bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of thermal damage caused by retinal implant in a feline eye
Authors: Rita de Cássia Fernandes de Lima  , Vítor Fernando de Souza Rodrigues  , Luciete Alves Bezerra
Published: January 2025

The advancement of the technology in the detection of some pathologies has provided several types of treatments that have been studied and applied to humans. Even hereditary diseases with no cure prognosis can be alleviated with the use of implanted devices. This is the case of Retinitis Pigmentosa, which has no cure. However, the use of retinal implants can help in partial recovery of the patient's vision. Several types of treatments have been studied and applied in humans. The present work was developed with the objective of obtaining insights that can help and guide a safe procedure for retinal implantation in patients with Retinitis Pigmentosa. In this process, certain precautions must be taken to avoid thermal damage of the patient's residual vision. Therefore, this work aims to calculate the thermal damage that may occur due to temperature increases as a result of the electrical power dissipated by the implant. To allow the validation of the three-dimensional geometry of the human eye, a previous study of a feline eye model with an epiretinal chip was carried out for which numerical simulation of temperature profiles and the calculation of thermal damage were done. In addition to temperature values, thermal damage is a function that quantifies the degree of cellular denaturation as a function of the power applied to the implant and its use time. Among some results presented, the main one proved that with the continuous application of an electrical power of 36.6 mW, the feline eye presented irreversible thermal damage after 5h12min. Furthermore, even after the implant is turned off, the thermal damage continues to increase, until the entire eye returns to its former thermal equilibrium. With the same methodology, an additional study is being carried out to calculate the advancement of the thermal damage in a human eye submitted to the ARGUS II implant, which was approved by the FDA (Foods and Drugs Administration  USA) for use in humans. In this work, the SolidWorks® software was used for three-dimensional geometric modeling of the eyeball, its respective tissues and the epiretinal implant. The Ansys-Fluent® was adopted for simulation of temperature profiles. The calculation of the thermal damage as well as the heat source term due to the blood perfusion were programmed and inserted into the Ansys-Fluent® program, using the Finite Volume Method and unstructured meshes.
Hand Vibration Analysis due Impact Equipment
Authors: Alysson Lucas Vieira  , Maria Lucia Machado Duarte  , Claysson Bruno Santos Vimieiro
Published: January 2025

Several human health problems can arise due to the loads transmission from impact equipment manipulated directly with the operator's hands. These issues can also extend to the upper limbs. Equipment such as stone breakers exhibit significant vibration levels during operation, and understanding how the intensity and duration of this vibration affect the efforts transmitted to the operator is necessary to assess potential mitigation during work. Therefore, this study aims to perform an operator's hand numerical model, using the finite element method, while operating the stone breaker, having as input data the vibration caused by the stone breaker. The objective is to determine the level of stress imposed and the resulting transmissibility on the worker's hands. In addition, to examining the changes in these values resulting from the positions modifications where the worker holds the equipment.
Intelligent Methodology Using Machine Learning for Epileptic Seizure Identification Based on Time-Frequency Analysis of EEG Signals
Authors: Diego Dutra Sampaio  , Priscila Lima Rocha  , Washigton  Luis Santos Silva  , Allan Kardec Duailibe Barros Filho
Published: January 2025

The diagnosis of epilepsy is conducted through visual inspection of electroencephalogram (EEG) signal recordings. However, due to the variations in convulsive disorders, it can be challenging for clinicians to constantly monitor the patient for seizure type, especially because EEG records contain hours of signal. Nevertheless, these patterns present in EEG signals can also be identified through signal classification methods based on signal processing and machine learning approaches. In light of this, this study proposes the development of a methodology for epileptic seizure type classification based on analysis of time-frequency characteristics of EEG signals, using Continuous Wavelet Transform (CWT) and joint moments of time-frequency distribution. Epileptic seizure classification was performed using a convolutional neural network (CNN), employing k-fold cross-validation methods. Accuracy, sensitivity, specificity, and area under the curve (AUC) metrics were obtained to validate this algorithm. The achieved results for the CNN classifier were 96.54% accuracy, 96.54% sensitivity, 96.54% specificity, and AUC = 0.90%.
Boundary element method for buckling analysis of elastically connected double-beam system
Authors: Angelo Vieira Mendonça  , Moab Bezerra Rodrigues  , Welky Klefson Ferreira de Brito  , Arthur Coutinho de Araújo Pereira  , Paulo Cavalcante do Nascimento Júnior
Published: January 2025

