Search Results (69)

With the IMO’s 2050 decarbonization target, hydrogen is a key zero-carbon fuel for shipping, but the lack of systematic risk assessment methods for hydrogen-powered marine propulsion systems (under harsh marine conditions) hinders its large-scale application. To address this gap, this study proposes an integrated risk evaluation framework by fusing Failure Mode, Effects, and Criticality Analysis (FMECA) with the Fuzzy Analytic Hierarchy Process (FAHP)—resolving the limitation of traditional single evaluation tools and adapting to the dynamic complexity of marine environments. Scientific findings from this framework confirm that hydrogen leakage, high-pressure storage tank valve leakage, and inverter overload are the three most critical failure modes, with hydrogen leakage being the primary risk source due to its high severity and detection difficulty. Further hazard matrix analysis reveals two key risk mechanisms: one type of failure (e.g., insufficient hydrogen concentration) features “high severity but low detectability,” requiring real-time monitoring; the other (e.g., distribution board tripping) shows “high frequency but controllable impact,” calling for optimized operations. This classification provides a theoretical basis for precise risk prevention. Targeted improvement measures (e.g., dual-sealed valves, redundant cooling circuits, AI-based regulation) are proposed and quantitatively validated, reducing the system’s overall risk value from 4.8 (moderate risk) to 1.8 (low risk). This study’s core contribution lies in developing a universally applicable scientific framework for marine hydrogen propulsion system risk assessment. It not only fills the methodological gap in traditional evaluations but also provides a theoretical basis for the safe promotion of hydrogen shipping, supporting the scientific realization of the IMO’s decarbonization goal. Full article

Energy management in hybrid fuel cell ship systems faces the dual challenges of optimizing hydrogen consumption and ensuring power quality. This study proposes an Improved Weighted Antlion Optimization (IW-ALO) algorithm for multi-objective problems. The method incorporates a dynamic weight adjustment mechanism and an elite-guided strategy, which significantly enhance global search capability and convergence performance. By integrating IW-ALO with the Equivalent Consumption Minimization Strategy (ECMS), an improved weighted ECMS (IW-ECMS) is developed, enabling real-time optimization of the equivalence factor and ensuring efficient energy sharing between the fuel cell and the lithium-ion battery. To validate the proposed strategy, a system simulation model is established in Matlab/Simulink 2017b. Compared with the rule-based state machine control and optimization-based ECMS methods over a representative 300 s ferry operating cycle, the IW-ECMS achieves a hydrogen consumption reduction of 43.4% and 42.6%, respectively, corresponding to a minimum total usage of 166.6 g under the specified load profile, while maintaining real-time system responsiveness. These reductions reflect the scenario tested, characterized by frequent load variations. Nonetheless, the results highlight the potential of IW-ECMS to enhance the economic performance of ship power systems and offer a novel approach for multi-objective cooperative optimization in complex energy systems. Full article

This study investigates the configuration of an energy storage system (ESS) and the optimization of energy management strategies for diesel-electric hybrid ships, with the goal of enhancing fuel economy and reducing emissions. An integrated mathematical model of the diesel generator set and the battery-based ESS is established. A rule-based energy management strategy (EMS) is proposed, in which the ship operating conditions are classified into berthing, maneuvering, and cruising modes. This classification enables coordinated power allocation between the diesel generator set and the ESS, while ensuring that the diesel engine operates within its high-efficiency region. The optimization framework considers the number of battery modules in series and the upper and lower bounds of the state of charge (SOC) as design variables. The dual objectives are set as lifecycle cost (LCC) and greenhouse gas (GHG) emissions, optimized using the Multi-Objective Coati Optimization Algorithm (MOCOA). The algorithm achieves a balance between global exploration and local exploitation. Numerical simulations indicate that, under the LCC-optimal solution, fuel consumption and GHG emissions are reduced by 16.12% and 13.18%, respectively, while under the GHG-minimization solution, reductions of 37.84% in fuel consumption and 35.02% in emissions are achieved. Compared with conventional algorithms, including Multi-Objective Particle Swarm Optimization (MOPSO), Non-dominated Sorting Dung Beetle Optimizer (NSDBO), and Multi-Objective Sparrow Search Algorithm (MOSSA), MOCOA exhibits superior convergence and solution diversity. The findings provide valuable engineering insights into the optimal configuration of ESS and EMS for hybrid ships, thereby contributing to the advancement of green shipping. Full article

