bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vortex-Induced Motion of a Novel Mono-Column FPSO in Waves and Currents
Authors: Gu Jian , Zhao Zhanhua , Yin Yan , Fan Yali , Han Xiangxi 
Published: August 2024

Abstract
The mono-column FPSO platform has recently attracted more attention from researchers due to its advantage of stability in waves and currents relative to the traditional Spar platform with the larger draft. However, the heave motion of the mono-column platform becomes a concomitant disadvantage for this type of platform. The submersible appendix is usually designed to suppress the heave motion of the platform, which could interrupt the flow patterns around the column. The vortex-induced motion (VIM) of the platform could be much different from the original column or Spar platform. The present article initially investigates the VIM performances of a novel mono-column FPSO with a heave suppression structure. The performance is studied numerically in the case of both currents only and currents with waves, respectively. The dependency of mesh and time step are observed to validate the numerical model. The characteristics of inflow and cross-flow responses are analyzed comprehensively. Further, the influence of waves is found limited to the overall responses of vortex-induced motion in the given cases. The present article is significant to the design of the novel mono-column FPSO platform and provides references for further study of vortex-induced motion.
An Attention-Based Deep Learning Model for Phase-Resolved Wave Prediction
Authors: Chen Jialun , Gunawan David , Zhao Wenhua , Taylor Paul H. , Chen Yunzhuo , Milne Ian A. 
Published: August 2024

Abstract
Phase-resolved wave prediction capability, even if only over two wave periods in advance, is of value for optimal control of wave energy converters (WECs), resulting in a dramatic increase in power generation efficiency. Previous studies on wave-by-wave predictions have shown that an Artificial Neural Network (ANN) model can outperform the traditional linear wave theory-based model in terms of both prediction accuracy and prediction horizon when using synthetic wave data. However, the prediction performance of ANN models is significantly reduced by the varying wave conditions and buoy positions that occur in the field. To overcome these limitations, a novel wave prediction method is developed based on the neural network with an attention mechanism. This study validates the new model using wave data measured at sea. The model utilizes past time histories of three Sofar Spotter wave buoys at upwave locations to predict a Datawell Waverider-4 at a downwave location. The results show that the attention-based neural network model is capable of capturing the slow variation in the displacement of the buoys, which significantly reduces the prediction error compared to a standard ANN model.
Numerical Simulation of Concurrent Flexural and Crushing Failure of Level Ice
Authors: Mokhtari Mojtaba , Kim Ekaterina , Amdahl Jørgen 
Published: August 2024

Abstract
This study presents a novel approach for simulating the concurrent flexural and crushing failure of level ice when interacting with sloping structures. The mechanical behaviour of ice is simulated by a nonlinear viscoelastic constitutive model with progressive damage, accounting for microstructural evolution and phase transitions in polycrystalline ice under compression. The constitutive model, scripted in Fortran, has been validated against laboratory-scale physical tests.
To simulate the flexural failure of ice, the ice domain is first discretized with hexahedral finite elements that do not share nodes with their neighbouring counterparts in the in-plane directions. Then, a cohesive contact model with a traction-separation law and damage evolution is implemented to define cohesive interaction behaviour at the vertical interface of adjacent elements. This model, based on a Discrete Finite Element Method (DFEM), allows for the computation of multiple crack initiations and propagations, effectively simulating ice fragmentation into rubble. Therefore, the proposed ice model eliminates the need for predetermining ice breaking length, a notable limitation in prior studies that utilized the cohesive zone method.
To validate the ice model, a numerical model of an ice-breaking cone mounted on a jacket structure in the Bohai Sea interacting with drifting level ice is developed. Good agreement between the numerical results and the field measurements is achieved, which demonstrates the effectiveness of the proposed ice model.
Extreme Wave Run-Up Loads on Monopile Appurtenances: A Practical Guide
Authors: Bermejo Jimenez Ana , Skourup Jesper , Lykke Andersen Thomas , Garborg Karsten , Ankerstjerne Rolland Louise 
Published: August 2024