Studies of Double-beam systems have received significant attention from researchers due to their wide applications in civil and mechanical engineering. Commonly, finite element method or exact solutions have been employed to solve double-beam systems, with few others considering buckling of axially loaded double-beam systems with classical boundary conditions. This paper presents a novel formulation of the Boundary Element Method (BEM) to determine the critical buckling load of the double-beam system elastically connected by a Winkler elastic layer with generalized boundary conditions. Based on the Euler-Bernoulli beam theory, the double-beam system is composed of two identical beams. This paper provides a detailed discussion of each step involved in the BEM, including the fundamental solution, boundary integral equations, and algebraic system. Examples considering different boundary conditions, material properties, and load cases are done and compared to corresponding analytical solution. The results show excellent agreement between the BEM approach and the analytical solution, confirming the accuracy and effectiveness of the technique.
Integrating mesh adaptivity and digital image correlation for full-field displacement evaluation of cracked bodies
Authors: Felipe Lorenzo Andrade de Oliveira  , Igor Paganatto Zago  , Vinicius Fiocco Sciuti  , Ricardo Afonso Angélico
Published: January 2025

The study of crack initiation and propagation is primary to the fracture mechanics domain and essential for developing new materials. Such a study is relevant for refractory ceramics adopted as thermal insulators in high-temperature industrial applications. In particular, mechanical and thermal tests are essential in measuring properties and contribute to the material selection process. Such tests can be assisted using non-intrusive measurement techniques, in particular, by the Digital Image Correlation (DIC) technique, which enables to obtain full-field information concerning the displacement and strain fields in a loaded configuration. Identifying the crack location is a challenge for DIC techniques and requires special treatment of the correlation process to get reasonable resolution around the crack. Global DIC approaches can benefit from mesh refinement strategies to improve the identification of the displacement field and, consequently, the crack's location. In this context, the present article introduces mesh refinement strategies to improve the image correlation, allowing to identify the crack location in cracked specimens better. The adaptivity approach is developed using Correli framework and the Application Programming Interface (API) of the GMsh software, which has several features to control the element mesh size distribution, particularly by controlling mesh size parameters using strain and local gray-level residue. Herein, the mesh strategies are applied in a model composite system submitted to temperature variation. The composite consists of a brass inclusion surrounded by an alumina matrix. The thermal expansion coefficient mismatch between the phases leads to a radial crack pattern when the material is heated. The evaluation of the mesh refinement algorithm is established in terms of reducing global gray-level residual in the correlation procedure, and the enhanced definition of the crack location. The present article contributes to the DIC processing, getting more information on specific regions based on strain and gray level residual information, and also furnishes information to verify computational fracture mechanics tools.
Numerical Modelling of Crack Propagation Using BemCracker2D Program and Comparison of Different Criteria
Authors: Gilberto Gomes  , Álvaro Martins Delgado Neto  , Iuri Augusto Alves Lustosa  , Danilo Carvalho de Moura
Published: January 2025

In this study, we explore crack propagation through numerical modelling using the academic software BemCracker2D. Developed in C++ and based on object-oriented programming, BemCracker2D provides an intuitive graphical interface for modelling and mesh generation of boundary elements. Specifically designed for 2D analysis of problems involving cracks, the software employs the Dual Boundary Element Method (DBEM) to handle crack faces. Additionally, BemCracker2D supports a variety of crack propagation criteria, including the maximal circumferential stress criterion, the strain energy density fracture criterion and the maximal strain energy release rate criterion. These criteria are crucial for predicting crack behavior in different scenarios and situations. The software also allows for the calculation of Stress Intensity Factor (SIF), evaluation of fatigue life, analysis of crack coalescence, among other functionalities. By investigating crack propagation and comparing the results obtained with different propagation criteria, this study aims to enhance our understanding of crack behavior in materials. Insights derived from these analyses are essential for the development of more resilient and safe materials in a variety of industrial applications.
Numerical and parametric analyses of four unreinforced embankments on soft soils
Authors: Naloan Coutinho Sampa  , Laura Zappellini Sassi
Published: January 2025

The conventional method of estimating safety factors during various stages of construction remains prevalent for embankment stability analysis. This typically involves employing stability charts, equations, Limit Equilibrium Methods, and the Strength Reduction Method, with the Limit Equilibrium Method being the most conventional and widely adopted. Additionally, there is an increasing trend in leveraging results from instrumented embankments for performance and stability analyses, indirectly assessing parameters such as horizontal and vertical displacements, pore pressure, and soil displacement volumes. Despite the widespread acceptance of these traditional methods, many studies tend to evaluate results individually, overlooking the benefits of direct comparison for a more comprehensive analysis. This study employs a variety of methods and approaches to assess the stability of embankments under different geometries and soil conditions. The safety factors for various embankment configurations are estimated directly using two stability charts (O'Connor and Mitchell, 1977; Barnes, 1991), two stability equations (Huang, 2018; Sampa and Schorr, 2024), the Limit Equilibrium Method implemented in GeoSlope software, and the Strength Reduction Method in Abaqus and Plaxis. Conversely, the results of the soil deformability analysis are normalized for the purposes of indirect stability analysis, with the Abaqus software serving this purpose. Analyses were conducted on models featuring either a single material for both the embankment and the soil foundation or different materials for each. The elastoplastic model employing the Mohr-Coulomb failure criterion characterized the behavior of granular materials, while modified Cam-Clay models implemented in Abaqus described the behavior of soft soils. The analysis results focus on three key aspects: (i) comparison of safety factors, (ii) establishment of behavior patterns from stability and deformability analyses, and (iii) discussion of limitations, accuracies, and advantages of the assessed methods and approaches. Finally, a critical analysis addresses the impacts of varying criteria used in Abaqus and Plaxis software for determining safety factors based on the Strength Reduction Method concept.
Numerical modelling of a soil structure interaction for a torpedo base conductor in a petroleum well under an extreme lateral load
Authors: Fabio Sawada Cutrim  , Leonardo Teixeira Fernandes Abreu  , Luiz Fernando Bermero Nardi
Published: January 2025

