bluuebunny/crossref_metadata_2025 huggingface dataset:
Disruptive Technology-Enabled Circular Economy for Improving the Sustainability of the Supply Chain
Authors: Rath Kali Charan , Muduli Kamalakanta , Das Rashmi Prava , Ramasamy Adimuthu , Mohammed Aezeden
Published: April 2022

Most industries are faced with the challenges of how the supply chain can be made sustainable with the assistance from digital technology and circular economy (CE). A survey has been carried out to review the involvement of disruptive technology (DT) and CE in certain sections of supply chain system and identify a clear path that need to be routed to best integrate sustainable practices in the industries to make supply chain more sustainable. Some of the major barrier factors identified are funding support, availability, and technological expertise or ‘know how', and management and policy regulation to implement CE and DT in supply chain management (SCM) to make it more sustainable. It also showed some of the adjustments that need to be made especially in developing countries before introducing the practices of sustainable SCM. When scrutinizing the entire process of SCM and its members, it shows that a single component of SCM cannot implement CE in isolation; it requires collective effort from all members of the supply chain, which is facilitated by integration of DT.
Artificial Intelligence in the Detection of Alzheimer's Disease
Authors: Galety Mohammad Gouse , Gupta Shweta
Published: April 2022

Dementia is a neurological illness that causes diversion from a variety of important cognitive activities. Common examples include memory, reasoning, orientation, understanding, computation, verbal communication, and decision making. Alzheimer's disease (AD) is one of the most common dementias affecting the elderly. It was projected that more than 47 million people globally will be affected by dementia in 2015; these predictions were verified, and forecasts for 2050 are much more concerning, with 131 million people living with dementia. The basic objective of AI is to improve human decision-making and automate operations that are too time-consuming or resource-intensive for people to accomplish. AI can operate as a fast, accurate, and in the long run, cost-effective method to assist human experience and intuition through predictive analytics. AI is an effective technique for AD detection as these methods are employed as a computer-aided diagnosis (CAD) system in clinical practices and play a crucial role in identifying variations in the brain images to detect AD.
Contending With Word Choices in Cross-Cultural Teacher Preparation
Authors: Bright Anita , Hendryx-Dobson Jesse Nicholas , Johnson Shani
Published: April 2022

Through this collaborative exploration of the meanings and meta-meanings of the words “welcome” and “sorry,” the authors of this work give voice to their unique positionalities, and reflect on the ways words carry power in different ways, contingent upon context. Drawing heavily from critical race theory, and particularly engaging with the construct of the microaggressions, this work pivots on the construct that a neutral perspective cannot exist, and that all work is political. The authors engage critical discourse analysis as well as autoethnographic explorations and tap into the ways “trigger words” can be used in ways that are coded and known to some members of a community, while being unfamiliar to or seen as neutral by other members of the community. Holding clear ideas about the ways in which language lands upon and shapes realities is central to this work.
Three Educational Perspectives Supporting Social Justice in a Globally Connected World
Authors: Mäntyneva Mikko
Published: April 2022

This chapter studies the three educational perspectives (student interest in learning about other cultures, awareness of global issues, and attitudes toward immigrants), their interrelationship, and whether they predict social justice and respect for people from other cultures. Empirical data were collected as a part of the PISA 2018 large-scale assessment. Students in those 26 OECD countries that participated in the global competence section of PISA 2018 were used as a sample (n = 180,114). The empirical results indicate that respect for people from other cultures can be supported by promoting student interest in learning about other cultures, their awareness of global issues, and their attitudes toward immigrants. Hypothesis testing revealed statistically significant relationships between constructs.
Opinion Mining and Text Analytics of Literary Reader Responses
Authors: Suhendra Nikmatul Husna Binti , Keikhosrokiani Pantea , Asl Moussa Pourya , Zhao Xian
Published: April 2022

Text mining is an important field of study that has proved beneficial for scholars of various disciplines. Literary scholars use text mining to examine the data produced by creative writers, literary readers, publishers, and distributing companies. The produced data are generally in unstructured form that cannot be used to extract useful information. Text mining can discover the unstructured data and convert it to interesting information through several processes. This chapter proposes a text mining technique by using topic modelling and sentiment analysis to retrieve information about the attitude of the user-readers toward the four volumes of KL Noir books on the Goodreads website. The main significance of this approach is to gain the trends by analyzing the book reviews written on Goodreads.
The Influence of Deep Learning in Detecting Cyber Attacks on E-Government Applications
Authors: Gaur Loveleen , Ujjan Raja Majid Ali , Hussain Manzoor
Published: April 2022

