As a critical structural component in marine engineering, the air-backed stiffened plate frame plays a vital role in large-scale offshore installations. Underwater explosions can cause severe damage to nearby structures. This paper investigates the cumulative damage characteristics of the air-backed stiffened plate frame under underwater explosion loads. Compared to a single explosion, secondary explosions induce more complex structural damage due to material hardening after initial loading and substantial changes in load distribution on deformed surfaces. The arbitrary Lagrangian-Eulerian method is adopted to simulate the entire dynamic response of the air-backed stiffened plate frames subjected to sequential secondary underwater explosions. Additionally, the damage characteristics of plate frame structures with varying materials, plate thicknesses, and stiffener configurations under sequential secondary underwater explosion loading are further examined. Results indicate that, under the same charge weight and standoff distance, sequential secondary explosions markedly exacerbate localized structural damage, with extreme cases exhibiting notable differences in damage models. In contrast, a single explosion leads to more pronounced overall structural damage, characterized by larger deformation amplitudes of the plate structure and greater energy absorption. The influence of the primary shock factor on the damage enhancement effect of structures under secondary blast loading is substantial. A smaller primary shock factor leads to larger damage amplification in subsequent explosions. Stiffened plate structures with varying material types, plate thicknesses, and stiffener configurations exhibit consistent patterns.

The deformations of the nets and cage volumes of gravity cages are investigated through experimental and numerical methods. The gravity cage model is towed in calm water as well as in regular waves. Pressure sensors are used to measure the depths at different points on the cage net. These depths are successfully measured in calm water and long waves. A numerical model is developed using ANSYS/APDL to compute the cage deformation. The results from the numerical model align well with the experimental results. Furthermore, cage volumes are calculated using a numerical method. Notably, the cage volume decreases as flow velocity increases. Increasing the bottom weight can help counteract the reduction in cage volume. Furthermore, the cage volume reduces more substantially in short waves, while that in long waves approaches the values observed in uniform flow. Finally, the limitations of the experiment are discussed, and suggestions for further enhancements are provided.

As crucial components in the advancement of tidal energy, tidal turbines are progressively transitioning from large standalone units to multi-unit arrays. In the context of tidal arrays, the blockage effect has become a key factor that necessitates careful consideration due to its substantial impact on turbine performance. This paper introduces an innovative optimization methodology aimed at improving the hydrodynamic performance of tidal turbines while specifically addressing the environmental blockage effect. The proposed approach integrates the blade element momentum-computational fluid dynamics hydrodynamic model, radial basis function neural networks, and the nondominated sorting genetic algorithm Ⅲ optimization algorithm. A case study is used to demonstrate this methodology, focusing on the optimization of a tidal turbine under varying blockage intensity levels. Comparative analyses of optimal turbine configurations indicate that strategic modifications in design parameters can substantially improve hydrodynamic performance in response to varying blockage intensity. Specifically, increasing the root chord length and decreasing the tip chord length effectively reduce the turbine’s load while maintaining operational efficiency as blockage intensity increases. Conversely, the blade pitch angle exhibits minimal sensitivity to the blockage effect. Moreover, the optimized turbines demonstrate lower velocity deficits in their near-field wake compared to the prototype. The case study not only validates the effectiveness of the proposed optimization method but also highlights the substantial impact of blockage effects on optimal turbine configurations. This research provides valuable theoretical insights for designing turbines intended for deployment in tidal arrays.

This study experimentally examines the hydrodynamic performance of a sloped floating breakwater under two distinct configurations one involves a single degree of freedom (1-DOF) system, which is restricted to heave motion; the other involves a three DOF (3-DOF) system, which allows heave, surge, and pitch motions. The main objective is to investigate the effect of DOF on wave attenuation, which particularly explores reflection, transmission, and dissipation mechanisms. Experiments were performed in a wave flume at a geometric scale of 1：15 and under regular and irregular wave scenarios covering various wave heights and periods. Results indicate that the 1-DOF configuration presents superior wave attenuation performance at shorter wave periods, with transmission coefficients up to 14% lower than those of the 3-DOF system. By contrast, at longer wave periods, the 3-DOF configuration exhibits better wave energy dissipation, which achieves 4%-10% lower transmission coefficients. Analysis of Response Amplitude Operators suggests that the decreased heave motion detected in the 3-DOF system at longer wave periods is due to mooring-induced constraints and the interaction among multiple DOFs. This reduction in the heave response considerably contributes to enhanced wave energy dissipation. These outcomes emphasize the vital role of structural flexibility and DOFs in optimizing floating breakwater designs, which offer practical guidance for tailored solutions under diverse wave scenarios.