This work aims to compare the performance, regarding the soil structure interaction, of a torpedo base conductor and a jetted conductor, considering a drilling rig drift-off scenario. This can be considered an extreme load scenario and the results will be shown for lateral loads coming from the interaction between the wellhead and the drilling rig, drilling riser and BOP.A complete 3D CAD model of the Torpedo Base Conductor was created and the soil was also modelled with 3D elements. Based on previous references, the selected 3D soil element was the Drucker-Prager constitutive model (Costa, 2008, Aysen, 2016 and Sanomia, 2016). Notably, the Drucker-Prager model accounts for non-homogeneous soil, meaning that the material properties vary with depth according to its undrained shear strength profile.The final results show the behavior of soil under lateral loads for both the torpedo base and the jetted conductor, as well as the structural response. The final conclusion is that the torpedo base has a better performance under lateral loads than the jetted conductor and can be considered a good well foundation solution to mitigate problems associated with interventions with dynamic position drilling rigs in shallower water depth.
Two-Dimensional Numerical Analysis of the Effects of Different Construction Methodologies on Tunnel Behavior
Authors: André Leonardo Torres de Oliveira  , Naloan Coutinho Sampa  , Marcos Aurélio Noronha
Published: January 2025

Abstract: The growth of urban populations necessitates the construction of robust infrastructure, including highways, public transportation systems, sanitation networks, and housing. Consequently, underground space utilization becomes pivotal, prompting the construction of tunnels, access shafts, and galleries. However, such construction encounters challenges due to the unpredictable geotechnical and geological characteristics of the excavation site, especially when sensitive structures are nearby. This study examines the impact of various tunnel construction methodologies on earth mass behavior, with a particular focus on deformations, surface displacements, and forces exerted on linings. To this end, numerical simulations were conducted utilizing ABAQUS finite element software under plane strain conditions. These simulations were designed to simulate conditions akin to a tunnel project in Florianópolis. The numerical model encompasses four layers of soils and rocks, spanning approximately 70 meters in depth and 190 meters in width. The tunnels, with an excavated area of 161.29 m², are situated 20 meters below ground and are equipped with primary and secondary linings. The soils/rock and linings are modeled using Mohr-Coulomb and linear elastic failure criteria, respectively. The soil domain was modeled with CPE4 elements, while the linings domain employed CPE4I elements. The study initially examines the convergence and confinement curves to incorporate the three-dimensional effects of construction, considering the degree of mass relaxation during lining application. The construction sequences for single and twin tunnels entail full-section excavation, subsequent placement of the definitive crown and inverted arch, and side drift associated with half-section and inverted arch. The results discuss and highlight earth mass deformation patterns, critical areas during construction, surface displacement basins, and forces exerted on linings at various excavation phases. The effectiveness of various construction methodologies in reducing deformations and enhancing project safety is evaluated. The conclusions drawn from the numerical analyses offer valuable insights for tunnel project professionals, facilitating the development of more efficient and safer construction practices.
Applications of the Circle-Inspired Optimization Algorithm: Comparison between MatLab and Python versions
Authors: Otavio Augusto Peter de Souza  , Letícia Fleck Fadel Miguel
Published: January 2025

