Search Results (49)

Growing demand for small satellite launches has increased the need for low-cost and environmentally sustainable propulsion systems. Hybrid rockets have garnered attention as a promising alternative, but most solid fuels are petroleum-derived, contributing to resource depletion and greenhouse gas emissions. This study evaluated the potential of polyethylene recovered from marine plastic waste (Marine Plastics) as a solid fuel for hybrid rockets. For thermal and elemental analyses, commercial high-density polyethylene pellets (Standard HDPEs) were used as a reference, while commercial HDPE cylindrical material (Combustion-grade HDPE) was used for combustion tests. Differential scanning calorimetry and thermogravimetric analyses revealed that Marine Plastics exhibited a melting point of approximately 403 K, comparable to Standard HDPE, with slightly lower thermal stability. Elemental analysis indicated the absence of oxygen atoms, suggesting minimal UV-induced degradation. Combustion tests demonstrated that both Marine Plastics and Combustion-grade HDPE achieved about 60% of the theoretical characteristic velocity, with Marine Plastics exhibiting a slightly higher regression rate. Furthermore, Marine Plastics contained a small amount of sodium chloride, suggesting the potential formation of hydrogen chloride during combustion. These results experimentally confirm that Marine Plastics possess thermal and combustion properties comparable to commercial HDPE, indicating their potential as an alternative solid fuel for hybrid rockets. Full article

With the increasing global demand for environmental protection and sustainable energy utilization, methanol, as a clean and renewable fuel, has become a research focus in the field of marine engines. However, its application in compression ignition engines faces bottlenecks such as low combustion efficiency and poor stability. Taking the L23/30H marine diesel engine as the research object, this paper establishes a combustion simulation model for a methanol/diesel dual-fuel direct-injection engine. The reliability of the model is ensured through grid independence verification and model calibration, and a coupled chemical reaction kinetic mechanism containing 126 species and 711 elementary reactions is constructed. A systematic study is conducted on the effects of injection strategies, including fuel operating modes, spray development patterns, injection intervals, and injection timing, on combustion characteristics. The results show that under the optimized injection strategy (vertical cross spray + synchronous injection) proposed in this study and operating conditions with a high methanol substitution ratio, the combustion efficiency, dynamic performance, and soot emission control effect of the dual-fuel mode are superior to those of the pure diesel mode. Simulation results show that the combined strategy of vertical cross injection and synchronous injection can significantly increase the indicated thermal efficiency (ITE) by 3.2%, reduce the brake specific fuel consumption (BSFC) by approximately 4.5%, advance the peak heat release by 2 °CA, and remarkably improve the combustion efficiency, while earlier injection timing is beneficial to air–fuel mixing. Further comparison of combustion and emission characteristics under different boundary conditions such as methanol energy ratios and injection pressures reveals that increasing methanol injection pressure, compression ratio, and initial pressure can improve combustion uniformity and reduce soot emissions, but NO_x emissions increase, which requires the coordination of after-treatment technologies. Through the comprehensive optimization of multiple parameters, efficient and clean combustion under a high methanol substitution rate is achieved. This paper provides theoretical support and practical guidance for the technological development of marine methanol dual-fuel engines. In the future, industrial applications can be promoted by combining actual engine tests and after-treatment technologies. Full article

As a pivotal element in the maritime sector’s green transition, fuel-cell-powered ships have attracted increasing attention due to the energy efficiency and stability of their onboard powertrains. Yet, the dynamic coordination and capacity optimization of fuel cells and supercapacitors remain among the most formidable technological challenges. In this study, a hybrid marine power system pairing fuel cells with supercapacitors is devised by integrating robust control with a particle swarm optimization (PSO) algorithm. The results reveal that, under complex operating conditions, robust control effectively mitigates system uncertainties and secures reliable operation of the ship’s energy system. Optimally allocating component capacities via PSO markedly enhances the synergy between the fuel cell and the supercapacitor. Compared with conventional schemes, optimized architecture boosts energy efficiency by 12.5%, shortens response time by 8.4%, and demonstrates clear superiority in robustness and stability. This robust-control-based hybrid configuration therefore delivers outstanding performance and offers compelling guidance for the refined design of marine propulsion systems. Full article

