bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring and Performance Evaluation of Plastic Cleanup Systems: Part II — Results and Analysis
Authors: Sainte-Rose Bruno , Wrenger Hendrik , Soares Ivan , Mosneron-Dupin Cosme , Duval Clara , Planchat Alban 
Published: December 2020

Abstract
The Ocean Cleanup Foundation is developing floating barrier systems to concentrate and extract buoyant plastic from the global accumulation zones. In that context, two cleanup systems have been designed, built and deployed in the Great Pacific Garbage Patch since 2018 to evaluate their performance in the field for which a large amount of data has been collected. This data serves to validate and calibrate numerical models that will be used to develop future generations of cleanup systems.
The main performance indicator in scrutiny is the field efficiency which can be derived from on the one hand the barrier horizontal motion in terms of displacement and span heading and on the other hand the plastic transport around and inside the barrier. After a first part dedicated to the presentation of the experimental campaign carried out to evaluate the field efficiency of the second cleanup system, this second part is dedicated to the presentation of some results and analysis performed to evaluate the interception efficiency.
This paper first focuses on the cross comparison of two measurement techniques to evaluate the barrier span length and heading, second the metocean models in terms of waves and wind are presented and compared against the available metocean measurements. Then, a multi-linear model is proposed to evaluate the barrier dynamics from the background metocean conditions and applied to the analysis of the barrier in the lifting bag configuration. Finally, the multi-linear model is compared to measured relative speed for all the drifter tests carried out in the campaign the whole test campaign.
Machine Learning Models With Engineering Insight: Case Studies From the Oil and Gas Industry
Authors: Chakraborty Ishita , Kluk Daniel , McNeill Scot 
Published: December 2020

Abstract
Machine learning is gaining rapid popularity as a tool of choice for applications in almost every field. In the oil and gas industry, machine learning is used as a tool for solving problems which could not be solved by traditional methods or for providing a cost-effective and faster data driven solution. Engineering expertise and knowledge of fundamentals remain relevant and necessary to draw meaningful conclusions from the data-based models. Two case studies are presented in different applications that will illustrate the importance of using engineering domain knowledge for feature extraction and feature manipulation in creating insightful machine learning models. The first case study involves condition-based monitoring (CBM) of pumps. A variety of pumps are employed in all aspects of the oilfield life cycle, such as drilling, completion (including hydraulic fracturing), production, and intervention. There is no well-established method to monitor the pump fault states as they are operating based on sensor feedback. As a result, maintenance is performed either prematurely or reactively, both of which result in wasteful downtime and unnecessary expense. A machine learning based neural network model is used for identifying different fault states in a triplex pump from measured pressure sensor data. In the second case study, failures of mooring lines of an offshore floating production unit are predicted from the vessel position data. Identifying a damaged mooring line can be critical for the structural health of the floating production system. In offshore floating platforms, mooring line tension is highly correlated to a vessel’s motions. The vessel position data is created from running coupled analysis models. A K-Nearest-Neighbor (KNN) classifier model is trained to predict mooring line failures. In all the case studies, the importance of combining a deep understanding of the physics of the problem with machine learning tools is emphasized.
Second Order Difference Frequency Wave-Current Loading Using Kelvin-Newman Approximation
Authors: Bakti Farid P. , Kim Moo-Hyun 
Published: December 2020

Abstract
Kelvin & Newman introduced a linearization method to include the current (or forward speed) effect into the diffraction & radiation wave field for large-slender floating bodies. The K-N method assumes a steady far-field current while disregarding the steady potential field due to the presence of the body. The method is proven to be reliable when the Froude number is relatively small, the body shape is relatively slender (∂∂x≪∂∂y,∂∂z), and the sea condition is mild. This requirement is fulfilled for typical FPSOs and ship-shaped vessels in a typical current (or forward speed) condition. Several studies suggested that the presence of the current might change the first order hydrodynamic coefficients such as the first order diffraction force, added mass, and radiation damping. Currents also contributed to a change in the second-order slowly-varying drift force. However, the effect of current in the second-order difference-frequency force is yet to be investigated. By expanding the Kelvin-Newman approximation up to the second order, and solving the problem in the frequency domain, we can save computational time while expanding the accuracy of the scheme.
The second order quadratic force is the main focus of this study, since it is the main contributor to the total second order difference frequency forces especially near the diagonal. By implementing the Kelvin-Newman wave current interaction approach up to the wave’s second order, we can assess the performance of the Kelvin-Newman wave current interaction formulation in various sea conditions.
A Convenient Technology to Calculate Geomechanical Properties From Drilling Data
Authors: Tahmeen Mazeda , Hareland Geir , Hayes John P. 
Published: December 2020

