bluuebunny/crossref_metadata_2025 huggingface dataset:
LYSOPHOSPHATIDIC ACID ACYLTRANSFERASE 2 (LPAT2) is required for de novo glycerolipid biosynthesis, growth, and development in vegetative and reproductive tissues of Arabidopsis
Authors: Barroga Niña Alyssa M. , Nakamura Yuki
Published: October 2022

The Kennedy pathway is a highly conserved de novo glycerolipid biosynthesis pathway in prokaryotes and eukaryotes. In Arabidopsis, LYSOPHOSPHATIDIC ACID ACYLTRANSFERASE 2 (LPAT2) was assumed to catalyze a crucial reaction step of the endoplasmic reticulum (ER)‐localized Kennedy pathway because of lethality in the lpat2‐1 knockout mutant. However, whether this lethal phenotype was due to the essential role of the Kennedy pathway or LPAT2 as the key enzyme of the Kennedy pathway was unclear. By creating non‐lethal LPAT2‐knockdown mutants in Arabidopsis, we found that LPAT2 is required for phospholipid content and plant development in vegetative and reproductive growth. Functional in vivo reporter assays revealed that LPAT2 was ubiquitously expressed and localized to the ER, where de novo phospholipid biosynthesis takes place. Intriguingly, our lipid analysis revealed that LPAT2 suppression had different effects among the organs examined: phospholipid levels were decreased both in leaves and flowers and the effect was more pronounced in flowers, a non‐photosynthetic organ enriched with phospholipids. Although seed size was reduced in the LPAT2 suppression lines, no remarkable effect was observed in the lipid content of mature siliques. Our results show that LPAT2 is involved in the ER‐localized Kennedy pathway, and suggest that its contribution to de novo phospholipid biosynthesis may have organ selectivity.
An AP‐3‐dependent pathway directs phagosome fusion with Rab8 and Rab11 vesicles involved in TLR2 signaling
Authors: Petnicki‐Ocwieja Tanja , Sharma Bijaya , Powale Urmila , Pathak Devesh , Tan Shumin , Hu Linden T.
Published: October 2022

Intracellular compartmentalization of ligands, receptors and signaling molecules has been recognized as an important regulator of inflammation. The toll‐like receptor (TLR) 2 pathway utilizes the trafficking molecule adaptor protein 3 (AP‐3) to activate interleukin (IL)‐6 signaling from within phagosomal compartments. To better understand the vesicular pathways that may contribute to intracellular signaling and cooperate with AP‐3, we performed a vesicular siRNA screen. We identified Rab8 and Rab11 GTPases as important in IL‐6 induction upon stimulation with the TLR2 ligand Pam3CSK4 or the pathogen, Borrelia burgdorferi (Bb), the causative agent of Lyme disease. These Rabs were recruited to late and lysosomal stage phagosomes and co‐transported with TLR2 signaling adaptors and effectors, such as MyD88, TRAM and TAK1, in an AP‐3‐dependent manner. Our data support a model where AP‐3 mediates the recruitment of recycling and secretory vesicles and the assembly of signaling complexes at the phagosome.
Electroencephalogram Pattern under Exposure of Audio Stimulation and Verbal Memory Assessment
Authors: Sayed Daud Syarifah Noor Syakiylla , Sudirman Rubita , Norhafizah Norhafizah
Published: October 2022

Discovering brain activities during mental and cognitive assessments is interesting research work. It aids people in understanding how the information is stimulated and processed in the brain. This recent work aims to investigate brain activities using electroencephalography (EEG) under audio and verbal memory assessment stimulation. Besides, the effect of audio on verbal memory performance was investigated based on behavioral data and its association with EEG patterns. The subject was required to memorize a list of words at three difficulties level under control conditions, listening to their favorite song, and exposure to ambient noise. The brain signal was acquired during the memorizing period using an EEG machine based 10-20 electrode placement system. The raw EEG signal was filtered using a Butterworth bandpass filter at 4 to 40 Hz. After that, the brain rhythms of alpha, beta, gamma, and theta were extracted from the EEG signal. The mean voltage and relative rhythm power were obtained to determine their pattern under provided stimulation. The findings indicated that the mean EEG voltage and relative rhythms power were the highest and the most influenced under audio stimulation for all assessment phases compared to the control condition. The relative rhythm power showed the increment and decrement trend relative to the control condition. Theta rhythms exhibit the highest relative power with the maximum value found in ambient noise stimulation. The behavioral data revealed that the subject memorized better the word lists in ambient noise conditions.
Permeability of Bone Scaffold with Different Pore Geometries Based on CFD Simulation
Authors: Jusoh Norhana , Kamal Arifin Muhammad Aqil Mustafa , Hilmi Sulaiman Muhammad Hamizan , Mohd Zaki Muhammad Aiman , Mohd Noh Nurul Ammira , Ahmad Nahran Nur Afiqah , Selvaganeson Koshelya , Ali Akbar Amy Nurain Syamimi
Published: October 2022

