Engineering

Abstract: Radar sensors, which enable the identification of the navigational situation and a preliminary assessment of collision risk, form the basis for safe ship control. This paper presents the author’s quantitative methods for assessing collision risk in the context of multi-ship navigation, and then synthesizes safe control methods. This study proposes four neural domain variants and three mathematical models of collision risk. Proprietary methods are presented: neural dynamic control (NDC) and game-based control (GC). An experimental comparison of these control methods is conducted using data from real-world navigation scenarios. Therefore, under favorable traffic conditions, the NDC method proves to be the most effective, while the GC method facilitates effective cooperative and non-cooperative management in situations of restricted ship traffic. The safe control methods proposed in this study will contribute to increased navigation safety, particularly in situations of high ship traffic density and challenging environmental conditions.

Abstract: Near-seabed contact operations with underwater hexapod robots can require one leg to execute a contact task, which reduces the stability of the remaining asymmetric five-legged support. To address this problem, this study proposes a five-legged asymmetric coordinated stability control method that integrates gait rhythm planning with attitude feedback. The method decouples the left middle leg from support, propulsion and CPG phase evolution to form a “5+1” asymmetric support base. This configuration reduces the periodic influence of task-induced disturbances on body balance. Meanwhile, a five-legged Hopf-CPG rhythm maintains continuous gait under asymmetric support. Low-bandwidth attitude feedback modulation is introduced between the CPG-generated foot trajectory and the inverse-kinematics input to balance attitude correction with foot-contact continuity. Full-degree-of-freedom underwater simulations in Webots show that, at a flow speed of 0.8 m/s, the method reduces combined attitude RMS by 41.52% relative to the no-feedback strategy. Relative to high-gain PD control, it reduces the RMS rate of change of the control output by 71.32%. These results indicate that the method improves input smoothness and compatibility with five-legged gait rhythms, with a moderate trade-off in transient attitude suppression. It therefore offers a coordinated approach to balancing attitude stability and gait continuity under asymmetric operation.

Abstract: Numerous studies indicate that a flapping-foil thruster installed at a ship’s bow can convert wave energy into propulsive power and reduce added wave resistance while improving dynamic stability. Building on prior research into the drag reduction mechanism of an elastic bow-flapping-foil system, this paper further compares its resistance reduction and motion response across three typical ship forms (DTMB 5415, KCS, and Wigley) under similar wave conditions. Using the ISIS-CFD solver in NUMECA software, the study simulates the ship coupled with a semi-active elastic flapping foil in head waves, analyzing the influences of spring stiffness, foil size, installation position, and encounter phase on system performance. Numerical results show effective wave energy harvesting, boosting propulsion and stability. Under optimized parameters, ship pitch and heave amplitudes decrease by up to 20.14%, resistance reduction reaches 9.60%, and DTMB 5415 achieves a comprehensive drag-reduction and thrust-increase efficiency of 31.39%. Further analysis reveals that thrust performance does not rise proportionally with spring stiffness, whereas drag and heaving reduction improve with increasing stiffness. The system performs best at a wavelength-to-ship-length ratio of 1.2 and a foil encounter phase of −90°. This work supports parameter optimization for such systems based on practical application scenarios and requirements.

Abstract: Submarine telecommunication cables carry over 99% of international data traffic yet remain persistently vulnerable to geophysical, anthropogenic, and oceanographic hazards. Existing risk assessment methods , GIS-based least-cost path analysis and cable-body condition monitoring , operate in isolation, cannot fuse heterogeneous multi-modal data, and yield neither uncertainty estimates nor physics-consistent predictions. We present MarineGuard-GNN, a physics-informed multimodal heterogeneous graph neural network that unifies four hazard modalities , bathymetric, oceanographic, vessel traffic, and seismic , in a single relational graph over four semantic node types and four typed relation edges. Three novel technical contributions distinguish the framework: (i) the Cross-Modal Spatiotemporal Tokenizer (CMST), which jointly encodes GEBCO bathymetric raster fields via a SatMAE-pretrained ViT-S and NOAA AIS vessel trajectories via a Transformer-XL into a unified 256-dimensional token space, addressing the modality-heterogeneity gap; (ii) a Physics-Informed Heterogeneous Graph Transformer with a differentiable Mohr–Coulomb geomechanical shear-stress regularization loss Lphys that prevents physically inconsistent risk assignments at steep bathymetric gradients; and (iii) a Bayesian Uncertainty-Aware Risk Head using Monte Carlo Dropout (K=50, p=0.3) to produce calibrated epistemic uncertainty maps for inspection prioritization. Under strict 4-fold geographic cross-validation across the Pacific, Atlantic, Indian, and Mediterranean basins using five publicly available datasets, MarineGuard-GNN achieves the highest mean AUC-ROC (0.7228±0.0665) and Average Precision (0.6418±0.1040) among five baselines. A Dijkstra-based spatial route optimizer reduces mean predicted fault risk by 0.0035 absolute on the Atlantic New York–UK corridor, avoiding one additional high-risk node at a distance overhead of only +7.4 km (+0.56%). All code, preprocessing pipelines, and datasets are publicly available.