A ship’s main engine is critical to the performance, operational continuity, and safe conduct of ship operations. However, the safety and operational efficiency of a ship may be endangered because of malfunctions and problems occurring in the ship’s main engine. This study introduces a systematic approach to risk analysis considering uncertainties and integrates the failure modes, effects, and criticality analysis (FMECA) and Dempster-Shafer (D-S) theory to evaluate prospective ship main engine failures. By analyzing ambiguous data derived from expert judgments, the D-S theory offers a more trustworthy failure assessment than the conventional FMECA. In this study, a survey was conducted on maritime experts using main engine failures in the Kongsberg Maritime Engine Room Simulator, and analyses were conducted by integrating FMECA and the D-S theory. This integration allowed for a more accurate prioritization of ship main engine critical failures. Failure modes 2.3, 2.1, and 3.6 were found to be the riskiest failures. By better managing uncertainty, this study offers a more accurate safety analysis than the conventional FMECA method and helps ship operators and marine engineers create proactive maintenance plans. The outcomes of the research are expected to provide unique contributions to maritime safety professionals, safety researchers, and safety inspectors for improving the operational safety of ship main engines.

The growing demand for renewable energy has driven advancements in ocean exploration technologies involving floating structures. These structures are exposed to waves, requiring careful design to ensure safety. To enhance protection, the present research focuses on floating breakwaters designed to mitigate wave action. When considering regular waves, the wave transmission coefficient (K_t) for two-dimensional (2D) box-type floating breakwaters is well-defined in the literature. However, the wave transmission coefficient computation for three-dimensional (3D) floating breakwaters still requires a standardized method. In this context, this study conducts a parametric analysis of a box-type floating breakwater, using numerical models based on potential flow theory to determine the 3D wave transmission coefficient. Results reveal that, unlike 2D cases, different K_t levels emerge for a given 3D scenario. These findings suggest that breakwaters featuring high relative breakwater beam ratios are likely to present convergent mean wave transmission coefficients. Furthermore, the research demonstrates that the wave-shelter area is highly dependent on the breakwater beam ratio, with larger ratios leading to lower K_t levels. The sheltered area changes exponentially with the K_t levels. In addition, a practical application is introduced, leveraging machine learning techniques to predict the wave-shelter area and optimize breakwater dimensions. The proposed design minimizes construction costs while ensuring effective wave attenuation for a one megawatt-peak floating solar photovoltaic system. These findings enhance understanding of the wave transmission coefficient for 3D floating breakwaters, highlighting that variations in breakwater dimensions and wave conditions significantly influence the sheltered area, which impacts the protection of offshore structures.

This study presents a stability analysis of suspension ships, with a specific focus on assessing how the key design parameters influence the ship’s stability. These parameters include the total mass, mass ratio, beam of ship, spring stiffness, allowable travel, and ride height of the suspension system. The stability analysis is performed based on a hydrostatic force model and a static analysis model including the suspension deflection induced by ship inclination and load variations on the cabin. The present numerical method is verified by a sensitivity study of hull surface discretization and comparisons of the initial and intact stability obtained using Orca3D. Numerical results show that the coupling effect of the heeling and trimming occurs when the total mass of the suspension ship exceeds a critical value. An increasing mass ratio significantly reduces the righting arm (GZ) and increases trim, while spring stiffness, allowable travel, and ride height have relatively less influence on the initial and intact stability of the suspension ship. The proper total mass of the investigated ship is suggested to be 95 to 125 tonnes based on the International Maritime Organization (IMO) intact stability resolution and total mass threshold defined in this study. A dynamic stability analysis based on IMO weather criterion indicates that the mass ratio should not exceed 0.75. In damaged conditions, flooding can intensify heel-trim coupling due to the added weight of floodwater, further deteriorating the ship’s damage stability. This study provides new insights into the stability characteristics of suspension ships, highlighting the effects of suspension parameters that differentiate suspension ships from conventional ships.