Scaffold plays a significant role in promoting cells proliferation and differentiation in bone regeneration. Permeability is one of the factors that affect the function as it is able to extract waste and supply nutrients or oxygen. The aim of this study was to design different pore shapes and to simulate its fluid model in order to predict permeability value of the scaffold. There were few steps in this project which were scaffold design, fluid simulation analysis and permeability calculation. Three different pore shapes were designed, which were circle, triangle, and hexagon by using the Solidworks software. Each scaffold was designed by the combination of three unit cells. Then, Computational Fluid Dynamics (CFD) simulation in the Ansys Fluent software was conducted to obtain the pressure drop from the pressure distribution within the pores. The permeability of scaffold was obtained by applying Darcy's permeability formula at inlet velocity of 0.001 m/s, 0.01 m/s and 0.1 m/s. Based on the calculation, the permeability for hexagon pore shape were 3.96691x10-07 m2, 3.52 x10- 07 and 1.92 x10-07 for 0.001 m/s, 0.01 m/s and 0.1 m/s inlet velocity, respectively. Therefore, by increasing the inlet velocities, permeability decreased for all types of scaffolds. Furthermore. hexagon pore shape showed the highest permeability value when compared with triangle and circle’s pore shape. Nevertheless, all pore shapes demonstrated permeability values that within the range of natural bone permeability.
The Hanna Neumann conjecture for surface groups
Authors: Antolín Yago , Jaikin-Zapirain Andrei
Published: October 2022

The Hanna Neumann conjecture is a statement about the rank of the intersection of two finitely generated subgroups of a free group. The conjecture was posed by Hanna Neumann in 1957. In 2011, a strengthened version of the conjecture was proved independently by Joel Friedman and by Igor Mineyev. In this paper we show that the strengthened Hanna Neumann conjecture holds not only in free groups but also in non-solvable surface groups. In addition, we show that a retract in a free group and in a surface group is inert. This implies the Dicks–Ventura inertia conjecture for free and surface groups.
Subtle or covert abuse within intimate partner relationships: a scoping review protocol
Authors: Parkinson Rosemary , James Neil , Hanson Sarah
Published: October 2022

Objective:

The objective of the review is to understand how academic literature on domestic violence has described or defined subtle, non-physical abuse in intimate heterosexual or same-sex relationships.

Introduction:

Academic literature frequently refers to subtle or covert abuse in intimate relationships; however, this kind of abuse, while recognized by therapists who work with victims, has not yet been researched. Without understanding how clients experiencing subtle abuse present in therapy, therapists may misunderstand the cause of their distress and do more harm than good. This scoping review aims to understand how the current literature describes or defines subtle or covert abuse to inform future research to enable therapists to recognize subtle abuse in their clients.

Inclusion criteria:

Academic work that describes or defines subtle or covert abuse in intimate partner relationships based on primary research or discussion papers published in English will be considered for inclusion. Work will be excluded if it only describes physical or overt non-physical abuse.

Methods:

MeSH terms and keywords relating to domestic violence literature found in preliminary searches were used to design the initial search strategies. Search terms based on these were chosen in discussion with a librarian. The following databases will be searched: PsycINFO (EBSCO), MEDLINE Complete (EBSCO), CINAHL (EBSCO), PsycArticles (EBSCO), and Scopus. Searches will be conducted for studies published between 1950 and 2021.
Computational Differential Algebraic Equation Framework and Multi Spatial and Time Discretizations Preserving Consistent Second-Order Accuracy: Nonlinear Dynamics
Authors: Tae David , Tamma Kumar K.
Published: October 2022

We propose the novel design, development, and implementation of the well-known generalized single step single solve (GS4) family of algorithms into the differential algebraic equation framework which not only allows altogether different numerical time integration algorithms within the GS4 family in each of the different subdomains but also additionally allows for the selection of different space discretized methods such as the finite element method and particle methods, and other spatial methods as well in a single analysis unlike existing state-of-the-art. For the first time, the user has the flexibility and robustness to embed different algorithms for time integration and different spatial methods for space discretization in a single analysis. In addition, the GS4 family enables a wide variety of choices of time integration methods in a single analysis and also ensures the second-order accuracy in time of all primary variables and Lagrange multipliers. This is not possible to date. However, the present framework provides the fusion of a wide variety of choices of time discretized methods and spatial methods and has the bandwidth and depth to engage in various types of research investigations as well and features for fine tuning of numerical simulations. It provides generality/versatility of the computational framework incorporating subdomains with different spatial and time integration algorithms with improved accuracy. The robustness and accuracy of the present work is not feasible in the current state of technology. Various numerical examples illustrate the significant capabilities and generality and effectiveness for general nonlinear dynamics.
Origami-Inspired Chiral Metamaterials With Tunable Circular Dichroism Through Mechanically Guided Three-Dimensional Assembly
Authors: Xu Xinlin , He Shuchang , Wang Chengjun , Chen Xuan , Wang Zuojia , Song Jizhou
Published: October 2022

