Vessel Design Research Articles

Vacuum vessel design with lofted toroidal surfaces for a QHS configuration

A vacuum vessel in between the hot plasma and the magnetic coils is crucial for a fusion reactor. In this work, a tool is presented to perform the initial design of such a vessel automatically. Starting from the last closed flux surface, an algorithm is developed which lofts this manifold out as much as possible. At the same time, the algorithm makes sure that no intersection with the coils takes place. In the presented work, this algorithm is applied to the HSX stellarator and it has been verified that the resulting vessel wall can be built from an engineering perspective. Using field line tracing, the strikepoints on the vessel wall indicate the initial locations for a divertor.

A modified adaptive large neighborhood search algorithm for solving the multi-port continuous berth allocation problem with vessel speed optimization

Despite its fast-growing popularity in maritime transportation, container shipping is still fraught with risks and uncertainties with its complex operating environments. This paper studies the multi-port continuous berth allocation problem with speed optimization (MCBAP). In the MCBAP, vessels visit multiple ports sequentially, and the problem aims at minimizing the sum of vessel sailing cost, waiting cost, delay cost and port handling cost, while satisfying various constraints related to vessel sailing and berthing. A mixed integer linear programming (MILP) model for MCBAP is formulated, and a modified adaptive large neighborhood search (MALNS) algorithm is proposed for solving large-scale MCBAPs. In the MALNS, an efficient initial solution generation strategy is developed, and a series of neighborhood solution generation operators are proposed. Finally, the proposed MILP model and MALNS algorithm are tested on a range of MCBAP instances. The numerical results demonstrate that the MILP model can be solved to optimality with CPLEX, and the MALNS can efficiently solve instances at various scales. In addition, sensitivity analyses on fuel prices and vessel design speeds (the planned maximum speeds) are performed, and management insights have been provided.

Mission profile oriented energy efficiency and CO2 footprint assessment of naval vessels at conceptual design phase: A comparative case study of conventional and hybrid energy systems

CO2 is the main green house gas (GHG) produced in fossil fuel burning engines on ships. The growth of activities of sea-going vessels, have been increasing interest and concerns over ship-born CO2 emissions. Consequently, numerous studies have been introduced for emission estimation. Each estimation approach has its own assumptions, thus uncertainty with data of vessel activities, vessel attributes, and calculating methods. The conceptual design phase is the first phase of ship design. One of the issues addressed at this phase is the assessment of energy system alternatives of relevant ship. A ship energy system provides propulsion and electrical power. The assessment of energy system alternatives for a naval vessel is a very complicated business that has a significant impact and interaction on overall vessel integration. Naval vessels and their energy systems constitute a noteworthy part of the total world ship fleet. The present study aims to present a realistic methodology for estimating efficiency, hence CO2 emissions, for candidate energy systems of surface vessels at conceptual design phase. A frigate is selected as the case (baseline) vessel. Three energy systems, namely CODAD, CODOG, and CODLOG-CC, are proposed as alternatives for the case vessel. Instead of general emission estimation approaches, the present study proposes a mission profile-oriented estimation methodology which provides more precise and accurate results. The Energy Efficiency Design Index (EEDI) defines efficiency and sets limitation during design and construction of specific merchant vessels, but since this index does not comply with unique characteristics of mission profile of surface vessels, the novel efficiency design index defined as integral warship EEDI (IWEEDI) is implemented for the case vessel. According to the analysis, CODAD is found to be the most efficient alternative, followed by CODLOG-CC and CODOG, respectively.

Mid-Term Outcomes of the Viabahn Balloon-Expandable Endoprosthesis as Bridging Stent Graft for Fenestrated and Branched Endovascular Aortic Repair.