This paper presents applications of the Circle Inspired Optimization Algorithm (CIOA), a modern optimization algorithm developed by the authors, in optimization problems from different areas of study implemented in MatLab and Python, with the main objective of making a comparison between versions of each computer language. Different sets of optimization problems were selected, involving classical benchmark functions, traditional truss structural optimization problems, and real-world optimization problems obtained in the 'CEC2020 Real-World One-Objective Constrained Optimization Competition'. Each optimization problem was solved multiple times on the same computer in MatLab and Python, to make comparisons between the accuracy and robustness of each version of the algorithm, evaluating the best solution and the mean and standard deviation between several solutions. Furthermore, a comparison of computational time was also performed. The results obtained attest to the efficiency of CIOA in both computational languages. In terms of accuracy and robustness, it was not possible to clearly identify a better version (MatLab or Python) for CIOA, as the differences obtained in the results were, in most cases, very small, and may be caused by the random characteristics of the algorithm. In the comparison of computational time, the MatLab version performed better in most optimization problems. This fact may be due to the efficiency of the specific libraries used and the programming experience of the authors in each computer language.
Data exploration: large language models in the construction of Knowledge Graphs
Authors: Cecília de Freitas Vieira Couto  , Nelson Francisco Favilla Ebecken
Published: January 2025

Knowledge graphs (KGs) are graphical representations of structured information that illustrate the relationships between concepts, entities, or data. KGs play a crucial role in enhancing the performance of artificial intelligence systems and search tools. However, constructing knowledge graphs is a complex undertaking, requiring the assimilation of substantial amounts of data. One approach to building KGs involves utilizing Large Language Models (LLMs), which leverage artificial intelligence to comprehend and generate natural language. Hence, this study advocates for the utilization of an LLM model in KG construction. The proposed model utilizes artificial intelligence to identify the most pertinent subjects within a domain of knowledge (nodes of the KG) and establish the connections between these topics (edges of the KG). To achieve this, the Stable Beluga 2 model, fine-tuned on Llama2 70B, was employed. The execution of the model utilized the Petals architecture, a system designed for collaborative inference and fine-tuning of large-scale models by pooling resources from multiple entities. This facilitates the execution of large-scale models with reduced computational resources. The outcome of this endeavor was the development of an artificial intelligence model capable of generating knowledge graphs that serve various purposes, including summarizing concepts, identifying correlations between areas of study, and responding to inquiries.
Emergency callback prioritize
Authors: Elisa Pissinatti Rodrigues  , Gustavo Maia de Almeida  , Filiphe Oliveira Louback
Published: January 2025

The need for performance evaluation of Electric Power Distributors by the National Electric Energy Agency (ANEEL), focusing on service quality, measured through the percentage of emergency occurrences with Power Interruption (PNIE). In response to the challenges faced by distributors in efficiently managing emergency complaints, with attention to reducing services without power interruption. The main objective is to develop an advanced system that optimizes service, establishes precise performance metrics, and reduces operational costs. We have a system that enables analysis, identification, prioritization, and forwarding of occurrences to the teams. Done through the mobile dispatch system, which streamlines communication between operations center operators and field teams. Once the service is completed, it becomes available for the next processing stage, where the data is analyzed and transformed into continuity indicators, providing a detailed view of service performance. Performance evaluation was conducted through meticulously selected metrics, allowing comprehensive analysis of Fuzzy logic, considering the diffuse and uncertain nature of the data. Among these metrics, calculation of the average degree of relevance, analysis of degree of relevance variation, and identification of minimum and maximum relevance stand out, providing a complete and detailed evaluation of model performance. After the initial tool implementation, it was observed that the percentage of unproductive displacement remained on average 40.64% over 12 months. Additionally, a significant increase of 18% in the entry of emergency occurrences was noted, indicating satisfactory initial effectiveness of the tool. Although there is room for additional improvements, these results suggest that we are on the right track in our pursuit of service optimization and continuous process improvement. Finally, the first round of model testing and validation has already shown promising results, indicating significant potential to reduce the percentage of unproductive displacements in the company. Based on solid foundations and previous analyses, it is expected that the model will positively contribute to operational efficiency, being considered a strategy to optimize operations. We are committed to closely monitoring the results to make continuous adjustments and improvements to the system.
Neuro-Fuzzy: Multivariable Identification of a Pumping System with Variable Demand
Authors: Hugo Augusto Marinho Moreira  , Juan Moises Mauricio Villanueva  , Heber Pimentel Gomes
Published: January 2025

Water supply systems (WSS) comprise a set of equipment, works and services aimed at supplying water, covering domestic, industrial and public consumption. WSS face challenges arising from hourly variation in demand, influenced by society's consumption patterns. These variations cause fluctuations in system pressures and energy inefficiencies. As a way of analyzing this aspect, intelligent techniques were used to identify an automated WSS with variable demand for the development of computational models. Two multivariable and non-linear models were developed based on Artificial Neural Networks (ANN) and Neuro-Fuzzy system (NF). The objective is to enable simulations of operation scenarios, analysis, design and implementation of new intelligent control algorithms. To collect the data used in training and validation, experiments were carried out throughout the system's operating region. For cross validation, tests were carried out in operating regions different from those used for training. The models were evaluated using performance criteria, such as: Root Mean Square Error (RMSE), Normalized Root Mean Square Error (NRMSE), Final Prediction Error (FPE) and Adjustment percentage. The results were obtained using an experimental bench and showed adjustments greater than 99%. The cross-validation results evaluated with performance indicators show the superiority of intelligent models in comparison to parametric and mathematical models in the multivariable and non-linear identification of water pumping systems for simulation and dynamics prediction purposes.
Structural Damage Detection using the Circle-Inspired Optimization Algorithm
Authors: Otavio Augusto Peter de Souza  , Daniele Kauctz Monteiro  , Letícia Fleck Fadel Miguel
Published: January 2025