Abstract
The multistage hydraulic fracturing is the best practice to stimulate unconventional hydrocarbon reservoirs for optimal production. Recent studies suggested that selective stimulation design could significantly increase production rates at a reduced cost rather than using non-selective geometric stages. An optimal design needs detailed logging and core information to selectively perforate and optimize the stimulation treatment. In most cases, the non-selective evenly spaced geometric stimulation design is used, primarily due to the time consuming and expensive conventional logging tools and techniques.
In this article, a 3D wellbore friction model is used to estimate the effective downhole weight on bit (DWOB) from the drilling data, directional survey data and drill string information. The estimated DWOB is used as an input to the inverted rate of penetration (ROP) model along with other drilling data, drill bit specifications and reservoir specific formation constants, to calculate rock mechanical and reservoir properties including, compressive strength, Young’s modulus, porosity, permeability and Poisson’s ratio without the use of expensive downhole logging tools. The rock brittleness index is calculated from the relationship between Young’s modulus and Poisson’s ratio based on the definitions of rock brittleness used in recent years.
The field data from horizontal drilling of three sample wells were used to investigate the geomechanical properties in the Montney shale formation and the lower Eagle Ford formation in North America. The calculated geomechanical properties were compared to the corresponding test analysis on cores. The authors investigated the rock brittleness index from the sample well data drilled horizontally in the lower Eagle Ford formation. This novel technology could help geologists and reservoir engineers better exploit unconventional reservoirs leading to optimal selective stimulations and greater net present value (NPV).
Relative Motion During Single Blade Installation: Measurements From the North Sea
Authors: Sander Aljoscha , Haselsteiner Andreas F. , Barat Kader , Janssen Michael , Oelker Stephan , Ohlendorf Jan-Hendrik , Thoben Klaus-Dieter 
Published: December 2020

Abstract
During single blade installation in offshore wind farms, relative motion between nacelle and blade root due to wind and wave excitation pose a significant challenge. Wave excitation can be modelled considerably well by employing state-of-the-art simulation tools and can, therefore, be included in installation planning. Other phenomena, such as flow-induced vibrations are hard to capture and hence challenging to account for when defining installation procedures and limitations. Here, we present measurements conducted during the installation of an offshore wind farm consisting of multi-megawatt turbines installed on monopile foundations in the North Sea. A custom-built sensor capturing linear & angular acceleration and GPS-data was deployed atop the nacelle. Both partially and fully assembled turbines displayed complex oscillation orbits, swiftly changing amplitude and direction. Mean nacelle deflection correlated strongly with significant wave height as well as mean wind speed. As wind speed and significant wave height showed a strong correlation as well, it is difficult to discern which load drives the observed relative motions. While wind loads are significantly smaller than wave loads on partially assembled turbines under installation conditions, additional momentum induced by vortex shedding may prove sufficient to cause the observed effects.
Algorithms for Supervised Machine Learning-Based Structural Performance Evaluation Framework
Authors: Wang Xiaowei , Heo YeongAe 
Published: December 2020

Abstract
Machine learning (ML) approaches have gained increasing attention in the structural engineering field to evaluate structural performance using structural health monitoring (SHM) data. Supervised ML approaches can accelerate the learning process by using labeled training datasets to map an input to output dataset. But, SHM data are not informative to drive a mapping function to determine the real-world performance of large-scale complex structures in particular for future events. To leverage a framework for evaluating the system-level structural performance, this study couples supervised ML approaches with an advanced finite element (FE) model considering pre- and post-event model validation and updating. A well-instrumented system experiencing multiple seismic events is employed as a case study to demonstrate the proposed framework. An FE model of the instrumented system is created and validated using pre-event SHM datasets. Numerical data obtained from the FE model are used for datasets to develop ML prediction models, which are then validated by a post-event SHM dataset. Eight popular ML algorithms are examined and compared to shed light on the effectiveness of the ML algorithms for the proposed framework. The case study results indicate that the Random Forests and Neural Network algorithms provide better estimation for the structural system. The results also imply the need of post-event updating for numerical models used in the case study.
SPIRE: Flexible Riser Condition Monitoring System Applied to Pre-Salt Fields With High CO2
Authors: Brandão M. O. , Lima J. , Almeida E. , Borges O. , McCarthy J. , Nott P. , McNab J. 
Published: December 2020