Chiral metamaterials with artificially engineered subwavelength structures can effectively couple incident waves and lead diverse electromagnetic responses to various circular polarizations. Here, we designed and fabricated an origami-inspired reconfigurable three-dimensional (3D) chiral metamaterial, whose circular dichroism can be dynamically controlled by simple mechanical stretch of its bonded elastomer substrate. The chiral metamaterial was obtained from a patterned planar achiral metasurface through mechanically guided 3D assembly based on the prestrain approach, which ensures deterministic and uniform deformations for each building block during stretching. Numerical simulations and experimental observations were carried out to illustrate the deformation mechanism and the electromagnetic response of the metamaterials under the applied strain. It is shown that the transmissions and chiroptical activities can be continuously tuned from complete spin selectivity to partial spin selectivity when the applied strain increases. The maximum circular dichroism was experimentally measured as high as 0.98, which can be even adjusted to near zero by mechanical stretching. Our work demonstrated an easily operated and promising way to control the chirality of origami-inspired metamaterial in the microwave region, which can be further extended to the terahertz frequency biosensing, imaging, and spectroscope.
Design and Evaluation of a High-Performance, Low-Cost Prosthetic Foot for Developing Countries
Authors: Johnson W. Brett , Prost Victor , Mukul Pooja , Winter V Amos G.
Published: October 2022

A novel, high-performance, cosmetic, rugged, appropriately costed, and mass-manufacturable prosthetic foot for use in low-income countries was designed and field tested. This ruggedized foot was created to accommodate the unique economic, environmental, and cultural requirements for users in India. A previous prototype that enabled able-bodied like gait was modified to include a durable cosmetic cover without altering the tuned stiffness of the overall foot. After undergoing mechanical benchtop testing, the foot was distributed to prosthesis users in India to for at least 5 months. Afterward, participants underwent clinical tests to evaluate walking performance, and additional benchtop testing was performed on the field-tested feet to identify changes in performance. The ruggedized foot endured 1 × 106 fatigue cycles without failure and demonstrated the desired stiffness properties. Subjects walked significantly faster (0.14 m/s) with the ruggedized foot compared to the Jaipur foot, and the feet showed no visible sign of damage after months of use. Additionally, the field-tested feet showed little difference in stiffness from a set of unused controls. Anecdotal feedback from the participants indicated that the foot improved their speed and/or walking effort, but may benefit from more degrees-of-freedom about the ankle. The results suggest that the foot fulfills its design requirements; however, further field testing is required with more participants over a longer period to make sure the foot is suitable for use in developing countries.
Predictive Modeling of Local Film-Cooling Flow on a Turbine Rotor Blade
Authors: DeShong Eric T. , Berdanier Reid A. , Thole Karen A.
Published: October 2022

In the turbine section of a modern gas turbine engine, components exposed to the main gas path flow rely on cooling air to maintain hardware durability targets. Therefore, monitoring turbine cooling flow is essential to the diagnostic and prognostic efficacy of a condition-based operation and maintenance (CBOM) approach. This study supports CBOM goals by leveraging supervised machine learning to estimate relative changes to local film-cooling flowrate using surface temperature measured on the pressure side of a rotating turbine blade operating at engine-relevant aerothermal conditions. Throughout the lifetime of a film-cooled turbine component, characteristics of the film-cooling flow—such as film trajectory and cooling effectiveness—vary as degradation-driven geometry distortions occur, which ultimately affects the relationship between the model input and the model output—film-cooling flowrate predictions. The present study addresses this complication by testing a data-driven model on multiple turbine blades of the same nominal design, but with each blade exhibiting different localized film-cooling flow characteristics. By testing the model in this manner, strategies for mitigating the detrimental effects of film-cooling flow characteristic variations on model performance were investigated, and the corresponding flowrate prediction accuracy was quantified.
Optimal Design of Polymer Gel Profile Control for Gaskule E31 Deep Reservoir
Authors: Xu Hualei , Jiang Houshun , Wang Jie
Published: October 2022

There are some problems in the development of Gaskule E31 reservoir, such as unbalanced reserves utilization, low injection-production correspondence rate, poor development effect and water-out at the bottom of the layer. In order to effectively improve the production capacity of the reservoir, the distribution of the remaining oil is analyzed. By means of mathematical geostatistical method, the detailed description and numerical simulation of reservoir flow field are carried out by comprehensively utilizing geological data, logging data, production testing data and production static and dynamic data. The results show that the south-down direction and east edge of the target block are the remaining oil enrichment areas ; the dominant flow channel mainly exists in the high permeability area of the main layer or the secondary main layer, and the breakthrough flow channel is obvious. The problem of flooding in the main strata of the target block is serious.

