bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural Analysis and Load Monitoring of a Loss of Tension Incident
Authors: Fjeldstad Dag André , Liu Junyan , Moe Per Thomas , Gustad Halvor S. , Hansen Mathias , Bjørset Arve 
Published: October 2021

Abstract
Monitoring of riser motion and loads is increasingly being used to assess metal fatigue and to assist rigs in operating safely. Monitoring systems provide valuable information on unexpected incidents. This paper shows how sensor data have been used in combination with structural analysis to assess consequences of a loss of tension for a top-tensioned CWO riser. In order to avoid that a single failure in a tensioning system causes total loss of tension and riser buckling risers should be operated using both rucker tensioners and top drive. However, prior to the retrieval of the riser only top tension was applied. Due to a power out the top drive tension was lost, and the resulting set down caused the riser to buckle. The consequence could in the worst case have been permanent damage to key riser components such as the Lower Tapered Stress Joint and Weak Link. However, as the riser was equipped with a monitoring system that provided accurate data on deformation at key locations, it was possible to show that the system had not been exposed to permanent deformations and could be safely used further. It is advisable to perform continuous monitoring of tension and put in place mitigation to avoid that such incidents lead to permanent damage in the future.
Benchmark Study of Supervised Machine Learning Methods for a Ship Speed-Power Prediction at Sea
Authors: Lang Xiao , Wu Da , Mao Wengang 
Published: October 2021

Abstract
The development and evaluation of energy efficiency measures to reduce air emissions from shipping strongly depends on reliable description of a ship’s performance when sailing at sea. Normally, model tests and semi-empirical formulas are used to model a ship’s performance but they are either expensive or lack accuracy. Nowadays, a lot of ship performance-related parameters have been recorded during a ship’s sailing, and different data driven machine learning methods have been applied for the ship speed-power modelling. This paper compares different supervised machine learning algorithms, i.e., eXtreme Gradient Boosting (XGBoost), neural network, support vector machine, and some statistical regression methods, for the ship speed-power modelling. A worldwide sailing chemical tanker with full-scale measurements is employed as the case study vessel. A general data pre-processing method for the machine learning is presented. The machine learning models are trained using measurement data including ship operation profiles and encountered metocean conditions. Through the benchmark study, the pros and cons of different machine learning methods for the ship’s speed-power performance modelling are identified. The accuracy of various algorithms based models for ship performance during individual voyages is also investigated.
Performance Modeling of a Variable-Geometry Oscillating Surge Wave Energy Converter on a Raised Foundation
Authors: Burge Cole , Tom Nathan , Thiagarajan Krish , Davis Jacob , Nguyen Nhu 
Published: October 2021

Abstract
This paper analyzes the power capture potential, structural loadings, and costs associated with an oscillating surge wave energy converter (OSWEC) operating on a raised foundation. The raised OSWEC offers opportunities for reduced installation costs, improved energy production, and greater flexibility of deployment when compared with fixed-bottom models. In this investigation, we simulated several different foundation geometries using WEC-Sim to estimate power capture and structural loads. In an effort to maximize power capture, several cases in which flat plates of varying size were attached to the top of the foundation, under and parallel with the OSWEC, were also simulated. These plates were found to enhance power capture by preventing the wave-induced pressure from passing underneath the OSWEC, diverting this pressure toward the OSWEC instead. The OSWEC was simulated in the six Wave Energy Prize sea states, which were chosen as a representative sample of U.S. deployment sites. A first-order estimate of structural costs was calculated using the Wave Energy Prize ACE metric, with the foundation comprised predominantly of steel-reinforced concrete and the OSWEC comprised of A36 steel. Influence of foundation geometry on power capture, structural loadings, and ACE are topics of particular interest. This work has been inspired by advances in large-scale additive manufacturing techniques that have the potential to dramatically reduce the cost of subsea foundations. These advancements may enable cost-effective WEC systems to be deployed on raised foundations.
On Lifetime Extension of Wind Turbine Drivetrains
Authors: Tartt Kelly , Nejad Amir R. , Kazemi-Amiri Abbas , McDonald Alasdair 
Published: October 2021

Abstract
The focused shift to reduce carbon emissions by substituting fossil fuels with renewable energy sources, including wind, is increasing. This means that more and more wind turbines are being installed, both onshore and offshore and as this number increases, more and more turbines are reaching their end of designed service life. Extending this designed service life, which is commonly referred to as lifetime extension (LTE), is particularly favoured by owner/operators, due to economic reasons. Whilst there are relatively well-established practices for lifetime extension of structural members or those preserving structural integrity, the electro-mechanical and drivetrain systems are often overlooked. Therefore, this paper reviews lifetime extension assessment practices executed within a variety of industries, such as oil and gas, marine vessels, electrical machines, mechanical rotating equipment and bearings, to determine if any of these practices can be implemented or adapted within the wind industry, particularly on wind turbine drivetrains.
Numerical Analysis of Cuttings Accumulation Tendency in Horizontal Annulus at Different Drilling Conditions
Authors: Rasul Golam , Rahman Mohammad Azizur , Butt Stephen 
Published: October 2021