Abstract: Ship path planning is a central challenge in autonomous navigation for unmanned surface vehicles and maritime autonomous surface ships. It is not simply a shortest-path problem, but a constrained sequential decision process that must reconcile collision risk, route efficiency, COLREGs compliance, vessel dynamics, and environmental uncertainty. Here we review the field through a unified framework based on planning scope, decision basis, and deployment requirements. We examine search- and sampling-based, geometric and rule-based, optimization-based, learning-driven, and hybrid methods, with particular emphasis on deep reinforcement learning for discrete decisions, continuous manoeuvring, multi-vessel interaction, and safety-oriented control. Representative studies are compared across objective and reward design, state representation, exploration and policy optimization, rule integration, disturbance modelling, simulation platforms, and operational validation. The synthesis identifies persistent barriers, including ambiguous rule formalization, partial observability, strategic coupling among vessels, inconsistent benchmarks, limited cross-scenario generalization, and insufficient full-scale validation. We further discuss priority directions in explicit safety constraints, digital twins, transfer and meta-learning, world models, scalable multi-agent coordination, and large-model-assisted mission reasoning. We argue that progress will depend less on further algorithmic proliferation than on integrated, verifiable architectures that combine data-driven adaptation with model-based structure, standardized evaluation, and staged real-world assurance.

Abstract: Since the heavy clutter seriously restricts the ability of radar to detect target, it is significant to build the target detector under heavy clutter. For practical situations without the secondary data or prior knowledge of target and clutter, this paper proposes a polarization-space-time detector. First, a general radar model is constructed for multiple pulses, multiple arrays, and multiple polarizations. Based on the theory of ternary hypothesis, the secondary data free (SDF) GLRT detector is proposed, which can maintain the constant false alarm probability (CFAR) in inhomogeneous clutter. Then, this paper proposes a matrix transform operator and an adaptive detection method using sliding window respectively, which do not need to know the steering vector of radar and the noncentral parameter of clutter in advance, so that the SDF-GLRT detector can adapt to different application scenarios. In addition, this paper optimizes the polarization waveform of the radar system by constructing a projection matrix, which can give the closed-form solutions of the optimal polarization and worst polarization, instead of relying on numerical solution. Finally, the performances of SDF-GLRT detector and other three detectors are compared by simulated and real data, which verifies that SDF-GLRT detector in this paper can still maintain superior performance in various clutter environments without secondary data.

Abstract: Monitoring the current technical condition of a marine internal combustion engine and diagnosing the causes of deviations of its operating parameters from reference values are important tasks for ensuring the efficient and safe operation of marine power plants and vessels in general. This paper investigates the theoretical founda-tions, methods, and practical implementation of a digital twin of a marine internal combustion engine as a tool for solving these tasks. The main requirements and stages of digital twin development are presented, including: calibration of the mathematical model; determination of the set of sensors and other input data obtained from the op-erating engine; identification of the current engine operating mode; definition of objec-tive functions characterizing deviations of engine operation from reference conditions; and automation of fault detection algorithms. In particular, modifications introduced into the mathematical model of engine operating processes are presented, allowing more flexible representation of fuel injection characteristics as well as automatic ad-justment of model parameters according to the identified engine operating mode. A fault detection method based on simulation modeling and the classical theory of design of experiments is proposed. The four-factor fractional factorial experiments were per-formed, followed by analysis of the obtained results using second-order polynomial regression equations. The results demonstrate that the proposed method provides cor-rect identification of engine faults, although the numerical values of the investigated factors are determined with a certain error. Therefore, further development of the proposed approach requires improvement of the mathematical model, formulation of explicit rules for selecting the investigated factors, and automation of fault identifica-tion methods under conditions of cycle-to-cycle variability of the engine working pro-cess and measurement uncertainties.

