bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical formulation for advanced analysis of semi-rigid steel-concrete composite frames
Authors: Ricardo Azoubel da Mota Silveira  , Luiz O. M. Teles  , Ígor J. M. Lemes  , Rafael C. Barros
Published: January 2025

The present work aims at the implementation and validation of a displacement-based two-dimensional numerical formulation including several sources of non-linearities in steel-concrete composite frames, such as second-order effects, plasticity and beam-to-column semi-rigid connections. The co-rotational-based approach is used to describe the finite element formulation, allowing large displacements and rotations in the numerical model. Two rotational pseudo-springs in series are positioned in the finite elements ends. One of them are used to include the gradual loss of stiffness determined by the cross-sectional plastification. The limiting of the uncracked, elastic and plastic regimes is defined in the Normal Force-Bending Moment diagram. In the cross-sectional analysis, the Strain Compatibility Method (SCM) is used to capture the axial strains in the section components. In this way, the constitutive models of the materials are described by continuous functions. The cracked effect is considered by the effective moment of inertia of the concrete cross-section. The other spring include the effects of the semi-rigid beam-to-column connections through the moment-rotation relationship. A multi-linear model for beam-to-column connections is used. To validate the proposed numerical formulation, the results obtained are compared with numerical and experimental data available in the literature. Since the model proposed here starts with the concentrated simulation of nonlinear effects, an examination of the finite element mesh refinement is also carried out. These comparisons indicated for the validation of the numerical procedure proposed and implemented here, highlighting the precision of the formulation in both the pre- and post-critical structures behavior.
Optimizing Mesh and CFD Simulation Performance: A Multivariate Analysis Approach
Authors: Tiago Martins de Azevedo  , Matheus Costa Pereira  , Anderson Paulo de Paiva  , Matheus Brendon Francisco
Published: January 2025

The objective of the study is to analyze mesh parameterization through the weighting of results that can define an increase in precision and a reduction in simulation time. To optimize the performance of a mesh and CFD simulation, we will adopt a systematic approach. Initially, we will employ experimental design, with five factors varied in three replications. These factors directly influence three responses. After collecting the experimental data, an evaluation of the significance between the independent variables was carried out, proposing a regression function capable of explaining the behavior of the factors and their relationship with the defined responses. Next, we will identify the individual optimal points using the Ordinary Least Squares method, representing ideal configurations of factors that maximize or minimize the responses of interest. Based on the results obtained, the Payoff matrix will be assembled, containing the individual optimal points and the reactions of the other variables. Thus, the scaling of functions will be performed to formulate and employ the minimization of the Mahalanobis multivariate distance, considering an adequate weighting between the optimal responses. This approach will guarantee the attainment of balanced and efficient solutions. Finally, we will integrate the results of the Payoff matrix into the mixture arrangement methodology, allowing for the conclusion of the analysis of optimal points for each function weight, providing efficient responses for the continuous improvement of the process. This systematic approach, which combines techniques of experimental design, regression, optimization, and multivariate analysis, will be fundamental to maximize the efficiency of mesh and CFD simulation, ensuring precise and reliable results.
Topology Optimization of Periodic Cellular Materials through the Progressive Directional Selection Method and Finite-Volume Theory
Authors: Luiz Carlos Lima Veras  , Márcio André Araújo Cavalcante  , Arnaldo dos Santos Júnior
Published: January 2025

This investigation presents the Progressive Directional Selection (PDS) method to optimize the topology of periodic cellular materials, achieving high performance and minimal weight. The homogenized elastic properties of cellular materials are determined using the homogenization method applied to periodic materials based on the unit cell concept as an intermediate step of the topology optimization procedure. The literature often constructs the design domain to conduct a finite element analysis. However, some problems are related to numerical issues, such as the checkerboard pattern and mesh dependence. The checkerboard effect is related to the assumptions of the finite element method, as the satisfaction of equilibrium and continuity conditions at the element nodes, particularly for linear triangular and quadrilateral discretizations in the absence of regularization schemes. This problem can be overcome by the Finite-Volume Theory (FVT), which satisfies the equilibrium equations at the subvolume level, and the compatibility conditions are established through the adjacent subvolume interfaces. The PDS method is inspired by natural selection processes found in biology and employs a strategy to meet the objective function of a discretized analyzed domain subject to a volume constraint. Population selection is based on performance criteria specific to the problem through an iterative process that concludes when the optimized topology ceases to evolve. Numerical examples of topology optimization for materials with periodic cellular microstructures are analyzed using PDS and FVT.
Finite element analysis of double nanobeams having Pasternak foundation in between
Authors: Angelo Vieira Mendonça  , Gabriella Lima Henrique  , Ana Clara Ferreira Siqueira  , Arthur C.A. Pereira  , Welky Klefson Ferreira de Brito  , Paulo Cavalcante do Nascimento Júnior
Published: January 2025