The digitalization revolution plays a crucial role in every government administration. It manages a considerable volume of user information and is currently seeing an increase in internet access. The absence of unorganized information, on the other hand, adds to the difficulty of data analysis. Data mining approaches have recently become more popular for addressing a variety of e-governance concerns, particularly data management, data processing, and so on. This chapter identifies and compares several existing data mining and data warehouses in e-government. Deep learning is a subset of a larger class of machine learning techniques that combine artificial neural networks. The significance and difficulties of e-governance are highlighted for future enhancement. As a result, with the growth of e-governance, risk and cyber-attacks have increased these days. Furthermore, the few e-governance application performance evaluations are included in this chapter. The purpose of this chapter is to focus on deep learning applications of e-governance in detecting cyber-attacks.
People Who Need Data People
Authors: Cook Cameron , Shimon Heather , Stevens Sarah , Adamus Trisha L. , Michaud Clare
Published: April 2022

UW-Madison has a thriving community of support around research data management and sharing, computational skills, and research reproducibility which are all building blocks for supporting campus data science needs. Support is provided through many campus organizations such as the Center for High Throughput Computing, the Research Cyberinfrastructure Initiative, Research Data Services, the Data Science Hub, and more. However, informal and formal interviews with researchers at UW-Madison have shown that as the campus invests in technological solutions and infrastructure to address common research bottlenecks, researchers are less limited by access to data and computing resources, but rather the knowledge to find, understand, and use those tools effectively. Specifically, researchers need “data people,” or people who can help them address these knowledge-based needs, who can fill in gaps in research support, who can advocate for their needs across campus silos, and who can build broad networks of relationships across campus to facilitate a better support experience.
Building, Sustaining, and Growing Multidisciplinary, Multi-Departmental Partnerships to Teach Open Science Tools
Authors: Hennesy Cody , Bakker Caitlin , Dunn Nicholas J. H. , Naughton David , Sayre Franklin , Traill Stacie
Published: April 2022

In three and a half years, the University of Minnesota Carpentries Initiative has taught over 180 hours of synchronous workshops covering research computing skills to over 400 students. During this time, learners from every college in the university have been exposed to best practices and hands-on guidance in the use of programming tools to streamline a range of research activities, from cleaning data to conducting analysis to creating visualizations. This cross-campus initiative has allowed departments and individuals to expand their networks and skillsets, creating opportunities for professional growth through a scalable, sustainable service model. This chapter describes lessons learned in recruiting, maintaining, and growing a multi-departmental team of librarians, technology specialists, and graduate students to deliver data science education.
Making Data Right
Authors: Marsolek Wanda , Barrick Katie , Kubas Alicia , McBurney Jenny , Hofelich Mohr Alicia
Published: April 2022

Learning how to wield data ethically and responsibly is a critical skill for data scientists, but one that is often lacking from traditional curriculum. Libraries have a long history of teaching data stewardship and sharing, and, in collaboration with collegiate research support entities, are good candidates to expose students engaging in data science to data ethics. This chapter presents four case studies on how the University of Minnesota Libraries and its partners have deeply integrated ethics into data management instruction. The chapter will highlight ethics for general data management instruction to undergraduate and graduate students from various disciplines, human subject data de-identification, qualitative methods and sharing, and biodiversity location data. Together, the case studies show how libraries and their partners are a natural fit to advance the work of data science curricula when it comes to managing data and the myriad ethical considerations that go along with this work.
Data Stewards, Curators, and Experts
Authors: Oxley Peter R. , Ben Maamar Sarah , Wheeler Terrie
Published: April 2022

Research data management practices continue to evolve as data become more connected, distributed, granular, and continuous. While keeping their mandate to serve the academic community, libraries are seeking to foster knowledge creation, learning, and information access in an ever more data-driven and online environment. In this chapter, the authors describe their perspectives that shape the library's mandate, roles, and technology. They detail specific roles that have been created to foster data engagement: a secure enclave data core, an institutional data catalog, scientific software management, bioinformatics and research reproducibility support, data integrity, and community engagement. A constant focus on customer service has shaped each role, built the library's reputation, and contributed to high-impact services.
A Decade of Research Data Management at the University of Edinburgh
Authors: Rice Robin
Published: April 2022

The chapter examines how research data management (RDM) policy and service developed at the University of Edinburgh, comprising three sections. First, the current shape of the service is examined, covering all of the service components and their utility to researchers in turn. Second, the service beginnings and foundations are laid out, such as the 2011 university RDM Policy and how this represented a strong institutional commitment to RDM, and how the first RDM Roadmap addressed policy fulfilment through service rollout. A look at governance, funding, and organisational structure completes this contextual background. Third, strategic directions are explored, focusing on the gaps and achievements of the most recent completed roadmap and a preview of a newly modernised RDM policy and its upcoming implementation.
Reading Fluency in Students With Dyslexia and ADHD
Authors: Picão Ana Sofia , Esteves Sandrina
Published: April 2022

