Knowledge of the effects of low/zero carbon green fuels on the performance of marine gas turbine-based propulsion systems is necessary for the decarbonization of gas-turbine powered ships. This work presents a general methodology to model an aeroderivative gas turbine-based marine propulsion system with some unique features. The gas turbine model is derived from a systematic search of discrete points of high-resolution component maps. Genetic algorithms (GA) have been used to auto-scale generic component maps to the known design point. This enables iterative re-scaling to calibrate parasitic losses and to optimize map selection. The gas turbine model is coupled to a data-based drive train/propeller model and emission model to predict ship speed and CO/CO 2 /NO x emissions for any given fuel flow rate. The integrated model was used to predict the performance of an Arleigh Burke class (DDG 51) destroyer over a 200 h, 2548 nautical mile trajectory with four different fuels: F76 Marine diesel, Liquid Hydrogen, Methanol and Liquefied Natural Gas. Predicted energy per mile and ship range were largely dependent on the tradeoff between energy density and gravimetric density of the fuels. The integrated model and aggregated data is publicly available and can be a useful tool to analyze or design marine decarbonization technologies.
A novel engine type well suited for operation with hydrogen or gaseous fuels is presented offering a viable two-stroke engine solution for ultra-low emissions. The stepped piston engine presented completely separates the lubrication and air scavenging systems and operates at significantly lower oil consumption levels than conventional two-stroke engines. The unique piston and crossover design provides separation of the hydrogen zones from the critical engine functional areas thereby minimizing or eliminating the corrosion problems observed from conventional hydrogen engines when left standing. Computational fluid dynamics using one dimensional code has confirmed the expectations for ultra-low oxides of nitrogen emission and elimination of other emissions when operating on hydrogen with specific power output of 51.7 kW/l simulated. Hydrogen model predictions indicated a minimum full load SFC of 0.103 kg/kWh at 3500 rpm and full load stoichiometric NOx emissions from 1000 to 5000 rpm of 4–543 ppm. Modelling and experimental performance using standard neat gasoline fuel is also presented and discussed. The experimental gasoline engine produces 55 kW at 5500 rpm and a minimum full load gasoline SFC of 0.304 kg/kWh at 2500 and 5000 rpm compared with 0.263 kg/kWh at 3500 rpm modelled using indolene. The maximum power modelled using indole was 49.4 kW at 5000 rpm.
Underwater object detection, a fundamental yet challenging task in ocean engineering, has been greatly advanced by the rapid development of deep learning. This paper provides a comprehensive review of recent deep learning–based methods for underwater object detection. Existing approaches are systematically categorized into seven groups: transfer of general object detection methods, feature fusion, image enhancement, feature enhancement, domain generalization, transformer-based models, and other emerging techniques. Representative algorithms within each category are analyzed and compared. Furthermore, the paper introduces commonly used evaluation metrics for both object detection and image quality assessment, and discusses four major challenges in the field: image feature degradation, variability in object scales, generalization capability, and the adaptability of models to robotic platforms. In addition, publicly available underwater datasets are reviewed and the performance of various methods on these datasets is summarized. Finally, based on the above synthesis, potential research directions and future perspectives for underwater object detection are highlighted. Compared to previous review articles, this paper proposes a classification scheme based on the unique characteristics of the underwater environment. Starting from the specific challenges being addressed, it systematically summarizes and categorizes existing methods, providing valuable insights for future methodological improvements. The article not only describes various techniques but also conducts a systematic comparison of representative literature through multiple structured tables. It reviews emerging technologies such as Transformer, Mamba, multi-modal fusion, and weakly-supervised learning, reflecting the latest trends in the field. Particularly, it introduces the application of Mamba in underwater image enhancement and object detection. Furthermore, it systematically summarizes commonly used evaluation metrics for object detection as well as underwater image quality assessment metrics.