The linear explosively formed projectile (LEFP) is a special type of linear shaped charge (LSC) and is developed on the basis of the explosively formed projectile. Known for their excellent penetration performance and directional destruction capacity, LEFPs are widely utilized in explosion dismantlement, petroleum exploration, concrete crushing, metal cutting, and penetrator interception. LEFPs can also induce multi-mode damage—combining penetrator impact, shock waves, and bubble effects—during underwater detonations. Thus, they are employed in applications including subsea pipeline disruption and effective neutralization of underwater vehicles. Adequate formation effect is a criterion for a desirable penetration performance of shaped charges. Therefore, investigating the formation characteristics of LEFPs in different media and optimizing the structural parameters are important tasks. In this study, the arbitrary Lagrangian-Eulerian (ALE) method is adopted for numerical simulation, and the efficacy of the ALE method is verified by the consistency between numerical and experimental results. Then, the formation effects of LEFPs in pure air medium, water medium, and water with air cavity are investigated separately. The results show that the stabilized velocity of the penetrator in air is 1 355 m/s, while the velocity is only 423.6 m/s in water. Furthermore, the liner cannot be completely closed in water and cannot form a slender penetrator as in air. After the addition of the air cavity, the stabilized velocity of the penetrator increases to 966.6 m/s, and its morphology is significantly enhanced. Moreover, explosive material, liner material, and liner thickness are chosen as the primary factors for orthogonal optimization. The optimized factor combination is RDX-Copper-1 mm. The peak velocity of the penetrator, the velocity before penetration, the velocity after penetration, and the length of penetration increase by 50.8%, 44.9%, 26%, and 10.3%, respectively.

The structural dynamics of scale model ships used in towing tank experiments may affect the measured values of propeller-induced pressure fluctuations. The International Towing Tank Conference (ITTC) recommends monitoring structural responses during the tests to evaluate this effect but does not provide a specific procedure for such monitoring. Apart from considering structural behavior during towing tests, having a reliable numerical model of the scale model ship structure is essential to be aware of its vibratory behavior not only prior to lab experimentation to control experimental errors but also when replacing costly physical experiments with cost-effective computational simulations. To address this, we generate a finite element (FE) model of the scale model ship used in our towing tests. We present a methodology for characterizing this FE model based on the physical model’s behavior to ensure its reliability for further numerical dynamic analyses. The properties of the FE model are updated by using response surface methodology (RSM) to align numerical and experimental resonance responses. Latin hypercube sampling (LHS) technique is employed to generate the design space, whereas the modal assurance criterion (MAC) serves as a performance metric to ensure modal consistency before and after optimization. This approach provides a reliable FE model that offers a cost-effective alternative to expensive physical tests for enhancing the precision of propeller-induced pressure measurements.

This study investigates wave interactions with different configurations of pile-restrained floating breakwater (T-shaped, ⊥-shaped, Π-shaped, H-shaped, I-shaped, and rectangular) with the multi-domain boundary element method. The analysis incorporates horizontal and vertical stratification in floating structures. Key scattering factors, including reflection, transmission, and dissipation coefficients, are evaluated to determine the influences of the structural and geometric parameters on floating breakwater performance. Additionally, this study examines the horizontal wave forces exerted on the seaward and leeward sides of the structures. Model convergence is validated, and the accuracy of the computational results is confirmed by comparing the wave reflection and transmission coefficient for rectangular floating pontoon and stratified submerged porous box. Further validation is provided by comparing the numerical results for an H-shaped model with experimental data obtained from wave flume testing. Findings indicate that the H-type breakwater demonstrates superior performance in deep-water environments, whereas the ⊥-type structure exhibits greater wave energy transmission and reflection in shallow-water environments. Moreover, the H-type configuration experiences the highest wave forces, whereas the ⊥-type structure experiences the least. The findings of this study offer valuable insights into the design and analysis of floating breakwaters in offshore environments.