The maritime industry is under increasing pressure to reduce greenhouse gas emissions, especially in countries such as Saudi Arabia that are actively working to transition to cleaner energy. In this paper, a new hybrid shipboard power system, which incorporates wind turbines, solar photovoltaic (PV) panels, proton-exchange membrane fuel cells (PEMFCs), and a battery energy storage system (BESS) together for propulsion and hotel load services, is proposed. A multi-loop Energy Management System (EMS) based on proportional–integral control (PI) is developed to coordinate the interconnections of the power sources in real time. In contrast to the widely reported model predictive or artificial intelligence optimization schemes, the PI-derived EMS achieves similar power stability and hydrogen utilization efficiency with significantly reduced computational overhead and full marine suitability. By taking advantage of the high solar irradiance and coastal wind resources in Saudi Arabia, the proposed configuration provides continuous near-zero-emission operation. Simulation results show that the PEMFC accounts for about 90% of the total energy demand, the BESS (±0.4 MW, 2 MWh) accounts for about 3%, and the stationary renewables account for about 7%, which reduces the demand for hydro-gas to about 160 kg. The DC-bus voltage is kept within ±5% of its nominal value of 750 V, and the battery state of charge (SOC) is kept within 20% to 80%. Sensitivity analyses show that by varying renewable input by ±20%, diesel consumption is ±5%. These results demonstrate the system’s ability to meet International Maritime Organization (IMO) emission targets by delivering stable near-zero-emission operation, while achieving high hydrogen efficiency and grid stability with minimal computational cost. Consequently, the proposed system presents a realistic, certifiable, and regionally optimized roadmap for next-generation hybrid PEMFC–battery–renewable marine power systems in Saudi Arabian coastal operations. Full article

The reliability of ocean-going ship engine fuel systems is crucial for the safety and continuous operation of vessels. Failure of this system can lead to serious operational and economic consequences; therefore, effective diagnostics and failure prediction are essential elements of modern fleet management. This paper presents an analysis of the reliability of fuel systems based on operational data from ten bulk carriers operated by Polska Żegluga Morska in Szczecin. The analysis combined classical statistical methods with artificial intelligence algorithms to develop a hybrid diagnostic and forecasting framework. The Weibull lifetime distribution was applied to estimate time-to-failure parameters, revealing mixed failure mechanisms—random failures (k < 1) and aging-related processes (k > 1). Using the k-means algorithm, ships were automatically classified into two reliability groups: high-failure-rate units and stable operational vessels. Individual linear regression models were then developed for each ship to forecast the time to the next failure, achieving satisfactory predictive performance (R² > 0.75 for most vessels). Sensitivity analysis quantified model robustness under different disturbance scenarios, yielding mean Relative Prediction Deviation (RPD) values of approximately 65% for Missing Data, 60% for False Failure, and 26% for Data Noise. These results confirm that the proposed hybrid reliability–AI framework is resistant to random noise but sensitive to incomplete or erroneous historical data. The developed approach provides an interpretable and effective tool for predictive maintenance, supporting reliability management and operational decision-making in marine engine systems. The article presents a hybrid model that has been developed to enable the detailed characterization of emergency processes and the identification of the most important factors that influence damage forecasting. For systems with variable failure risk, it was found that both classical probabilistic models and machine learning methods must be considered to interpret damage patterns correctly. Implementing data filtration and validation procedures before using data in artificial intelligence models has been shown to improve forecast stability and increase the usefulness of forecasts for planning repairs. Full article

The precise regulation of water content plays a pivotal role in determining several the critical properties of marine fuels, including combustion stability, corrosion resistance, and the mitigation of pollutant emissions. The present study introduces an innovative, additive-free technique for moisture extraction from Marine Gasoil (MGO) utilizing the hydrophilic polymer polyacrylamide, which leverages its polar amino groups to attract water molecules. This process facilitates the physical extraction of moisture without modifying the fuel’s composition, in contrast to traditional drying techniques or chemical additions. Experimental findings indicate a 34.6% decrease in water content in MGO (from 29.3 mg/kg to 19.15 mg/kg) and a 36.5% reduction in MGO–biodiesel blends (from 32.04 mg/kg to 20.34 mg/kg), accomplished within one hour of treatment. The scientific significance of this work lies in its discovery of polyacrylamide’s ability to retain moisture within a nonpolar fuel matrix—a phenomenon not previously investigated in maritime fuel applications. The findings highlight the potential for further research into polymer–fuel interactions and non-chemical strategies for fuel enhancement. Economically, the proposed technology reduces dependence on costly chemical additives and energy-intensive drying processes, while environmentally, it improves combustion efficiency and lowers emissions of hydrocarbons (HC), carbon monoxide (CO), and smoke. Overall, the results introduce a novel, sustainable, and practical process for improving maritime fuel quality, while supporting compliance with increasingly stringent regional and global environmental regulations. Full article