Environmental emissions from the maritime sector, including CO₂, NO_x, and SO_x, contribute significantly to global air pollution and climate change. The International Maritime Organization (IMO) has set a target to reduce greenhouse gas emissions from international shipping to reach zero GHG by 2050 compared to 2008 levels. To meet these goals, the IMO strongly encourages the transition to alternative fuels, such as hydrogen, ammonia, and biofuels, as part of a broader decarbonization strategy. This study presents a comparative analysis of converting conventional diesel engines to dual-fuel systems utilizing alternative fuels such as methanol or natural gas. The methodology of this research is based on theoretical calculations to estimate various types of emissions produced by conventional marine fuels. These results are then compared with the emissions generated when using methanol and natural gas in dual-fuel engines. The analysis is conducted using the EVER ALOT container ship as a case study. The evaluation focuses on both environmental and economic aspects of engines operating in natural gas–diesel and methanol–diesel dual-fuel modes. The results show that using 89% natural gas in a dual fuel engine reduces nitrogen oxides (NO_x), sulfur oxides (SO_x), carbon dioxide (CO₂), particulate matter (PM), and carbon monoxide (CO) pollutions by 77.69%, 89.00%, 18.17%, 89.00%, and 30.51%, respectively, while the emissions percentage will be 77.78%, 91.00%, 54.67%, 91.00%, and 55.90%, in order, when using methanol as a dual fuel with percentage 91.00% Methanol. This study is significant as it highlights the potential of natural gas and methanol as viable alternative fuels for reducing harmful emissions in the maritime sector. The shift toward these cleaner fuels could play a crucial role in supporting the maritime industry’s transition to low-emission operations, aligning with global environmental regulations and sustainability goals. Full article

Although wind-assisted ship propulsion (WASP) is an effective technique for reducing the emissions of merchant ships, the best fuel type for complementing WASP remains an open question. This study presents a new original life cycle assessment method for ship fuels that uses a validated ship performance prediction model and actual operation conditions for a WASP ship. As a case study, the method is used to evaluate the fuel consumption and environmental impact of different fuels for a WASP ship operating in the Baltic Sea. Using a novel in-house-developed platform for predicting ship performance under actual operation conditions using hindcast data, the engine and fuel tank were sized while accounting for fluctuating weather conditions over a year. The results showed significant variation in the required fuel tank capacity across fuel types, with liquid hydrogen requiring the largest volume, followed by LNG and ammonia. Additionally, a well-to-wake life cycle assessment revealed that dual-fuel engines using green ammonia and hydrogen exhibit the lowest global warming potential (GWP), while grey ammonia and blue hydrogen have substantially higher GWP levels. Notably, NOx, SOx, and particulate matter emissions were consistently lower for dual-fuel and liquid natural gas scenarios than for single-fuel marine diesel oil engines. These results underscore the importance of selecting both an appropriate fuel type and production method to optimize environmental performance. This study advocates for transitioning to greener fuel options derived from sustainable pathways for WASP ships to mitigate the environmental impact of maritime operations and support global climate change efforts. Full article

Background: Increasing regulatory pressure for maritime decarbonization (e.g., IMO CII, FuelEU) drives adoption of low-carbon fuels and prompts reassessment of regional ports’ competitiveness. This study aims to evaluate the economic and environmental viability of rerouting deep-sea container services to regional ports in a decarbonizing world. Methods: A scenario-based analysis is used to evaluate total costs and CO₂ emissions across the entire container shipping supply chain, incorporating deep-sea shipping, port operations, feeder services, and inland rail/road transport. The Port of Liverpool serves as the primary case study for rerouting Asia–Europe services from major ports. Results: Analysis indicates Liverpool’s competitiveness improves with shipping lines’ slow steaming, growth in hinterland shipment volume, reductions in the emission factors of alternative low-carbon fuels, and an increased modal shift to rail matching that of competitor ports (e.g., Southampton). A dual-port strategy, rerouting services to call at both Liverpool and Southampton, shows potential for both economic and environmental benefits. Conclusions: The study concludes that rerouting deep-sea services to regional ports can offer cost and emission advantages under specific operational and market conditions. Findings on factors and conditions influencing competitiveness and the dual-port strategy provide insights for shippers, ports, shipping lines, logistics agents, and policymakers navigating maritime decarbonization. Full article