This review presents a comprehensive examination of ship energy efficiency strategies in the context of maritime decarbonization imperatives. It synthesizes current technological advancements, regulatory frameworks, and fuel alternatives that aim to reduce greenhouse gas (GHG) emissions in alignment with international mandates, particularly those issued by the International Maritime Organization (IMO) and regional bodies. The review categorizes the evaluated measures into seven principal domains: internal combustion engines and alternative fuels, carbon capture and storage (CCS) systems, cold ironing (shore power connectivity), waste heat recovery systems (WHRS), air lubrication systems (ALS), solar and wind energy applications, integration of batteries and fuel cells, nuclear energy and other technologies. Each category is critically assessed in terms of its technological maturity, retrofit potential, operational feasibility, economic viability, and environmental impact. The analysis reveals that while mature technologies like WHRS and dual-fuel engines offer short-term benefits, more disruptive innovations such as fuel cells and hybrid propulsion systems remain constrained by cost, infrastructure, and safety concerns. The review highlights the growing prominence of hybrid and integrative configurations, such as WHRS coupled with CCS or wind-assisted propulsion integrated with route optimization algorithms, as promising pathways for maximizing efficiency and reducing emissions. Ultimately, this review serves as a decision-support resource for ship owners, marine engineers, and policymakers. By mapping out the trade-offs and synergies among diverse technologies, it provides a nuanced foundation for aligning strategic investments with evolving decarbonization targets and operational realities in the global maritime sector.
To address the problem of excessive swing amplitude and potential safety hazards associated with traditional A-frame cranes during operation, this study proposes a cable-driven wave compensation system. Based on this system, comprehensive kinematic and dynamic models were established to analyze the swing characteristics of the payload. First, the inverse kinematics model of the compensation device was derived using the vector loop closure method, and the system dynamics models were formulated through both the Newton-Euler and Lagrangian approaches. Then, under practical operating conditions, MATLAB-ADAMS co-simulation was conducted to investigate the spatial motion of the lifting point and the variation in the in-plane and out-of-plane swing angles of the payload. Combined with a cable tension distribution algorithm, ADAMS was employed to optimize abnormal tension values, yielding tension distribution curves consistent with realistic conditions and thereby validating the accuracy of the proposed models. Meanwhile, the anti-sway performance of the device under different operating conditions was verified, and the results demonstrated that the proposed system effectively suppresses payload swing and exhibits excellent motion stabilization performance. Finally, several key factors influencing the swing amplitude were analyzed, and swing characteristic curves were extracted to clarify the effects of each factor. Based on these findings, practical operational guidelines with engineering relevance were proposed. The outcomes of this study provide a theoretical foundation for subsequent research on cable tension setting and contribute to the structural optimization and control system development of wave compensation devices.
This paper investigates the role of accelerated ageing tests on the mechanical properties of two affordable glass fibre-reinforced polymers. The study considers a biaxial (+/- 45) stitched E-glass and a twill weave woven roving E-glass fabrics combined with an epoxy matrix. A set of mechanical tests is carried out to evaluate the impact, compression after impact, tensile, flexural and interlaminar fracture behaviour of both materials for dry and aged specimens, following the recommendations of established standards. The novelty of this paper lies in the evaluation of the degradation of the mechanical properties of affordable marine composites under accelerated ageing tests for wave energy purposes. The results demonstrate that these materials can withstand long-term exposure to the harsh ocean environments where wave energy converters are deployed. While the stitched fabric laminates exhibited a more ductile response, the woven roving laminates were brittle but demonstrated a greater capacity to maintain their integrity against low-velocity impacts. Lastly, recommendations for implementing these materials for specific components of wave energy converters are provided, based on both mechanical test results and affordability.