Abstract
The influence of rotational speed and eccentricity of the drill pipe as well as the effect of fluid flow rate on the accumulation of cuttings in the horizontal annulus are the focus of this study. Computational Fluid Dynamics (CFD) is utilized to model a horizontal annulus section which conveys solid-liquid two-phase flow at different drilling conditions. In this numerical study, the Eulerian multiphase flow model has been adopted for solidliquid characteristics analysis. Here the basic continuity and momentum equations have been considered, which have further been reduced to solve the conservation of mass and momentum equations with appropriate boundary and initial conditions. The study has considered the transient, turbulent model (k-epsilon) with no-slip conditions at pipe walls as well as velocity inlet and pressure outlet at the boundaries. The result indicates the clear impact of rotational speed on the cuttings removal process in the horizontal annulus section. As the rotational speed of the drill pipe increases, the cuttings concentration drops down significantly in the annulus section. Around 20% less accumulation is noticed if the drill pipe rotation is increased from 0 RPM to 120 RPM, which happens due to momentum created by the rotation that does not allow the particles to be accumulated. The eccentricity has a significant impact on solid accumulation as well. However, with increased flow rate and eccentricity, the pressure across the annulus section drops substantially. The difference in pressure drop is noticed as much as around 61 Pa/m with the flow rate change. Consequently, a higher pressure drop per length for the higher velocity of fluid implies higher pumping power consumption. The findings from this study may help to understand the optimum operating conditions for horizontal drilling. The effects of drilling conditions are identified and the complex multiphase flow in the annulus is modeled that could be extended to further related studies.
Development of Simplified Wear Estimation Method Considering Rolling Motion Between Mooring Chain Links for Floating Structures
Authors: Takeuchi Takaaki , Utsunomiya Tomoaki , Gotoh Koji , Sato Iku 
Published: October 2021

Abstract
For the development of floating offshore wind turbines (FOWTs) in Japan, reliability assessment and cost reduction by efficient maintenance on mooring chains are part of the key issues because sites deeper than 60 m require mooring systems for station keeping. In this paper, attempts have been made to simplify the wear estimation method which was previously proposed by using a 3-D rigid-body link model for improvement of accuracy. These investigations are performed about a spar-type floating structure moored with three catenary lines at Goto, Nagasaki prefecture, Japan.
In the previous study, it was confirmed that the estimation method using the 3-D link model can calculate the interlink wear amount closer to the chain diameter measurements and more reasonable than the method using the conventional mass-spring model by removing the rolling distance from the displacement of contact points. However, the estimation method has technical difficulty in terms of calculation of contact properties and analysis costs for the mooring chain design. For this reason, the wear estimation method is simplified and verified by considering the rolling motion between mooring chain links modeled by the widely employed mass-spring model based on the method proposed by Mooring Integrity JIP. Firstly, the wear due to the rolling is reproduced by a three-dimensional FE analysis to investigate the actual wear phenomenon including the effect of the proof load test as well as the idealized configuration. Secondly, the application method is proposed against the response of the mooring chain subjected to irregular waves Finally, a comparison with the measurement is conducted to verify the proposed wear estimation method.
Automatic Tsunami Barrier
Authors: Hamada Eigai , Morita Shoichi , Iiboshi Ayumu , Hiraishi Tetsuya 
Published: October 2021

Abstract
The Anti-Tsunami Laboratory (ATL) invented and developed the Anti-Tsunami Door (ATD) barrier as an automatic tsunami barrier. In September 2018, ATL and Kyoto University tested a mid-scale model of a three-stage ATD unit and confirmed its performance: (1) functioning automatically (refer to Figure 9); (2) achieving reasonable wave height reduction, which is approximately 40%–80% that of a solid barrier of the same height; and (3) demonstrating reasonable strength for a wooden structure under the mid-scale model test conditions. ATL had planned to test a large-scale model of an ATD unit in Oregon State University in May 2020, but that test has been delayed owing to the COVID-19 pandemic. Because the wave pressure on the ATD unit is expected to be high during the large-scale model test, ATL requested that the Explosion Research Institute (ERI) simulate the wave pressure on a large-scale model ATD unit, and based on the results, ATL will reinforce the ATD unit. After testing the large-scale model unit, ATL will install ATD barriers along the coast of Japan, customizing the barrier for specific tsunami hazards.
Application of Deep Learning Technique to Predict Downhole Pressure Differential in Eccentric Annulus of Ultra-Deep Well
Authors: Krishna Shwetank , Ridha Syahrir , Ilyas Suhaib Umer , Campbell Scott , Bhan Uday , Bataee Mahmood 
Published: October 2021