After comprehensive analysis of reservoir geological data, the profile control agent system and profile control parameters matching the reservoir environment are determined by CMG numerical simulation. For the selected profile control well y2-13, organic gel, inorganic gel and surfactant are used for multislug design. Numerical simulation calculations are carried out with different concentrations and dosages, and the best profile control design scheme is selected according to the oil-increasing effect. The results show that the injection volume is 6000m3, the concentration is organic gel (agent A: agent B: agent C = 0.5%: 0.4%: 0.3%), inorganic gel 1 (agent A: agent B: agent C = 0.5%: 0.5%:0.05%), inorganic gel 2 (agent A: agent B: agent C = 1.5%:0.75%:0.05%), surfactant (RTS-1 = 0.3%) is the best solution, and the total increase is expected oil is 280.06t. The design idea of the construction scheme has important reference significance for the formulation and optimization of profile control scheme of similar wells.
Lessons Learned: The Influence of Testing Properties on Uniaxial Compression Tests of Ice
Authors: Böhm Angelo Mario , Herrnring Hauke , von Bock und Polach Franz
Published: October 2022

This paper describes the influence of testing properties (test rig stiffness and PID controller settings) on the uniaxial compression test of granular laboratory-made ice in a single-factor design experiment. Global warming causes the decline of sea ice in the Arctic regions. Enabling the Northern Sea Route and the Northwest Passage to be more accessible for the shipping industry and therefore reduces the energy consumption compared to the Suez Canal Route. Nevertheless, ice will remain an interacting element with ships and structures in Polar and Sub-Arctic regions. A good assessment of forces exerted by the ice on the offshore structure or the ship is essential for designing these arctic structures. Ice-structure interactions depend on the mechanical properties of the ice, which are still not fully explored but can be determined by experimental testing. Over the years, many experiments have been conducted with similar test setups but different testing properties. Therefore the influence of the test properties on the compressive strength of ice is analyzed and discussed by comparing the results of different test settings in this paper. The tests are conducted in a single-factor design experiment. The applied velocities range from 0.01 mm/s to 500 mm/s, causing the ice to behave ductile at lower velocities and brittle at higher velocities.
An Efficient 1st Order Stress Hysteresis Model for Helically Laid Rectangular Elements in Power Cables and Umbilicals
Authors: Karlsen Kjetil André
Published: October 2022

It is essential to calculate the mechanical stress efficiently in power cables, umbilicals and hybrids to reduce the risk of failure and halts during production, transportation, installation and operation phases. The global analysis, where these conditions are simulated, can under certain circumstances produce a very large volume of data, which often needs to be processed into a specific format or transformed into a result.

This paper describes a model for helically laid rectangular elements, that efficiently process large data volumes into 1st order stress. The hysteresis model applies the results from the global analysis as input, together with stress parameters from local FEA, element dimensions and material properties. As it is positioned as a link between the global and local analysis, it calculates the stress in time domain, which can either be used directly or processed further.

A case study is also being presented in this paper where time domain results from the 1st order stress model are first run through a rainflow counting algorithm, which extracts all the ranges and their associated cycles. These ranges are afterward measured against the element’s SN curve, followed by a Palmgren-Miner summation to give an estimate of the local fatigue damage. The model has through this study shown to give an improved fatigue life compared to an alternative 1st order technique used in the past and is found highly efficient compared to its complexity.
Optimal Management of Offshore Wind Assets at Different Stages of Life Extension Accounting for Uncertainty Propagation
Authors: Yeter Baran , Garbatov Yordan , Guedes Soares Carlos
Published: October 2022

The objective of the present study is to develop an optimal life extension management strategy for ageing offshore wind farms. The optimal management strategy is attained by minimising the overall risk of a group of different assets based on the principles of the modern portfolio theory. The statistical measures regarding the risk and expected return are obtained through a probabilistic techno-economic assessment, which considers the mean wind speed, capacity factor, degradation severity, initial crack size and feed-in tariff as stochastic variables. The expected return accounts for the time-weighted incremental free cash flows. The risk and return of the offshore wind farm are investigated under optimistic, moderate, and pessimistic scenarios. Finally, the optimal allocation (portfolio) of offshore wind assets attained based on the mean-variance optimisation is presented for the different stages of the life extension of the offshore wind farms accounting for the uncertainty propagation during the life extension. The uncertainty propagation is reflected in the correlation and variability between the offshore wind turbines and their operation. The results indicate that a significant risk reduction can be achieved by employing an offshore wind asset allocation according to the risk-adjusted portfolio. Also, the benefit of using a risk-adjusted allocation increases as the life extension moves on. The outcome of the present study can be useful for the feature engineering part of the deep neural network training for the classification of ageing offshore wind turbines.
Splitting-Tests of Laboratory-Made Granular Ice With a Propeller-Like Indenter
Authors: Böhm Angelo Mario , Herrnring Hauke , von Bock und Polach Franz
Published: October 2022

