algorithms and ten advanced swarm intelligence variants. The experimental results demonstrate that CCHSMA outperforms the other algorithms tested on the benchmark functions. To further validate its practical utility, CCHSMA's performance was also benchmarked against leading algorithms in real-world engineering applications. This paper uses detailed statistical methods, including the Wilcoxon signed-rank test and the Friedman test, to validate the comparative results. Our findings show that CCHSMA outperforms other algorithms in solving complex engineering optimization problems such as tension/compression spring design, pressure vessel design, and three-bar truss design, proving to be a robust tool for complex engineering optimization. Its enhanced initial population diversity and improved global search efficiency are essential for effectively addressing diverse engineering challenges.

Impact of automation and zero-emission propulsion on design of small inland cargo vessels

Abstract Small inland waterways offer considerable capacity for modal shift of cargo transport. Revitalization of smaller inland waterways, however, may require new vessel designs as most of the existing small vessels are outdated and incompatible with the present state of the technology development and the current commercial and regulatory requirements. This paper investigates the possibilities for modernization of small inland vessel designs and offers a systematic analysis of impact of “automation” and “zero-emission propulsion technology” on reference designs of standard European inland cargo vessels of CEMT classes I, II, III, and IV. The adopted level of automation enables the vessels to be remotely operated without human crew onboard, whereas the adopted zero-emission propulsion concept is based on electrification of the powertrain. The paper identifies the impacts of the modernization on general arrangement, cargo capacity, safety, structural design, etc. and indicates the vessel classes which could be the most promising candidates for the design of a future small autonomous inland ships.

Resistance performance study and hull form optimization of aquaculture vessel by CFD method

Abstract Aquaculture vessel is a novel form of deep-sea aquaculture engineering with a wide range of applications. The resistance performance of the aquaculture vessel was studied by the computational fluid dynamics method and compared with the experiment. Two optimization schemes, namely, straight bow and bulbous bow, are designed to optimize the original design, focusing on improving the bow profile. The effectiveness of the two optimization schemes in terms of resistance reduction was evaluated by the CFD method. The resistance calculated by numerical calculations was found to be in good agreement with the experimental results. The bulbous bow scheme reduces resistance better than the upright scheme, with a resistance reduction of 2.92% at 11 kn. This study can guide the overall design of an aquaculture vessel.

HSMAOA: An enhanced arithmetic optimization algorithm with an adaptive hierarchical structure for its solution analysis and application in optimization problems

The Arithmetic Optimization Algorithm (AOA) has recently gained significant attention as a novel meta-heuristic algorithm. However, it faces challenges such as premature convergence and entrapment in local optima when addressing complex optimization problems. To overcome these limitations, this paper proposes an enhanced AOA, termed the Self-Adaptive Hierarchical Arithmetic Optimization Algorithm (HSMAOA). The proposed method integrates three key strategies: Firstly, a spiral-guided random walk mechanism is introduced to improve global search ability. Secondly, a novel adaptive hierarchy leader and follower mechanism is proposed, which establishes a complete multi-branch tree hierarchy with decreasing branching degrees within the population, thereby increasing information exchange among population individuals to escape local optima. Finally, a differential mutation strategy based on ranked selection is introduced to enhance candidate solution quality. HSMAOA's performance was evaluated on the CEC2022 test suite against some state-of-the-art algorithms. Results, including optimization accuracy analysis, convergence curves, and various statistical tests, demonstrate HSMAOA's superior optimization capability and robustness. In addition, tests on eight engineering structure optimization problems, including the pressure vessel design problem, the multiple disk clutch brake design problem, and the step-cone pulley problem, and so forth, further validate its effectiveness. Thus, HSMAOA shows strong competitiveness in complex optimization tasks and potential for a wide range of applications, and is an advantageous and promising alternative solution for optimization problems.