This paper presents a novelty approach to vibration-based damage detection using matrix updating with the Circle-Inspired Optimization Algorithm (CIOA). The methodology is evaluated through numerical simulations of three structures: a 10-bar truss, a cantilever beam, and a Warren truss. In all cases, the systems are subject to ambient vibrations with varying noise levels to replicate inaccuracies in the acceleration signals. Furthermore, different analysis scenarios were considered, including single and multiple damages. The Data-driven Stochastic Subspace Identification (SSI-DATA) technique is employed to determine the modal parameters of these signals. Natural frequencies and mode shapes are compared under healthy and damaged conditions to identify the damage state through the methodology. The parameters of the optimization algorithm, CIOA, were set to θ = 97º and GlobIt = 0.90. In addition, a factor specific to the algorithm, the radius reduction factor, was reduced from 0.99 to 0.98 to accelerate convergence. The number of search agents and iterations varied according to the complexity of each structure. Considering all analyses for each scenario and noise level, the highest percentage errors in damage detection obtained were 0.163% in a multiple damage scenario with noise of 3% for the 10-bar truss, 1.453% in a multiple damage scenario with 5% noise for the cantilever beam, 3.600% in a multi damage scenario with 5% noise for the Warren truss. Therefore, results demonstrate the proposed approachs promise in identifying, locating, and quantifying single and multiple damages.
A finite element model to predict axial forces with friction in tubing strings
Authors: Otávio Bruno de Araújo Rodrigues  , Catarina Nogueira de Araújo Fernandes  , João Paulo Nogueira de Araújo  , William Wagner Matos Lira  , João Paulo Lima Santos  , Charlton Okama de Souza
Published: January 2025

This work shows a one-dimensional finite element model to predict axial forces with friction in tubing strings subjected to operational loads in the production of oil and gas. These strings undergo different combinations of axial forces throughout their lifetime. Accurate prediction of these forces is essential to maintain the structural integrity of this fundamental component of the well barrier system. Frictional forces, which impact axial forces, occur due to the contact between the string and the casing, which happens when the tube buckles. In directional wells, the weight and trajectory of the tubing also generate frictional forces along the casing. Due to the variety of operational loads, a general solution to the friction problem requires a numerical approach. To achieve the proposed objective, the adopted modeling is verified through analytical solutions, investigating results regarding the axial forces and displacements experienced by the tubing in different operations. Mesh refinement studies and computational cost of the model are also discussed. Its observed a good concordance between numerical and analytical results, coupled with an acceptable computational cost. The main contribution of the work is the possibility of using numerical modeling for tubing, including friction, with good accuracy, low computational cost, and potential for real-time analysis.
A Numerical Investigation of Conductor Casing Installation Using Material Point Method
Authors: Mávyla Sandreya Correia Tenório  , Jennifer Mikaella Ferreira Melo  , Beatriz Ramos Barboza  , Raniel Deivisson de Alcantara Albuquerque  , João Paulo Lima Santos  , Fabio Sawada Cutrim  , Rafael Dias
Published: January 2025

The initial phases of well drilling projects involves the crucial step of installing conductor casing, which can be achieved through various methods, including conductor driving. This operation consists by three distinct stages: self-weight penetration, suction, and hammering. Given the often-challenging environmental conditions, conducting experimental analyses of drilling parameters becomes impractical. Consequently, numerical modeling emerges as a feasible and reliable alternative for process control. In this study, the open-source software ANURA 3D was adopted, which utilizes the Material Point Method (MPM) in its solutions. Therefore, this research aims to explore the impact of numerical parameters associated with computational modeling on problem solution. For this purpose, a two-dimensional axisymmetric computational model of self-weight penetration was employed. This model facilitated the necessary modifications to deeply understand the problem while optimizing computational cost. This approach enabled an understanding of how the analyzed parameters influence not only the displacement of the conductor casing but also the behavior of soil stresses.
Advancing Anomaly Detection in Oil Production Wells with TranAD: A Deep Transformer Network Approach
Authors: Igor de Melo Nery Oliveira  , Pedro Esteves Aranha  , Thales Miranda de Almeida Vieira  , Andressa Celestino Araújo da Silva  , Davi Leão Ramos  , Eduardo Toledo de Lima Junior
Published: January 2025