Abstract
The development of Brazil’s Offshore fields has been performed using flexible pipes because this pipe technology offers significantly increased flexibility, enabling the movement of pipes between wells and reducing lead time to bring a well onstream as compared to rigid pipe solutions. In addition, the decision of where exactly to drill development wells can be delayed, thus making the drilling campaigns easier, cheaper and faster [1].
With the increased activity in Pre-Salt, some challenges to flexible pipes were uncovered and needed to be addressed, notably oil composition and corrosive agents, e.g. H2S, and, specifically for the case of this paper, CO2. At high pressures, such as found in pre-Salt fields, these contaminants create new Stress Corrosion Cracking (SCC) failure modes and several mitigation measures have been adopted to overcome them, focused either on the installed fleet or on the next generation of pipes to be delivered. SCC is a condition that induces failure in the pipes’ metallic layers, but it needs three elements to occur: water, tensile stress exceeding a critical level and a susceptible material. If one of these three elements is suppressed, the phenomena does not to happen.
This paper will cover and present a technology developed to detect the annulus water condition — dry or flooded — and thereby allow a correct integrity management strategy to be adopted. The technology is based on an embedded sensing system together with topside equipment to read the status. The use of such a system is important for the next generation of flexible pipes as it will allow better management of the fleet, with the required measurements performed from the production unit without the need of any support vessel and hence at a reduced cost.
Effect of Annealing Temperature on Physical Features of PVDF Pipe Material
Authors: Rabello Nascimento Christine , Costa Celio A. , Gervasoni Chaves Érica , Teixeira Sylvia , Bertolino Luiz Carlos 
Published: December 2020

Abstract
A PVDF grade typically used in off-shore applications was annealed at 70, 90 and 120°C. The samples were characterized and it was observed a small change in the crystallinity, but, on the other hand, the Elastic modulus of the sample annealed at 120°C increased from 1.52 to 1.85 GPa. The relaxations observed by Dynamic Mechanical Analysis (DMA) indicate that a morphological change took place at annealing process, which led to a stiffness rises of amorphous phase.
A Fundamental Study on Motion Characteristics of the Large-Scale Floating Coal Transshipment Station by Elastic Mooring Lines
Authors: Eto Hiroaki , Sekiguchi Ryo , Kashima Hitomi , Ikoma Tomoki , Aida Yasuhiro , Masuda Koichi 
Published: December 2020

Abstract
This paper describes the motion characteristics and cargo handling efficiency of the Large-Scale Floating Coal Transshipment Station (LFTS). Indonesia is the main country supplying coal in the Asia-Pacific region, it is important to ensure stable coal supply to Japan. Because the topography of the seabed near East Kalimantan Island, Indonesia’s main coal production area, is shallow, it is difficult for bulk carriers to reach the coast. And then, Large-scale Floating Transposition Station for Loading Coal (hereafter LFTS) was proposed, which will be used as a transposition station between small coal barge coming down the river and bulk carriers stay offshore. By installing LFTS, improvement of coal transport efficiency is expected.
As a previous study, the motion characteristics of LFTS using a catenary chain in its mooring system were grasped. However, LFTS can carry up to 500,000 tons of coal, and the draft of LFTS tends to change greatly depending on the coal loading conditions. Besides, the tidal difference in the sea area where the LFTS is installed is about 2 m, and the mounting position of the mooring system on the LFTS side moves up and down by about 10 m at maximum due to changes in the draft and tidal differences. For this reason, when the mounting position of the mooring system is in the lowest state, the mooring line is loosened and the horizontal force is reduced, and it is considered that sufficient restraining force is not exhibited. And, when the mounting position of the mooring system becomes high, the mooring line tension increases and the mooring line may break in some cases.
Therefore, in this study, an attempt was made to use an elastic mooring line as a mooring system for LFTS. An elastic mooring line is a mooring line that incorporates a highly stretchable material between mooring lines that connect anchors and floating body. Even if the mooring line attached to the LFTS moves up and down, an appropriate tension always acts on the elastic mooring line, and it can be expected to suppress the oscillation of the floating body and prevent the mooring line from breaking due to excessive tension. However, elastic mooring lines are mainly used for mooring small structures such as piers and aquaculture facilities, but there are no examples where these mooring lines have been applied to structures over 500m like LFTS. Therefore, elastic mooring lines are adopted for the mooring system of LFTS, systematically calculated according to various setting conditions of elastic mooring lines, and it is grasped whether elastic mooring lines can be applied to LFTS, and the motion characteristics of LFTS moored by elastic mooring lines was also grasped.
Investigating the Impact of Power-Take-Off System Parameters and Control Law on a Rotational Wave Energy Converter’s Peak-to-Average Power Ratio Reduction
Authors: Karayaka H. Bora , Yu Yi-Hsiang , Tom Nathan , Muljadi Eduard 
Published: December 2020