Abstract
Monopiles are often the preferred foundation concept for an offshore wind turbine. The interaction between extreme waves and the large diameter monopile will in some cases result in a vertical jet of water uprush on the monopile (i.e., wave run-up) which subsequently may lead to large slamming loads on monopile appurtenances like the external working platform.
Extreme wave run-up interaction with an external working platform is often an area of concern during the design phase of an offshore wind project as an overly conservative assessment of the run-up loads may lead to unneeded costs in material and an increased project carbon footprint. An insufficient assessment of the run-up loads may lead to structural failure of the appurtenances and subsequent costly maintenance and repair works, further exacerbated by possibly difficult access to the damaged platform.
The practical process in the assessment of wave run-up on monopiles and associated loads on appurtenances can be a challenge to the designer due to lack of guidance on this topic in governing standards. The designer may then have to rely on several sources of available literature and must assess and include the effect of associated uncertainties like: Adjustment to site specific environmental conditions, unclear or unconcise terminology in the literature, lack of model test results representing the actual geometry and limited knowledge of spatial and temporal run-up load distribution on the appurtenances.
The aim of the present paper is to describe a complete methodology for assessment of wave run-up on monopiles and associated loads on appurtenances. The methodology, which will serve as a practical guide, is based on a collection of existing methods with new analysis to consider the pressure distribution on modern asymmetric grated platforms. This was based on experiences gained and challenges encountered during a detail design project of a monopile foundation for an offshore wind turbine in extreme environmental conditions. The sensitivity of the run-up assessment related to the design input (water depth, wave height and period, associated water level and current conditions) is discussed by considering a matrix with various environmental input combinations representing extreme environmental conditions.
Effects of Temperature and Water on the Fatigue Performance of Composite Materials and Steel-Composite Bonded Interfaces
Authors: Karpenko Olena , Egilsson Sigurdur , Moreira Arouche Marcio , Pavlović Marko 
Published: August 2024

Abstract
This work investigates the effect of temperatures and salt water exposure on the fatigue performance of Glass Fibre-polymer Composite and composite-to-steel interfaces. Four-point end notched flexure tests are employed to gauge interface fracture behavior under the fatigue loading, along with cyclic tensile tests for material assessment. A digital image correlation system is employed to track the progressive crack development on the steel-composite interface, while an extensometer paired with thermocouples are integrated in the fatigue testing of the composite material. As the result the fatigue crack propagation behavior and material fatigue performance are compared between reference and temperature/moisture exposed specimens.
Non-Stationary Equivalent Storm Model for Long-Term Statistics of Ocean Storms
Authors: Laface Valentina , Arena Felice , Bitner-Gregersen Elzbieta 
Published: August 2024

Abstract
In the last decade many researchers focused on the study of non-stationary pattern of climatic variables., It is well established that marine signals e.g., significant wave height or sea water level exhibit a long-term trend due to climate change. The classical approach for the estimation of extreme values analyses may not be enough reliable. The need to account for non-stationarity has involved the development of non-stationary extreme value analysis (NS-EVA) approaches. The main idea is to modify the classical extreme value analysis approach by using non-stationary distributions instead of the stationary ones. Non-stationary probability distributions are analogue to the stationary ones, but their parameters are time dependent. The time dependency may involve all or some of the distribution parameters which may be expressed in different ways. In this paper, this basic concept is applied to develop a non-stationary Equivalent Storm Model (ESM) using the concept of Equivalent Triangular Storm (ETS). The ESM approach is a semi-analytical approach based on the statistic equivalence between actual and an associated simplified storm characterized by a standardized storm shape which leads to the equivalence of wave risk between actual storm sequence and simplified storm sequence at a given site. Due to the equality of wave risk between actual and simplified storm sequences, the problem of calculating return period of sea storm with assigned characteristics can be managed analytically referring to the standardized storm shape, providing very simple analytical formulae dependent on the significant wave height probability distribution and on a duration-intensity regression function at the considered site. The non-stationary ESM is achieved by substituting these two stationary functions with time dependent ones in a similar way as NS-EVA does. A data analysis is proposed to elucidate the differences on significant wave height return values estimation between stationary and non-stationary ESM approach due to non-stationarity of significant wave height and storm duration.
Recognition of Surface Corrosion Morphology on Coastal Engineering Structures Using Machine Vision Technology
Authors: Yu Qifeng , Han Yudong 
Published: August 2024