Children with dyslexia have significant difficulties in reading and writing that are characterized by weaknesses in decoding and accurate word recognition, reading and spelling accuracy, reading fluency/speed, reading comprehension, among others. There is a high rate of comorbidities associated with dyslexia, one of which is attention-deficit hyperactivity disorder (ADHD). This study aimed to assess the three dimensions of reading fluency—accuracy, speed, and prosody—in children diagnosed with dyslexia and ADHD and to intervene to minimize their difficulties in this area. Three children, one male and two females, aged between 9 and 11 years old attending the 4th grade, took part in the study. It was found that the biggest difficulties experienced by the participants were in prosody and speed. Thus, intervention tasks were prepared and developed during nine sessions to improve the results obtained. At the end of the intervention phase, it was found that a direct intervention on the most frequent errors undoubtedly led to an improvement in reading fluency scores.
Reading for Babies
Authors: Coelho Palma Silvana , Araújo Luísa
Published: April 2022

This chapter describes the first step in the implementation of the Program Ler + Dá Saúde (Read + Health) Project in a healthcare centre in Portugal. It aims to establish a protocol for promoting health literacy in the healthcare visits of families with babies aged 0-18 months. In so doing, it illustrates, using concrete examples, how literacy was integrated in routine consultations by extending the guidelines contained in the National Child and Youth Health Plan. The materials and procedures proposed are intended to be a part of the activities and strategies that health professionals, namely family nurses, should adopt in their care of babies and their parents.
Network Relaxation and Cooperativity in Ion Conducting Polymers PEO-Li: An Analysis Based on the BSCNF Model
Authors: Aniya Masaru , Ikeda Masahiro
Published: April 2022

The understanding of fundamental materials properties is indispensable for the development of functional materials. Some years ago, it has been reported that the fragility in poly (ethylene oxide)-based Li+ ion conductors decreases with the Li+ ion content. The behavior was considered as unexpected and the origin unclear. In the present study, it is shown that the Bond Strength-Coordination Number Fluctuation (BSCNF) model of structural relaxation developed by the present authors provides an explanation to the observed behavior. The analysis based on the BSCNF model indicates that the cooperativity, or the number of correlated structural units involved in the network relaxation decreases with the Li+ ion content.
Effect of Die Edge Roundness on Crack Initiation near Punch Edge in Blanking
Authors: Imada Kenta , Maekawa Yoshikatsu , Sasada Masahiro , Tanaka Tatsuya
Published: April 2022

In this study, the effect of die edge radius on crack initiation was discussed in finish blanking. Experiments were carried out using die with rounded cutting edge. As a result, it was confirmed that crack initiation near the punch edge occurred earlier than that near the die edge. It was also confirmed that the burnished surface increased with an increase in the die edge radius. Finite element method was carried out from the initial stage of shearing and until the punch penetration depth was achieved just before the occurrence of the cracks to investigate the distribution of the mean stress. As a result, it was confirmed that the punch stroke, where the mean stress began to increase rapidly to a positive value, increased with an increase in the die edge radius, and the punch stroke at which the mean stress increased rapidly also increased.
Structures and Mechanical Properties of Pure Titanium by Different Boriding and Nitriding Conditions
Authors: Chen Tong , Koyama Shinji
Published: April 2022

Structure and mechanical properties of pure titanium by combined processing of boriding and nitriding with different processing temperatures in the heating furnace have been investigated. The effect of combined processing temperature for 2 h on the structure and mechanical properties of the treated specimens. As a result of the examination, combined processing at all designed temperatures resulted in the formation of titanium nitride, where the content of the nitride depended greatly on the processing temperature. When the processing temperature is 1300°C, the cross-sectional hardness of the hardened layer reaches the maximum. At the same temperature, the bonding strength also reaches the maximum, which is related to the performance of the hardened layer. Based on these results, when the processing temperature is 1300°C, the combined processing of pure titanium can improve the overall performance.
Effect of Electron Beam Welding on the Microstructure and Mechanical Properties of Low-Cost Titanium Alloys
Authors: Akhonin S.V. , Belous V.Yu. , Selin R.V.
Published: April 2022