Abstract
Due to the irregular nature of real waves, the power captured in a wave energy converter (WEC) system is highly variable. This is an important barrier to the effective use of WECs. To address this challenge, this study focuses on a rotational WEC power-take-off system in which high-speed and high-efficiency generators along with a torque/power smoothing inertia element can be effectively utilized. In the first phase of this study, the U.S. Department of Energy’s reference model 3 (WEC-Sim RM3; two-body point absorber), along with a slider-crank WEC, were integrated for linear to rotational conversion. Relative motion between the float and spar in RM3 was the driving force for this slider-crank WEC, which is connected to a motor/generator set through a gearbox. RM3 geometry was scaled down by 25 times to work within the limits of the physical motor/generator set used in the experimentation. Once the integration in a hardware-in-the-loop simulation environment was successfully completed, data on the peak-to-average power ratio was collected for various wave conditions including regular and irregular waves. The control algorithm designed to keep the system in resonance with waves was able to maintain relatively high speed depending on the specific gear ratio and wave period. Initial results with hardware-in-the-loop simulations reveal that gear ratio and crank radius have a strong impact on the peak-to-average power ratio. In addition, it was found that output power from the generator was maximized at a larger gear ratio, as the crank radius was increased.
Numerical Analysis of Impact Loads on Subsea Structures During Water Entry in Presence of Waves
Authors: Momm Gustavo Garcia , Mota de Menezes Ivan Fábio 
Published: December 2020

Abstract
Subsea structures employed on offshore oil and gas production systems are likely to be subject to severe loads during deployment. Lowering these structures through the wave zone is a critical operation and the prediction of the loads associated is complex as it involves accelerations of these bodies induced by the vessel motion and the sea surface displacements. This work presents a numerical approach to assessment of the effect of waves on the impact loads that subsea structures are subject to during water entry. A 2D one degree of freedom model using the SPH method was developed to estimate slamming loads on rigid bodies during water entry considering both calm and wavy surfaces. Initially the model was employed to simulate the water entry of wedge considering both free fall and constant velocity cases, obtaining loads profile similar to experiments and numerical simulations from the literature. Later, the constant velocity model was configured to a flat bottom surface rigid body in order to represent a subsea manifold. A regular waves generator provided different wavelength, height and phase enabling slamming load assessment in various situations.
Design and Testing of AUV Docking Modules for a Renewably Powered Offshore AUV Servicing Platform
Authors: Haji Maha N. , Tran Jimmy , Norheim Johannes , de Weck Olivier L. 
Published: December 2020

Abstract
Autonomous Underwater Vehicle (AUV) missions are limited in range and duration by the vehicle’s battery capacity, and sensor payloads are limited by the processing power onboard which is also restricted by the vehicle’s battery capacity. Furthermore, the power consumption of a vehicle’s acoustic system limits the possibility of substantial data transmission, requiring the AUV be retrieved to download most data. The Platform for Expanding AUV exploRation to Longer ranges (PEARL), described in this paper, aims to extend the range and endurance of AUVs while reducing data latency and operating costs. PEARL is an integrated autonomous floating servicing station that utilizes renewable energy to simultaneously provide AUV battery recharging and data uplink via new generation high-bandwidth low-Earth orbit satellite constellations. This paper details the design and testing of two potential AUV docking modules of the PEARL system. The modules are uniquely located near the ocean surface, an energetic environment that presents a particular set of challenges for AUV docking. The results will be used to inform the design of a prototype system to be tested in an ocean setting.
Development of Accidental Scenarios Involving Human Errors for Risk Assessment in Restricted Waters
Authors: Abreu Danilo Taverna Martins Pereira de , Coelho Maturana Marcos , Martins Marcelo Ramos 
Published: December 2020

Abstract
The navigation in restricted waters imposes several challenges when compared to open sea navigation. Smaller dimensions, higher traffic density and the dynamics of obstacles such as sandbanks are examples of contributors to the difficulty. Due to these aspects, local experienced maritime pilots go onboard in order to support the ship’s crew with their skills and specific regional knowledge. Despite these efforts, several accidents still occur around the world. In order to contribute to a better understanding of the events composing accidental sequences, this paper presents a hybrid modelling specific for restricted waters. The main techniques used are the fault tree analysis and event tree analysis. The former provides a framework to investigate the causes, while the latter allows modelling the sequence of actions necessary to avoid an accident. The models are quantified using statistical data available in the literature and a prospective human performance model developed by the Technique for Early Consideration of Human Reliability (TECHR). The results include combined estimates of human error probabilities and technical failure probabilities, which can be used to inform the causation factor for a waterway risk analysis model. In other words, given that the ship encounters a potential accidental scenario while navigating, the proposed models allow computing the failure probability that of the evasive actions sequence. The novelty of this work resides on the possibility of explicitly considering dynamicity and recovery actions when computing the causation factor, what is not a typical feature of similar works. The results obtained were compared with several results available in the literature and have been shown to be compatible.