The oil and gas industry is undergoing a profound transformation, leveraging cutting-edge technologies such as artificial intelligence, cloud computing, and the Internet of Things to optimize operational efficiency and safety. Within this context, ensuring the integrity of oil production wells is paramount for operational safety, environmental preservation, and minimizing production losses. Detecting unexpected events, namely anomalies such as spurious closures of Downhole Safety Valves (DHSV) and rapid productivity loss events, in well operations in a timely manner is crucial. The integration of sensor-based monitoring and computational modeling provides vital insights for identifying and mitigating such anomalies, thereby bolstering the industry's reliability and sustainability. However, the complexity of anomaly detection in oil production wells presents significant challenges. Firstly, historical data from producing oil wells tends to be highly unbalanced, with only occasional unexpected events occurring over the well's lifetime. Secondly, frequent valve change operations during the well's productive lifespan, while expected, can substantially alter pressure and temperature behavior, potentially confounding unsupervised techniques. To address these challenges, this paper proposes the evaluation of TranAD, a deep transformer network-based multivariate time-series anomaly detection model, applied on oil production wells data. TranAD utilizes attention-based sequence encoders to detect anomalies solely based on non-anomalous training data in the context of oil production wells. This study aims to assess the effectiveness of TranAD models in detecting anomalies using the 3W database, the first public repository released by Petrobras containing rare real-world undesirable events in oil wells. This dataset serves as a benchmark for the development of machine learning techniques tailored to the inherent complexities of real-world data. TranAD models trained on the 3W dataset will be compared with established benchmark techniques to validate their efficacy in this scenario. Drawing from previous case studies where TranAD demonstrated superior performance in detection and diagnosis across various domains, along with its data and time-efficient training, it is anticipated that TranAD will yield promising results in detecting anomalies in oil production wells.
Application of YOLO V5 for front-end loader detection in collision risk zones with reclaimers within a coal yard
Authors: Elsirlei de Oliveira Maria Valim  , Fidelis Zanetti de Castro  , Gustavo M. Almeida
Published: January 2025

In port operations, large machines known as reclaimers are used. Some of these machines are capable of reclaiming stored products at a nominal capacity of 8,000 tons per hour. While utilizing these colossal machines enhances productivity and reduces costs, their large dimensions have an unintended side effect: an increased risk of material and personal damage in the event of a collision.To mitigate this risk, a solution was proposed: training a YOLO V5 neural network to detect and alert the presence of other equipment within the defined risk zone. The target object for detection in this work is the front-end loader (pá carregadeira), chosen due to its high exposure to collision risk.For training the neural network, 3,195 images of various types of front-end loaders were collected, depicting different scenarios and positions. Additional background images were included. Annotations for bounding boxes were created using a tool provided by the website app.roboflow.com. The dataset was divided into 80% training images and 20% validation images12.For training the network, 3,195 images of various types of front-end loaders were collected, depicting different scenarios and positions. Additional background images were included. Annotations for bounding boxes were created using a tool provided by the website app.roboflow.com. Only a single class was defined, and the dataset was divided into 80% training images and 20% validation images.The training process was conducted in a staggered manner to optimize GPU consumption on Google Colab. Initially, a test was performed with 50 epochs, a batch size of 30 samples, and input images in the 640x640 pixel format. Subsequently, based on the weights from the first training, a second test was conducted by increasing the number of epochs to 100. Following the same logic, a new test was performed with the following parameters: a batch size of 60 and tests at 100 and 200 epochs.Remarkably, even in the first training, promising results were achieved: Recall: 0.94; mAP@0.5: 0.97; mAP@0.95: 0.77; Precision: 0.97The second training yielded even better results when compared to the first:Overall recall: 0.94; mAP@0.5: 0.97; mAP@0.5:0.95: 0.78414; Precision: 0.99Upon analyzing some machine images, the confidence of the markings increased to approximately 90% certainty. In conclusion, the work thus far has demonstrated satisfactory and promising results, justifying the continuation of further studies and simulations
Computational Modeling of Torpedo Base Penetration at Seabed Using Piezocone Tests
Authors: Tácio Valmir Dantas de Almeida  , Christiano Augusto Ferrario Várady Filho  , Joyce Kelly França Tenório  , João Paulo Lima Santos  , Rafael Dias  , Fabio Sawada Cutrim
Published: January 2025

