bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Integrated Finite Volume–Finite Volume Numerical Model for Wave-Structure Interactions
Authors: Rai Ranjodh S. , Ma Zhihua , Qian Ling , Bai Wei , Lin Zaibin , Khait Anatoliy 
Published: September 2023

Abstract
This paper presents a new integrated (hybrid) hydrodynamic numerical model which couples a finite volume-based fully nonlinear potential flow (FNPF) solver with an incompressible two-phase Navier-Stokes (NS) solver in OpenFOAM. The coupling procedure follows a domain (zonal) decomposition approach in which an overlapping relaxation zone is utilised to implement a weak (one-way) coupling. The method for transferring information is simple, and the coupling accurate. Indeed, given that both solvers have been developed in OpenFOAM and are finite volume-based, only a method to calculate the volume fraction from the free-surface elevation has to be implemented: the velocity and pressure are already calculated as part of the FNPF solution and can be transferred accordingly — simplifying things greatly and avoiding unwanted errors. In addition, existing advanced OpenFOAM functionalities are used for the required interpolation. The relaxation zone then also ensures the coupling process is stable through a smooth transition from the FNPF solution to the N-S solution, as well as by absorbing any reflected waves. The new model is then validated through a number of benchmark test cases involving wave propagation, transformation, and structure interaction. It is shown to produce accurate numerical solutions that agree well with existing theoretical results and experimental data.
Steel Lazy Wave Riser Optimization Using Particle Swarm Optimization Algorithm
Authors: Lal Mayank , Yenduri Anurag , Sebastian Abhilash 
Published: September 2023

Abstract
Steel lazy wave risers have become a preferred riser solution as offshore oil and gas developments are happening in deeper waters and harsher environments. Steel lazy wave risers work well with FPSOs even though FPSO motions are worse compared to other floating platforms such as Spars and Semisubmersibles. FPSOs offer a tremendous advantage compared to other floating platforms as they can be used in regions with inadequate pipeline infrastructure to transport oil and gas to shore. The targeted placement of buoyancy modules on steel lazy wave risers improves the strength and fatigue performance compared to steel catenary risers making them feasible for use with FPSO’s. Also, buoyancy modules on steel lazy wave risers help reduce the top tension compared to steel catenary risers which gains significance in ultra-deepwater developments where top tensions for steel catenary risers make them an infeasible riser solution.
Steel lazy wave riser configuration design is dependent on a few parameters such as hang-off angle, length to start of buoyancy section, length of buoyancy section, type of buoyancy, and buoyancy factor. Theoretically, there are infinite solutions for a steel lazy wave riser configuration. Hence, the design of steel lazy wave riser is an optimization problem in which the parameters that govern the design can be varied to get an optimized configuration. In this paper, the particle swarm algorithm which is a bio-inspired algorithm is used to find an optimal solution for steel lazy wave riser configuration. The solution space is searched for an optimal steel lazy wave riser configuration based on an objective function which is a function of strength response, fatigue response, and cost. Solutions with poor interference response are penalized in the algorithm and rejected as part of the solution space search process. Finding an optimal solution automatically will help reduce the overall cost of risers which is a significant part of any offshore development. Also, it will help in making the riser design efficient from strength and fatigue point of view in addition to making it robust and streamlined.
Is the 100-Year Return Value for Significant Wave Height Increasing in the Tasman Sea?
Authors: Ewans Kevin , Jonathan Philip 
Published: September 2023

Abstract
Climate change is frequently reported to be the cause of an apparent increase in the occurrence and intensity of extreme events around the globe. Recent studies have found that increases can be expected in sea state extremes for some regions of the world’s oceans. We investigate temporal trends in storm peak significant wave height for a central Tasman Sea location, using output from the FIO-ESM v2.0 CMIP6 Earth System Model of [1], [2]. These data include time-series of significant wave height for several Shared Socioeconomic Pathways (SSP) as well as 165-year historical and 700-year pre-industrial realisations. This allows estimates to be made of 100-year return values for significant wave height at the end of the 21st century, for several future atmospheric forcing scenarios, and comparison of these against estimates for present day, based on the historical data base, and estimates for pre-industrial conditions. The estimates are made with a non-stationary extreme value analysis method that allows return values of storm peak significant wave height to be estimated as a function of time and to quantify if changes in return values are statistically significant. Evidence supporting climate-related changes at the Tasman location studied is weak. Estimates of most probable changes in 100-year return value for storm peak significant wave height between 2015 and 2100, for the three SSP scenarios considered, suggest the assumption of a 2m increase in 100-year return value to be reasonable, whilst noting that this value is small compared to the inherent uncertainty (of at least ±5m) present.
Short-Term Sea Surface Elevation Prediction Using Deep Learning Methods
Authors: Pang Tak Yin , Ding Boyin , Liu Lingqiao , Sergiienko Nataliia 
Published: September 2023

