bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rheological and Mechanical Properties of Rock-Based Geopolymers Developed for Well Abandonment: Effect of Chemical Admixtures at Elevated Temperatures
Authors: Chamssine Fawzi , Khalifeh Mahmoud , Saasen Arild 
Published: October 2022

Abstract
Examination of alternative cementitious material cured under elevated temperatures is essential to qualify their applicability in field operations. Geopolymers rise as an alternative for Ordinary Portland Cement in oil and gas applications due to its lower carbon footprint and raw material availability. Using chemical admixtures is crucial to engineer geopolymer material for displacement and to maintain well integrity and zonal isolation under elevated temperature and pressure. In this study, the rheological and mechanical properties of rock-based geopolymers, developed for utilization at elevated temperatures, have been examined with the addition of chemical admixtures to test their performance under operational conditions. Neat Class-G cement, by Dyckerhoff, was used as a reference sample for comparison at elevated conditions. The effect of Zn2+, K+, Na+ and Ca2+ species was examined on geopolymer properties. Samples were cured for 1,3, and 7 days at bottomhole static conditions. Properties examined in this study include workability, fluid loss, and viscosity for slurry properties. On the other hand, sonic strength, uniaxial compressive strength, and tensile strength were examined throughout the curing periods. The obtained results exhibited an enhancement in overall properties with an increase in workability and overall strength of the material while considering the poisoning effects from the usage of Zn2+ species. It was concluded that the combination of Na+ and Ca2+compensated the poisoning effect foreseen by the addition of Zn2+ species in geopolymer systems.
The Influence of Edge Treatment on Fatigue Behavior of Thermal Cut Edges
Authors: Grimm Jan-Hendrik , Diniz e Castro Juliana , von Selle Hubertus , Braun Moritz , von Bock und Polach Franz , Ehlers Sören , Hensel Jonas , Hesse Ann-Christin , Dilger Klaus 
Published: October 2022

Abstract
Thermal cut edges can be found in most maritime structures, e.g. in window openings or hatch corners on ships. It is very common to treat free plate edges by grinding or sandblasting due to fatigue and coating requirements. The aim of this study is to review the fatigue behavior of typical treatment methods. Within this study several fatigue tests are performed to outline the influence of treatment methods used for different steel grades, plate thicknesses and cutting processes. Especially the influence of the local edge geometry caused by treatment like grinding or milling is not covered by fatigue rules and guidelines like Eurocode or IIW. Also, the influence of yield strength is not considered by these regulations. Only in shipbuilding a fatigue bonus for high strength steels is given. However, these rules are based on older data and an update is requested by ship building industries. For the investigation shipyards and partners from other industries produced a big number of specimens for fatigue tests. Steel grades are from S235 to S460. Surface roughness as well as local treatment geometry are well documented. In addition, hardness as well as residual stress measurements were performed. Finally fatigue tests were done. Overall goal of the study is to present applicable FAT curves to be used for fatigue assessment.
Ice Basin Tests for Ice-Induced Vibrations of Offshore Structures in the SHIVER Project
Authors: Hendrikse Hayo , Hammer Tim C. , Owen Cody C. , van den Berg Marnix , van Beek Kees , Polojärvi Arttu , Puolakka Otto , Willems Tom 
Published: October 2022

Abstract
With the recent surge in development of offshore wind in the Baltic Sea, Bohai Sea and other ice-prone regions, a need has arisen for new basin tests to qualify the interaction between offshore wind turbines and sea ice. To this end, a series of model tests was performed at the Aalto ice basin as part of the SHIVER project. The tests were aimed at modeling the dynamic interaction between flexible, vertically-sided structures and ice failing in crushing. A real-time hybrid test setup was used which combines numerical and physical components to model the structure. This novel test setup enabled the testing of a wide range of structure types, including existing full-scale structures for which ice-induced vibrations have been documented, and a series of single-degree-of-freedom oscillators to obtain a better understanding of the fundamental processes during dynamic ice-structure interaction. The tests were primarily focused on the dynamic behavior of support structures for offshore wind turbines under ice crushing loads. First results of the campaign show that the combination of the use of cold model ice and not scaling time and deflection of the structure can yield representative ice-structure interaction in the basin. This is demonstrated with experiments during which a scaled model of the Norströmsgrund lighthouse and Molikpaq caisson were used. The offshore wind turbine tests resulted in multi-modal interaction which can be shown to be relevant for the design of the support structure. The dataset has been made publicly available for further analysis.
Physic Based Approach for Solid Transport in Deviated and Horizontal Well
Authors: Purwandari Sartika D. , Lund Bjørnar , Hovda Sigve 
Published: October 2022