An expansion of titanium to mass production industries, such as the automotive, is prevented by its high extraction and production costs (e.g. extraction of titanium from its ores is 15 times and 3 times higher than that of iron and aluminum, respectively). One possible way to reduce the cost of titanium is to use cheaper alloying elements instead of vanadium or niobium to stabilize the body-centered-cubic β-phase. Iron has been considered for the development of few low-cost titanium alloys, such as the Ti–2.8Al–5.1Mo–4.9Fe, Ti-1.5Al-6.3Mo-4.4Fe and Ti-3.6Fe-0.25O alloys, because of its stabilizing effect of the β-phase. Nevertheless, due to the high density of iron, high quantity of β-stabilizing elements and the formation of TiFe-based brittle intermetallic phases, welding joints of low-cost titanium alloys are prone to formation of cold cracks which is very important limiting factor for obtaining welded joints with a strength of at least 90% compared to the strength of base material. Electron Beam Welding with its higher welding speed and intensity used in the process has its advantages over other welding methods in achieving the higher temperature required for melting and joining titanium alloys and obtaining welds with better mechanical properties. In this work the influence of the electron beam welding thermal cycle on the structure and mechanical properties of low-cost titanium alloys Ti–2.8Al–5.1Mo–4.9Fe, Ti-1.5Al-6.3Mo-4.4Fe and Ti-3.6Fe-0.25O will be studied.
Effect of Friction Stir Forming Parameters and Heat Treatment on Mechanical Properties of Fibre-Reinforced Aluminium Alloy
Authors: Tabatabaei Hamed Mofidi , Ohashi Takahiro , Nishihara Tadashi
Published: April 2022

Fibre-reinforced materials have garnered attention due to their significant properties such as abrasion and heat resistance, as well as specific strength, which can result in environmental conservation and improved mechanical properties that can solve the limitation of developing light-weight constructions. A new method of joining stainless steel strands with an aluminium alloy using friction stir forming has recently been developed in our laboratory. In present study, the influence of the process parameters on the mechanical properties of a fibre-reinforced aluminium alloy using friction stir forming was investigated. In particular, the effect of process parameters on microstructure, hardness, and tensile properties of A5083 and A6061 alloys was evaluated. The highest tensile strength was observed at 880 and 1,240 rpm, whereas for lower rotation speeds (440 and 620 rpm), the strength decreased due to low temperatures and lower heat input. Heat treatments were applied to improve the mechanical properties of the developed A6061 fibre-reinforced composite. The effects of process parameters and heat treatment conditions on mechanical properties were experimentally investigated, and it revealed improved mechanical properties after applying T6 and age hardening treatments. It was confirmed that the strength after the heat treatment of A6061 was higher than that of the base material (310 MPa), and a high strength of 345 MPa was obtained at a rotation speed of 1240 rpm. It was concluded that rotational speed and heat treatment conditions significantly affect the metal microstructure and mechanical properties of the joint.
Mechanical, Thermal and Shape Memory Characterization of a Novel Epoxy Shape Memory Polymer
Authors: Unnam Mahesh , Velmurugan Ramachandran , Kumar Shanmugam
Published: April 2022

In past 3 decades a large number of shape memory polymers are available for various applications. This paper is aimed to produce a novel epoxy polymer by combining an epoxy base polymer Diglycidyl Ether of Bisphenol-A (DGEBA-Araldite LY556) and Polypropylene Glycol Diglycidyl Ether (PPGDE). The mechanical, thermal and shape memory characterization of material is done. It was found that the tensile strength of the material is reduced linearly with increasing the percentage of PPGDE. The elongation at break of the material is increased from 10% to 60% with 25% addition of PPGDE. The glass transition temperature of the material decreases linearly with increasing PPGDE percentage. D-70-P-30 (DGEBA-PPGDE) combination of the material is chosen for shape memory characterisation as its glass transition is above and within the vicinity of room temperature which is the pre-requisite for cold programming. The material shows good shape memory properties such as shape fixity and shape recovery.
Factors That Affect Pile Driving With A Vibro Hammer
Authors: Verbeek Gerald , Van Dorp Rob , Moscoso Nicolas , Bielefeld Marcel
Published: April 2022

When assessing the driveability of a pile into the soil using a vibro hammer it is important that all factors that affect that process are recognized. For a particular project, the soil conditions are obviously fixed as they are determined by the project location, and the only true variables are the selection and operation of the hammer, as in many cases the pile is already designed without taking into account all aspects that are related to the driveability with a vibro hammer. The paper explores the soil related aspects (so that the hammer can be selected to generate the movement in the pile to enhance soil penetration), the pile related aspects (to illustrate how pile parameters can affect the penetration process), and the operational aspects of the pile driving. These aspects are then illustrated through simulation results and actual installation records of the monopile installation for the NAM L13-F1-1 platform on the Dutch sector of the North Sea.
Early Detection and Assessment of Asphaltene Precipitation and Gas Hydrate Formation at Field Conditions
Authors: Delgado-Linares Jose G. , Pohl Mathias , Majid Ahmad A. A. , Yoda Chitose , Tanaka Norio , Zerpa Luis E. , Prasad Manika , Koh Carolyn A.
Published: April 2022

The detection of asphaltene precipitation and gas hydrate formation is critical to preventing production losses and to optimize strategies for mitigation and remediation. Likewise, the evaluation of some flow properties (e.g., viscosity and yield stress) of the slurries formed for asphaltenes and hydrates are paramount when developing and testing prediction tools for safe field operations. Several complications must be considered when dealing with asphaltenes and hydrates at field conditions, e.g., harsher conditions (especially high or extremely high pressure), the variation of fluid composition over time, and the lack of information on the thermodynamic conditions at which those solids (asphaltenes and hydrates) form. One possibility to face this challenge is to use field information to calibrate existing prediction models/tools and make them applicable for new field conditions. Hence, there is interest in industry to develop new tools that allow the detection of asphaltenes and hydrates in the early stages of their formation.