Somersault Foraging and Elite Opposition-Based Learning Dung Beetle Optimization Algorithm

To tackle the shortcomings of the Dung Beetle Optimization (DBO) Algorithm, which include slow convergence speed, an imbalance between exploration and exploitation, and susceptibility to local optima, a Somersault Foraging and Elite Opposition-Based Learning Dung Beetle Optimization (SFEDBO) Algorithm is proposed. This algorithm utilizes an elite opposition-based learning strategy as the method for generating the initial population, resulting in a more diverse initial population. To address the imbalance between exploration and exploitation in the algorithm, an adaptive strategy is employed to dynamically adjust the number of dung beetles and eggs with each iteration of the population. Inspired by the Manta Ray Foraging Optimization (MRFO) algorithm, we utilize its somersault foraging strategy to perturb the position of the optimal individual, thereby enhancing the algorithm’s ability to escape from local optima. To verify the effectiveness of the proposed improvements, the SFEDBO algorithm is utilized to optimize 23 benchmark test functions. The results show that the SFEDBO algorithm achieves better solution accuracy and stability, outperforming the DBO algorithm in terms of optimization results on the test functions. Finally, the SFEDBO algorithm was applied to the practical application problems of pressure vessel design, tension/extension spring design, and 3D unmanned aerial vehicle (UAV) path planning, and better optimization results were obtained. The research shows that the SFEDBO algorithm proposed in this paper is applicable to actual optimization problems and has better performance.

System-based ship design of a deep-sea mining vessel

ABSTRACT This paper applies the system-based ship design (SBSD) method to the conceptual design of a deep-sea mining vessel. The anticipated mine site is situated on the Norwegian extended continental shelf, where three production scenarios are assessed. The design process is documented, including a problem statement, mission description, functions, space requirements of various sub-systems, stability calculations, and preliminary cost estimates. A combination of data from existing technologies and estimates is used to set the relevant parameters, and the applicability of SBSD in the conceptual design of novel vessels is discussed. We find that when data is lacking in conceptual ship design, inspiration can be found from similar systems in established maritime industries, such as the offshore oil and gas industry.

Divertor Tokamak Test facility project: status of design and implementation

Abstract An overview is presented of the progress since 2021 in the construction and scientific programme preparation of the Divertor Tokamak Test (DTT) facility. Licensing for building construction has been granted at the end of 2021. Licensing for Cat. A radiologic source has been also granted in 2022. The construction of the toroidal field magnet system is progressing. The prototype of the 170GHz gyrotron has been produced and it is now under test on the FALCON facility. The design of the vacuum vessel, the poloidal field coils and the civil infrastructures has been completed. The shape of the first DTT divertor has been agreed with EUROfusion to test different plasma and exhaust scenarios: single null, double null, XD divertor and negative triangularity plasmas. A detailed research plan is being elaborated with the involvement of the EUROfusion laboratories.

Coyote and Badger Optimization (CBO): A natural inspired meta-heuristic algorithm based on cooperative hunting

Optimization techniques play a pivotal role in refining problem-solving methods across various domains. These methods have demonstrated their efficacy in addressing real-world complexities. Continuous efforts are made to create and enhance techniques in the realm of research. This paper introduces a novel technique that distinguishes itself through its clarity, logical mathematical structure, and robust mathematical equations, particularly in the second phase. This study presents the development of a new metaheuristic algorithm named Coyote and Badger Optimization (CBO). CBO draws inspiration from the cooperative behaviors observed in honey badgers and coyotes, with a specific focus on their intriguing communication process. Utilizing the inherent traits of these animals, the proposed CBO algorithm offers an intuitive and effective solution for addressing engineering optimization challenges by providing the best fitness values. To validate CBO's effectiveness in real-time applications, complex engineering problems called pressure vessel design, feature selection in medical system, and tension-compression spring design are used as case studies for testing the proposed CBO compared to other recent algorithms. Additionally, ten benchmark functions and also statistical analysis methods (mean, standard deviation, confidence intervals, t-test, and Wilcoxon test) are used. Experimental results demonstrate that the CBO algorithm surpasses eleven recent algorithms when subjected to common ten benchmark functions. Additionally, CBO outperforms other recent eleven algorithms according to three different case studies. According to the ten benchmark functions (F1 to F10), CBO provides the minimum fitness values which are closed to the exact (standard) values; 0, 0, 0.003, 0.0002, -1.0316, 3.0058, 0.398, 0.02, 0.00076, and 0.000725 respectively. Related to statistical analysis, CBO provides the best mean, standard deviation, confidence intervals, t-test, and Wilcoxon test values. According to case studies, CBO provided the minimum cost value for pressure vessel design, the maximum accuracy value for feature selection, and the minimum cost value for spring design. Hence, CBO superiors other recent algorithms.