The synergistic interaction of underwater ocean currents and surface wave dynamics governs the hydrodynamic behavior of structures in practical marine environments. However, research on their kinematic characteristics under composite hydrodynamic loading across varying sea state conditions is lacking. To elucidate the effects of wave-current coupling on the motion characteristics of structures, this study simulates the motion processes of a cylindrical structure in diverse sea state conditions. Changes in the structure’s attitude, velocity, and trajectory height are considered. Through the analysis of the pressure and velocity fields during the movement of the cylindrical structure, the hydrodynamic characteristics of the structure’s surface emergence are further systematically investigated. The results demonstrate the minimal fluid-structure interaction influence on cylindrical structure dynamics during the underwater phase. Notably, the horizontal motion characteristics exhibit intensified variations with the increases in wave levels, which reveals a strong coupling between near-surface dynamics and wave. Further investigation of the cylindrical structure’s motion characteristics during water exit at various wave phases under identical sea state conditions reveals the emergence of the cylindrical structure at the wave crest, and its lateral displacement is considerably larger than when it emerges at the wave trough. In addition, the emergence of the cylindrical structure at corresponding opposite phases reverses the cylindrical structure’s deflection direction. Under the combined effect of wave-current coupling, the cylindrical structure’s lateral displacement in the negative direction of the x-axis increases with current velocity enhancement during the underwater movement phase, and it is accompanied by a corresponding reduction in the deflection angle between the cylindrical structure body and free surface. Furthermore, the hydrodynamic effect of varying sea states during water exit induces a pronounced lateral motion in the postemergence trajectory and concurrently causes a substantial reduction in vertical altitude. Investigation of the cylindrical structure’s dynamic behavior under the combined influence of multiple complex launch conditions can provide a scientific reference to ensure the safety of underwater cylindrical structure launches.

In this study, we evaluate the residual longitudinal strength index of three double-hull oil tankers—Aframax, Suezmax, and very large crude carrier (VLCC)—based on collision and grounding scenarios by employing an improved progressive collapse method (PCM). We define the extent of damage based on the IACS-CSR. This study mainly contributes to the extraction of new quadratic equations, which are derived from 51 analytical simulations using curve-fitting. The objective is to establish the relationship between residual strength index (RSI) and damage size ratio (DSR). The proposed PCM incorporates the neutral axis (NA) rotation, overcoming a critical limitation in previous methodologies. Results indicate that not considering NA rotation can lead to a 26% overestimation of RSI. Furthermore, the results of grounding scenarios indicate a larger RSI reduction under hogging conditions than that under sagging conditions; this is attributed to the progressive deck failure and buckling of the inner bottom plating. A comparative analysis shows that inner hull damage significantly deteriorates the RSI reduction, emphasizing the need for refined structural integrity evaluations. Additionally, we analyze the factors affecting the longitudinal strength behavior of damaged ships. The newly extracted RSI-DSR equations and diagrams can be used in practice for rapid damage assessment and RSI estimation, contributing to improvements in ship structural safety and reliability.

In ice mechanics, the strain rate-dependent properties of ice under uniaxial compression have attracted attention. In this work, the rate-dependent properties of polycrystalline ice are studied through experiments and numerical simulation. For the experimental part, uniaxial compression tests are carried out on polycrystalline ice with different strain rates. For numerical simulation, a discrete element numerical model based on grain is constructed, and the microscopic parameter calibration is completed. Ice compression at different strain rates is simulated by combining the mechanical properties of single-crystal ice and polycrystalline ice, and the simulation and experimental findings are mutually verified. The results show that the uniaxial compressive strength of polycrystalline ice increases exponentially with the strain rate. The ice samples break substantially at a high strain rate, and the average broken area is inversely proportional to the strain rate. In the crack initiation, propagation, and coalescence of polycrystalline ice, intergranular failure is dominant. In terms of crack type, tensile failure is dominant. On the basis of existing studies, a rate-dependent model of the uniaxial compressive strength of polycrystalline ice is proposed.

The mine countermeasure operations consist of hunting i.e. searching for possible mines from the seabed and water column as well as demolition or disposal of found mines to enable safe passage of other naval units. Mine hunting is a task conducted by specialized naval units aiming to clear sea areas from estimated or realized naval mine threats. The search is usually initiated by sweeping broad areas with a side scan sonar to produce an initial picture of the seabed and localize possible threats for closer examination. The manual analysis process is challenging and time-consuming, especially in environments where seabeds are littered with mine-like objects such as rocks and other roughness. This paper researches the possibility of enhancing littoral mine hunting with object detection using a deep convolutional neural network and vision transformer methods separately and as a Mixture of Experts system to do the preliminary object detection and classification of the data multiples faster than a sole sonar operator. The results indicate that even a processed sonar image can be used to enhance mine hunting operations in a transparent, explainable manner but would benefit from enriching with additional data and signal analysis to ensure the detection of the most difficult targets.