This research develops a dual physics-based machine learning system to forecast fuel consumption and CO₂ emissions for a 100 m oil tanker across six operational scenarios: Original, Paint, Advanced Propeller, Fin, Bulbous Bow, and Combined. The combination of hydrodynamic calculations with Monte Carlo simulations provides a solid foundation for training machine learning models, particularly in cases where dataset restrictions are present. The XGBoost model demonstrated superior performance compared to Support Vector Regression, Gaussian Process Regression, Random Forest, and Shallow Neural Network models, achieving near-zero prediction errors that closely matched physics-based calculations. The physics-based analysis demonstrated that the Combined scenario, which combines hull coatings with bulbous bow modifications, produced the largest fuel consumption reduction (5.37% at 15 knots), followed by the Advanced Propeller scenario. The results demonstrate that user inputs (e.g., engine power: 870 kW, speed: 12.7 knots) match the Advanced Propeller scenario, followed by Paint, which indicates that advanced propellers or hull coatings would optimize efficiency. The obtained insights help ship operators modify their operational parameters and designers select essential modifications for sustainable operations. The model maintains its strength at low speeds, where fuel consumption is minimal, making it applicable to other oil tankers. The hybrid approach provides a new tool for maritime efficiency analysis, yielding interpretable results that support International Maritime Organization objectives, despite starting with a limited dataset. The model requires additional research to enhance its predictive accuracy using larger datasets and real-time data collection, which will aid in achieving global environmental stewardship. Full article

Liquefied natural gas (LNG) is increasingly used as a marine fuel due to its capacity to significantly reduce emissions of particulate matter, sulfur oxides (SO_x), and nitrogen oxides (NO_x), compared to conventional fuels. In addition, LNG combustion produces less carbon dioxide (CO₂) than conventional marine fuels, and the use of non-fossil LNG offers further potential for reducing greenhouse gas emissions. However, this benefit can be partially offset by methane slip—the release of unburned methane in engine exhaust—which has a much higher global warming potential than CO₂. This study presents an experimental evaluation of methane emissions from a RoPax vessel powered by low-pressure dual-fuel four-stroke engines with a direct mechanical propulsion system. Methane slip was measured directly during onboard testing and combined with a year-long analysis of engine operation using an Engine Load Monitoring (ELM) method. The yearly average methane slip coefficient (C_slip) obtained was 1.57%, slightly lower than values reported in previous studies on cruise ships (1.7%), and significantly lower than the default values specified by the FuelEU (3.1%) Maritime regulation and IMO (3.5%) LCA guidelines. This result reflects the ship’s operational profile, characterized by long crossings at high and stable engine loads. This study provides results that could support more representative emission assessments and can contribute to ongoing regulatory discussions. Full article

The accurate prediction of autonomous vessel CO₂ emissions is critical for achieving IMO 2050 carbon neutrality and optimizing low-carbon maritime operations. Traditional models face limitations in real-time multi-source data analysis and dynamic cross-variable dependency modeling, hindering data-driven decision-making for sustainable autonomous shipping. This study proposes a Multi-scale Channel-aligned Transformer (MCAT) model, integrated with a 5G–satellite–IoT communication architecture, to address these challenges. The MCAT model employs multi-scale token reconstruction and a dual-level attention mechanism, effectively capturing spatiotemporal dependencies in heterogeneous data streams (AIS, sensors, weather) while suppressing high-frequency noise. To enable seamless data collaboration, a hybrid transmission framework combining satellite (Inmarsat/Iridium), 5G URLLC slicing, and industrial Ethernet is designed, achieving ultra-low latency (10 ms) and nanosecond-level synchronization via IEEE 1588v2. Validated on a 22-dimensional real autonomous vessel dataset, MCAT reduces prediction errors by 12.5% MAE and 24% MSE compared to state-of-the-art methods, demonstrating superior robustness under noisy scenarios. Furthermore, the proposed architecture supports smart autonomous shipping solutions by providing demonstrably interpretable emission insights through its dual-level attention mechanism (visualized via attention maps) for route optimization, fuel efficiency enhancement, and compliance with CII regulations. This research bridges AI-driven predictive analytics with green autonomous shipping technologies, offering a scalable framework for digitalized and sustainable maritime operations. Full article