Abstract
Accurate prediction of downhole pressure differential (surge/swab pressure gradient) in the eccentric annulus of ultra-deep wells during tripping operation is a necessity to optimize well geometry, reduction of drilling anomalies, and prevention of hazardous drilling accidents. Therefore, a new predictive model is developed to forecast surge/swab pressure gradient by using feed-forward and backpropagation deep neural networks (FFBP-DNN). A theoretical-based model is developed that follows the physical and mechanical aspects of surge/swab pressure generation in eccentric annulus during tripping operation. The data generated from this model, field data, and experimental data are used to train and test the FFBP-DNN networks. The network is developed used Keras’s deep learning framework. After testing the models, the most optimal arrangement of FFBP-DNN is the ReLU algorithm as an activation function, 4-hidden layers, the learning rate of 0.003, and 2300 of training numbers. The optimum FFBP-DNN model is validated by comparing it with field data (Wells K 470 and K 480, North Sea). It shows an excellent argument between predicted data and field data with an error range of ±7.68 %.
Dynamic Ultimate Strength Characteristics of Stiffened Plates Subjected to the In-Plane Impact Load and Lateral Pressure
Authors: Zhong Qiang , Wang De-yu 
Published: October 2021

Abstract
Dynamic capacity is totally different from quasi-static capacity of ship structural components, although most ultimate strength analyses at present by researchers are performed under quasi-static conditions. To investigate the dynamic ultimate strength characteristics, the dynamic ultimate strength analyses of stiffened plates subjected to impact load were studied based on a 3-D nonlinear explicit finite element method (FEM) in this paper. The impact load in the present work is characterized as a half-sine function. A series of nonlinear finite element analyses are carried out using Budiansky-Roth (B-R) criterion. The influence of impact durations, model ranges, boundary conditions, initial imperfections and impact loads on the dynamic ultimate strength of stiffened plates are discussed. In addition, the ultimate strength of stiffened plates under the in-plane impact combined with lateral pressure was also calculated, which shows lateral pressure has a negligible effect on the dynamic ultimate strength of stiffened plates subjected to the impact load with short durations. Other important conclusions can be obtained from this paper, which are useful insights for the development of ultimate strength theory of ship structures and lay a good foundation for the study of dynamic ultimate strength in the future.
Hybrid Verification of a Deepwater FPSO Using Truncated Model Tests and Numerical Simulations
Authors: Liu Xiangbo , Liong Ching Theng , Kumar Nitesh , Chua Kie Hian , Magee Allan Ross , Choo Yoo Sang 
Published: October 2021

Abstract
This paper presents verification of a deep water FPSO with a semi-taut mooring system using model tests and numerical modelling commonly referred to as the hybrid method. The vessel under investigation is a FPSO of 310m in length and 47m in beam with an internal turret mooring system of 12 lines in 2000m water depth. Two configurations of the mooring systems i.e. inline and bisecting are investigated for sea-states up to 1000yr return period. A full depth mooring system has been developed for the FPSO and model tests will be carried out to verify the model. Due to limitations to the size of the model basins, the model tests will be carried out for a truncated mooring setup. Non-linear horizontal stiffness of a single mooring line and the complete mooring system with truncation is compared to that of the existing full depth mooring system. Discrepancies in the vertical forces due to truncation of line length will be discussed in the paper. A numerical model of the truncated set-up will be calibrated using model test results.
Neural Network Meta-Models for FPSO Motion Prediction From Environmental Data
Authors: Cotrim Lucas Pereira , Oliveira Henrique Barros , Queiroz Filho Asdrubal N. , Santos Ismael H. F. , Barreira Rodrigo Augusto , Tannuri Eduardo Aoun , Costa Anna Helena Reali , Gomi Edson Satoshi 
Published: October 2021

Abstract
The current design process of mooring systems for FPSOs is highly dependent on the availability of the platform’s mathematical model and accuracy of dynamic simulations, through which resulting time series motion is evaluated according to design constraints. This process can be time-consuming and present inaccurate results due to the mathematical model’s limitations and overall complexity of the vessel’s dynamics. We propose a Neural Simulator, a set of data-based surrogate models with environmental data as input, each specialized in the prediction of different motion statistics relevant to mooring system design: Maximum Roll, Platform Offset and Fairlead Displacements. The meta-models are trained by real current, wind and wave data measured in 3h periods at the Campos Basin (Brazil) from 2003 to 2010 and the associated dynamic response of a spread-moored FPSO obtained through time-domain simulations using the Dynasim software. A comparative analysis of different model architectures is conducted and the proposed models are shown to correctly capture platform dynamics, providing good results when compared to the statistical analysis of time series motion obtained from Dynasim.
Real Gas Effect on Gas Slippage Phenomenon in Shale
Authors: Chen Yufei , Leung Juliana Y. , Jiang Changbao , Wojtanowicz Andrew K. 
Published: October 2021