This study presents a comprehensive investigation into the dynamics of torpedo anchor penetration at the seabed, leveraging real marine soil data obtained from Piezocone Tests (CPTu tests) provided by a prominent Brazilian oil and gas company. Recognizing the significance of accurate soil characterization, particularly in marine environments, the research meticulously characterizes undrained shear strength in a piecewise manner, thus addressing a key limitation of existing methods. By overcoming the one-layered soil constraint inherent in True's method, the study offers a more comprehensive understanding of torpedo anchor behavior across diverse soil stratifications. The utilization of CPTu tests provides several advantages, including real-time data acquisition, continuous profiling, and minimal soil disturbance, enabling precise modeling of torpedo anchor penetration. This approach not only enhances the accuracy of anchor penetration depth predictions but also contributes to a more robust analysis of seabed stability and anchor performance. To further refine the computational methodology, the study integrates the fourth-order Runge-Kutta technique, enhancing the precision of numerical simulations and facilitating more reliable predictions of anchor behavior. In addition to analyzing anchor penetration depths, the study comprehensively examines the balance of forces during the penetration phase, shedding light on the dynamic interplay between various factors influencing anchor embedment. Detailed torpedo base velocity profiles, analyzed depth-wise, provide valuable insights into the velocity distribution and its implications for seabed interactions. Furthermore, comparative analyses between controlled velocity deployment and free-fall installation scenarios offer practical insights into optimizing anchor performance and enhancing seabed stability in offshore engineering applications. By integrating real marine soil data with advanced numerical techniques and comprehensive analyses, this research significantly advances our understanding of torpedo anchor dynamics. The insights gleaned from this study have profound implications for the design and implementation of seabed installations, informing more efficient and reliable practices in offshore engineering.
Geological storage of CO2 in depleted reservoirs with lithological modeling and analysis of technical viability
Authors: Ruan da Silva Nobre  , Zenilda Vieira Batista  , Jonathan da Cunha Teixeira  , Rafael de Lima Omena  , Glydianne Mara diógenes fernandes
Published: January 2025

The objective of the work is to understand the key variables that dictate the complexity and viability of the implementation of carbon capture and storage (CCS). This involves examining the mathematical relationship between the storage capacity available in a reservoir and the various costs associated with injection implementation together with technical challenges such as, for example, lack of porosity or not proper lithology  Initially considering factors such as the distance from the reservoir to gas pipelines and facilities survey around them In other words: Will make it able to conclude which fields have a higher viability for CCS project installation.This research began with the survey of geological and production data from all fields that have been in production for over 30 years [1,2], totaling 104 production fields. Then were calculated the feasibility value by multiplying the fractions of oil and gas produced by the OOIP and OGIP, summing them, and then dividing by the distance in meters from the pipelines. These fields were then narrowed down to the 10 most viable fields in each basin according to these feasibility value. On another front of the study, the fields, and pipelines in the two basins were georeferenced using the QGIS software [3] and organized within it with bubble charts depicting their workable value. It was concluded that the most viable fields, respectively, are Guamaré (with almost double the viability of the second-ranked), Fazenda Junco, and Porto Carão. All fields in the Recôncavo Basin proved to be significantly more feasible for the storage technique than those in the Potiguar Basin. This is mainly due to the estimated 'storage space' determined through OOIP (Original Oil in Place) [4]. That was bigger in Recôncavo Basin.Then, were made lithological descriptions, and properties of previously produced methane from wells in the Guamaré field will be gathered. The goal is to estimate a comprehensive geological model of the fields and reservoir through statistical interpolation. This process will involve compilation, geotransformation, spatial location, and 3D geometry generation using Python scripts [5] in order to integrate with tnavigator simulator and the reservoir shape made with Python/VTK in 3D using spatial location of the wells. This stage is crucial to predict and contributes to a better understanding of the storage quality in terms of time and quantity of CO2 stored. This, in turn, leads to a more reliable conclusion regarding the feasibility of CCS in these two fields.
Integrated Computer-Aided Design for Well Cementing: Analyzing Containment in Deepwater Wells
Authors: Rafael Peralta Muniz Moreira  , Carlos Pessanha Costa Carvalho  , Ingrid Ezechiello da Silva  , José Marcelo Silva Rocha  , Emilio Cesar Cavalcante Melo da Silva  , Thiago Silva Piedade
Published: January 2025