Bridging stent grafts (BSG) implanted during fenestrated and branched endovascular aortic repair (F/B-EVAR) are crucial for the successful exclusion of thoracoabdominal and complex abdominal aortic aneurysms (AAA). The aim of this study was to analyze the outcomes of the Gore Viabahn VBX stent graft as BSG for renal and visceral target vessels during F/B-EVAR. All consecutive patients undergoing F/B-EVAR for thoracoabdominal or complex AAAs from January 2019 to May 2023 who were treated with at least 1 VBX stent graft as BSG were included. Procedural, radiological, and follow-up data of the included patients were retrospectively reviewed. Primary outcome of the study was technical success of VBX stent graft implantation. Secondary endpoints were VBX-related adverse events, target vessel instability, endoleaks, and overall survival. A total of 273 VBX stent grafts were implanted in 263 target vessels in 38 FEVAR, 46 BEVAR, and 3 F/B-EVAR (combined design) stent grafts in 87 patients (74.7% male; mean age, 73.6 ± 7.0 years). Technical success of VBX stent graft implantation was 97.5% with 273 successful implantations in 280 attempts. The VBX-related secondary endpoints were evaluated for 269 VBX stent grafts in 259 target vessels. Target vessel designs included 107 fenestrations (41.3%), 82 outer-branches (31.7%), and 70 inner-branches (27.0%). Freedom from VBX-related adverse events at 12 months postoperatively was 96.6% (95% CI: 92.9%-100%) for target vessels with a fenestration and 93.6% (95% CI: 89.4%-98.0%) for target vessels with a branch. Freedom from target vessel instability at 12 months postoperatively for fenestrations and branches was 98.1% (95% CI: 94.4%-100%) and 97.6% (95% CI: 94.9%-100%) respectively. A total of 9 (3.5%) VBX-related endoleaks were detected during follow-up. Overall survival of all treated patients was 86.7% (95% CI: 79.1%-94.9%) at a median follow-up of 14 months. The VBX stent graft shows an excellent performance as a BSG in F/B-EVAR. The VBX stent graft has a high technical implantation success and shows a high mid-term freedom from stent graft-related adverse events and target vessel instability for both target vessels with a fenestration and a branch. Long-term follow-up data of the performance of the VBX stent graft are to be awaited. This study evaluated the outcomes of the Gore Viabahn VBX stent graft as a bridging stent graft (BSG) for renal and visceral target vessels. It is important to evaluate the performance of such recently introduced stent grafts as these are essentially used in procedures outside of the Instructions for Use. This comprehensive analysis of the VBX stent graft as a BSG adds to the evidence of the performance of this stent graft as a BSG.

Escape: an optimization method based on crowd evacuation behaviors

Meta-heuristic algorithms, particularly those based on swarm intelligence, are highly effective for solving black-box optimization problems. However, maintaining a balance between exploration and exploitation within these algorithms remains a significant challenge. This paper introduces a useful algorithm, called Escape or Escape Algorithm (ESC), inspired by crowd evacuation behavior, to solve real-world cases and benchmark problems. The ESC algorithm simulates the behavior of crowds during the evacuation, where the population is divided into calm, herding, and panic groups during the exploration phase, reflecting different levels of decision-making and emotional states. Calm individuals guide the crowd toward safety, herding individuals imitate others in less secure areas, and panic individuals make volatile decisions in the most dangerous zones. As the algorithm transitions into the exploitation phase, the population converges toward optimal solutions, akin to finding the safest exit. The effectiveness of the ESC algorithm is validated on two adjustable problem size test suites, CEC 2017 and CEC 2022. ESC ranked first in the 10-dimensional, 30-dimensional tests of CEC 2017, and the 10-dimensional and 20-dimensional tests of CEC 2022, and second in the 50-dimensional and 100-dimensional tests of CEC 2017. Additionally, ESC performed exceptionally well, ranking first in the engineering problems of pressure vessel design, tension/compression spring design, and rolling element bearing design, as well as in two 3D UAV path planning problems, demonstrating its efficiency in solving real-world complex problems, particularly complex problems like 3D UAV path planning. Compared with 12 other high-performance, classical, and advanced algorithms, ESC exhibited superior performance in complex optimization problems. The source codes of ESC algorithm will be shared at https://aliasgharheidari.com/ESC.html and other websites.

Rechargeable Hydrogen Gas Batteries: Fundamentals, Principles, Materials, and Applications.