Single/double nanobeams (nanowires) have attractive features including reduced sizes and high flexibility and conductivity. As a result, many engineering applications such nanoelectromechanical systems (NEMS) and biomedical devices have been developed in technology industries. Due to the extremely high surface area-to-volume ratio, the properties of nanobeams have size-dependent behavior. In this paper, elastically connected double nanobeams are represented on Eringens nonlocal elasticity theory. Each nanobeam of double beam is modeled as Euler-Bernoulli beam and the interconnecting layer is represented by a Pasternaks elastic foundation model. A four-node double-beam finite element with eight degrees of freedom using approximate functions to interpolate transverse displacements and rotations is derived where both stiffness matrix and load vector are explicitly shown. The present FEM solution is validated by numerical examples where the influence of effects of dimensionless small-scale parameters, boundary conditions, and shear parameter of Pasternak foundation on displacements and stress resultants of double nanobeams are investigated.
An investigation on the collapse pressure prediction of subsea pipelines with realistic corrosion defects
Authors: Savanna Cristina Medeiros D'Aguiar  , Renato de Siqueira Motta  , Adriano Dayvson Marques Ferreira  , Silvana Maria Bastos Afonso da Silva
Published: January 2025

Subsea pipelines are widely used for oil and gas transportation, but they are susceptible to failure due to corrosion. Corrosion in pipelines typically results in defects of varying depths and complex shapes. The computational simulation through the finite element (FE) method is one of the most efficient and accurate tools for assessing the integrity of corroded subsea pipes by allowing the simulation of the nonlinear behavior and assessing the hydrostatic collapse. This paper evaluates the collapse response of subsea pipelines with realistic corrosion defects. The study uses the PIPEFLAW system - developed by the PADMEC (High-Performance Processing on Computational Mechanics) research group from UFPE - which integrates reliable tools for automatic FE model generation and performs nonlinear analyses. After validation based on the experimental tests available in the literature, the effect of realistic corrosion defects on the collapse pressure of subsea pipelines is analyzed in detail. The results are compared to results obtained using a semi-empirical method and numerical results obtained considering idealized FE models, i.e., constant-depth and elliptical-shaped corrosion defects. It is observed that the non-uniformity of defects is an important factor affecting the collapse response of pipes. In addition, the idealized geometry of the corrosion defects, especially when considering constant depth, leads to an excessively conservative prediction of the hydrostatic collapse.
Artificial Neural Networks for Optimization procedures of Mooring System of Floating Platforms
Authors: Bruno da Fonseca Monteiro  , Mauro Henrique Alves de Lima Junior  , Carl Horst Albrecht  , Breno Pinheiro Jacob	Federal University of Rio de Janeiro
Published: January 2025

Floating production systems (FPS) are widely used for oil exploitation by offshore industry. Installation of these systems have been advanced to deep and ultra-deep water subject to both extreme and operational environmental conditions. Under these conditions, mooring systems assume a fundamental role of keeping the FPS on the location and thus ensuring the integrity of other systems. Numerical model of these systems requires rigorous nonlinear static and dynamic analysis in the time domain using Finite Element Method (FEM) which have high computational costs. Therefore, an optimization process that may requires hundreds or thousands of analyses of the candidate solutions can take a long time. Thus, this work aims to optimize a mooring system of a floating production system, changing the evaluation of the objective function and the associated constraints from Finite Element Procedure by an Artificial Neural Network, in order to reduce the computational costs. Such reduction of time consuming may favor the accomplishment of several studies of the system in question. Case study presents a real-world scenario and the optimization tool employs the Particle Swarm Optimization (PSO) method. From the results we can see that the replacement of the FEM analyses by ANN meta-model has a high level of accuracy and presents low computational cost.
Cost-Optimized Mooring Systems integrating Load Reduction Device for 15 MW FOWT
Authors: Salvatore Verde  , Alverlando Silva Ricardo  , Eduardo Nobre Lages
Published: January 2025

The wind energy sector is shifting towards larger turbines to reduce energy costs, posing challenges for installations in shallow and intermediate waters (60-150 meters) that require smaller platforms and mooring systems. Previous research utilized a multi-objective optimization (MO) framework, employing tools like NSGA2 and OpenFast with MoorDyn, to design systems compatible with synthetic lines. Incorporating load reduction devices (LDRs) in mooring systems offers significant benefits by reducing loads on anchors and mooring lines, allowing for smaller, lighter anchors, and mitigating fatigue damage. LDRs, such as ballasted pendulums, polymer springs, and hydraulic dampers, feature unique non-linear stiffness curves crucial for performance. This study advances the MO framework by assessing a mooring system with spring polymer LDRs and conducting a sensitivity analysis of key design variables using the design of experiments (DOE) approach. It integrates the Pymoo optimization library with industrial software like OrcaFlex and OrcaWave, promoting broader industry adoption. The findings indicate significant reductions in mooring system costs, particularly for smaller mooring radii, and a 22% decrease in computational costs with fewer design variables, enhancing the mooring design process for any floating platform in any water depth.
Into the gray matter: construction and coupling of multiscale highly-detailed arterial networks in the human cerebral cortex
Authors: Eduardo Guerreiro Zilves  , Gonzalo Daniel Maso Talou  , Lucas Omar Müller  , Pablo Javier Blanco
Published: January 2025