Global warming will decline the sea ice in the upcoming decades. However, sea ice will prevail long enough in the subarctic and polar regions to remain a challenge for the shipping industry and arctic engineers. The decline in sea ice makes some economically interesting routes through ice-covered water more accessible. Still, at the same time, climatic changes can cause more dynamics of ice sheets and ice features. Therefore a better understanding of ice-propeller interaction is required with experimentally validated simulations. Propeller contact loads can be classified into milling loads and impact loads. The input ice property for existing numerical models of propeller ice interaction is usually the compressive strength at relatively low strain rates representing the impact scenario. Independent from the applied interaction velocity, a compressive test does not describe the milling type interaction well, which is characterized by fracture and splitting of the ice. This paper describes the splitting-test of laboratory-made granular ice with a propellerlike indenter. Splitting-tests of granular ice specimens show no dependence on the L/D ratio. The force measurement during the splitting-tests shows a dependency on the thickness of the indenter and, in addition, for the 6 mm wide indenter, a rate dependency. The force measurement of the splitting-test with the 3 mm wide indenter shows no rate dependency. The higher specific strain energies in splitting-tests of ice could lead to the lower measured forces.
A Generalized Model for Field Assessment of Particle Settling Velocity in Viscoelastic Fluids
Authors: Chen Hongbo , Kuru Ergun
Published: October 2022

It has been long known that drilling fluid viscoelastic properties have a significant impact on various elements of drilling hydraulics design (e.g., assessment of frictional pressure loss, particle settling velocity, hole cleaning, etc.). However, efforts for considering the viscoelastic fluid properties in drilling hydraulics design are traditionally hindered by the fact that there was no practical methodology to measure these critical fluid properties in the field.

Previous studies have highlighted the advantages of using the concept of “energy dissipation” for the quantitative evaluation of fluid elasticity. Energy dissipation theory provides a more comprehensive description of the fluid elasticity by considering the two characteristics of the fluid simultaneously; stretchiness (oscillation strain % at the crossover point of G’ and G” curves) and the stress corresponding to crossover point (i.e., flow point). In a recent study, we have shown that the “energy dissipation” of viscoelastic fluids can be correlated to fluid physical properties such as apparent viscosity and funnel viscosity, which can be conveniently measured using standard field-testing equipment (i.e., Rotational Viscometer and Funnel viscometer). Based on these findings, a new methodology for the field assessment of drilling fluid viscoelasticity has been developed, opening new opportunities to develop improved hydraulics models.

In this paper, using the new methodology developed in a recent study, we present a new generalized model for the field assessment of the particle settling velocity in viscoelastic fluids. The main objectives of the study were to: 1) Develop a generalized model for the field assessment of particle settling velocity in shear-thinning viscoelastic fluids by using the energy dissipation concept as an indicator of the fluid viscoelasticity; 2) Investigate the significant factors that influence the particle settling velocity to help provide a solution to the potential problem encountered in field drilling operations.

We prepared ten different fluids, which were divided into two groups based on their shear viscosity values. In each group, five fluids were having similar shear viscosity and variable elasticity values. Nineteen different spherical particles were used to conduct particle settling experiments with a density range from 2700 kg/m3 to 6000kg/m3 and a diameter range from 1mm to 4mm. Rheological characterizations of the fluids have been conducted by using funnel viscometer, API Rotational viscometer, controlled shear rate, and amplitude sweep test measurements.

Based on the experimental results and theory of the particle settling in non-Newtonian fluids, we developed a new model that can be used for predicting particle settling velocity in viscoelastic fluids. The statistical analyses had shown that the root means square error and mean absolute percentage error of model predictions were 0.0032 m/s and 4.1 percent, respectively.
Gas Diffusion in Flexible Pipes: A Comparison Between Two- and Three-Dimensional FE Models to Predict Annulus Composition
Authors: Vieira João Marcos Bastos , Mendes de Sousa José Renato
Published: October 2022

The Brazilian offshore oil and gas industry uses flexible pipes to transport water, oil, and/or gas. Currently, the high concentration of acid gases, such as carbon dioxide (CO2) and hydrogen sulfide (H2S), in Brazilian pre-salt wells has been introducing new challenges to these pipes. The acid gases may migrate from the bore to the annulus of these structures, forming a corrosive environment that can induce the steel armors’ failure by SCC (Stress Corrosion Cracking) or HIC (Hydrogen Induced Cracking). Hence, predicting the gas composition in the annulus is of fundamental importance to ensure the safe operation of flexible pipes. However, this prediction involves complex gas permeation analyses through the layers of these pipes. For instance, the permeation rate depends on temperature, gases partial pressures, and the free volume distribution. Therefore, new tools are required to understand better the fluid permeation between the flexible pipes’ layers.

Therefore, this paper presents and compares two finite element (FE) models to predict the annulus composition of flexible pipes. Both models consider the temperature gradient effects on the layers’ material properties. On the one hand, the first approach deals with a two-dimensional model that considers helical layers as rings. So, the shielding effect is simplified. On the other, the second develops a complete three-dimensional model of the cross-section geometry. The results indicate that, while being faster, the two-dimensional approach shows higher concentration results than the three-dimensional approach. Furthermore, the difference between the two approaches suggests that the shielding provided by the helicoidal wires is relevant.
Slamming Induced Fatigue in a Moonpool With a Recess
Authors: Chalkias Dimitris , Sulaiman Zana
Published: October 2022

This paper presents a method of assessing fatigue life due to slamming on the structural components inside drillship moonpools with a recess. The effect of free surface deformation in the moonpool, the resulting slamming pressure on the moonpool’s bulkheads, and the resulting stresses and fatigue life are studied for two typical drillship moonpools with a recess.