The growing demand for renewable energy sources has accelerated a boom in research on new battery chemistries. Despite decades of development for various battery types, including lithium-ion batteries, their suitability for grid-scale energy storage applications remains imperfect. In recent years, rechargeable hydrogen gas batteries (HGBs), utilizing hydrogen catalytic electrode as anode, have attracted extensive academic and industrial attention. HGBs, facilitated by appropriate catalysts, demonstrate notable attributes such as high power density, high capacity, excellent low-temperature performance, and ultralong cycle life. This review presents a comprehensive overview of four key aspects pertaining to HGBs: fundamentals, principles, materials, and applications. First, detailed insights are provided into hydrogen electrodes, encompassing electrochemical principles, hydrogen catalytic mechanisms, advancements in hydrogen catalytic materials, and structural considerations in hydrogen electrode design. Second, an examination and future prospects of cathode material compatibility, encompassing both current and potential materials, are summarized. Third, other components and engineering considerations of HGBs are elaborated, including cell stack design and pressure vessel design. Finally, a techno-economic analysis and outlook offers an overview of the current status and future prospects of HGBs, indicating their orientation for further research and application advancements.

Enhancing safety in the storage of hazardous molecules: The case of hydroxylamine

Handling large quantities of thermally unstable compounds in storage vessels can result in severe accidents due to runaway reactions. Therefore, developing inherently safe design strategies for storage equipment is crucial for enhancing chemical plant reliability and preventing hazardous scenarios. The Frank-Kamenetskii theory (FKT) of self-heating offers practical tools for designing procedures to address phenomena that could lead to uncontrolled chemical reactions. This study introduces a design procedure based on the FKT for creating intrinsically safe storage vessels. An expanded FKT version incorporating parametric sensitivity analysis has been developed to improve the method's reliability. To understand self-heating phenomena, stability and performance diagrams were created, relating critical design parameters (e.g., the critical value of the Frank-Kamenetskii number) and verification parameters (e.g., maximum reached dimensionless temperature) to the dimensionless activation energy (γ). Additionally, the proposed design strategy includes a procedure for designing relief systems to mitigate the risk of equipment explosions from runaway reactions. The applicability of this procedure was tested using two cases: (I) an aqueous solution containing 50% w/w hydroxylamine (HA) and (II) a 50% w/w HA aqueous solution with 1% w/w hydroxylamine hydrochloride (HA-derived salt). Results indicate that for large γ values, the traditional FKT formulation and the expanded theory yield similar vessel designs. However, for finite γ values (γ≤100), the refined FKT version allows for less conservative storage equipment design. Combining DIERS guidelines with standard procedures for relief systems results in a more versatile and consistent protocol. However, incorporating relief systems is often impractical for large storage vessels due to the excessively large venting areas required for runaway reactions. In such cases, intrinsically safe vessel designs become the only feasible solution to prevent catastrophic incidents.

Comprehensive design and preliminary experiments of liquid hydrogen storage tank for trucks

As the global demand for lower carbon emissions intensifies, the deployment of medium and small-scale liquid hydrogen (LH2) storage tanks in heavy-duty trucking and aviation is expected to increase. However, heat leakage into these cryogenic vessels leads to a continuous increase in tank pressure, potentially resulting in sudden hydrogen release and other safety concerns. While horizontal LH2 tanks demonstrate greater suitability in the transportation sector compared to vertical tanks, investigations in this domain remain scarce. Research on horizontal tanks is crucial for safe and efficient storage. Understanding these dynamics is essential for predicting temperature and pressure changes during self-pressurization, ensuring safe liquid hydrogen storage. This study designed and built a 500-liter horizontal liquid hydrogen tank for vehicle fuel storage, following ISO 13985 standards to ensure practical applicability. The project encompassed material selection, structural design, and both stress and thermodynamic analyses. Preliminary experiments were conducted using liquid nitrogen as a substitute for liquid hydrogen. Experiments assessed tank heat leakage, vapor-cooled shield insulation performance, thermal stratification, lossless storage time, and pressure changes during self-pressurization and steady-state evaporation. Results validate the efficiency of our pressure vessel design method for complex conditions, enhancing understanding of self-pressurization and thermal stratification in horizontal tanks. The vapor-cooled shield reduced heat leakage into the tank by 22.7%, decreasing the daily evaporation rate under liquid nitrogen conditions from 1.87 wt% to 1.5 wt%. and maintaining an initial liquid level of 50% extended the lossless storage time to 50 h in the LN2 scenario. These findings offer valuable insights for assessing the performance of subsequent liquid hydrogen experiments.