Abstract
Cuttings transport is one significant challenge during drilling especially in high deviated and horizontal wellbores. At high degree of inclination, cutting particles may settle to the low side of the wellbore. Below a threshold flow rate, the fluid forces on a particle at the wall will be insufficient to re-entrain the particle and a moving bed of particles will accumulate. The removal of cuttings bed could be difficult once it is formed. Cuttings bed accumulation can create operational problems with respect to drill time and drill cost. Therefore, a good strategy is needed to combine drilling parameters that influence the cuttings transport in efficient and economical ways.
In this study, bed shear stress from cuttings transport experiments in a 10 m annular flow loop is estimated using three different methods. The bed shear stress predicted using bedload transport model differed by less than 5% from the average wall shear stress calculated from experimental values for pressure drop and bed hold up. Calculation using a friction factor correlation gave significantly lower values than obtained with the other two methods. Inclination appears to have larger effect on particle transport properties to water based mud (WBM) than oil based mud (OBM) at low flow rate.
Development of Low Carbon Dioxide Intensive Rock-Based Geopolymers for Well Cementing Applications – One-Part Geopolymer
Authors: Omran Mohamed , Khalifeh Mahmoud 
Published: October 2022

Abstract
This study aims to reveal the development of short-term mechanical and chemical properties of one-part geopolymers for utilization in well construction and well abandonment activities. These geopolymers are heat-cured rock-based one-part products. The rock-based geopolymer precursor was activated by solid powders of potassium silicate. To enhance the setting time and early strength development of the geopolymers, a small portion of alkaline solution (KOH) was used as an accelerator. Properties of the slurry were characterized through investigating mechanical and chemical techniques. Sonic strength and uniaxial compressive strength of the specimens were studied. In addition, the mineralogy of the solidified samples was analyzed through crystallography to better understand their microstructure. Moderate compressive strength of ca. 7 to 10 MPa within 24 hours and up to 7 days were developed for the investigated one-part geopolymer mixes that have been activated by a solid activator with a modulus ratio of 2.4. One-part geopolymers not only could provide user-friendly slurries, but also can facilitate their commercialization and large-scale application in petroleum and civil engineering sectors.
A Single Cavitation Bubble Induced Damage
Authors: Sagar Hemant , el Moctar Ould 
Published: October 2022

Abstract
In the present work, we experimentally and numerically investigated the dynamics of a millimeter-sized cavitation bubble generated nearby a solid surface. In experiments, bubbles are induced by a focused Nd-YAG laser generating plasma. A specimen of the commercially pure aluminum surface was placed nearby a bubble at varying relative wall distances. Here, the relative wall distance is a ratio of the distance between the bubble center and specimen surface, and the maximum radius of the bubble. In experiments, we captured the bubble’s dynamics by back illumination method using a highspeed camera. Damage obtained was characterized by an optical microscope and profilometer. The surface profiles and damage patterns quantified the damage characteristics. The three-dimensional flow was captured numerically by solving the Navier-Stokes equations in an Euler-Euler approach with barotropic equations of state. The computations were performed assuming both water and vapor as compressible phases. The dynamics of a single bubble obtained in computations were compared with the experiments for shapes and collapsing times. The computed characteristics of flow around a bubble near the solid surface, e.g. impact velocities and pressures were also discussed. Additionally, the dynamics of a microscopic bubble collapse near the surface was also investigated to compute collapse-induced wall shear rate and flow around the collapsing bubble. The results of numerical simulations were compared with the existing experimental data. The comparisons showed, a good qualitative and quantitative agreement. Overall, the numerical method well reflected the dynamics bubble up to three collapses and resolved flow around the bubble. The statistical data of pits obtained are also useful in deriving loads induced by a single bubble collapse. Overall, this work extensively comprises the single cavitation bubble dynamics and induced damage. This article summarizes the investigations of Sagar (2018) and Sagar & el Moctar (2020).
The Effect of the Height of the Regular Wave on Seabed Liquefaction
Authors: Kazimierowicz-Frankowska Krystyna , Kulczykowski Marek , Majewski Dawid , Mierczyński Jacek , Smyczyński Marcin 
Published: October 2022

Abstract
This paper presents the results of an experimental study of seabed liquefaction under progressive waves. Firstly, during preliminary tests, the physical and mechanical parameters of the soil selected as the subgrade material were determined. A series of monotonic triaxial shear tests were carried out at different initial void ratios and mean effective stresses. The susceptibility of soil samples to liquefaction was estimated. The results were used to design experiments in a wave flume. Their main purpose was to study the effect of wave height on wave-induced liquefaction. The experiments were carried out in a wave flume that is 64.1 m long, 0.6 m wide, and 1.4 m high, in a specially built experimental stand located 5.0 m from the wave generator below the flume bottom. Wave propagation was conducted over constant water depth which was equal h = 0.5 m. The wave surface elevation was measured by resistance type wave gauges. The pore-water pressure was measured by transducers located in the middle of the sediment pit, at four different soil depths. Parametric studies were carried out to investigate the influence of wave height on the liquefaction process. The results of experiments shown that pressure buildup is a strong function of the wave height and increases with increasing its value.
Numerical Research on the Resistance Performance of a Ship Under Pack Ice Conditions
Authors: Tang Xiang-Jie , Zou Ming , Zou Lu , Zou Zao-Jian 
Published: October 2022