In this work, acoustic and nuclear magnetic resonance (NMR) measurements are utilized to detect asphaltene precipitation in crude and model oils. Asphaltene detection was performed at ambient pressure and at CO2 pressurized conditions. Acoustic and NMR measurements were sensitive to the asphaltene concentration in the tested oils. In addition, rheological properties such as viscosity and yield stress were determined for hydrate slurries in crude oil systems at different water volume fractions, salt (NaCl) concentrations and gas compositions. Gas hydrate slurry formed from a CO2-rich gas exhibited a phase inversion in rheological experiments (external phase changed from oil to water), which was possibly promoted by the CO2-activated natural surfactants of the crude oil.
Cloud-Based Array Electromagnetics Contributing to Zero Carbon Footprint
Authors: Strack Kurt Martin , Martinez Yardenia Lara , Passalacqua Herminio , Xu Xiayu
Published: April 2022

Fluid imaging technologies are used in a wide range of E&P applications. Among geophysical methods, electromagnetics (EM) determines subsurface resistivities and thus respond to fluid changes. On the path to zero CO2 footprint, the biggest potential for EM lies in monitoring geothermal, carbon capture utilization and storage (CCUS), and enhanced oil recovery (EOR) of hydrocarbon reservoirs. For EOR of hydrocarbon reservoirs, EM methods also increase the recovery factor. At the same time, usage of CO2 for flooding can help reaching zero carbon footprint faster.

In geothermal applications EM is a standard geophysical method. Monitoring is often carried out in compliance with induced seismicity monitoring to better understand the fluid movement inside the reservoir – here we suggest adding EM. For carbon capture applications, only recently EM methods have become of interest because there is a strong resistivity contrast between CO2 saturated fluid and normal reservoir fluids.

We designed a new EM acquisition architecture that combines novel technologies and addresses the need of calibrating surface and borehole data with each other. This is necessary to obtain reservoir scale parameters. We also add various borehole receivers to the system to improve image focus and resolution. Our array acquisition system applies multiple electromagnetic methods as well as microseismic in ONE layout. This reduces operational cost and provides synergy between the methods. In a production scenario, using multi-component EM allows resolving oil and water-bearing zones equally well, as well as obtaining fluid flow directions. The modular architecture allows a fit-for-purpose configuration tailored to specific exploration/monitoring targets (in terms of depth, frequency range, and sensitivity required). The entire system combines hardware with processing and 3D modeling/inversion software, streamlining the workflow for the different methods.

Acquiring and interpreting in combination with artificial intelligence and Cloud-based data transmission and quality assurance achieves near real-time operations. The biggest value is in faster operations and making decisions at a time when they can impact acquisition data quality. We use a multi-layered Cloud solution, for acquisition, processing, and interpretation. This acceleration then opens new doors for the breakthrough of this technology from exploration to production and monitoring. It also allows the application envelope to be enlarged to much noisier environments where real time feedback allows for better noise compensation methods.

Once all components are commercialized, this could become a real game changer by providing near real-time 3-dimensional subsurface images because of a reduction of operational cost and by reducing the carbon footprint per barrel produced.
Energy Transition Options for Offshore Vessels
Authors: Hollebrands Jeroen J. P. G. , Mestemaker Benny B. T. W. , Westhoeve Jan J. A. , Meijer-Buijs Annemarie A. , den Boer Leonard L. J. A.
Published: April 2022

The upcoming energy transition - necessitated by the requirement to reduce greenhouse gas emissions - will have a major impact on the offshore market. The future offshore fleet will have to comply with emission regulations and policies that become more stringent over time. Any new build ordered now, must comply to these tightening policies. It is therefore of great importance to make the right decisions on emission reduction technologies and preparing the vessel for future fuel options to keep the vessel compliant over time - as well as gain a competitive edge.

The offshore fleet has specific operational requirements that affect the feasibility of zero emission solutions: 1) safety is number one, operational robustness and redundancy are essential, 2) a large endurance is required and trading is global, 3) large load variations may occur and in harsh weather conditions. The Royal IHC cable-lay vessels (CLV) are designed to meet these requirements and are used as a basis in the following analysis. As a side note, an offshore vessel with fixed port of call is mentioned. Many different alternatives are currently presented as zero emission solutions. This paper highlights the different types of fuels and drives systems. The ones that are realistically feasible and ready to order now in an IHC Offshore vessel are explored in this document. 1) Low-sulphur marine gasoil (LSMGO) as base case. 2) Methanol in (dual fuel) combustion engines and fuel cells (with differentiation between LT-PEM and SOFC). 3) Hydrogen as fuel in fuel cells (LT-PEMFC) while taking into account the different storage methods proposed (liquefied, or stored in other medium such as methanol, LNG and ammonia).