The fatigue life is predicted using a practical engineering approach. The natural period of the moonpool is determined by using a potential flow radiation/diffraction solver. The flow characteristics and slamming pressure in the moonpool are calculated using CFD. Subsequently, the slamming pressure results are used in a structural FEM model to calculate the stress on the structural elements. The fatigue life of the structure inside the moonpool is predicted using suitable S-N curves from classification society rules.

In this paper, a high-level description of the problem is made, the methodology for the prediction of fatigue life of the critical structural elements in the moonpool is described, and mitigation solutions are proposed to increase the fatigue life of the structural components.
Predicting the Dynamic Response of a Steel Lazy Wave Riser in the Time Domain Using Artificial Neural Networks
Authors: Cheng Ankang , Low Ying Min
Published: October 2022

Metamodeling (also referred to as surrogate modeling) has attracted increasing attention from researchers in the field of offshore engineering for its advantage in computation efficiency. Among the many metamodeling techniques, artificial neural network (ANN) has long been recognized as one of the most versatile and powerful. In this paper, metamodels of ANN type are constructed to predict time-domain dynamic responses of a steel lazy wave riser (SLWR) in irregular waves based on wave elevations. The work is first carried out with short-term variabilities in waves considered only. The capabilities of dynamic recurrent neural networks with exogenous inputs on the basis of nonlinear autoregression (NARX) is carefully studied. The prediction accuracy is evaluated by the coefficient of determination and the root mean squared error, and the possible overfitting is prevented using k-fold cross-validation. Then the work is expanded to include long-term variabilities in waves into consideration. The time series data of structural dynamic responses are generated from finite element method (FEM) based numerical simulations and are further used to train and validate the ANN. The results obtained suggest that time-domain dynamic responses of SLWRs subject to irregular waves can be effectively predicted by ANN type metamodels directly from wave elevations.
Well Path Design Using Q-Learning Algorithms and Bezier Curves With Obstacles Avoidance
Authors: Cao Jie , Ehsan Chowdhury Samiul , Wiktorski Tomasz , Sui Dan
Published: October 2022

Designing an optimal path has been considered as the one of the key challenges for drilling engineers. Even for a group of competent engineers, it takes several months to plan a well. A robust optimized path can influence the total cost of wellbore, wellbore quality and stability, transport efficiency, and drilling speed. A properly optimized path can be called if it is with a shortest path, avoids well-collisions, low touristy, and has maximum contact with the reservoir. Optimal design of wellbore trajectory is very demanding due to many complex and interacted drilling variables, models’ uncertainties, and design constraints. In drilling engineering, well path optimization is typically based on the objectives to minimize of the total length of wellbore, drilling cost and time in consideration of well-collision avoidance. Optimization algorithms such as genetic algorithm, dynamic programming, particle swarm optimization etc. might provide probable solutions to the optimization problem.

Recently, machine learning technology becomes more attractive in drilling engineering to deal with complicated cases, like regression, classification, control and optimization problems. The aim of this paper is to investigate the implementation feasibility and efficiency of Reinforcement Learning algorithms to design an optimal path with the obstacle detection and avoidance. Our work has applied Q-Learning of Reinforcement Learning to plan a path with minimum measure depth, and in the meanwhile to avoid different shapes of obstacles. The agent interacts with the environment, achieving maximum reward upon reaching the target with passing through the given obstacles or receiving penalties when it fails. This work shows the behavior of the algorithms to obey the main criterion of the trajectory design as an alternative solution. In addition, one engineering path plan method based on Bezier curve to modify the generated path from Q-Learning is proposed, where the minimum dog leg severity (DLS) is considered to make the designed trajectory close to the real ones. To the best of authors’ knowledge, it might be the first attempt to use Reinforcement Learning for well path design. The presented work will be a good example to introduce more and more artificial intelligent (AI) methods to petroleum engineering and explore a wise way to combine traditional engineering design methods with AI approaches.
An Artificial Neural Network Approach for Fatigue Analysis of Slender Marine Structures
Authors: Rodrigues Thiago Camargo , Gonzalez Gabriel Mattos , Sagrilo Luis Volnei Sudati
Published: October 2022

Fatigue life calculation of slender marine structures, such as risers and mooring lines, usually requires a high computational cost. This cost comes from using finite element-based numerical models to predict the stress response of such structures under the action of many fatigue-inducing environmental loadings that they will face during their operational life. Lately, alternative methods to reduce the computational cost of these predictions have been proposed. One consists of a hybrid method that combines the FEM (Finite Element Method) with Artificial Neural Networks (ANN). Most of the available hybrid FEM-ANN models are based on shallow neural networks, and the models are trained individually for each fatigue load case. The main goal of this work is to investigate a fatigue analysis methodology based on hybrid FEM-ANN models where the ANN modeling is developed using modern deep learning techniques, such as Long Short-Term Memory (LSTM). Besides, instead of using a case-to-case approach, this work presents a generalized deep learning model, i.e., the trained hybrid FEM-ANN model can make predictions in the top of the riser for various environmental loadings without the need for new training. The model is tested for a flexible lazy-wave riser and a free-hanging flexible riser. Results of the hybrid FEM-ANN model are compared to those from the complete FEM-based numerical analyses to show the former model’s accuracy.
Effect of Low Pretension on the Fatigue Performance of Large Bolts
Authors: Johnston Carol
Published: October 2022