A ship's safety domain is a principal element in conflict detection and avoidance manoeuvres and consequently collision risk. Conflict detection depends on the ability to predict the intrusion of another vessel into the safety domain of the own-ship. To resolve a conflict the own-ship must manoeuvre so that the intruder remains outside this domain. In this study the shape, size and realisation of a safety domain on the North Sea are examined using Automatic Identification System (AIS) data collected from the Dutch sector of the North Sea (March-May 2014). In this study, encounters between ships over 45 m in length and travelling at 5-25 knot were analysed. Five hypotheses were tested: (1) the safety domain is elliptical rather than circular; (2) the domain size is a function of the ship speed; and (3) ship size has no effect on domain size when distances are measured hull-to-hull; (4) safety domains are created using minimal course changes; (5) those course changes are based on CPA calculations. The empirical results confirm that domains can be described by ellipses. The major-axis length increases with speed while the minor-axis is independent of speed, and ship size does not influence domain size as defined significantly. Analysis of manoeuvring behaviour shows that bridge teams seem to rely on ARPA-derived CPA and TCPA calculations, initiating avoidance manoeuvres typically between 600 and 1800 s before the predicted closest point of approach. Most course changes are modest and aim to maintain a CPA that corresponds to the empirically derived elliptical domain. The study suggests that an elliptical safety domain can be defined for vessels operating in deep-sea conditions. Such a domain would provide a practical basis for improving conflict-detection algorithms, decision-support tools for bridge teams, and autonomous-ship navigation systems while remaining consistent with the COLREGs.
Waste heat recovery from marine engines plays an important role in reducing harmful emissions into the atmosphere. This study presents the thermal, economic and environmental analyses of a thermoelectric power generation system for a ferry. In this study, the temperature and voltage distributions on the thermoelectric module are obtained by the COMSOL Multiphysics software for thermoelectric modules of TGMT-19W-4V and TE-MOD-22W-7V-56 at different exhaust gas temperatures for various engine loads and the sea water temperature of 20 degrees C. The results indicate that the maximum electrical power of 3 kW is produced for the TE-MOD-22W-7V-56 at the engine load of 100%, while the minimum electrical power of 0.44 kW is produced for the TGMT-19W-4V at 25% engine load. The amortization periods of the thermoelectric power generation system are 16.5 and 9.4 years for TGMT-19W-4V and TE-MOD-22W-7V-56, respectively. The maximum and minimum annual reduction of emissions are obtained for CO2 and CO, respectively, for both thermoelectric modules. These are 4084 kg of CO2 for TGMT-19W-4V and 9085 kg of CO2 for TE-MOD-22W-7V-56 and 0.7 kg of CO for TGMT-19W-4V and 1.5 kg of CO for TE-MOD-22W-7V-56.
Fault detection in Autonomous Underwater Vehicles (AUVs) is crucial for ensuring their safe and efficient operation, especially in challenging underwater environments. In this study, we investigate traditional machine learning models to detect common AUV conditions, Add Weight, Pressure Gain Constant, PropellerDamageBad, and PropellerDamageSlight, using a comprehensive dataset of sensor readings and control signals. First, the data were segmented into four time windows (20, 50, 100, and 150 s) to address dimensionality and optimize model performance. To complement these time-series features, we then extracted basic descriptive statistical features (mean, standard deviation, min/max, 25th/50th/75th percentiles, skewness, and kurtosis) for each window and retrained our classifiers on this enriched feature set. Among all models, the Cubic SVM achieved the highest test accuracy of 96.7%. Finally, we applied SHapley Additive exPlanations (SHAP) to interpret the Cubic SVM's predictions and identify the top-10 features driving correct classification for each class. Our results demonstrate that the Cubic SVM not only delivers a balanced trade-off between accuracy and computational efficiency, suitable for real-time, resource-constrained deployment, but also, through SHAP, yields actionable insights into the most discriminative sensor and control-signal statistics for each AUV condition. Future work will explore online adaptation and further model compression to enhance deployment in fully autonomous missions.