Abstract: This study validates the URANS k-ω SST turbulence model in OpenFOAM for simulating 2D flow around a fixed circular cylinder, a key benchmark for offshore structure design. Balancing accuracy and computational cost, the model was tested for laminar (Re=40) and subcritical turbulent (Re=10,000) regimes. Results showed excellent agreement with benchmarks: for laminar flow, a drag coefficient (Cd) of 1.54 and separation angle of 52.3°; for turbulent flow, a mean Cd of 1.15, a Strouhal number of 0.22 at x/D=2, and a separation angle of 86.5°. This confirms the model's reliability for predicting integral forces and vortex shedding in these regimes. However, the study also highlights the inherent limitations of the 2D domain due to its inability to resolve 3D anisotropic wake turbulence.

Abstract: The ship recycling industry experiences frequent accidents with severe consequences attributed to human and organizational factors. Existing human factors frameworks, including the Human Factors Analysis and Classification System (HFACS), provide comprehensive taxonomies for accident analysis, but their complexity and granularity pose challenges in low-resource, high-risk contexts such as ship dismantling yards. This paper presents the development of HFACS-SR (HFACS for Ship Recycling), a simplified human factors taxonomy tailored to the ship recycling sector, retaining the systemic insight of HFACS while enhancing usability for practitioners in shipbreaking yards. A participatory card-sorting study with 14 industry experts (safety officers, academics, regulators, supervisors, and an NGO representative) used 117 human factor codes derived from the SHIELD taxonomy, developed under the EU SAFEMODE project for aviation and maritime safety occurrences. Participants sorted the codes via KardSort, rated their relevance to ship recycling, and suggested modifications. Quantitative tiering identified 50 high-consensus codes. Qualitative refinement merged overlapping codes, promoted practitioner-identified gaps, and retained threshold-adjacent codes on evidential grounds, reducing the taxonomy from 117 to 53 codes across five levels. A new External Influences level captures regulatory, economic, and political pressures unique to ship recycling and absent from conventional HFACS. Inter-rater agreement was substantial (Fleiss' κ = 0.69). Plain language renaming further enhanced frontline usability. HFACS-SR preserves the multi-layered systemic perspective of HFACS while improving applicability in ship recycling, offering practitioners a clearer, context-specific framework for accident investigation and safety management.

Abstract: Autonomous inspection of ballast water tanks requires three-dimensional (3D) LiDAR-based simultaneous localization and mapping (SLAM) in Global Positioning System (GPS)-denied, geometrically repetitive interiors, where sensing, mapping, and control modules share a limited onboard memory budget. Graph SLAM backends that rely on sparse factorization can incur fill-in, increasing peak memory and limiting deployment on edge computers. The proposed architecture couples a robust hierarchical bundle adjustment frontend with a factorization-free Kaczmarz backend. The frontend combines residual-adaptive weighting, damped and bounded pose updates, soft fallback, local-map compression, and memory-aware keyframe control. The backend stores the whitened Jacobian in compressed sparse row (CSR) format and performs row-wise projections without explicitly forming the normal equations, a Cholesky factor, or a transpose cache. Evaluation used Norwegian University of Science and Technology (NTNU) Ballast Water Tank missions 1--3, containing 851, 1202, and 1084 LiDAR frames. Following robust local bundle adjustment and verified similarity alignment, translational root-mean-square errors were 0.080, 0.110, and 0.127m, corresponding to 0.137%, 0.144%, and 0.122% of the reference path lengths; archived baseline ratios ranged from 0.281% to 0.372%. The results support a numerical architecture that combines frontend stabilization, row-wise optimization, and memory-aware policies for resource-constrained marine inspection robots.