The researched fuels all have different characteristics with significant implications on the design of the offshore vessel. This paper explains the consequence of the different combinations on the vessel design and operational profile based on implementation in the IHC CLV design. In addition, the paper further explains why these solutions are considered and why other potential solutions have been discarded.

Critical to the life cycle performance are the future policies. Several scenarios with varying fuel prices and emission costs are applied in the Life Cycle Performance Assessment (LCPA) tool. The real effect of these choices are thus considered for the entire life cycle of the product. The LCPA calculation results for different fuel types and different policy scenarios provide feedback on capital cost, operational expenses, and voyage expenses. While a CLV is taken as calculation basis, the results provide the audience a LCPA for emission reduction technologies and emission compliance and the effects of that on capital and operational expenses. The insights will be useful for the entire offshore fleet.
Preparation and Properties of Spray-Pyrolyzed Nanostructured Titanium Dioxide Films as Perovskite Solar Cell Component to Meet the Oil & Gas Industry Needs on Renewable Energy
Authors: Jardim Verônica Quirino , Paes Herval Ramos , Alves Andrey Escala , Fernandes Thaís Maria De Souza
Published: April 2022

According to forecasts, oil will continue to dominate the world energy demand in the next years. The International Energy Agency estimates that over 50% of the technology needed to achieve zero net emissions by 2050 is still under development. Therefore, refineries are currently incorporating renewable energy sources to reduce environmental impact. This article aims to study titanium dioxide films for application in perovskite-based solar cells which have high conversion efficiency and low production cost.

The precursor solution for deposition of titanium dioxide films (TiO2) was prepared by dissolving titanium isopropoxide in a solution of nitric acid and deionized water. TiO2 films were deposited by the spray-pyrolysis technique, which is simple, economical, and feasible for large-scale production. The deposition temperature was fixed at 450°C to achieve the Anastase phase. Deposition parameters such as time, flow and solution concentration were varied to assess their impact upon the morphological, structural, optical, and electrical characteristics of TiO2 films.

The morphology of the spray-pyrolyzed films consisted of homogeneous crowds of small crystals. No cracks were found across film surface. X-ray diffraction analysis confirmed the Anatase crystal structure, necessary for perovskite solar cell applications. The crystallite size ranged from 27.23 to 32.51 nm. The concentration of the precursor solution affected the optical gap energy. The thickness did not show great influence since samples with similar thicknesses, 2.12 and 2.58μm, presented optical gap values of 3.15 and 3.36 eV, respectively. All deposited films exhibited semiconductor characteristics with activation energies for the electrical conduction process between 0.24 and 0.49 eV. The samples deposited from a solution ratio of 450:3.25:37 (H2O: HNO3: Ti(iOPR)4) showed high values of electrical conductivity at room temperature compared to the films deposited from diluted solutions.

This study demonstrates how TiO2 films can be produce by spray-pyrolysis under the deposition conditions needed to improve film characteristics. Thus, it contributes to the development of more efficient and durable perovskite solar cells to make them more accessible and attractive for mass production and industrial use. Additionally, TiO2 films have corrosion resistance and photocatalytic properties that could be of interest to the oil and gas industry.
Using Predicted Dynamic Properties to Perform Seismic Site Response Analyses on a Bay of Campeche Calcareous Soil Deposit
Authors: Taboada Victor Manuel , Cao Shuang Cindy , Cruz Roque Diego , Barrera Nabor Procoro , Flores Lopez Francisco Alonso
Published: April 2022

This study presents the influence of using predicted (calculated) normalized shear modulus (G/Gmax) and material damping ratio (D) curves on the design acceleration spectrum at the depth of maximum soil–pile interaction of a calcareous soil deposit in the Bay of Campeche.When comparing the predicted curves to the laboratory curves, it is concluded that due to limitations in the predicting models, the minimum confining pressure (σ’m) that must be used to get a good match with the laboratory curves is 150 kPa. After performing site response analyses for three shear wave velocity profiles and eight recorded acceleration time histories, the design acceleration spectrum was developed based on the envelope of the 24 calculated acceleration spectra. The acceleration amplitudes of the design spectrum in the short period range are slightly larger using the calculated curves than the laboratory curves. For periods longer than 0.27 seconds, the acceleration amplitudes of the design acceleration spectra are identical for practical purposes when both calculated and laboratory curves are used. Therefore, it is recommened to use the equations presented herein to calculate the curves of G/Gmax and D for calcareous soils in practice for preliminary and final seismic site response analyses. They can be especially useful in final evaluations of large or critical projects to calculate the curves when time and cost constraints make it impractical to perform direct experimental determinations of G/Gmax and D curves for each soil layer encountered in the soil deposit.
Calculation of the Collapse Rating of Individual Pipe Joints for OCTG Casing and Tubing
Authors: Filgueiras Pedro , Klever Frans J , Bellani Luca , Compare Michele , Almeida Gustavo , Ybarra Maria Beatriz , Oliveira Jonathas , Zio Enrico
Published: April 2022