Hydrogen fuel presents a promising pathway for achieving long-term decarbonization in the maritime sector. However, its use in diesel engines introduces challenges due to high reactivity, leading to increased NOx emissions and combustion instability. The aim of this study is to identify settings so that the investigated engine operates with 60% hydrogen energy fraction at high load through CFD modelling. The model is utilized to simulate a four-stroke, 10.5 MW marine engine at 90% load, incorporating 60% hydrogen injection by energy at the engine intake port. The CFD model is verified using experimental data from diesel operation of the marine engine and hydrogen operation of a light-duty engine. The engine performance was determined and detailed emissions analysis was conducted, including NO, NO₂, HO₂, and OH. The findings indicate a substantial rise in NOx emissions as opposed to diesel operation, due to elevated combustion temperatures and increased residence time at elevated temperature of the mixture in-cylinder. The presence of HO₂ and OH highlights critical zones of combustion, which contribute to operational stability. The novelty of this study is supported by the examination of the high hydrogen energy fraction, the advanced emissions analysis, and the insights into the emissions–performance trade-offs in hydrogen-fueled dual-fuel marine engines. The results offer guidance for the development of sustainable hydrogen-based marine propulsion systems. Full article

Selecting an appropriate Multi-Criteria Decision-Making (MCDM) algorithm for optimizing marine diesel engine operation presents a complex challenge due to the diversity in mathematical formulations, normalization schemes, and trade-off resolutions across methods. This study systematically evaluates fourteen MCDM algorithms, which are grouped into five primary methodological categories: Scoring-Based, Distance-Based, Pairwise Comparison, Outranking, and Hybrid/Intelligent System-Based methods. The goal is to identify the most suitable algorithm for real-time performance optimization of two stroke marine diesel engines. Using Diesel-RK software, calibrated for marine diesel applications, simulations were performed on a variant of the MAN-B&W-S60-MC-C8-8 engine. A refined five-dimensional parameter space was constructed by systematically varying five key control variables: Start of Injection (SOI), Dwell Time, Fuel Mass Fraction, Fuel Rail Pressure, and Exhaust Valve Timing. A subset of 4454 high-potential alternatives was systematically evaluated according to three equally important criteria: Specific Fuel Consumption (SFC), Nitrogen Oxides (NO_x), and Particulate Matter (PM). The MCDM algorithms were evaluated based on ranking consistency and stability. Among them, Proximity Indexed Value (PIV), Integrated Simple Weighted Sum Product (WISP), and TriMetric Fusion (TMF) emerged as the most stable and consistently aligned with the overall consensus. These methods reliably identified optimal engine control strategies with minimal sensitivity to normalization, making them the most suitable candidates for integration into automated marine engine decision-support systems. The results underscore the importance of algorithm selection and provide a rigorous basis for establishing MCDM in emission-constrained maritime environments. This study is the first comprehensive, simulation-based evaluation of fourteen MCDM algorithms applied specifically to the optimization of two stroke marine diesel engines using Diesel-RK software. Full article

Addressing IMO 2020 compliance, this study investigates marine fuel oil production from hydrotreated residues, focusing on mitigating excessive total sediment potential (TSP) caused by over-hydrotreatment. This study systematically investigates the impact of blending ratios of Fluid Catalytic Cracking (FCC) slurry oil with Residue Desulfurization (RDS) heavy oil on TSP, colloidal stability, and asphaltene structure evolution. Techniques such as XRD, SEM, and XPS were employed to analyze the structural changes in asphaltenes during the TSP exceeding process. The results indicate that as the FCC slurry oil blending ratio increases, TSP in the blended oil initially rises and then decreases. The peak TSP value of 0.41% occurs at a 10% FCC slurry oil blending ratio, primarily due to high-saturation hydrocarbons in RDS heavy oil disrupting the colloidal stability of asphaltenes in FCC slurry oil. When the blending ratio reaches 25%, TSP significantly decreases to 0.09%, attributed to the solubilizing effect of high aromatic compounds in the FCC slurry oil on the asphaltenes. The ω(Asp)/ω(Res) ratio mirrors the TSP trend, and the colloidal solubilizing capacity of asphaltenes increases with the blending ratio. Asphaltenes in RDS heavy oil exhibit a spherical structure, whereas those in FCC slurry oil show a layered structure. The precipitated asphaltenes in the blends primarily result from the aggregation of asphaltenes in FCC slurry oil, with heteroatoms (N, S, O) mainly originating from RDS heavy oil asphaltenes. During the early stage of blending, TSP formation is dominated by FCC slurry oil asphaltenes, but increasing the aromatic content in the system can significantly reduce TSP. This work provides theoretical and technical support for optimizing marine fuel blending processes in petrochemical enterprises. Full article