Abstract
For a ship navigating in waterways covered by pack ices, the ice load including resistance prediction is a critical issue at the design stage, which is directly related to the safety of the ship, and it is of great significance to the research of ship propulsion efficiency. This paper adopts a coupled numerical method to simulate the ship-ice interaction under pack-ice conditions: the fluid flow is solved by Computational Fluid Dynamics (CFD) method, while the governing equations of ice is solved and the ship-ice and ice-ice collisions are simulated by the Discrete Element Method (DEM). In addition, this method is also capable of building a random pack ice field. The DEM-based ice particles are established according to the model test conditions and the parameters in a published reference. The comparison between the present results with the model test data and the results in another study by the Finite Element Method (FEM) under the same conditions shows that the numerical model established in this paper has higher accuracy in predicting ice resistance. On this basis, the influence of ship speed on the ice resistance under different concentrations of pack ice is investigated.
Dynamic Simulation of an Offshore Aquaculture Structure Under Combined Wave and Current Conditions
Authors: Cheng Hui , Ong Muk Chen , Li Lin 
Published: October 2022

Abstract
The reliable design of offshore aquaculture structure (OAS) for fish farming in the open ocean is vital to the marine aquaculture industry in the future. However, the lack of easy-to-access numerical tools for the dynamic analysis of OAS challenges the development of marine aquaculture. This article presents a newly developed numerical library under an open-source, finite-element analysis code, Code_Aster, enabling the dynamic analysis of OAS. A numerical model of OAS is first developed using the present numerical library, and then validated against experiments. The validation shows a good agreement in terms of structural motions and tensions in mooring lines. After that, the dynamic responses of this model are analyzed under irregular waves and current conditions from field measurements on an offshore fish farm site. The results indicate that a negative mean pitch angle will occur when the current velocity is large.
Analysis of Welding Influences on Extruded Aluminum Panel Buckling
Authors: Wang Xintong , Amdahl Jørgen 
Published: October 2022

Abstract
Extruded aluminum panels are increasingly used in the marine industry, owing to the high strength-to-weight ratio and less welding paths. However, sensitivity to the welding makes it difficult to predict the structural resistance in the design stage with existed analytical formulations. It is therefore necessary to resort to numerical investigation. In this study, a previously developed numerical model that takes into account the welding effects is used to simulate the buckling behavior of extruded aluminum panels. Buckling of panels with two stiffener types, open (L-shaped) and closed (trapezoid), are investigated. The ultimate load sensitivity with respect to welding effects including different patterns, imperfection fields and amplitudes are discussed. Through comparison with design rules, the applicability of existed closed form methods is discussed. Regarding the ultimate load prediction of extruded aluminum panels, suggestions related to imperfection field introduction are addressed. The simulations can be further used as a foundation for development of improved analytical formulations.
Three-Dimensional Finite Element Models of a Flexible Pipe Interlocked Carcass Under Bending
Authors: Geremias Toni Fernando , de Arruda Martins Clóvis , Provasi Rodrigo 
Published: October 2022

Abstract
The main function of an interlocked carcass is to provide radial stiffness to the flexible pipe, preventing failure modes such as collapse and crushing. The carcass is designed to withstand a specified collapse pressure while attaining minimum flexibility levels, the main parameter for its functionality. This combination of both high radial stiffness and flexibility arises from the interlocked profile and its associated clearances, which are also the main responsible for the highly nonlinear mechanical behavior of the carcass due to the wide range of self-contacts possibilities. In this way, given the complexities of modeling the interlocked carcass considering its exact geometry, most approaches available in the literature adopted simplifying hypotheses, the equivalent orthotropic layer being the most common one. However, with that, important effects from the interlocking are disregarded, such as stiffness variations and stress concentrations. For collapse problems in specific, three-dimensional carcass finite element models have already been developed, but there is nothing similar in the literature for bending loadings. Therefore, the present work proposes two full three-dimensional finite element models of an interlocked carcass, the last one also containing an inner polymeric sheath. For comparison, a third model was also developed, containing just a polymeric sheath. All models were meshed with second-order solid isoparametric finite elements, considering, therefore, all details of the interlocked profile and the self-contacts possibilities. The results are then presented in detail and comparison are carried out, allowing the evaluation of the interlocking effects during bending and how it influences the mechanical behavior of the carcass.
Application of Machine Learning for the Generation of Tailored Wave Sequences
Authors: Klein Marco , Stender Merten , Wedler Mathies , Ehlers Svenja , Hartmann Moritz , Desmars Nicolas , Pick Marc-André , Seifried Robert , Hoffmann Norbert 
Published: October 2022