Large bolts are used in applications which are subjected to fatigue loads, such as the M72 bolts used in ring flanges of wind turbine towers. Pretension is used as a means of protecting bolts against fatigue loading. Design standards require particular levels of pretension to be applied. For example, 70% of the bolt’s proof strength is often specified. However, in practice, bolts may not be experiencing the required level of pretension. Pretensioning procedure, joint face distortion and in-service relaxation can all influence resulting bolt pretension. However, no guidance is available on the fatigue performance of pretensioned bolts when the pretension is less than the specified value. In this work, a series of tests was carried out using a specially designed test jig, which allowed bolts to be pretensioned and then a fatigue load to be applied to the joint faces. Pretension was applied to the bolts using a hydraulic tensioning tool, and the resulting bolt tension was measured using strain gauges. The pretensions used were intentionally less than the recommended level. The fatigue test results showed that it was necessary to apply a significantly higher level of tension (an overtension) with the hydraulic tool prior to tightening the nut in order to achieve a particular target level of pretension. This overtension was more than two times the target tension. In terms of bolt fatigue performance, as expected, increasing the pretension reduced the load range experienced by the bolts and so increased fatigue life. The mean S-N curve for the pretensioned bolts was similar to and slightly higher than the mean S-N curve obtained from bolts tested without pretension. A relationship was derived, which allows bolt load range to be calculated for a given bolt pretension and applied load range.
Development of a Stress Intensity Factor Solution for Mechanically Lined Pipe
Authors: Johnston Carol , London Tyler
Published: October 2022

Mechanically lined pipe (MLP) is a lower cost alternative to clad pipe, and is used to carry corrosive fluids in oil and gas applications. The pipe includes a liner which is made from corrosion resistant alloy (CRA). The liner is fixed at both ends using seal welds and a length of weld overlay. This results in a junction between the backing steel, weld overlay and liner, which is called the transition point or the triple point. When lined pipe is subjected to fatigue loading, the triple point has been shown to be location where fatigue cracks initiate. Flaws present at the triple point will grow in service. When a flaw breaches the liner, the backing steel will be exposed to the corrosive fluid, limiting the remaining life of the pipeline. It is therefore of interest to perform fracture mechanics calculations to understand fatigue crack growth from the triple point, so that the operational service life of MLP can be calculated if a flaw is present at the triple point. In order to do this, a stress intensity factor, K, is needed which describes the stress intensity at a crack tip at the triple point. However, owing to the unique geometry of this location, no stress intensity factor solution currently exists for the triple point location. To overcome this challenge, parametric finite element models were developed to calculate stress intensity factors for triple point crack-like flaws. This paper presents results from a work package from a joint industry project whose aim was to understand the fatigue performance of mechanically lined pipe. Finite element analysis was used to develop K solutions for the triple point in mechanically lined pipe by developing geometry-specific Y-factors for the MLP triple point geometry. An engineering critical assessment was then performed. The calculated fatigue life agreed well with results from full scale resonance fatigue tests and demonstrates the value of using FEA to derive geometry-specific K solutions for this geometry.
Automatic Clustering of Metocean Conditions in the Brazilian Coast
Authors: M. Moreno Felipe , G. Cozman Fabio , A. Tannuri Eduardo
Published: October 2022

This paper introduces a pipeline that, first, assembles a dataset of metocean conditions consisting of wind, wave and surface currents, and, second, clusters this data to find the characteristic environmental conditions of each region in the Brazilian coast and the associated Exclusive Economic Zone. Clustering uses the Partitioning Around Medoids algorithm with the silhouette coefficient. As examples, we first present an analysis for the whole Exclusive Economic Zone and then a focused analysis around the Santos port in Southeastern Brazil.
Genetic Algorithms Applied to the Concept of Risk Based Inspection (RBI): Optimization of Inspection Plans
Authors: Morais Carlos Henrique Bittencourt , Abrahão Elcio , Maturana Marcos Coelho , Martins Marcelo Ramos , Rossi André Luis Debiaso , Schleder Adriana Miralles , Moura Fernanda Marques de , Barros Leonardo Oliveira de , Orlowski Rene Thiago Capelari
Published: October 2022