Abstract
Many ocean applications such as control optimization of wave energy converters and ship navigation rely on ocean wave prediction to improve the efficiency and safety of offshore operations. The two main types of ocean wave prediction methods are deterministic sea wave prediction (DSWP) and same point prediction. DSWP are based on several upstream wave measurements, which aid in prediction but are expensive due to the amount of measuring equipment necessary. Furthermore, the majority of DSWP are physical models that work on certain sea states such as deep water condition and are based on a knowledge of ocean physics and the assumptions of linear wave theory. On the other side, same-point prediction solely uses past measurements to estimate future sea elevation, which reduces measurement costs but adds extra complexity. For same-point prediction, researchers in the existing literature apply data-driven models such as auto-regressive models or neural networks; nevertheless, neural networks do not perform better.
In this paper, we examine the performance of Temporal Convolutional Networks (TCNs) and traditional Artificial Neural Networks (ANNs) for short-term ocean wave prediction on the same point wave measurement. With dilated causal convolutional layers and residual blocks, TCNs are designed to extract features from complex long-term patterns and capture the nonlinearity of the wave time series data. Wave time series data are simulated using the Pierson-Moskowitz spectrum with different levels of non-linearity for the experiment. The experiment results illustrate the efficacy of two deep learning models as influenced by nonlinearity and noise levels, but TCNs do not outperform ANNs in the same point wave prediction.
On the Distribution of Aerodynamic Load and Stress on Wind Turbine Blade
Authors: Dao My Ha , Le Quang Tuyen , Zhao Xiang 
Published: September 2023

Abstract
Making use of a large database obtained from high-fidelity CFD simulations of a 5MW NREL wind turbine, we perform an analysis of loading distributions on different sections of the turbine blade and their possible shifts with respect to the change in the operating conditions, i.e. inflow wind speed, rotating speed, tilt and pitch angles. In this paper, we will present a computational fluid dynamics model designed for mass generation of aerodynamic loading data, a finite element analysis structural model for simulating the turbine deformation and stress. Finally, verification of the model, data processing and analysis, and the results of loading and stress distributions on different sections of the turbine blade will be presented.
Hydroelastic Responses of a Circular Net Cage Under Wave Action
Authors: Ma Mingyuan , Zhang Hong , Jeng Dong-Sheng , Wang Chien Ming 
Published: September 2023

Abstract
The accurate assessment of hydrodynamic loads acting on a fish-cage is a topic that has received considerable attention in engineering. However, the sheer complexity of such a net-type structure makes it difficult to model with computational fluid dynamics (CFD) techniques. This has resulted in empirical methods being most commonly used in engineering practice. The present study proposes an efficient numerical model for predicting the hydro-elastic behavior of net cages under wave action. The finite element method (FEM) based dynamic solver AquaSim was adopted to simulate the hydro-elastic behavior of the net-type structure with a modified Morrison formula being used to estimate the hydrodynamic loads acting on the net structure. Beam elements and truss elements were employed to model the floating collar and mooring lines respectively, and the net chamber itself was modelled by membrane elements. The simulation results show that the net at the top of the cage undergoes more significant deformation due to the surface wave effect. The parametric study revealed that the cage system has an obvious nonlinear relationship with the incident wave amplitude. These findings provide a reference for the engineering design of marine aquaculture systems.
A Detailed Analysis Framework of Fully Coupled Dynamic Responses for Offshore Wind Turbine Blade
Authors: Wang Baoxuan , Liang Xu , Zhang Jianwei , Rui Shengjie , Zha Xing , Wang Shaoyang , Chen Yue 
Published: September 2023

Abstract
As the critical components of a wind turbine to capture wind energy, blades are complex structures, both in terms of shape and composite layup. The outside shape of blades is designed based on aerodynamic considerations, while the internal architecture mainly depends on the bearing capacity of the structure. In the wind turbine industry, the aerodynamic loads of the blade are calculated by the Blade Element Momentum (BEM) based models and then coupled with the dynamic responses of the whole system. The structure dynamics calculation of this method is usually based on highly simplified beam-elements model, which is an efficient calculation model that only applicable to the preliminary design, the final design and inspection of the blade structure requires more detailed three-dimensional (3D) finite element analysis. In this regard, this work developed a set of automatic algorithms to implement the time-domain ANSYS calculation based on OpenFAST and associate the deformation of 3D blade finite element model with the loads acting on it at each time step so as to carry out multi-scale detailed analysis of dynamic responses such as stress/strain on the global blade and local components including skin, spar, shear web and their constituent materials within the integrated framework. As a practical example, the program was used to analyze one of the blades for a 5MW jacket offshore wind turbine in normal power production state under the combined action of wind, wave and current. The effect of soil-structure interaction and marine growth were also taken into account, so as to reflecting the advantages of the integration. In this example, each module of the developed algorithm and the overall calculation results were checked, and the feasibility of the framework was verified. This methodology can be used to perform the detailed analysis of blade structure and material dynamic responses in the integrated design of wind turbines, providing a good starting point for subsequent studies.
Alternative Rope Materials in Towed Fishing Gear to Reduce Plastic Waste, A Comparative Study of Mechanical Properties and Tolerance Against Wear and Tear
Authors: Moe Føre Heidi , Hatlebrekke Hanne Hjelle , Grimaldo Eduardo 
Published: September 2023