Advancement in the Modeling and Design of Composite Pressure Vessels for Hydrogen Storage: A Comprehensive Review

The industrial and technological sectors are pushing the boundaries to develop a new class of high-pressure vessels for hydrogen storage that aim to improve durability and and endure harsh operating conditions. This review serves as a strategic foundation for the integration of hydrogen tanks into transport applications while also proposing innovative approaches to designing high-performance composite tanks. The goal is to offer optimized, safe, and cost-effective solutions for the next generation of high-pressure vessels, contributing significantly to energy security through technological advancements. Additionally, the review deepens our understanding of the relationship between microscopic failure mechanisms and the initial failure of reinforced composites. The investigation will focus on the behavior and damaging processes of composite overwrapped pressure vessels (COPVs). Moreover, the review summarizes relevant simulation models in conjunction with experimental work to predict the burst pressure and to continuously monitor the degree of structural weakening and fatigue lifetime of COPVs. Simultaneously, understanding the adverse effects of in-service applications is vital for maintaining structural health during the operational life cycle.

Research on Move-to-Escape Enhanced Dung Beetle Optimization and Its Applications.

The dung beetle optimization (DBO) algorithm is acknowledged for its robust optimization capabilities and rapid convergence as an efficient swarm intelligence optimization technique. Nevertheless, DBO, similar to other swarm intelligence algorithms, often gets trapped in local optima during the later stages of optimization. To mitigate this challenge, we propose the Move-to-Escape dung beetle optimization (MEDBO) algorithm in this paper. MEDBO utilizes a good point set strategy for initializing the swarm's initial population, ensuring a more uniform distribution and diminishing the risk of local optima entrapment. Moreover, it incorporates convergence factors and dynamically balances the number of offspring and foraging individuals, prioritizing global exploration initially and local exploration subsequently. This dynamic adjustment not only enhances the search speed but also prevents local optima stagnation. The algorithm's performance was assessed using the CEC2017 benchmark suite, which confirmed MEDBO's significant improvements. Additionally, we applied MEDBO to three engineering problems: pressure vessel design, three-bar truss design, and spring design. MEDBO exhibited an excellent performance in these applications, demonstrating its practicality and efficacy in real-world problem-solving contexts.

Temperature-Driven Instabilities in High-Pressure Vessel Flat Plates: A Thermal Buckling Study

In the realm of high-pressure vessel simulation, conventional finite element method (FEM) approaches, as per ASME standards, may inadequately predict the behavior of flat surfaces under elevated temperatures. This study challenges the efficacy of shell-type mesh modeling for high-temperature flat plates, demonstrating that the thermal conditions within such high-pressure vessels can induce thermal instability and buckling, not accounted for by traditional FEM methods recommended by ASME. Through comprehensive analytical investigations, we reveal that traditional shell-type meshing techniques, while suitable for certain applications, fail to capture the intricate thermal stresses and deformation patterns inherent in high-temperature flat plate configurations. Our analysis delineates distinct stability regimes governed by key design parameters, including plate thickness, operating temperature, and geometric dimensions, profoundly impacting the structural integrity of heating plates under thermal loading. Specifically, we found that increasing the plate thickness enhances resistance to thermal buckling, clamping the plate edges raises the critical buckling temperature, and selecting materials with lower thermal expansion coefficients improves stability. These findings provide engineers with critical insights necessary for optimizing the design and performance of high-temperature equipment. This includes the design of high-pressure vessels with flat surfaces for heating materials, flanges in high-temperature environments, and fins in heat exchangers across various industries such as oil and gas, pyrolysis, and power plants. The findings presented herein serve as a valuable reference for engineers seeking to comprehend and mitigate instability phenomena in solid mechanics, offering practical guidance for developing robust and reliable high-temperature structures in demanding industrial environments.