FOX-TSA: Navigating Complex Search Spaces and Superior Performance in Benchmark and Real-World Optimization Problems

In the dynamic field of optimisation, hybrid algorithms have garnered significant attention for their ability to combine the strengths of multiple methods. This study presents the Hybrid FOX-TSA algorithm, a novel optimisation technique that merges the exploratory capabilities of the FOX algorithm with the exploitative power of the TSA algorithm. The primary objective is to evaluate the efficiency, robustness, and scalability of this hybrid approach across multiple CEC benchmark suites, including CEC2014, CEC2017, CEC2019, CEC2020, and CEC2022, alongside real-world engineering design problems. The results demonstrate that the Hybrid FOX-TSA algorithm consistently outperforms established optimisation techniques, such as PSO, GWO, and the original FOX and TSA algorithms, in terms of convergence speed, solution quality, and computational efficiency. Notably, the hybrid approach avoids premature convergence and navigating complex search spaces, producing optimal or near-optimal solutions in various test cases. For instance, the algorithm achieved superior performance in minimizing design costs in the Pressure Vessel and Welded Beam Design problems, as well as effectively handling the complex landscapes of the CEC2020 and CEC2022 benchmarks. These results affirm the Hybrid FOX-TSA algorithm as a powerful and adaptable tool for tackling complex optimization problems, particularly in high-dimensional and multimodal landscapes. The integration of statistical analyses, such as t-tests and Wilcoxon signed-rank tests, further supports the statistical significance of its performance improvements.

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

Standardization of Turbine Design and Installation Vessels to Accelerate the Offshore Wind Industry in the United States

Offshore wind energy has gained attention as a promising renewable energy source with many benefits, including clean, sustainable, and scalable electricity production. Despite the vast potential for offshore wind production in the United States, the country lags in its development. The industry struggles with supply chain challenges related to the complex logistics around the design and construction of many component parts, installation and maintenance vessels, and shipyards that can accommodate the massive turbine components before installation. These challenges are complicated by the rapid increase in size of offshore wind turbines to achieve higher power generation, which are not easily handled by other parts of the supply chain. The US lacks access to wind turbine installation vessels (WTIVs), particularly those that can install very large turbines. To address these issues, we propose policy options to the US Bureau of Ocean Energy Management of the Department of Interior and the US Department of Energy to spearhead standardization in this sector of the economy by exploring standardization of maximum turbine size, investment in WTIVs, or allowance of unrestricted or market-driven offshore wind farm development. These options have great potential to enable growth in the offshore wind energy sector in the US and achieve the federal government's goal of 30 GW of offshore wind energy by 2030.

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. HSMAOAʼs 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 HSMAOAʼs 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.

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.

Reliability-based composite pressure vessel design optimization with cure-induced stresses and spatial material variability

The future green hydrogen economy requires reliable and affordable composite pressure vessels. These vessels are expensive to manufacture, for a large part due to the high cost of carbon fibers in the composite layup. This study minimizes the thickness (and cost) of a composite pressure vessel layup without a reduction of its reliability. The study applies a multiphysics and multiscale uncertainty quantification framework that predicts the nondeterministic vessel burst pressure. A thermomechanical curing simulation accounts for cure-induced stress. It shows a good qualitative agreement with experimental measurements. A previously validated nondeterministic mechanical burst simulation accounts for experimentally measured spatial material variability of fiber misalignment, fiber volume fraction, and fiber strength. The workflow is coupled with a global optimization strategy that minimizes the layup thickness and retains the same 1% probability of failure pressure as a baseline pressure vessel. The optimization varies the number of layers in the layup, and their winding angle. A 27.3% thickness reduction is achieved.

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.