Abstract
The harsh marine atmospheric conditions, including high temperatures, humidity, and salt spray, prevalent in the coastal areas of Hainan, pose a significant challenge to the durability of ground facilities and equipment, often resulting in corrosion and functional degradation. Hence, accurate monitoring of corrosion is paramount for maintaining coastal engineering structures. This study leveraged data from the Chinese National Center for Materials Corrosion and Protection Science to extract corrosion morphology features using image analysis techniques. Subsequently, a corrosion identification model was developed using machine learning algorithms. The model’s accuracy was validated through various evaluation metrics. The research outcomes have practical applications in the maintenance and management of coastal engineering structures by providing automatic corrosion morphology recognition. This enables maintenance personnel to promptly undertake repair measures, thereby reducing maintenance costs and enhancing structural sustainability.
An Investigation of Winter Navigation and Icebreaker Needs in the Ice-Infested Water: The Gulf of Finland and the Gulf of Riga
Authors: Lu Liangliang , Kondratenko Aleksandr , Kulkarni Ketki , Li Fang , Kujala Pentti , Musharraf Mashrura 
Published: August 2024

Abstract
With climate change, the ice cover in the Arctic and subArctic regions is likely to change relatively quickly. The Baltic Sea is a region with much maritime traffic and meanwhile some parts are covered by ice during wintertime. Icebreakers are usually needed in this region to assist the traffic in ice. However, icebreakers are a limited and expensive resource, and the number of vessels waiting for assistance often outnumbers the available icebreakers. Therefore, whether the current icebreaker strategy needs to change under the impact of the changing ice environment is important. This paper aims to establish a wintertime traffic simulation model with icebreaker assistance for an ice-infested area, i.e., the Gulf of Finland and the Gulf of Riga to see the possible trend. The model is developed with traffic data, ice data and icebreaker information, etc. With the model developed, investigations are conducted by varying different parameters to estimate their effect on the system. This way, the icebreaker needs under different future winter scenarios can be estimated with appropriate system behavior indicators calculated. The results show that the different winter scenarios have quite different icebreaker needs and system behaviors.
Analysis of Higher Harmonic Loads on a Fixed Truncated Vertical Cylinder
Authors: Chen Junru , Feng Xingya , Li Ye 
Published: August 2024

Abstract
Understanding the characteristics of the nonlinear extreme waves loading has both scientific and economic benefits of the offshore structures design. This paper investigates the higher-harmonic loads on a fixed truncated vertical circular cylinder under the action of nonlinear focused waves. This is the concern of the excitation force on the foundation of the cylindrical floating wind turbines in extreme waves. In order to analyse the higher-harmonic loads, focused wave groups are generated by a fully nonlinear potential flow model based on the assumption of a “Stokes-type” nonlinear harmonic structure. A general phase-based harmonic decomposition method is employed for the higher-harmonic hydrodynamic loading on a fixed structure in water waves of moderate steepness. The local wave elevations around the structure are also visualized and compared with the pure wave elevations for the first three harmonics in order to reveal the local dynamics driving higher harmonic loads. The results show that the higher-harmonic load components satisfy the nonlinear harmonic structure of the Stokes expansion. Accordingly, higher-harmonic loads of a focused wave group on the fixed truncated vertical circular cylinder can be estimated by a simple mathematical model with the linear component. The simple estimation results are compared with both the experimental data and the analytical solutions to validate the accuracy.
Diving Into Subsea Decommissioning: the Challenge of an Economic Approach Beyond Costs Model
Authors: Santos Thauan , Santos Luan , Fontainha Tharcisio , Infante Carlos Eduardo , Grangeia Carol , Nascimento Annyeli , Cordon Marco , Tosto Giovanna , Ivo Marcelo 
Published: August 2024