This study examines the relationship between ship traffic and ambient air pollutant concentrations in Quintero Bay, Chile, an industrial coastal area characterized by intense port activity. The analysis integrates air quality measurements from the national monitoring network (SINCA) with vessel movement data derived from the AIS, combined with advanced time-frequency analysis techniques. Unlike traditional emission inventories, which aim to quantify emissions at the source, SINCA provides real-time ambient pollutant concentrations expressed in & micro;g/m3 and ppb. Therefore, the objective of this study is not to directly estimate ship emissions, but to evaluate how variations in maritime activity co-vary with observed pollutant levels at air quality monitoring stations. The investigation focuses on pollutants commonly associated with shipping activities, including PM10 and PM2.5, NOx, SO2, and CO. A detailed characterization of the vessel fleet operating in the study area was performed using both static and dynamic AIS data. This included ship type classification, estimation of main engine power based on gross-tonnage models, and calculation of engine load distributions derived from AIS-reported vessel speeds. Although these parameters allow the estimation of emission factors, the present work emphasizes identifying temporal associations between ship movements and ambient pollutant concentrations rather than quantifying emissions. Additionally, pollution roses and Conditional Probability Functions (CPF) were used to evaluate the directional origin of high-concentration episodes in relation to prevailing wind conditions. The results show that several episodes of elevated NOx, SO2, and PM10 concentrations exhibit significant coherence with ship activity, particularly at daily time scales influenced by local meteorology. Among the analyzed pollutants, PM10 displays the strongest and most recurrent association with maritime traffic, highlighting the influence of port operations on air quality in Quintero Bay.
The complex and uncertain steering dynamics of ships present significant challenges to traditional model-based controlstrategies, particularly under environmental disturbances and mechanical degradation. This study proposes an active dis-turbance rejection control scheme for ship course keeping, integrating a modified Smith predictor and an ESO to esti-mate and compensate for total disturbances in real time. Sea trial data from the training vesselYukunindicate thatexperienced operators naturally employ discrete steering actions at 7.90-14.87 s intervals, contrasting with conventionalautopilots that continuously output control signals for fine-tuning adjustments. To replicate this discrete control beha-vior, this study integrates a ZOH mechanism with holding timeuinto the ADRC framework, reducing control frequencywithout compromising accuracy. Testing across Sea States 6-9 demonstrates robust performance. With optimal holdingtimeu= 10-15 s, the controller maintains65 degrees heading accuracy while reducing steering operations by 43%-58%compared to high-frequency control. The controller maintains performance under650% parameter variations withoutgain scheduling. Software-only implementation enables immediate deployment on existing vessels, providing significantadvantages for commercial fleet operations
Control systems enable automatic monitoring and ensure operational security. Optimizing the control system can effectively reduce human errors, enhance production efficiency, and significantly lower costs. To further improve the operation and maintenance reliability of the subsea oil and gas production control system, this paper proposes two optimized design schemes, analyzes the reliability influencing factors of the subsea control system, and compares three configurations: serial, multi-machine hot standby redundancy, and cross-hot standby redundancy. The problem of configuration selection for subsea control systems is addressed. The feasibility of the analysis results is verified through dynamic Bayesian network simulation. This research directly addresses concerns related to marine energy and offshore engineering. By referring to the comparative reliability results for subsea control systems in this paper, designers can select appropriate configurations and better optimize operation and maintenance costs. Therefore, the work provides a scalable and cost-effective reference for the development of subsea control system configurations.
Fracture of the connecting rod in marine diesel engines results in catastrophic mechanical failure, immediate loss of propulsion, and extensive internal damage. While fatigue and overload are often cited, the role of maintenance deviation remains underexplored, particularly in the context of failure prevention systems. This study reconstructs a real-world incident of connecting rod rupture in an ISOTTA V1312 engine, directly linked to miscalibrated intake valve lash. A multi-tiered diagnostic approach was used, combining finite element analysis of combustion and inertial loads, dynamic simulation of tappet oscillation under excessive clearance, and scanning electron microscopy of fractured cap bolts. Results demonstrate that abnormal valve lash destabilized tappet motion, triggering a cascading failure sequence involving bracket fracture, piston-valve collision, and progressive valvetrain misalignment. Fractographic analysis confirmed ductile fracture due to impact in the cap bolts, with no evidence of fatigue. This is the first validated reconstruction directly connecting a single maintenance deviation to a multi-stage structural collapse. The findings emphasize the need to integrate empirical failure markers into safety diagnostics such as Failure Mode, Effects, and Criticality Analysis (FMECA). In-cylinder pressure monitoring is further highlighted as a vital tool for early detection of valvetrain dynamics anomalies.