The prediction of ship roll motion is important for the safety of marine vessels and the efficiency of offshore operations. This study aims to address the issues of low prediction accuracy and incapability to illustrate the uncertainty of ship roll motion in traditional deterministic prediction models. Thus, a probabilistic interval prediction scheme for ship roll motion is established utilizing the novel data preprocessing strategy and non-parametric kernel density estimation (KDE). The novel data preprocessing method based on multi-resolution decomposition and reconstruction strategy is used to reduce the non-stationarity of the time series and number of mode components. This method is also utilized to extract trends from the mode components for preserving more effective information. Accordingly, the dynamic recurrent neural network is adopted to enable the identification and deterministic prediction of reconstruction data for ship roll motion. The deterministic prediction values of ship motion status can be obtained by reconstructing the predicted outcomes of the mode components. Non-parametric KDE is applied to predict the fluctuation range of ship roll status by combining deterministic prediction results. The feasibility and effectiveness of the probability prediction scheme are exhibited through the measured data of M.V. YuKun. Results show that the deterministic prediction accuracy of the proposed scheme is superior to those of traditional deterministic prediction models, with maximum improvements of 22.7% and 27.5% for single-and multi-step prediction accuracies, respectively. The minimum prediction interval coverage probability at the 85% confidence level is 98%. The reliable fluctuation range of ship roll can be realized through the non-parametric KDE, which can offer more effective reference information for ship operators. The proposed model not only satisfies the requirements of deterministic prediction accuracy but also produces reliable uncertainty estimates of ship roll motion status.

Fixed offshore wind turbines generally use statistical parameters of sea conditions in or near the target sea area as design benchmarks during the design phase. However, these sea state statistical parameters vary substantially from the actual sea state parameters experienced by offshore wind turbines. This situation brings uncertainty to the structural safety of offshore wind turbines. Online monitoring of wind loads exerted on the wind tower topside, which uses monitoring the structural response of the wind tower to determine wind load online, provides another technical approach for accurately measuring the wind loads exerted on the wind tower topside. However, online monitoring of wind loads can be affected by factors such as the ill-posedness of mathematical models and errors in monitoring data. The mathematical model for wind load monitoring is usually optimized only with the ill-posedness index as the objective function to reduce or overcome model ill-posedness. The error level of monitoring data is not considered in optimization, which likely leads to a high proportion of monitoring data error and then reduces the quality of monitoring data. Hence, a fuzzy optimization method was developed in this study to reduce the ill-posedness index of mathematical models and the influence of monitoring data errors on the monitoring results, in which the ill-posedness index of the mathematical models is weighted and unified with the error index of the monitoring data. In addition, the effectiveness and reliability of the method developed were demonstrated through numerical examples of jacket wind turbines, and structural damage can be accurately analyzed using the monitored wind loads.

The engine speed control system is critical to marine propulsion, particularly for ships navigating in wave conditions. Fluctuations in propeller torque, caused by wave-induced variations in the ship’s speed and direction, can lead to undesirable effects such as increased fuel consumption and greenhouse gas emissions, increased engine wear and tear, and degraded performance. In the field of marine diesel engines, a proportional-integral-derivative (PID) control algorithm is the most widely used method for speed regulation. Aiming to maintain a constant engine speed, the PID governor continuously adjusts the fuel injection into the engine cylinders in response to propeller torque fluctuations. The quality of control, and thus engine performance, depends on a set of PID control gains. However, these optimal PID gains are typically determined during engine testbed commissioning and remain fixed, which leads to suboptimal performance under varying operational conditions. While model-based tuning techniques can achieve satisfactory results in relatively simple control tasks, particularly when the number of tunable parameters is small, adaptive tuning of controller parameters, while meeting multiple, often conflicting objectives, presents a considerable challenge. This paper explores the application of a reinforcement learning (RL) algorithm to adaptively tune PID gains, aiming to optimize engine performance under varying sea conditions and operational demands. A specific reward function is designed to effectively balance variations in engine shaft rotational speed and fuel pump index, ensuring optimal engine efficiency. The performance of the trust-region policy optimization and proximal policy optimization algorithms is evaluated for their suitability in continuous-action space control, demonstrating stable convergence and robustness. Simulation results indicate that the proposed RL algorithm outperforms the reference PID controller, offering promising results for adaptive gain scheduling in propulsion system control.