This research has successfully addressed the technical challenge of generating nanobubbles in diesel fuel, which inherently lacks hydrophilic structures and charged ions, enabling the effective production of high-concentration nanobubble diesel fuel. This breakthrough lays a solid foundation for subsequent research into the combustion performance and combustion mechanism of high-concentration nanobubble fuels. Furthermore, it holds promising potential to advance high-concentration nanobubble fuel as a viable new type of energy source. A specialized device was designed to generate nanobubble-embedded diesel, and particle tracking analysis with n-hexadecane dilution was employed to quantify nanobubble concentration. The results demonstrate that the nanobubble concentration in diesel increases with both circulation time and pressure, reaching up to 5 × 10⁸ ± 3.1 × 10⁷ bubbles/mL under a pressure of 2.5 MPa. Stability tests indicate an initial rapid decay (50% reduction within one week), followed by a slower decline, which stabilizes at 4.5 × 10⁷ ± 3.13 × 10⁶ bubbles/mL after two months. Notably, nanobubble concentration has a minimal impact on the density and viscosity of diesel but slightly decreases its surface tension. This study presents a feasible method for preparing high-concentration nanobubble diesel, which lays a foundation for investigating the combustion mode and mechanism of nanobubble diesel fuel. With the goal of enhancing combustion efficiency and reducing pollutant emissions, this work further paves the way for the application of high-concentration nanobubble diesel as a new energy source in fields including automotive, marine, and aerospace industries. Full article

Ammonia is emerging as a promising zero-carbon marine fuel due to its high hydrogen density, low storage pressure, and long-term stability, making it well-suited for supporting sustainable maritime energy systems. However, its adoption introduces serious safety challenges, as its toxic, flammable, and corrosive properties pose greater risks than many other alternative fuels, necessitating rigorous risk assessment and safety management. This study presents a comprehensive investigation of potential ammonia leakage scenarios that may arise during the fuel gas supply process within confined compartments of marine vessels, such as the fuel preparation room and engine room. The simulations were conducted using FLACS-CFD V22.2, a validated computational fluid dynamics tool specialized for flammable gas dispersion and explosion risk analysis in complex geometries. The model enables detailed assessment of gas concentration evolution, toxic exposure zones, and overpressure development under various leakage conditions, providing valuable insights for emergency planning, ventilation design, and structural safety reinforcement in ammonia-fueled ship systems. Prolonged ammonia exposure is driven by three key factors: leakage occurring opposite the main ventilation flow, equipment layout obstructing airflow and causing gas accumulation, and delayed sensor response due to recirculating flow patterns. Simulation results revealed that within 1.675 s of ammonia leakage and ignition, critical impact zones capable of causing fatal injuries or severe structural damage were largely contained within a 10 m radius of the explosion source. However, lower overpressure zones extended much further, with slight damage reaching up to 14.51 m and minor injury risks encompassing the entire fuel preparation room, highlighting a wider threat to crew safety beyond the immediate blast zone. Overall, the study highlights the importance of targeted emergency planning and structural reinforcement to mitigate explosion risks in ammonia-fueled environments. Full article

Marine biofouling, the process of marine microorganisms, algae, and invertebrates attaching to and forming biofilms on ship hulls, underwater infrastructure, and marine equipment in ocean environments, severely impacts shipping and underwater operations by increasing fuel consumption, maintenance costs, and corrosion risks, and by threatening marine ecosystem stability via invasive species transport. This study reports the development of a hydrogel-metal-organic framework (MOF)-quorum sensing inhibitor (QSI) antifouling coating on 304 stainless steel (SS) substrates. Inspired by mussel adhesion, a hydrophilic bionic hydrogel was first constructed via metal ion coordination. The traditional metal ion source was replaced with a zeolitic imidazolate framework-8 (ZIF-8) loaded with 2-(5H)-furanone (HF, a QSI) without altering coating formation. Physicochemical characterization using Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), the Brunauer–Emmett–Teller (BET) method, and the diffraction of x-rays (XRD) confirmed successful HF loading into ZIF-8 with intact crystal structures. Antifouling tests showed HF@ZIF-8 enhanced antibacterial inhibition against Staphylococcus aureus (97.28%) and Escherichia coli (>97%) and suppressed Chromobacterium violaceum CV026 pigment synthesis at 0.25 mg/mL (sub-growth concentration). The reconstructed PG/PVP/PEI/HF@ZIF-8 coating achieved 72.47% corrosion inhibition via synergistic anodic protection and physical shielding. This work provides a novel green approach for surface antifouling and drag reduction, highlighting MOF-loaded QSIs as promising additives to enhance the antifouling performance of hydrogel coatings, anti-corrosion performance, and QSI performance for sustainable marine engineering applications. Full article