To achieve high-precision infrared thermography (IRT) inspection of composite hull structures, it is essential to understand how fabric characteristics influence IRT performance. This study examines the effects of two fabric combinations-chopped strand mat (CSM) as a single-fabric material and a combination of CSM and woven roving (WR)-on the IRT behavior of glass fiber reinforced plastic (GFRP) hull laminates. Specimens with artificial defects were fabricated using the hand lay-up method. IRT experiments were performed under varying heating times (5, 7, and 10 min) and temperatures (60 degrees C, 65 degrees C, and 70 degrees C), and the results were analyzed using statistical techniques. For the CSM + WR combined-fabric laminates, optimal defect detection occurred at 60 degrees C, whereas for the CSM single-fabric laminates, a higher temperature of 70 degrees C was required. This variation indicates that CSM-only laminates pose greater challenges for IRT-based inspection. The findings underscore the importance of fabric combination in determining appropriate IRT conditions for effective defect detection in GFRP hull structures.
Current knowledge regarding the assessment of forward and sideways accelerations on human safety onboard the high-speed craft (HSC) remains limited, and most conventional shock mitigation seats for these vessels are designed primarily to mitigate vertical accelerations. This study analyzes recorded accelerations onboard a high-speed craft (HSC) in multiple directions to evaluate the effects of forward, sideways, and vertical accelerations on human health and comfort in accordance with ISO 2631-1:1997. To address the shortcomings of conventional seat systems, this research proposes a shock mitigation seat model that incorporates both forward and vertical suspension systems. A mathematical model is developed to predict the seat's ability to reduce multidirectional acceleration exposure, with an emphasis on vertical acceleration-the direction with the highest intensity-and the forward direction, which is often overlooked in existing designs. The results demonstrate that combining forward and vertical suspension systems in seat design can significantly reduce health and comfort risks associated with accelerations in these directions. This study provides a foundation for future innovations in HSC seat design and encourages the integration of forward suspension systems to enhance occupant safety and comfort.
The study focuses on the wave interactions with a pile-restrained H-shaped breakwater in the presence of different configurations of seawall. The presence of ellipse shaped seawall (ESS), vertical cum ellipse seawall (VES), inclined cum ellipse seawall (IES), stepped cum ellipse seawall (SES) and circular cum parabolic seawall (CPS) are considered to analyse the performance of H-shaped breakwater. The study is performed to examine the variations of the reflection coefficient of seawall and different structural parameters such as flange width, web draft of the H-shaped breakwater and relative distance between the structure and the seawall using multi-domain boundary element method (MDBEM). The hydrodynamic parameters such as wave the reflection coefficient, wave run-up on the seawall and wave force on the breakwater and seawall are evaluated considering the boundary and edge conditions for fluid-structure interfaces, rigid horizontal seabed, free water surface region, input boundary region, and partially reflecting seawall. The validation of the numerical approach using MDBEM approach is performed with the results available in the literature. In addition, the convergence of the boundary elements is also conducted for the accuracy of the numerical results. The analysis of the hydrodynamic effects of different seawalls interacting with breakwaters offers important insights into coastal engineering. The study also focuses on the effect of wave energy reflection, wave dynamics and overall stability of coastal defensive systems for different configurations and designs of the seawall.
To address the large-deformation problem that may occur in a drill string-riser system under internal solitary waves (ISWs), a physical model is developed based on Hamilton's principle, in which the coupled effects of ISWs, the drill string, drilling fluid, and the drilling riser are comprehensively considered. To accurately describe the post-collision displacement evolution of the drill string and the riser, an iterative collision-updating method is introduced for correction. The results indicate that the presence of the drill string can suppress the increase in riser displacement, but it increases the Von Mises stress. The collision loads are mainly concentrated in the upper section of the riser and shift with variations in environmental parameters. Parametric analysis shows that increasing the tension ratio can reduce displacement while increasing the equivalent stress, whereas changes in the weight on bit (WOB) do not significantly alter the motion trend of the drilling riser. The wave amplitude and the pycnocline depth are identified as key environmental factors. When eta 0 increases from 90 to 120 m, the maximum collision force increases from 814 to 1241 N. When d u increases from 100 to 400 m, the maximum displacement increases from 5.684 to 12.525 m, while the maximum collision force decreases from 1487 to 1064 N.