This paper analyzes the potential of retrofitting in “greening” of European inland vessels and coastal ships, which are normally not the focus of major international environmental policies aimed at waterborne transport. Therefore, greening of the examined fleets would result, for the most part, in additional emission reductions to the environmental targets put forth by the International Maritime Organization. By scoping past and ongoing pilot projects, the most prominent retrofit trends in the greening of inland and coastal ships are identified. Assuming a scenario in which the observed trends are scaled up to the fleet level, the possible emission abatement is estimated (both on the tank-to-wake and well-to-wake bases), as well as the capital and operational costs associated with the retrofit. Therefore, the paper shows what can be achieved in terms of greening if the current trends are followed. The results show that the term “greening” may take a significantly different meaning contingent on the approaches, perspectives, and targets considered. The total costs of a retrofit of a single vessel may be excessively high; however, the costs may significantly vary depending on the vessel power requirements, operational profile, and technology applied. While some trends are worth following (electrification of ferries and small inland passenger ships), others may be too cost-intensive and not satisfactorily efficient in terms of emissions reduction (retrofit of offshore supply vessels with dual-fuel methanol engines). Nevertheless, the assessment of different retrofit technologies strongly depends on the adopted criteria, including but not limited to the total cost of the retrofit of the entire fleet segment, cost of the retrofit of a single vessel, emission abatement achieved by the retrofit of a fleet segment, average emission abatement per retrofitted vessel, and cost of abatement of one ton of greenhouse gases, etc. Full article

Marine diesel engines face persistent challenges in balancing transient black smoke emissions and maneuverability under low-speed conditions due to inherent limitations of single turbocharger systems, such as high inertia and delayed intake response, compounded by control strategies prioritizing steady-state efficiency. To address this gap, this study proposes a dual -turbocharger dynamic matching framework integrated with a speed–pitch synergistic control strategy—the first mechanical-control co-design solution for transient emission suppression. By establishing a λ-opacity correlation model and a multi-physics ship–engine–propeller simulation platform, we demonstrate that the Type-C dual turbocharger reduces rotational inertia by 80%, shortens intake pressure buildup time to 25.8 s (54.7% faster than single turbochargers), and eliminates high-risk black smoke regions (maintaining λ > 1.5). The optimized system reduces the fuel consumption rate by 12.9 g·(kW·h)⁻¹ under extreme loading conditions and decreases the duration of high-risk zones by 74.4–100%. This study provides theoretical and practical support for resolving the trade-off between transient emissions and maneuverability in marine power systems through synergistic innovations in mechanical design and control strategies. Full article

To address greenhouse gas (GHG) emissions from the maritime sector, the European Union (EU) has introduced the FuelEU Maritime regulation to incentivize ships to adopt diversified compliance pathways and energy solutions. This study aims to determine the optimal alternative fuel configurations for dual-fuel ships of different types under environmental, economic, and regulatory constraints. An integrated environmental and cost assessment model from a well-to-wake (WtW) perspective to systematically evaluate the environmental benefits and economic feasibility of fossil-based, bio-based, and renewable electricity-based alternative fuels applied in dual-fuel ships. By incorporating the PROMETHEE II method within a multi-criteria decision analysis (MCDA) framework, together with the CRITIC objective weighting method, the study enables a robust ranking of alternative fuel configurations across three key dimensions: environmental performance, cost feasibility, and regulatory compliance. The results indicate that, regardless of ship type, the very low sulfur fuel oil (VLSFO) + marine gas oil (MGO) and VLSFO + methanol (MEOH) combinations fail to meet the GHG intensity targets for 2025–2050. Only the VLSFO + electrolytic liquid hydrogen (E-LH₂) and VLSFO + electrolytic ammonia (E-NH₃) configurations are compliant. Although e-fuels incur the highest annual costs, the EU compliance penalty associated with fossil fuels increases exponentially. In contrast, e-fuels retain long-term cost advantages, ultimately driving a sector-wide transition toward e-fuel-dominated energy structures by 2050. Their superior environmental performance and regulatory compatibility emerge as the core drivers of the maritime energy transition. Full article