Commonly accepted procedures in the industry for calculating high collapse ratings of OCTG casing and tubing are described in Annexes G and H of API 5C3. Both approaches are limited to the analysis of historical data. Moreover, modern pipe dimensional mapping during production allows to provide properties specific to each individual pipe joint that were impossible before. In this paper, a method for calculating the collapse rating of each individual pipe produced is presented. In the developed method, the uncertainties on the quantification of each parameter are accounted for and the collapse rating of individual pipes is calculated to a pre-defined target reliability level (TRL). The statistical approach used to arrive at the collapse rating for a pipe joint is explained, and the consistency with the conventional method based on sample data is demonstrated. The developed method, therefore, enables practices long expected by the Oil & Gas industry, such as the clustering of the produced pipes based on their collapse performance. This allows the pipe manufacturer to assign high-performing pipes to the location of most severe loads in a well, while avoiding the delivery to the rig of the worst performing pipes.
A Review of Hydraulic Fracturing and Latest Developments in Unconventional Reservoirs
Authors: Temizel Cenk , Canbaz Celal Hakan , Palabiyik Yildiray , Hosgor Fatma Bahar , Atayev Hakmyrat , Ozyurtkan Mustafa Hakan , Aydin Hakki , Yurukcu Mesut , Boppana Narendra
Published: April 2022

Hydraulic fracturing is a widely accepted and applied stimulation method in the unconventional oil and gas industry. With the increasing attention to unconventional reservoirs, hydraulic fracturing technologies have developed and improved more in the last few years. This study explores all applications of hydraulic fracturing methods to a great extent. It can be used as a guideline study, covering all the procedures and collected data for conventional reservoirs by considering the limited parameters of unconventional reservoirs.

This paper intends to be a reference article containing all the aspects of the hydraulic fracturing method. A comprehensive study has been created by having a wide scope of examinations from the applied mechanisms to the technological materials conveyed from the different industries to utilize this technique efficiently. Furthermore, this study analyses the method, worldwide applications, advantages and disadvantages, and comparisons in different unconventional reservoirs. Various case studies that examine the challenges and pros & cons of hydraulic fracturing are included.

Hydraulic fracturing is a promising stimulation technique that has been widely applied worldwide. It is challenging due to the tight and nanoporous nature, low permeability, complex geological structure, and in-situ stress field in unconventional reservoirs. Consequently, economic conditions and various parameters should be analyzed individually in each case for efficient applications. Therefore, this study provides the primary parameters and elaborate analysis of the techniques applied for a successful stimulation under SPECIFIC circumstances and provides a full spectrum of information needed for unconventional field developments. All the results are evaluated and detailed for each field case by providing the principles of applying hydraulic fracturing technologies.

Many literature reviews provide different examples of hydraulic fraction methods; however, no study covers and links up both the main parameters and learnings from real cases worldwide. This study will fill this gap and illuminate the application of the hydraulic fracturing method.
Harnessing Offshore Wind: Using Mobile Floating Wind Units MOWUs and Energy Storage to Provide Clean Power to Production Installations
Authors: Ventrelli Saverio , Lund Per
Published: April 2022

This paper describes a novel concept that enables offshore operators to power their facilities with microgrids consisting of mobile offshore wind units (MOWUs). The MOWU consists of a floating unit anchored to the seabed. On the floating unit is a wind turbine with a generation capacity of 11-14MW. A battery energy storage solution (BESS) is included as part of the system, along with AC power distribution, transformers, switchboards, and a power management system (PMS).

The MOWU can connect to any offshore installation by means of a short length of subsea cable (up to several kilometers). The solution is scalable and can be adapted and deployed in the configuration needed to match the load profile and power needs of the host production (fixed or floating) or drilling facility. The primary objective of the concept is to reduce localized power production from existing onboard diesel and gas turbine generators. Initial estimates indicate that the improved energy mix with wind and energy storage combined can reduce carbon emissions by as much as 60-70% when compared to conventional generation with gas turbines, thus providing a technically sound solution to economically extend the field life of mature assets.
Optimisation of Oil Production with RCP Autonomous Inflow Control Devices in a Field in Offshore Malaysia, A Case Study with Shell Malaysia
Authors: Krishnan Thanushya , Sandhu Harwinder , Lai Chin-Lin , Konopczynski Michael , Moradi Mojtaba
Published: April 2022

During 2019 and 2020 the field operator conducted development campaigns in a thin oil rim carbonate reservoir offshore Malaysia. The horizontal development wells were expected to intersect heterogeneous formations with varying properties resulting in an uneven reservoir influx toward the wellbore. Oil production from these wells was expected to suffer severely from an early gas breakthrough. These challenges were recognized to be mitigated by deploying Autonomous Inflow Control Devices (AICDs), installed at reservoir interface along the horizontal section of the wells. The AICDs can manage the reservoir fluid influx entering the wellbore and therefore optimise the well performance.