Cost optimization of asset management is a central issue in the offshore Oil and Gas strategy, and risk-based approaches, such as Risk Based Inspection (RBI), have been more and more employed to assist the segment in the concretization of that goal. The inspection procedure aims mitigating the uncertainty related to the asset degradation state, enabling a better quantification of the actual damage, and, consequently, increases the accuracy of remaining life projections. Since the costs involved in offshore subsea inspections are considerable, inspection plans optimization plays a crucial role in the balance of an asset management program. The present paper discusses the use of genetic algorithms, GA, an optimization technique inspired in the concepts of evolutionary genetics, in the development of inspection plans for subsea equipment. The genes are defined in terms of two variables: the type of inspection to be done and in which period it occurs, considering a finite window of opportunities for inspection occurrences. The optimization process considers a multicriteria objective function, consisting in the dimensions time, cost, and risk. Finally, the application of the proposed methodology is illustrated by means of the elaboration of the inspection plans for a subsea Christmas-tree.
Navigational Simulation of Cruising AUVs
Authors: Fujiwara Toshifumi , Umeda Jun , Sato Takumi , Kim Kangsoo , Sasano Masahiko
Published: October 2022

Navigational simulation of autonomous underwater vehicles (AUVs) is important for the navigational planning of the AUVs to confirm operational safety and navigational quality.

This paper presents examples of the situation method of cruising AUVs, which is based on the maneuvering mathematical modeling group (MMG) model proposed for estimating ship maneuvering. The AUV motion equations of external forces in the simulation method are consist of the sum of thrust forces, hydrodynamic ones of the main hull and rudders. Hydrodynamic coefficients in the motion equations were decided by towing and forced oscillation tests using a small AUV model, and the computational fluid dynamics (CFD) calculation.

The calculated results were compared with sea trial test ones conducted at Suruga Bay in Japan. The validity and effectiveness of the simulation method are enough shown by the comparison, in which the simulation and sea trial results have coincided with each other. As a result, it was confirmed that the presented simulation method using simple linear mathematical formulation is useful and has no large problem.
Life Cycle Assessment of Different Marine Fuel Types and Powertrain Configurations for Financial and Environmental Impact Assessment in Shipping
Authors: Taghavifar Hadi , Perera Lokukaluge P.
Published: October 2022

The fuel type selection according to optimal pathway from extraction of a raw material (feedstock) to its processing to transportation and finally its use in marine engines (well to wheel) based on the cost and emission criteria is the main motivation factor to conduct the current investigation. The undertaken procedure has been customized based on the available data (ship/bunker route and mileage, the ship powertrain system, etc.) of the shipping industry under the SeaTech H2020 project (seatech2020.eu). The selected modeling platform is utilized for the life cycle assessment of three potential fuels of diesel, methanol, and liquefied natural gas (LNG). Different fuel production pathways and powertrain dual-fuel technologies have been taken into account as the main variables, while the subsidiary factors such as transportation parameters (fuel economy and Avg. speed) are included in the calculations. The economic aspect and emission reduction trade-off for various scenarios are conducted to introduce the optimal solution based on the stakeholder interest in the shipping industry. The study also considers the fuel transport to the respective ports for a selected vessel from diverse fuel export locations and travelled routes according to datasets available for the same project. The results provide a guideline to the shipping industry on selecting possible conventional/renewable fuel resources to use in marine engines with emission content during each adopted pathway, where the respective subsequent expenditure per 1 MJ of each fuel sample as the functional unit has been evaluated.
Small Sizes of Molybdenum Disulfide Nanosheets As Heavy Oil Viscosity Reducers
Authors: Wu Guodong , Liu Yanchi , Anwaier Maieryemuguli , Yao Erdong , Ren Hongda , Li Yuan
Published: October 2022

The high content of asphaltenes and colloids in heavy oil lead to their high viscosity, making it difficult to exploit and transport. Nanomaterials have become an important additive in reducing viscosity of crude oil. In this work, a series of amphiphilic molybdenum dioxide (MoS2) nanosheets are developed to reduce the viscosity of crude oil by an ultralow concentration aqueous solution.

Firstly, nanosheets were synthesized by the hydrothermal methods. The influence factors such as raw material ratio, temperature and time were investigated. Then, SEM are used to systemically characterize the morphology and structure of MoS2 nanosheets. Then, the properties (i.e., size, viscosity reduction, and interfacial activity) of MoS2 nanosheets are tested. The relationship between these properties and viscosity reduction abilities were studied. Finally, based on viscosity reduction testing results, optimal MoS2 nanosheets formulation and dosage are determined.

By controlling the stirring and temperature, hydrophilic MoS2 nanosheets with sizes from 40 nm to 160 nm were synthesized, respectively. Modifying them with oleyl amine, the amphiphilic nanosheets can be obtained. SEM show that they are materials with layered nano-structure and commonly composed of 8–10 layers. These nanosheets have good interfacial activity, wetting and emulsifying ability. By adding 100 ppm of MoS2 nanosheets to the mixture of heavy oil and water, the viscosity of these system can fall from > 880 mPa·s to 9 mPa·s. The smaller the size of the MoS2 nanosheets is, the better the viscosity reduction ability will be. The optimal using dosage of these nanosheets is 300–400 ppm, and the optimal size is 40–60 nm. It is predicted that nanosheets will gradually become a new field for the development of heavy oil.