Abstract
This paper presents a comparative study assessing the wear tolerance of rope materials in demersal fisheries, specifically seine ropes and dolly ropes. Fourteen different rope materials were assessed in this study, including conventional and alternative commercially available synthetic polymers, and biodegradable materials including natural fibre ropes and custom-made polyester monofilaments. The sample materials were subjected to controlled wear from a rotating abrasive drum. Tensile testing was performed to determine and compare mechanical properties of the samples before and after exposure to wear. A wear tolerance coefficient has been suggested, i.e. a comparative unit between the different rope material samples and a standard blended polyester/polyethylene rope material as reference.
The tested nylon ropes showed the lowest reduction in breaking strength post wear and thus the highest wear tolerance of all tested materials. Conventional and biodegradable polyester ropes and monofilaments also performed well compared to the standard reference rope.
The performed tests did not only consider the effect of different raw materials, but the combined effect of material and structural properties. A rope’s tolerance to wear may be affected not only by the mechanical properties of the raw material, but also fibre thickness and cross section, and rope thickness, structure and lay of rope.
This study demonstrated the potential of using biodegradable polymers with higher tolerance to wear than conventional non-degradable plastic materials as a circular solution to reduce microplastic pollution caused by demersal fisheries worldwide. Application of alternative commercially available ropes and hard-lay rope structures may increase the tolerance to wear and by that reduce plastic waste.
Ship Performance Evaluation and Green Ship Type Scheme Under Complex Channel Conditions
Authors: Lian Zhengchen , Wang Lizheng 
Published: September 2023

Abstract
At present, the interaction and adaptability between ships and complex channels reflect the efficiency of ship operation. Therefore, it is very important to explore the adaptability of navigable ship types and complex channels. In order to study the ship performance evaluation and carbon emission scheme under complex channel conditions, this paper selects the numerical simulation of four typical working conditions of typical ships in the navigation tunnel environment of the Three Gorges New Channel and the numerical calculation of corresponding ship carbon emission inventory. Through model calculation and verification, the effective power of the real ship under various working conditions can be obtained. By analyzing the curve of power changing with speed, it can be concluded that with the increase of ship speed, the water depth has a greater impact on the power of the real ship than the channel width. Based on the ship power at different tonnage and speed, the emission list of four ship types in the speed range of 1–3m/s is obtained by using the emission coefficient method. To carry out the adaptability analysis of ships in key sections and propose the green ship type scheme with excellent comprehensive performance.
Online Modeling of Ship Maneuvering Motion With Varying Loading Conditions
Authors: Yu Yao-Hui , Wang Zi-Hao , Qu Dong , Song Rui , Peng Yan 
Published: September 2023

Abstract
As influenced by the changes in ship loading conditions, the dynamic characteristics of the ship will change accordingly, leading to inaccuracy of the established ship motion model. Therefore, it is necessary to update the model to consistently provide accurate motion predictions. This paper investigated the adaptability of two online learning modes (i.e., incremental learning and sliding window) when the ship loading conditions change. The incremental learning method updates the model quickly with streaming data, while the sliding window method retrains the model with batch data over a period of time. The ε-Support Vector Regression (ε-SVR) is selected as the identification algorithm due to its good generalization ability and nonlinear mapping ability. The KCS container ship is taken as the study object. By changing its loading conditions, the incremental learning and sliding window methods are tested and verified with different amounts of new data. The results indicate that ε-SVR combined with the sliding window has better performance than combined with the incremental learning. The accuracy of the two methods is compared, and the adaptability is further analyzed.
Numerical Investigation of Comprehensive Behaviors of OMNI-Max Anchors in Sand
Authors: Zhang Chengyang , Liu Haixiao , Xiao Zhong , Zhang Wei 
Published: September 2023