In complex marine environments, ship fuel consumption is jointly affected by hull motion, propulsion load, and wind-wave conditions, while operational data are often intermittent and non-stationary, which makes accurate prediction challenging. Based on full-scale data from a container ship, this study develops a multi-source data-driven framework that fuses AIS navigation information, onboard sensor measurements, and ERA5 metocean reanalysis on a unified spatiotemporal grid. Sailing-state filtering and fixed-length sliding windows are used to retain continuous propulsion segments, where multi-step multi-source features form input sequences and fuel consumption at the window end is taken as the prediction target. An improved CNN-BiLSTM-Attention model is then constructed: convolutional layers extract local "sea state-operating condition" patterns, BiLSTM captures temporal dependencies, and a temporal attention mechanism adaptively weights different time steps. Non-negativity of fuel consumption and power/speed consistency are embedded into the loss function as physical constraints. Ablation studies and wind-wave regime analyses show that the proposed model achieves R2 = 99.28%, RMSE = 0.0178 t/h, and MAPE = 1.35%, and that removing environmental or engine-room features significantly degrades accuracy, while attention weight visualization confirms the model's interpretability, thereby confirming both the effectiveness and interpretability of the improved CNN-BiLSTM-Attention model for fuel consumption prediction under complex sea conditions.
As container ships continue to grow in size, the instability of stacks caused by lashing system failures under dynamic sea conditions has become a primary cause of cargo losses at sea. However, current classification society regulations for the research on dynamic failure mechanisms in lashing systems remain insufficient, particularly concerning the nonlinear response characteristics under multi-stack coupling. A multi-stack dynamic test system, constructed based on Froude similarity principles, is employed to analyze the dynamic responses of displacement and acceleration within the system's internal structure. The focus lies on the evolution characteristics of collision energy dissipation between stacks, load transfer path reconstruction, and nonlinear dynamic responses during the progressive failure of lashing rods. The findings indicate that nonlinear factors such as twist-lock gaps, corner casting contact, and friction can induce phase differences in motion between double-stacks, leading to reduced acceleration coherence between adjacent stacks. Lashing failure further exacerbates asymmetric collisions between double-stacks, resulting in complex coupling features in top container displacement and acceleration. Additionally, internal lashing failure shifts load distribution from vertical transmission to lateral diffusion, while external lashing failure is more likely to trigger lateral load transfer within, causing the dynamic tensile force in bottom lashing rods to enter a high-risk zone, thereby initiating a chain reaction of corner casting sliding-separation-collision. This research provides quantitative evidence for dynamic failure warning and redundant lashing design in multi-stack securing systems, addressing gaps in current standards regarding the assessment of dynamic failure modes.
This paper proposes a composite observer-based anti-disturbance and fault-tolerant stabilization for three-degree-of-freedom (3-DOF) sea launch platforms with actuator faults and input saturation. This composite observer-based anti-disturbance and fault-tolerant stabilization control scheme is built through integrating a disturbance observer and a fault observer with the backstepping technique together with an actuator saturation compensator and the robustifying term. The disturbance observer is utilized to provide on-line estimates of the time-varying disturbance in the ocean environment. The actuator fault observer is exploited to achieve the on-line fault estimations of actuator faults. The actuator saturation compensator is employed to attenuate the adverse effects of actuator saturation. The robustifying term is used to attenuate norm-bounded unmodeled dynamics. It is proved that the composite observer-based anti-disturbance and fault-tolerant stabilization controller can achieve the attenuation and rejection of disturbances and faults simultaneously. It is proved by illustrative simulations that the composite observer-based anti-disturbance and fault-tolerant stabilization control strategy can strongly stabilize the sea launch platform.