Abstract
This paper explores the applicability of machine learning techniques for the generation of tailored wave sequences. For this purpose, a fully convolutional neural network was implemented for relating the target wave sequence at the target location in time domain to the respective wave sequence at the wave board. The synthetic training and validation data were acquired by applying the high-order spectral (HOS) method. The HOS method is a very accurate method for modeling non-linear wave propagation and its numerical efficiency allows the generation of large synthetic data sets. The training data featured wave groups of short duration based on JONSWAP spectra. The sea state parameters wave steepness, wave period and enhancement factor were systematically varied. At the end of the training process, the trained models were able to predict the wave sequences at the wave board based on the time series of the target wave defined for a specific target location in the wave tank. The accuracy of the trained models were evaluated by means of unseen validation data. In addition, the predictive accuracy of the trained models was compared with the classical linear transformation approach.
Assessment of Sea State Estimation With Convolutional Neural Networks Based on the Motion of a Moored FPSO Subjected to High-Frequency Wave Excitation
Authors: Bisinotto Gustavo A. , Cotrim Lucas P. , G. Cozman Fabio , A. Tannuri Eduardo 
Published: October 2022

Abstract
Motion-based wave inference has been extensively discussed over the past years to estimate sea state parameters from the measured motions of a vessel. Most of those methods rely on the linearity assumption between waves and ship response and present a limitation related to high-frequency waves, whose first-order excitation is mostly filtered by the vessel.
In a previous study in this project, the motion of a spread-moored FPSO platform, associated with a dataset of environmental conditions, was used to train convolutional neural networks models so as to estimate sea state parameters, displaying good results, even for high-frequency waves. This paper further explores this supervised learning inference method, focusing on the estimation of unimodal high-frequency waves along with an evaluation of particular features related to the approach.
The analysis is performed by training estimation models under different circumstances. First, models are obtained from the simulated platform response out of a dataset with synthetic sea state parameters, that are uniformly distributed. Then, a second dataset of metocean conditions, with unimodal waves observed at a Brazilian Offshore Basin, is considered to verify the behavior of the models with data that have different distributions of wave parameters. Next, the input time series are filtered to separate first-order response and slow drift motion, allowing the derivation of distinct models and the determination of the contribution of each motion component to the estimation. Finally, a comparison among the outcomes of the approach based on neural networks evaluated under those conditions and the results obtained by the traditional Bayesian modeling is carried out, to assess the performance presented by the proposed models and their applicability to face one of the classical issues on motion-based wave inference.
Estimation of Ocean’s Currents Acting on a Turret-Moored FPSO Using Machine Learning
Authors: Lavra Dias Pedro Felipe , Aoun Tannuri Eduardo , Costa Anna Helena Reali , Caurin Glauco Augusto De Paula , Bisinotto Gustavo Alencar 
Published: October 2022

Abstract
Ocean’s surface currents, although not easily measured by ship’s sensors, affect the movements of any vessel at sea. Especially when dealing with Turret-Moored FPSOs, due to its weathervaning property, there is an intrinsic relationship between the Platform’s motion and environmental conditions. In this sense, we propose using Machine Learning regression algorithms to estimate the surface currents that affect a Turret-Moored FPSO based on data commonly measured on board. These data are expressed by wind speed and direction (measured via anemometer and anemoscope); Platform’s heading (obtained by GPS or Magnetic/Gyro compass); and FPSO’s oscillating motion that is given by the standard deviation of pitch, roll, heave and yaw (measured by MRU sensors and considered as proxy variables of first-order waves’ forces). The prior dataset was composed by local environmental conditions at a specific offshore Basin (in Brazil), observed over ten years at a 3-hour time stamp. This corresponds to approximately 30,000 conditions, each used as input into numerical simulations for a partially loaded FPSO (length between perpendiculars: 257 m, beam: 52 m, draught: 15.6 m). Simulation results provide the Platform’s motion time-series used to generate the final dataset previously mentioned. After dividing this final dataset for train/validation/test into 70/20/10 proportion, a K-means algorithm was fitted to the training data, which grouped it into 3 clusters in which, for each one, 2 ‘specialized’ MultiLayer Perceptron (MLP) Neural Network (one for current’s velocity and another for direction) were implemented for. The mean measured value of current’s velocity of the test dataset is 0.33 m/s, whereas the mean prediction with the method proposed is 0.32 m/s. In current’s direction, the mean measured value is 220°, while the mean prediction is 225°.