To improve oil production and ultimate recovery, AICDs were incorporated in the lower completion design for the development wells. The Rate Controlled Production (RCP) AICD was chosen for this application. It is an active flow control device, delivering a variable flow restriction in response to the properties of the fluid and the rate of flow passing through it. This paper summarizes the integrated technical learnings from this project.

An integrated workflow was followed to design and deliver the AICD applications successfully for the operator in an offshore light oil reservoir with huge uncertainties in remaining oil thickness and reservoir properties. The wells with a horizontal length of ~6000 ft were drilled in a relatively thin oil formation. The well intersected different geological layers with different rock properties. The lower well completions comprised of RCP AICD valves, shrouded with debris filter screens with an in-situ gas lift system in the upper completions helping to lift the fluids to the surface. The wells were segmented into compartments with blank joints and swell packers and tailored AICD placements based on individual well's real-time log data to properly restrict the production of unwanted fluids. Through teamwork between the companies, the wells were successfully completed with AICDs.

The final modelling was performed just in the time span between reaching target depth and running the completion. Over two years of production, the wells completed with AICD not only have not seen any problem in terms of solid production, but they have also successfully exhibited limited GOR development which enabled oil production optimization. A PLT was also run recently in one of the wells to analyze further the zonal contribution of each section of the well and how AICD has effectively choked back the gas in selective zones.

The results show that the AICD completion ensured a balanced contribution from the entire 6000 ft long horizontal section in the well despite the heterogeneity of the carbonate reservoir and has potentially reduced the gas production significantly to enable more optimized oil production within gas offtake limits in the reservoir management plan.
Intelligent Hydrogen Gas Monitoring in Natural Gas/Hydrogen Blending
Authors: Davis Bryce , Stuart Daniel , Nieves Maldonado Mary , Kamavaram Venkat , Cheng Quan , Veedu Vinod
Published: April 2022

Hydrogen energy is a viable solution for reducing society's dependence on fossil fuels and decarbonizing several energy sectors such as solar, wind, and nuclear. One method actively being pursued to phase hydrogen into the energy sector is natural gas/hydrogen (NG/H2) blending. As the name suggests, NG/H2 blending integrates concentrations of hydrogen into existing natural gas pipelines to reduce the carbon concentration of methane. This blending carries the hydrogen and natural gas mix to municipal utility scales for extraction and consumer end-use. However, there are potential risks transporting hydrogen using the existing natural gas pipeline network. These include leakage, gas buildup, hydrogen embrittlement, and explosion threats to property and life near natural gas transmission pipelines. If these are to be utilized, there will be a critical need to provide "real-time" hydrogen monitoring capabilities for NG/H2 blends throughout the Nation's natural gas transportation and storage infrastructure. Moreover, the US natural gas transportation system is expansive. It requires a complex sensor network that can continuously monitor, record, and notify specific NG/H2 conditions at various pipeline locations to operators and managers. This paper describes the limited scale work, development, and potential "real-time" hydrogen detection and monitoring in NG/H2 blends using an intelligent optical sensor system. The transport efficiency of the pipeline, safety aspects, and in particular, questions about the capability of existing and new infrastructure to safely use NG/H2 mixtures as fuel will be addressed in this paper.
Artificial Intelligence for Automating and Monitoring Safety, Efficiency and Productivity in Industrial Facilities
Authors: Shaji Harikrishnan Arangali , Bishnu Sumit Kumar , Mishra Tarun , Ramakrishna M. V. S. Siva , Krishna R. S. Nikhil , Thomas K. Renil , David Daniel Raj
Published: April 2022

This paper delves into artificial intelligence (AI) based approaches to provide an automated approach to enhancing safety, efficiency, and productivity in modern industrial facilities, on a digital platform T-Pulse®. It explores the challenges and considerations to be taken when using such approaches to ensure that there are no errors for practical application. Broad examples are provided under each of the three categories to elaborate on the practical benefits of the same. Under AI approaches, both image processing models and numerical input models are covered based on the application. The image processing models are used to capture safety observations, resource utilization trends, milestone monitoring during maintenance activities, and automating the analysis of inspection data. In contrast, the numerical input models are used mainly from a process and planning optimization perspective.