With the long-term operation of ships, the performance of marine diesel engines gradually declines due to the wear of internal moving components, increasing the risk of potential failures. Fuel consumption is a critical indicator for assessing engine operating conditions, and accurately predicting baseline fuel consumption under normal operating conditions is essential for evaluating ship energy efficiency and conducting fault diagnosis. To address common issues in marine engine operational data, such as noise pollution, missing values, inconsistent scales, and feature redundancy, a Diesel Engine Data Enhancement and Optimization Framework (DEOF) was developed to systematically improve data quality. Furthermore, to overcome the limitations of existing models, such as insufficient prediction accuracy and poor stability under complex operating conditions, a Meta-learning Diffusion Residual Attention Network (MD-RAN) is proposed. This approach leverages the strengths of diffusion models in nonlinear generative modeling, integrates meta-learning mechanisms to enhance task adaptation speed, employs multi-head attention modules to strengthen feature extraction, and incorporates dynamic residual connections to improve training stability and flexibility. The data used in this study were collected from real-world operations of ocean-going vessels, ensuring high representativeness. This paper systematically benchmarks the proposed model with the traditional learning model. The results are verified to be effective. The MD-RAN algorithm is significantly better than the original model in terms of prediction accuracy, stability, and nonlinear expression ability. The R² value can reach 0.9853, and the RMSE and MAE are as low as 1.5801 and 1.1879, respectively. Its feasibility will be further evaluated in practical applications in the future. This study not only provides a systematic data-driven modeling framework, offering technical insights for constructing high-quality datasets, but also establishes a novel generative modeling approach for marine diesel engine fuel consumption prediction, providing robust support for intelligent engine maintenance and energy efficiency optimization. Full article

Brazil has emerged as one of the global leaders in adopting renewable energy, standing out in the implementation of onshore wind energy and, more recently, in the development of future offshore wind energy projects. Onshore wind energy has experienced exponential growth in the last decade, positioning Brazil as one of the countries with the largest installed capacity in the world by 2023, with 30 GW. Wind farms are mainly concentrated in the northeast region, where winds are constant and powerful, enabling efficient and cost-competitive generation. Although in its early stages, offshore wind energy presents significant potential of 1228 GW due to Brazil’s extensive coastline, which exceeds 7000 km. Offshore wind projects promise greater generating capacity and stability, as offshore winds are more constant than onshore winds. However, their development faces challenges such as high initial costs, environmental impacts on marine ecosystems, and the need for specialized infrastructure. From a sustainability perspective, this article discusses that both types of wind energy are key to Brazil’s energy transition. They reduce dependence on fossil fuels, generate green jobs, and foster technological innovation. However, it is crucial to implement policies that foster synergy with green hydrogen production and minimize socio-environmental impacts, such as impacts on local communities and biodiversity. Finally, the article concludes that by 2050, Brazil is expected to consolidate its leadership in renewable energy by integrating advanced technologies, such as larger, more efficient turbines, energy storage systems, and green hydrogen production. The combination of onshore and offshore wind energy and other renewable sources could position the country as a global model for a clean, sustainable, and resilient energy mix. Full article

Methanol has garnered attention as a promising alternative fuel for marine engines due to its high octane number and superior knock resistance. However, methanol-fueled engines face cold-start challenges under low-temperature conditions. Laser ignition technology, an emerging ignition approach, shows potential to replace conventional spark ignition systems. This study investigates the effects of laser ignition on combustion and emission characteristics of direct-injection methanol engines based on methanol fuel combustion mechanisms using the AVL-Fire simulation platform, focusing on optimizing key parameters, including ignition energy, longitudinal depth, and lateral position, to provide theoretical support for efficient and clean combustion in marine medium-speed methanol engines. Key findings include an ignition energy threshold (60 mJ) for methanol combustion stability, with combustion parameters (peak pressure, heat release rate) stabilizing when energy reaches ≥80 mJ, recommending 80 mJ as the optimal energy level (balancing ignition reliability and energy consumption economy). Laser longitudinal depth significantly influences flame propagation characteristics, showing a 23% increase in flame propagation speed at 15 mm depth and a reduction of unburned methanol mass fraction to 0.8% at the end of combustion. Full article