Abstract
This article aims to identify national and international studies and practical experiences in the economic analysis related to subsea decommissioning, in order to identify the best alternatives applied to the Brazilian case. Since the country has a schedule of offshore structures to be decommissioned in the coming decades, studies are needed to support public policymakers by proposing sustainable strategies in line with international standards and practices. To this end, the methodology initially used a literature review based on bibliometric analysis, using scientific publications available on the Scopus and Web of Science databases. Lastly, the article highlights the importance of the multi-criteria analysis to define decommissioning alternatives considering not only economic results, but other perspectives, such as social, environmental, and waste. As the main results, the research identifies the lack of literature and the sectoral limitations of current best practices worldwide. The main reasons for those limitations are the disparity of projects and technological and regional characteristics, and consequently difficulties for costs measurements and benchmarking; lack of professional capabilities on sustainable subsea decommissioning, limited availability of studies, and fragmented regulatory approach on this matter.
Barge Maneuvering Using a Fleet of Autonomous Surface Vessels: Simulations and Experiments
Authors: M. de Andrade Emerson , Fernandes Antonio C. , Sales Junior Joel S. 
Published: August 2024

Abstract
In recent years, there has been a growing trend in the use of autonomous surface vessels for various everyday tasks. These vessels’ capabilities include, for instance, monitoring water quality, surveillance, passenger transportation, and underwater mapping. However, overcoming the challenge of using autonomous surface vessels to transport larger vessels and floating structures is not an easy task, requiring a multidisciplinary approach. In our study, we delve into the potential of employing six autonomous surface vessels to transport a non-self-propelled rectangular barge. Our methodology is based on numerical and experimental tests. In the first part, we prepare our simulations using the 3D Gazebo Simulator and the Robot Operating System (ROS), where we build models for both the barge and the autonomous surface vessels (ASVs). These vessels maneuver using a non-linear approach, taking into account the characteristics of each floating object to calculate the forces and moments during the simulations. To proceed with the transportation of the barge, we implement a PID controller and a thrust-allocation algorithm. Then, we build reduced-scale models to carry out experimental tests in the visualization tank at the Laboratory of Waves and Current (LOC/COPPE/UFRJ). Finally, our combined numerical and experimental findings confirm the viability of using a fleet of autonomous surface vessels and our proposed approach for barge transportation.
Early Lost Circulation Monitoring Using a Hybrid CNN-LSTM Model
Authors: Wu Liwei , Han Liang , Li Gensheng , Song Xianzhi , Zhang Qilong , Zhang Rui , Zhang Ziyue 
Published: August 2024

Abstract
Lost circulation is one of the most common issues affecting drilling safety, known for its sudden occurrence. Traditional expert diagnosis methods heavily rely on expert experience, exhibiting a high degree of subjectivity and lag. Conventional machine learning approaches struggle to fully capture the spatial and temporal variations within the multidimensional data of lost circulation, leading to insufficient accuracy. To address the challenge, this paper proposes an early intelligent monitoring hybrid model for lost circulation by concatenating Convolutional Neural Network (CNN) and Long Short-Term Memory Neural Network (LSTM). Initially, sliding window method is employed to structure historical data of lost circulation into time series samples. Subsequently, these time series samples are input into one-dimensional CNN network to extract spatial feature vectors. Following this, the extracted feature vectors are input into LSTM network to uncover temporal feature information. Finally, the Softmax function is applied at the network’s output layer for classification. The proposed model is tested on real dataset of lost circulation. The results show that the performance of this hybrid model is superior to traditional machine learning models, with accuracy of 94%, missed alarm rate of 4%, and false alarm rate of 8% on the test set. Compared with expert diagnosis, hybrid model can detect lost circulation risk earlier and significantly improve monitoring timeliness. This study is of great significance for ensuring drilling safety and improving drilling efficiency.
Comprehensive Hydrodynamic Performance Evaluations of Representative Atlantic Canadian Fishing Vessels
Authors: Islam Mohammed , Akinturk Ayhan , Faramarzifar Ali 
Published: August 2024