The ocean, which is a key component of Earth’s ecosystem, requires advanced technologies for deep and highly comprehensive exploration. Unmanned underwater vehicles (UUVs) play an important role in this task, but their development encounters great challenges due to the complex and dynamic underwater environment. Reinforcement learning (RL) has recently emerged as a promising method to improve the capabilities of UUVs. This study comprehensively reviews the implementations of RL in UUVs, with a focus on key tasks such as motion planning, navigation and control, and multiagent coordination. We investigate current difficulties and emerging trends, as illustrated by a case study. This review aims to provide a foundation for RL-based control and decision-making in UUVs and offer actionable insights for advancing studies in this rapidly evolving domain.

In this study, a hybrid path planning algorithm for ships in ice areas is proposed. First, the operation space of ships in ice areas is established in accordance with the raster method. Second, improvement strategies are introduced to address the slow iteration speed and poor solution quality of the traditional ant colony algorithm, and the Ant Colony Optimization (ACO) algorithm is used to plan the global path in a static environment. Then, the node deletion algorithm is proposed to optimize the global path. Finally, the dynamic window approach (DWA) algorithm is optimized, and the subnodes of the preprocessed path are considered the subobjectives to be optimized. The final path in the dynamic environment is solved using the improved DWA algorithm. The simulation results show that: the ACO algorithm can plan a high-quality global path with a high iteration speed, the node deletion algorithm can effectively eliminate redundant nodes and reduce the computational complexity of the subsequent algorithms, and the improved DWA algorithm can efficiently avoid dynamic obstacles in the environment on an original global path and solve the path that meets the motion performance of the ship in ice areas.

Accurate modeling of submarine magnetic anomaly characteristics is a fundamental component in evaluating magnetic stealth capabilities. Previous studies have primarily focused on analyzing the spatial magnetic anomaly induced by stationary submarines, with insufficient attention given to the comprehensive impact mechanisms of varying speed, course, and depth in moving submarines. This paper provides a detailed analysis of the spatiotemporal characteristics of submarine magnetic anomaly under typical motion scenarios. Initially, a foundational research submarine model was established using the finite element method (FEM), followed by an examination of the spatiotemporal characteristics of magnetic anomaly during both routine cruise and evasive maneuver scenarios. The simulation results reveal several key findings: 1) During routine cruising, the magnetic anomaly induced by the submarine is not significantly affected by its speed, to reduce the risk of detection by aircraft with magnetic anomaly detection (MAD) sensors, submarines should maintain a relatively high speed to quickly exit hazardous waters. 2) During evasive maneuvering, the magnetic anomaly is slightly stronger when turning left than turning right at a fixed depth, and it is lower at larger elevator angles during emergency diving. Therefore, to reduce the risk of detection by aircraft, submarines should opt for a right rudder angle or a larger elevator angle. 3) When the angle remains the same during evasive maneuvering, submarine exhibits superior magnetic stealth capabilities in emergency diving compared to depth-fixed turning. 4) Combining a specific rightward rudder angle with an elevator angle is the most effective evasive maneuver for submarines. This approach ensures stability and safety by preventing excessive bow tilt and potential instability. The research methodology proposed in this paper has potential value to enhance the development of submarine magnetic stealth technologies.

The application of renewable energy plays a crucial role in advancing sustainable development, with one such source being ocean thermal energy conversion (OTEC). OTEC systems harness the temperature difference between sea surface water and deep seawater to generate electricity. A key component of the OTEC system is the piping network, which, despite its importance, has not been extensively studied. Thus, the current study aims to investigate how geometric variations and material properties affect pipe strength and to develop a predictive formula for estimating the pipe’s bending capacity. The analysis uses the finite element method (FEM), starting with a validation phase against previous studies to ensure the accuracy of the scenario and test module settings. A simulation case study is then conducted, focusing on pipe bending by varying pipe geometry and material yield stress. The results of the variation analysis show that each parameter substantially impacts pipe performance. Specifically, a smaller length-to-diameter (L/D) ratio results in a stiffer pipe, as does a smaller diameter-to-thickness (D/t) ratio. In addition, materials with low yield strength deform easily. Using the test data, a nonlinear regression model was developed to generate a predictive formula for estimating the ultimate flexural capacity of the pipe. The validation results of this formula show that the developed equation is highly accurate and outperforms existing empirical formulas. This study provides valuable insights for designing efficient and optimized OTEC piping systems, offering a fast and accurate estimation tool.