The amendment to MARPOL Annex VI, which limits the sulfur content in marine fuels to a maximum of 0.5 wt.%, came into effect in January 2020. This includes reducing sulfur oxide (SO_X) emissions and establishing nitrogen oxide (NO_X) emission standards (Tiers I, II, and III) based on the ship’s engine type and construction date. Furthermore, the regulations require oil tankers to control volatile organic compound (VOC) emissions and prohibit the installation of new equipment containing ozone-depleting substances. After a four-year exploration phase, global shipping companies still lack consistent evaluation criteria for the selection and use of alternative fuels, resulting in divergence across the industry. According to the latest data, methanol can reduce NO_X, SO_X, and particulate matter (PM) emissions by approximately 80%, 99%, and 95%, respectively, compared to traditional heavy fuel oil. Furthermore, green methanol has the potential for near-zero greenhouse gas emissions and can meet the stringent standards of Emission Control Areas. Therefore, this study adopts a cost-benefit analysis method to evaluate the feasibility and implementation benefits of two promising strategies: methanol dual fuel and very low-sulfur fuel oil (VLSFO). A 6600-TEU container ship was selected as a representative case, and the evaluation was conducted by replacing an older ship with a newly built one. The reductions in total pollutants and CO₂-equivalent emissions of the container ship, as well as the cost-effectiveness of each specific strategy, were calculated. This study found that, in the first five years of operation, the total incremental cost of Vessel A, which uses 100% VLSFO, will be significantly lower than that of Vessel B, which uses a blend of 30% e-methanol + 70% VLSFO as fuel. Furthermore, compared to a scenario without any improvement strategies, the total incremental cost for Vessels A and B will increase by 69.90% and 178.15%, respectively, over five years. Vessel B effectively reduced the total greenhouse gas emission equivalent (CO₂e) of CO₂, CH_4, and N₂O by 24.72% over five years, while Vessel A reduced the CO₂e amount by 12.18%. Furthermore, the cost-benefit ratio (CBR) based on total pollutant emission reduction is higher for Vessel A than for Vessel B within five years of operation. However, in terms of the cost-effectiveness of CO₂e emission reduction, the CBR of Vessel A becomes lower than Vessel B after 4.7 years of operation. Therefore, Vessel A’s strategy should be considered a short-term option for reducing CO₂e within 4.7 years, whereas the strategy of Vessel B is more suitable as a long-term solution for more than 4.7 years. Full article

This study established a numerical model for ammonia leakage and diffusion in confined ship engine room spaces and validated its effectiveness through existing experiments. The research revealed the evolution patterns of ammonia cloud dispersion under various working conditions. Multi-parameter coupling analysis demonstrated that the combined effect of leakage source location and obstacle distribution alters the spatial configuration of gas clouds. When leakage jets directly impact obstacles, the resulting vortex structures maximize the coverage area of high-concentration ammonia near the ground. Ventilation system efficiency shows a significant negative correlation with hazardous zone volume. The hazardous zone volume was reduced by 50% when employing a bottom dual-side air intake combined with a top symmetric exhaust scheme, compared to the bottom single-side intake with an opposite-side top exhaust configuration. By enhancing the synergistic effect between longitudinal convection and top suction, harmful gas accumulation in lower spaces was effectively controlled. These findings not only provide a theoretical basis for ventilation system design in ammonia-fueled ships but also offer practical applications for risk prevention and control of maritime ammonia leakage. Full article

Methanol/diesel hybrid−powered vessels represent a significant advancement in green and low−carbon innovation in the maritime transportation sector and have been widely adopted across various shipping markets. However, the dual−fuel power system modifies the fire load within the engine room compared to traditional vessels, thereby significantly influencing the fire safety of methanol/diesel−powered ships. In this study, anhydrous methanol and light−duty diesel (with 0 °C pour point) were used as fuels to investigate the mixed combustion characteristics of these immiscible fuels in circular pools with diameters of 6, 10, 14, and 20 cm at various mixing ratios. By analyzing the fuel mass loss rate, flame morphology, and heat transfer characteristics, it was determined that methanol and diesel exhibited distinct stratification during combustion, with the process comprising three phases: pure methanol combustion phase, transitional combustion phase, and pure diesel combustion phase. Slopover occurred during the transitional combustion phase, and its intensity decreased as the pool diameter or methanol fuel quantity increased. Based on this conclusion, a quantitative relationship was established between slopover intensity, pool diameter, and the methanol/diesel volume ratio. Additionally, during the transitional combustion phase, the average flame height exhibited an exponential coupling relationship with the pool diameter and the methanol/diesel volume ratio. Therefore, a modification was made to the classical flame height model to account for these effects. Moreover, a prediction model for the burning rate of methanol/diesel pool fires was established based on transient temperature variations within the fuel layer. This model incorporated a correction factor related to pool diameter and fuel mixture ratio. Additionally, the causes of slopover were analyzed from the perspectives of heat transfer and fire dynamics, further refining the physical interpretation of the correction factor. Full article