Abstract: Ship recycling is expanding in Nigeria with no dedicated statutory framework to govern it, creating a mismatch between a high-hazard industry and an underdeveloped regulatory environment. Although Nigeria ranks among the top ten emerging ship-recycling countries, the sector remains informally governed, with overlapping mandates, thin enforcement capacity, and fragmented risk-assessment practices. This study evaluates Nigeria's approach through a robustness lens, drawing on Rasmussen's socio-technical levels, Renn's integrative risk-governance model, and Hale's robustness criteria, with Hollnagel's Safety-II as a complementary, proactive perspective. The analysis combines documentary review, field observations across four recycling hubs (Lagos, Warri, Onne/Port Harcourt, and Calabar), and semi-structured interviews with fifteen stakeholders, including yard managers, regulators, workers and safety officers, and maritime experts, followed by a multi-stakeholder validation workshop. Of nineteen sub-criteria, only six are formally present, four are partially addressed, and nine are absent altogether, and even the elements that exist on paper are generic and weakly enforced. Field visits revealed ad hoc practices, hazardous working conditions, weak supervision, and little institutional learning. On this basis we propose a Nigeria-fit Robustness-Focused Risk-Governance Framework built on three pillars: multi-level safety oversight, an integrative risk-governance process, and enhanced mitigation strategies. It emphasises legal recognition, clearer accountabilities, interdisciplinary assessment, transparent risk-acceptance criteria, continuous monitoring, and feedback loops, with a phased implementation pathway. The study shows why robustness, not resilience, should be the organising principle for governing emergent high-hazard sectors in developing economies, and offers practical steps for strengthening institutional capacity in Nigeria's maritime domain.

Abstract: Liquefied natural gas (LNG) is increasingly used in maritime propulsion systems as a means to reduce atmospheric emissions. However, methane slip from dual-fuel engines remains a critical limitation due to the high global warming potential of methane. This study presents a comprehensive experimental assessment of greenhouse gas (GHG) emissions from a new-generation four-stroke dual-fuel engine installed on a cruise vessel and operating on both LNG and marine gas oil (MGO). Measurements were carried out during full-scale sea trials under real navigation conditions. Results show that methane slip remains strongly dependent on engine load, with low and stable values at medium-to-high loads (1.95 g/kWh average over the 60–90% range) and a significant increase at low load. Compared with a previous engine generation (46DF), the 46TS-DF engine exhibits an approximate 18% reduction in methane slip above 60% load. On a well-to-wake basis, this results in an overall CO₂-equivalent emission reduction of about 6%, of which 42% is attributable to methane slip reduction and the remainder to improved energy efficiency. In contrast, switching from LNG to MGO operation leads to a 23.5% increase in CO₂-equivalent emissions. Black carbon (BC) emissions were measured and as expected despite the limited number of available studies, they were found to be significantly lower in LNG mode, with reductions exceeding 90% compared with MGO operation. Finally, an Engine Load Monitoring (ELM) analysis based on one year of operational data highlights the strong influence of vessel operating profiles on methane slip. The application of both IMO and FuelEU methodologies yields consistent methane slip coefficients (1.34% and 1.36%, respectively), significantly lower than current default values, noting that these estimates do not include crankcase emissions. These results demonstrate the importance of integrating real operational conditions into emission assessment frameworks for LNG-fuelled vessels.

Abstract: The deployment of Autonomous Underwater Vehicle (AUV) swarms has become pivotal for oceanographic exploration and monitoring. However, the efficacy of swarm formation control is heavily constrained by the harsh characteristics of underwater acoustic communication networks (UACNs), particularly in non-fully connected networks where topology changes dynamically. To tackle high packet collision rates and excessive signaling overhead in existing Medium Access Control (MAC) protocols, this paper proposes a novel Cluster-based Mobile MAC (CM-MAC) protocol tailored for hierarchical clustered AUV networks. The CM-MAC protocol operates under a distributed two-tier architecture. The first-level cluster head initiates scheduling, followed by the second-level cluster heads, which coordinate transmissions within their sub-clusters by exploiting locally known state information and scheduling decisions. We establish the transmission constraints that prevent packet collisions among mobile nodes amid topology changes. Building upon the transmission constraints, genetic algorithms are applied across all layers’ transmission scheduling to optimize the sending sequence and timing, reducing overall latency. Simulation results indicate that the CM-MAC protocol significantly improves network throughput and decreases information-sharing update intervals compared to traditional TDMA, pure Aloha, and random-access CM-MAC. This study provides a robust communication framework for large-scale AUV swarm coordination in complex underwater environments.

Abstract: Accurate significant wave height prediction is essential for fuel-efficient ship operation and weather routing, as wave-induced resistance directly affects propulsion demand and fuel consumption. This study proposes a Residual U-Net-based deep learning correction model to improve long-range SWH forecasts from WAVEWATCH III (WW3). WW3 global forecast fields were corrected using the proposed model, with CMEMS reanalysis data used as the ground-truth reference. The corrected outputs, denoted as WW3_UNET, were evaluated against 10-minute-resolution main engine fuel oil consumption (ME1_FOC) records and onboard wave observations from a commercial vessel traversing the South Atlantic in 2025. WW3_UNET showed markedly improved agreement with ship observations compared with the raw WW3 forecast across all lead times from 0 to 288 h. When a 24-hour moving average was applied, WW3_UNET achieved a correlation of 0.720 with ME1_FOC at the 168–180 h lead time, closely approaching the 0.736 obtained from onboard wave measurements. These results indicate that AI-corrected forecasts can provide observation-consistent wave information up to 7–8 days in advance. The proposed approach can support fuel-aware weather routing and voyage planning, thereby contributing to improved maritime energy efficiency and decarbonization.