Abstract
OMNI-Max anchors are newly developed gravity installed anchors(GIAs) with great potential due to its keying and diving behaviors when subjected to pullout loading. Although the motion behavior of OMNI-Max anchors in clay has been relatively well studied, the attention to OMNI-Max anchors in sand has been relatively limited. In recent years, the booster attached at the tail of the GIAs can make the anchor to achieve a greater initial embedment depth during the installation process, which provides the feasibility for the application of GIAs in sand. This paper investigates the trajectory of OMNI-Max anchors upon pullout in sand, focusing on whether it can dive. The study employs the coupled Eulerian-Lagrangian (CEL) method with a bounding-surface plasticity model which has the ability to reflect the strain hardening of loose sand and strain softening of dense sand. The results indicate that the anchor can not dive in sand under certain conditions unless the position of the shackle are changed. A parametric study is also carried out to quantify the effects of various factors including embedment depth, soil property, cable parameters and the friction coefficient on the behavior of OMNI-Max anchors.
Hydrodynamic Forces on a Near-Bottom Pipeline Subject to Wave-Induced Boundary Layer
Authors: Yin Guang , Ong Muk Chen , Ye Naiquan 
Published: September 2023

Abstract
Hydrodynamic forces on small diameter subsea pipelines and cables placed near seabed are important for their on-bottom stability design. In offshore environments, these pipelines are usually subjected to extreme wave conditions. The present study investigates hydrodynamic forces acting on a pipeline near a flat seabed subjected to a wave-induced boundary layer flow. The Keulegan-Carpenter numbers (KC) of the wave-induced boundary layer flow are 20, 140 and 200, defined based on the pipeline diameter (D), the maximum velocity of the undisturbed near-bed orbital velocity (Uw) and the period of the incoming oscillatory flow (Tw). Reynolds number is 1 × 104 based on Um and D. A seabed roughness ratio ks/D (ks is the Nikuradse equivalent sand roughness) of up to 0.1 and different gap ratios of G/D = 0.05∼0.5 between the pipeline and the seabed are considered. Numerical simulations have been carried out based on two-dimensional (2D) Unsteady Reynolds-Averaged Navier-Stokes (URANS) equations combined with the k-ω Shear Stress Transport (SST) turbulence model. A preliminary one-dimensional (1D) simulation is carried out to obtain a fully developed wave-induced boundary layer velocity profile, which is used as inlet flow for the 2D simulations. The numerical model is validated against the experimental data reported by Sumer et al. (1991)[1] at KC = 10. Influences of KC, ks/D and G/D on the hydrodynamic forces and the surrounding flows are discussed in detail.
Basic Study on Monitoring Technique for Concretes Prestressed With CFRP by Using Fiber-Optic Sensors
Authors: Zhang Tianjun , Azuma Shungo , Hanaoka Daishin , Tanaka Yasushi , Miyazato Shinichi , Kageyama Kazuro , Murayama Hideaki 
Published: September 2023

Abstract
Carbon fiber reinforced plastic prestressed concrete (CFRPC) is a material that utilizes CFRP strand cables as tendons, exhibiting exceptional performance in terms of specific stiffness, strength, and high corrosion resistance [1]. Particularly when used in offshore structures, it is considered to overcome the drawbacks of steel strand cables [2]. In this study, we propose the use of fiber-optic sensors to assess the structural integrity when considering the application of CFRPC to long-life offshore structures. We perform two experiments. First, we conduct tensile tests on three types of CFRP strand cables and one steel strand cable to measure the strain distributions and understand the differences in mechanical properties between the steel and CFRP strand cables, as well as differences between different types of CFRP coatings. Second, we fabricate a CFRPC beam with the CFRP strand cable and bond fiber-optic sensors to a CFRP strand and outside of the concrete beam to measure the strain distribution and verify the feasibility of structural health monitoring of CFRPC. Through these two experiments, we continuously measure the strain along the length of the CFRP strand and the strain distribution of CFRPC from the introduction of prestress until the crack develops. We also investigate the relationship with the breakage behavior and evaluate the mechanical properties, such as the stiffness of the strand cables during the tensile test.
Study on Self-Propelled Wake Characteristics of Surface Ship
Authors: Xiang Han , Deng Weihua , Zou Yanlin , Wang Xunming , Feng Dakui 
Published: September 2023

Abstract
The complex wake generated by the coupling of the propeller rotating wake, the separated wake and the free surface wave-making has a great influence on the multi-ship parallel, replenishment and recovery. The study of self-propelled near-field wake of surface ships is of great significance to the design of ships close to the mother ship, such as recovery boats. This paper focuses on the near-field turbulent wake, propeller rotating wake and Kelvin wake area behind the hull. The ship model DTMB5415M with the propeller model PROP4058 is selected as the research object. URANS simulation method is used to simulate the wake velocity, flow field pressure. The wave pattern, and the wake velocity are simulated and analyzed. The wave height distribution, velocity distribution of the hull wake field and the flow characteristics are obtained. Grid Sensitivity verification is done and the grid is monotonically convergent. At the same time, the wave crest and trough cross sections are found. Taking into account the smallest possible wave height and speed, as well as the shortest possible distance, the optimal path for the recovery boats can be planned.