Objective: This study investigates the impact of numerical simulations on cement integrity during the drilling of deepwater top holes through salt formations. The primary aim is to enhance well containment analysis by optimizing cement sheath quality.Approach: We begin with a comprehensive literature review, examining industry practices for drilling and cementing in salt zones. By analyzing existing literature, we gain insights into best practices and challenges related to cementing in deepwater wells. Next, we leverage field data from hundreds of wells in the Santos basin pre-salt region. This data allows us to identify critical aspects affecting cement quality and determine the main variables necessary for consideration. The heart of our approach lies in real-scale numerical simulations using chemo-thermo-mechanical finite-element models. These simulations guide our design process, considering factors such as well geometry (inclination, tortuosity, and hole enlargement) and different cement slurry properties. Importantly, the simulations also account for severe thermal and mechanical stress during worst-case scenarios of discharge and shut in. By ensuring effective well-control containment, we assure that the casing cement will not fail in the event of a blowout.Key Findings: For geometry requirements, meeting specific well geometry criteria is essential for achieving the desired cement sheath quality. As for cement slurry design, simulations indicate that salt-based cement slurry is favored due to its superior bond strength and field performance. We also evaluate the impact of cement expansion and shrinkage for different scenarios, showing the enhanced performance of expansive cement in long-term integrity.Industry Impact: Integrating simulations into standard cementing practices offers significant advancements in maintaining deepwater well integrity. By optimizing cement sheath quality, we enhance well containment and contribute to safer drilling operations in challenging environments.
Numerical modeling of rupture disk as a method of controlling pressure in oil well annulus
Authors: Gilberto Lucas Leandro dos Santos  , Catarina Nogueira de Araújo Fernandes  , Thiago Barbosa da Silva  , William Wagner Matos Lira  , Charlton Okama de Souza  , Emilio Cesar Cavalcante Melo da Silva
Published: January 2025

The work objective is to present a methodology for computational modeling for pressure control in confined annulus of oil wells using rupture disks. Throughout the oil wellbore cycle life, different operations cause variations in its temperature, causing pressure increases in its annular spaces, a phenomenon called APB (Annular Pressure Build-Up). In some cases, the difference between internal and external pressures on the casing or production columns can result in the loss of their respective integrity caused by burst failure or collapse. When using a rupture disk, once the pressure difference over the column is greater than the disk collapse pressure, there is a hydraulic communication between the annulus, balancing the volume and pressure between them. This pressure balance significantly increases the safety factors of the coatings, whether for burst failure or collapse. The methodology adopted to achieve the objective of this work consists of five macro steps: i) bibliographical review on the use of rupture discs in the context of APB, identifying their functioning and advantages; ii) definition and numerical implementation of pressure balance models following those available in the literature; iii) simulation of a reference scenario to verify pressure balance models; iv) simulations of variations in the rupture disc positioning in the reference scenario and calculation of the casing safety factors (burst and collapse); and v) final evaluation of the disk's ability to control annular pressures and protect the casings. The results indicate that the proposed methodology presents good results compared to the state-of-the-art. Additionally, possible modeling adjustments can allow a closer approximation to reality in the field. The main work contribution is to advance studies on pressure control methods in annular using a methodology proposed in the literature. In addition, to developing a computational tool that reproduces this methodology.
Simulation of continuous gas-lift technique in oil-gas systems using OpenFOAM and the Volume of Fluid method
Authors: Naim Jessé dos Santos Carvalho  , Livia Flavia Carletti Jatobá  , Grazione de Souza  , Helio Pedro Amaral Souto
Published: January 2025

In order to maintain optimal production rates in oil reservoirs, artificial lift methods are employed as reservoir pressure declines over time due to oil extraction. The gas lift technique is one of such methods where a compressed gas, usually a mixture of hydrocarbons with low molecular weight, is injected into the lower section of the pipeline through valves. The expected result is that the additional energy provided will propel the oil to the surface and the mixture of gas and oil will have a lower effective density, thus making it easier to be transported to the surface. This artificial lift method, when applied to restore productivity is not limited by the well depth and can be applied to offshore facilities and allows operation regimes in both continuous or intermittent lift. While computational fluid dynamics (CFD) simulations for gas lift problems commonly use commercial softwares, we propose CFD simulations using the free toolbox OpenFOAM-10 using the Volume of Fluid (VOF) method. This approach aims to simulate a gas lift scenario where a methane-like gas is injected horizontally into a pipe containing upward-flowing oil, replicating real-world oil industry conditions. The main goal is to investigate the gas lift process, analyzing how the gas propels oil and increases oil production compared to scenarios without gas lift. We focus on the continuous gas lift injection regime and compare VOF simulation results with those obtained from the Smoothed Particle Hydrodynamics (SPH) method for the same problem.
A numerical procedure to identify vugs and fractures in rock samples based on CT scan data
Authors: Victor Manuel  Villegas Salabarria  , Yan Lobo  , Nathan Shauer  , Philippe Remy Bernard Devloo
Published: January 2025

This article introduces novel algorithms for fractures and vugs recognition in computed tomography (CT) rock images. The proposed algorithms can be used in both two-dimensional (2D) and three-dimensional (3D) approaches to accurately identify fractures and vugs within rock samples. A detailed explanation of the implemented method is provided, elucidating the underlying principles of the algorithms. Furthermore, the method's applicability is investigated through testing with various models of pre-trained neural networks.The study contributes to rock image analysis by introducing effective techniques for identifying fractures and vugs in CT scans that can be applied for geological and engineering purposes. In a demonstrative application, this methodology was implemented to generate a two-dimensional finite element mesh, thereby facilitating the simulation of the Darcy equation using the Finite Elements Method.