Abstract: This comprehensive review investigates hybrid propulsion technologies as a pathway to decarbonization and improved energy efficiency in the maritime sector. Through a review of recent literature, this study synthesizes current knowledge on energy management strategies and capacity sizing approaches for hybrid ship propulsion systems. Reported results indicate that optimized energy management can reduce fuel consumption and greenhouse gas emissions while minimizing total operational costs. Among real-time strategies, the equivalent consumption minimization strategy emerges as particularly suitable for maritime use due to its low computational demand and independence from full voyage profile knowledge, yet its maritime application remains far less developed than in the automotive domain. Capacity sizing and energy management are usually treated as separate optimization problems, limiting the achievability of truly optimal solutions. Only a few studies adopt integrated co-optimization frameworks, and these are typically built around simplified or fixed operational profiles. Moreover, the coupling between energy management parameters, such as the ECMS equivalence factor, and hardware sizing remains insufficiently explored. The findings suggest that future research should prioritize adaptive energy management formulations calibrated for stochastic maritime duty cycles, the incorporation of battery degradation models into co-optimization, and validation against stochastic, real-world operating conditions.

Abstract: Autonomous underwater glider fleets are increasingly deployed to observe mesoscale eddies, yet a methodology for evaluating observation quality under uncertainty remains lacking. This paper presents SCOPE, a framework integrating uncertainty propagation, multi-dimensional assessment, and objective metric selection. A 27-metric evaluation system spanning seven quality categories is constructed; an Adaptive Core Metric Selection (ACMS) algorithm compresses these to a compact core subset. Two-stage sensitivity analysis identifies the velocity ratio as the dominant parameter with a non-monotonic effect. The optimal velocity ratio decreases with eddy intensity in both an analytical model (0.58 to 0.47) and four real HYCOM eddies (2.35 to 0.35). ACMS converges on all four real eddies, and parameter rankings are consistent across environments. An ablation experiment in the analytical model validates the effectiveness of the two sensitivity-derived design rules (25% and 45.8%) gap closure and reveals their non-additive interaction. SCOPE offers a framework and diagnostic workflow for uncertainty-aware evaluation of autonomous ocean observation systems.

Abstract: The pronounced aero-hydrodynamic coupling effects of modern Wind-Assisted Propulsion System (WAPS) ships challenge the applicability of traditional stability frameworks, which are predicated on hydrostatic energy balance, in satisfying the dynamic constraints of the Second Generation Intact Stability Criteria (SGISC). This paper systematically reviews the methodological evolution of dynamic stability assessments for WAPS ships under extreme and damaged conditions. By introducing a "Hierarchy of Evidence" evaluation framework, this study delineates the applicability boundaries of aerodynamic Reduced-Order Models (ROM), extended 3/4-DOF maneuvering equations, and 6-DOF time-domain hybrid architectures, defining the role of high-fidelity CFD-VPP in establishing calibration benchmarks. The review also discusses the damping distortion mechanisms induced by multiphase flow sloshing under damaged conditions. Synthesized findings indicate that transitioning towards a 6-DOF time-domain coupled architecture provides clear advantages for capturing unsteady aerodynamic hysteresis and nonlinear interference. Meanwhile, surrogate models, such as Physics-Informed Neural Networks (PINNs), offer a potential pathway to mitigate the computational demands associated with long-term extreme value extrapolations. Ultimately, this review provides a methodological reference for the high-fidelity assessment of WAPS and the development of Digital Twin systems.