Abstract
The past decade has seen the rapid development of shale gas across the world, as the record-breaking success and on-going surge of commercial shale gas production in such unconventional reservoirs pose a tremendous potential to meet the global energy supply. However, questions have been raised about the intricate gas transport mechanisms in the shale matrix, of which the gas slippage phenomenon is one of the key mechanisms for enhancing the fluid transport capacity and, therefore, the overall gas production. Given that shale reservoirs are often naturally deposited in the deep underground formations at high pressure and temperature conditions (much deeper than most typical conventional deposits), the real gas effect cannot be ignored as gas properties may vary significantly under such conditions. The purpose of this study is thus to investigate the real gas effect on the gas slippage phenomenon in shale by taking into account the gas compressibility factor (Z) and Knudsen number (Kn).
This study begins with a specific determination of Z for natural gas at various pressures and temperatures under the real gas effect, followed by several calculations of the gas molecular mean free path at in-situ conditions. Following this, the real gas effect on gas slippage phenomenon in shale is specifically analyzed by examining the change in Knudsen number. Also discussed are the permeability deviation from Darcy flux (non-Darcy flow) due to the combination of gas slippage and real gas effect and the specific range of pressure and pore size for gas slippage phenomenon in shale reservoirs.
The results show that the gas molecular mean free path generally increases with decreasing pressure, especially at relatively low pressures (&lt; 20 MPa). And, increasing temperature will cause the gas molecular mean free path to rise, also at low pressures. Knudsen number of an ideal gas is greater than that of a real gas; while lower than that of a real gas as pressure continues to rise. That is, the real gas effect suppresses the gas slippage phenomenon at low pressures, while enhancing it at high pressures. Also, Darcy’s law starts deviating when Kn &gt; 0.01 and becomes invalid at high Knudsen numbers, and this deviation increases with decreasing pore size. No matter how pore size varies, this deviation increases with decreasing pressure, meaning that the gas slippage effect is significant at low pressures. Finally, slip flow dominates in the various gas transport mechanisms given the typical range of pressure and pore size in shale reservoirs (1 MPa &lt; P &lt; 80 MPa; 3 nm &lt; d &lt; 3000 nm). Gas transport in shale is predominantly controlled by the slippage effect that mostly occurs in micro- or meso-pores (10 to 200 nm). Moreover, considering the real gas effect would improve the accuracy for determining the specific pressure range of the gas slippage phenomenon in shale.
The Use of Mathematical Programming to Determine Optimal Production and Drilling Schedule in an Offshore Oil Field, A Case Study From the Barents Sea
Authors: Lei Guowen , Stanko Milan , Silva Thiago Lima , Widerøe Tom , Skogvang Arnljot 
Published: October 2021

Abstract
A field with two neighboring reservoirs was discovered in the Barents Sea in 2013 and 2014. After a successful extended well test of an appraisal well in 2018 and initial field planning tasks, a preliminary drilling and production schedule was proposed based on cross-domain collaboration and group work involving several disciplines. In this paper, mathematical programming is employed to model and optimize the economic value of the project in order to determine the best drilling and production schedule for the field. The optimization includes some of the technical constraints considered by the field development team while also considering uncertainties such as reservoir size, productivity of well, and cost. These have been systematically evaluated by using simulation-based optimization (sampling). The results were that the use of mathematical programming allows the field planner to evaluate several scenarios within a reasonable time frame, thereby enabling rapid changes in the decisions to respond to new information and risk considerations in a dynamic environment. This paper illustrates the benefits of utilizing mathematical programming in early field planning to optimize the drilling and production schedule.
Helical Flow of Drilling Mud With Cuttings in a Vertical Well
Authors: Ignatenko Yaroslav , Gavrilov Andrey , Bocharov Oleg 
Published: October 2021

Abstract
The paper presents the results of an investigation into drilling mud flow with cuttings in a vertical well. The drilling mud rheology was described with the Herschel-Bulkley model. The axial Reynolds number was around 1000, the flow regime changing together with drill pipe RPM. The investigation covered the flow’s structures, integral parameters and cuttings transport in relation to drill pipe RPM and rate of penetration (ROP). In the laminar flow, most of the particles were localized in the quasi-solid region to move together with the last; the integral parameters had little dependence on drill pipe RPM increase. Increasing drill pipe RPM resulted in formation of the Görtler vortices near the channel’s external and internal walls, whose interaction led to the formation of smaller eddies converting the flow into a turbulent one. Due to the turbulence dispersion, the region taken by the particles widened. Particles suppress the vortex intensity near the channel’s external wall. Under the conditions described, increasing drill pipe RPM and ROP resulted in higher pressure drops and lower transport efficiency.