Abstract
Domestic vessel designs are generally aimed at satisfying certain operational specifications, not targeting optimized fuel consumption, greenhouse gas (GHG) emissions or Underwater Radiated Noise (URN) generation. This can be observed in Canadian domestic vessels, as Canada encompasses vast maritime terrain and a long history of shipping and fishing industry. The situation may be more challenging for Canadian fishing vessels, primarily constructed to satisfy economic needs that meet the minimum jurisdictional requirements. The high length/beam ratio, deep hull shape, off-the-shelf propeller and rudder and other hull appendages are often selected to maximize the profit/capacity and with insufficient attention to their impacts on the hydrodynamic performance, stability and the GHG and URN emission aspects. The impact of the not-well-designed propeller, rudder, and hull shape and appendages on various performance indices such as fuel consumption and greenhouse gas (GHG) emissions (powering performance), manoeuvring, seakeeping and URN emissions are poorly understood.
The primary objective of this research is to gain insights into existing designs of Canadian fishing vessels’ hull, propeller, rudder and appendage systems to improve understanding of the hydrodynamic interactions and the resulting impacts on performance efficiencies, GHG and URN emissions. As the first step in achieving this objective, the research team has selected and physically modelled a representative Atlantic Canadian fishing vessel at a suitable scale. The team utilized both physical and numerical modelling tools and techniques to conduct the investigations on the hydrodynamic performance evaluations of the fishing vessel model at realistic operating conditions in terms of bare and appended hull resistance, powering predictions using self-propulsion tests, free running manoeuvring and seakeeping performance. This paper presents the preliminary results of the physical and numerical modelling campaign, specifically investigations of the effects of a hull appendage known as a keel cooler. This work improves understanding of the interactions between the vessel, propeller, rudder, and hull appendages regarding hydrodynamic, dynamic stability and GHG and URN emissions performance.
Combining Drilling Condition Analysis With Unsupervised Time Series Models for Kick Monitoring
Authors: Zhou Detao , Zhu Zhaopeng , Li Gensheng , Song Xianzhi , Han Liang , Li Qihao , Zhou Chenzhan 
Published: August 2024

Abstract
With the continuous development of petroleum exploration and production technology and the increasing complexity of geological conditions, the problem of narrow-margin safe drilling has become a major challenge in the field of petroleum exploration and development. Kick is also one of the high-frequency, high-hazard accidents in drilling. To reduce drilling costs and improve drilling safety, it is crucial to accurately monitor kicks and prevent their further development. A method for monitoring kick, based on the variation of logging parameters, currently exists. However, it does not take into account the impact of abnormal conditions such as pump stoppages on the outlet flow rate and the total volume of drilling fluid in the tank, which can lead to false alarms. In order to improve the accuracy of risk identification and reduce the false alarm rate, a kick monitoring method is proposed that combines drilling conditions with an unsupervised Bidirectional Long Short-Term Memory Autoencoder (BiLSTM-AE). This model simultaneously considers past and future information through forward and backward propagation, effectively extracting temporal features from sequences using bidirectional information. The proposed method was tested using kick monitoring data from 3 wells. The experimental results indicate that the recognition accuracy of the kick intelligent monitoring model based on BiLSTM-AE is 88.85%, surpassing other existing intelligent monitoring models. When combined with abnormal conditions such as pump stoppages, the model’s false alarm rate is reduced by 9.33%.
This research can provide a theoretical foundation and important technical reference for accurate kick risk monitoring, especially in conditions where kick risk data labels are lacking. Moreover, it holds significant potential for practical field applications.