Abstract: Electric vehicle (EV) transport by ship is expanding beyond industrial logistics centered on automobile production, trade, and pure car and truck carriers (PCTCs) into daily transportation for island tourism, commuting, and essential mobility. According to Korea Maritime Transportation Safety Authority (KOMSA) vessel status data as of March 2026, 104 of 146 domestic passenger ships were car-ferry passenger ships, accounting for 71.2% of the fleet and operating on 75 of 99 designated routes nationwide. Korea Shipping Association (KSA) operational records show that the EV transport rate on these routes increased from 0.76% in 2024 to 1.21% in 2025, with some routes exceeding 2.0–4.7%. Unlike enclosed multi-deck PCTC vehicle spaces, Korean coastal car-ferry passenger ships generally have single-tier open vehicle decks and bow ramp gates. Crosswinds on open decks may reduce smoke detector activation probability by 60–75%. Although Article 97 of the Standard for Ship Fire-Fighting Appliance newly requires dedicated EV fire-fighting equipment for car-ferry ships, it remains primarily equipment-prescriptive and does not yet provide open-deck-specific performance requirements for wind-resistant detection, fixed EV-zone cooling, EV-designated stowage arrangements, or passenger-operator safety management obligations. This study applies the five-step International Maritime Organization (IMO) Formal Safety Assessment (FSA) procedure to support improvements to EV fire-fighting equipment standards for coastal car-ferry passenger ships. Hazard Identification (HAZID) was conducted with a 15-member advisory panel, and probability elicitation was performed through a Delphi survey with 10 core experts, showing strong consensus (Kendall’s W = 0.74, p < 0.01). Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) probabilities were derived from the Delphi results and international literature. H-07, representing wind-induced smoke dilution, was identified as the only first-order minimal cut set. Monte Carlo-based FTA–ETA analysis (n = 10,000) estimated annual fire frequencies of 5.9 × 10⁻², 1.8 × 10⁻¹, and 2.9 × 10⁻¹ yr⁻¹ at EV loading ratios of 10%, 30%, and 50%, respectively, with 2.47 expected fatalities per fire. Risk entered the IMO ALARP band above a 30% EV loading ratio and exceeded the maximum tolerable crew risk above 50%. The combined application of Risk Control Option (RCO) 2, 3, and 4 reduced annual expected fatalities by 85.6%. Based on these results, six RCOs and institutional recommendations are proposed, including strengthened safety management obligations for passenger ship operators.

Abstract: To ensure the operational safety of the OCTABUOY platform used for offshore wind turbine installation in shallow waters, an eight-point symmetric mooring system was designed based on its octagonal structural configuration. The system provides high horizontal stiffness and balanced load distribution, enhancing stability under complex environmental conditions.Physical model tests were conducted under combined wind, wave, and current loading, considering multiple wave directions, environmental cases, and five draft conditions. The mooring tensions and six-degree-of-freedom motions were systematically analyzed to evaluate system performance and safety.Results show that the proposed mooring system effectively limits platform motions and maintains stable load-sharing characteristics. The minimum safety factor under the most unfavorable condition exceeds the design requirement. In addition, the system demonstrates good redundancy: after single-line failure, remaining mooring lines redistribute loads without progressive collapse. Draft and wave incident angle significantly influence peak tensions and motion responses, with smaller drafts and oblique wave directions producing relatively higher loads.The experimental results confirm the reliability and safety margin of the eight-point mooring system and provide practical guidance for the engineering application and operational assessment of the OCTABUOY platform in shallow-water wind installation projects..

Abstract: A systematic experimental investigation was conducted on the motion response (RAO) and mooring performance of a novel disk-shaped buoy (geometric scale 1:10) subjected to combined wind, wave, and current actions. A hybrid experimental strategy was employed, integrating a large-scale wave flume (for long-period waves and currents) with a harbor basin (for short-period waves and wind), aiming to mitigate the scale effects inherent in Froude-scaled models, particularly with regard to drag force measurements. The test matrix included free decay in calm water, RAOs under regular waves, motion and mooring line tension under irregular waves, and measurements of wind and current drag coefficients. Key results indicate a natural roll period of approximately 3.0 s with a notably high dimensionless damping ratio (ζ ≈ 0.14–0.15), which is conducive to rapid motion attenuation. A pronounced resonance peak in the roll RAO (26.6°/m) was observed near the 3 s period. Under an extreme sea state (Hₛ = 13.8 m, Tₚ = 16.1 s), the maximum roll angle and dynamic mooring line tension reached 21.30° and 61.56 kN, respectively, the latter being about 3.0 times the static pretension. The mean wind drag coefficient and current drag coefficient were determined as 0.76 and 0.44. This research provides a validated dataset and critical insights for the design, mooring system optimization, and operational safety assessment of such disk-shaped buoys. The effectiveness of the hybrid testing approach is confirmed, and the favorable damping characteristic of this buoy form is highlighted.