The Challenges of Naval Electromobility in Amazônia

Introduction: This study aims to assess the feasibility of replacing a diesel-powered tourist boat with a Solar Electric Hybrid Catamaran with a capacity for fifty people to promote sustainable tourism in the Amazon, specifically in the Belém-Pará region. The initiative seeks to take advantage of the opportunity presented by COP 2030 to innovate in the waterway transportation matrix through renewable energy sources. The research is based on sustainability concepts, the environmental impacts of using fossil fuels and the advantages of using solar energy for waterway transportation. The methodology includes a comparative analysis of diesel-powered vessels' operational and environmental costs and a Hybrid Electric system based on data compiled from a master's thesis. The expected results include identifying significant benefits in terms of reduced carbon emissions. The discussion will address the challenges faced in implementation, such as the initial investment costs, the maintenance of the new technologies, and the adaptation of operators and tourists to the latest transportation conditions. The implications of this research are vast; it can serve as an incentive for energy transition in the river transportation sector. Furthermore, this research pioneers the proposal of replacing diesel-powered tourist boats with solar electric hybrid models in the Amazon region. The study adds value by presenting a practical and sustainable solution to the environmental challenges the tourism sector faces, in line with the global sustainability goals set by COP 2030. Objective: This research outlines the importance and potential of naval electric mobility in the Eastern Amazon region, highlighting its relevance within COP 2030 and the SDGs for promoting ecotourism for the Amazon region. Theoretical Framework: The research is based on sustainability concepts, the environmental impacts of using fossil fuels, and the advantages of using solar energy for water transportation. In addition, previous experiences of implementing similar technologies in other regions and the potential for replicability in the Amazon are considered, focusing on environmental conservation and economic development. Method: This research is a compilation of the master's thesis entitled "Waterway electric propulsion technologies: conceptual design of a hybrid vessel with a focus on meeting environmental, social and Governance (ESG) practices," where the study was carried out in the municipality of Belém, Pará in the year 2023. Results and Discussion: The expected results include identifying significant benefits in terms of reduced carbon emissions, lower noise pollution and improved air quality. The discussion will address the challenges faced in implementation, such as initial investment costs, maintaining the new technologies and adapting operators and tourists to the new transportation conditions. Social acceptance and the potential for a positive impact on local tourism will also be assessed. Research Implications: This research has vast implications, ranging from contributing to climate change mitigation to promoting more sustainable tourism practices in the Amazon. Adopting the Solar Electric Hybrid Catamaran can serve as a model for other areas with similar geographical characteristics, encouraging public policies aimed at using renewable energies in the transportation sector. Originality/Value: This research pioneers the proposal of the replacement of diesel-powered tourist boats with a solar electric hybrid model in the Amazon region. The study adds value by presenting a practical and sustainable solution to the environmental challenges faced by the tourism sector, which is in line with the global sustainability goals set by COP 2030.

Achieving the global net-zero maritime shipping goal: The urgencies, challenges, regulatory measures and strategic solutions

Maritime shipping emissions have been identified as a remaining issue and have been the key focus for a decade. This study systematically summarises the Imperatives, Challenges, Strategic Regulatory and R&D Measures based on our investigations and analysis. In addition to the strategies and measures we gathered and brought here for the goal of a clean maritime world, some tactical technology gaps were identified along with a breakthrough technology development idea to integrate marine vessel design and efficiency processes systematically.

Design optimization of cubic-shaped pressurant tank for CubeSat propulsion system

From a technical and economic point of view, cold gas propulsion for nanosatellites is one of the more rational systems. There is a problem, however: the optimal spherical shape for a high-pressure vessel only takes up half the cubic volume of the CubeSat unit. To increase the volume, it is proposed to switch to a cubic-shaped tank. The aim of this work is to synthesize the more rational structural design of a pressurant tank that fits within a cubic constraint, which provides the perfect balance between the mass of the structure and the delta-V budget available for the propulsion system. The proposed variants are as follows: a set of four cylinders with spherical bottoms; 14 equal spheres arranged in a face-centered cubic packing; a thin-walled cube supported by ribs, the location and parameters of which provide the smallest mass of the structure; a cube, the reinforcement scheme of which is calculated using topology optimization method; an original polyspheric and bypass design schemes where the filling of the volume of the cube is created by a set of spherical and cylindrical shells of different radii. All the considered vessel variants can be obtained using additive technologies, such as selective laser sintering. For each variant, the internal volume and mass of the vessels were obtained, as well as the delta-V budget, taking into account the mass of the tank and the mass of the stored gas. The analysis of the results reveals that there are two structures that are more rational. The new bypass scheme provides the largest delta-V budget, but it has a 1.6 times larger mass than the initial spherical vessel design. It should be noted that the difference in vessel mass is not crucial for CubeSat form factor satellites. Choosing a rational design may require a larger delta-V budget. The possibility of increasing the reserve delta-V of the CubeSat cold gas propulsion system by 25–35 % due to the transition from a spherical to a cube-shaped tank has been demonstrated. At the same time, the mass of the tank structure increases by 1.6–6.3 times, which can be considered an acceptable price for increasing the efficiency of the propulsion system. The new bypass scheme offers the optimal balance of mass and delta-V reserve.