Stroke-related diseases represent 11% of worldwide deaths. State-of-the-art medical imaging describes many aspects of cerebral circulation. Nevertheless, the limited resolution of these techniques hinders the study of the hemodynamics in smaller vessels. Computational models aid in this problem, providing tools to characterize cerebral hemodynamics in clinical scenarios of interest that are otherwise inaccessible. This work aims to build vascular networks in the human cerebral cortex to study hemodynamics across different regions of the gray matter. The method is based on the Constrained Constructive Optimization method (CCO), called PDCCO, which generates vascular networks following a set of anatomical rules. A patient-specific MRI geometry of the cerebral gray matter is used to register an existing vascular model of the major cerebral vessels in the pial surface of the brain, from where the network is expanded. The brain geometry is partitioned into three territories for each large cerebral artery. The vascular generation is conducted independently for each territory and merged into a single network. First, a thin volume of the pial surface is filled with blood vessels down to the scale of penetrating arterioles of 50 μm. The network is further extended downwards to penetrate the gray matter, and deep vascularization is achieved by appending sub-tree networks to each terminal vessel. These sub-trees are generated separately with vascular properties associated with the gray matter. The final network reaches 234000 vascular segments in the pial network, out of which 116977 are terminal vessels. In turn, each terminal vessel gives rise to a network of 50 terminals, yielding 5 million terminals, and 10 million vascular segments, for each hemisphere. Over the pial surface, the diameters vary between 2100 μm and 26 μm, with terminals between 50 μm and 60 μm, and the pressure drops from 100 mmHg to a range between 50 mmHg and 70 mmHg. The network can be coupled with existing blood flow models of the entire cardiovascular system for the simulation of pulsatile blood flow to study pressure heterogeneities along the cerebral cortex in normal and pathological systemic conditions. This novel approach proposes a strategy for the automatic vascularization of the brain, with the aim of understanding microcirculation under different conditions, allowing the study of the risk of stroke, among other mechanisms involved in the onset and progress of degenerative diseases.
Isometric Boundary Element Method for 2D analysis of elastostatic structural issues
Authors: Evyllyn Dos Santos Vieira  , Márcio Farias Italiano de Araújo  , João carlos cordeiro barbirato
Published: January 2025

In structural engineering, there is a growing trend towards using elements that better conform to geometric characteristics. This is particularly true when leveraging surface (or line, in 2D cases) generation in CAD environments, directly benefiting from more precise geometry. In this context, the need for Isogeometric elements arises. Through their utilization, the analysis of more complex stress and strain distributions is conducted with greater accuracy. This paper presents an alternative for analyzing the structural behavior of elastostatic structural cases through 2D modeling, employing an approximate method with Isogeometric elements. A computational implementation of the Boundary Element Method (BEM) was developed using the Python programming language. The "2D BEM" code was adapted, employing Kelvin's fundamental solution with the use of continuous and discontinuous linear elements, as well as higher-order elements, for more accurate boundary discretization. The formulation of BEM thus enables the modeling of the domain, in this case, the analysis of 2D bodies in the presence of mechanical damage, with iterative monitoring. The behavior is assessed through the displacements obtained for the boundary and internal points, as well as the stresses, conveniently evaluated in graphical representations. Applications are presented to test the implemented modeling and to provide an alternative for analyzing an important area within structural systems in civil construction projects, among others.
Phase-field modeling of hydraulic fracture interaction with natural fractures
Authors: Eduarda Marques Ferreira  , Roque Luiz da Silva Pitangueira  , Lapo Gori
Published: January 2025

The problem of hydraulic fracturing has been the subject of several studies in recent years, including different proposals for analytical, experimental, and numerical models. This interest is justified by the complexity of the problem and its great relevance, with applications in various areas including the industrial, energy and engineering sectors. Several applications deal with natural reservoirs which are usually characterized by the presence of inclusions, heterogeneities and natural fractures, the latter being the subject of this study. These pre-existing fractures affect the circulation of the pressurized fluid inserted into the reservoir, influencing the path of the hydraulic fracture. The interaction between hydraulic and natural fractures generates complex fracture propagation patterns involving arrest, cross and branch phenomena between the cracks. In this sense, an interesting approach to modeling hydraulic fracturing is the use of phase-field models (PFM). Through its variational approach, the PFM is able to automatically deal with any number of cracks without restricting their shapes or trajectories and the crack path is obtained directly as part of the solution to the energy minimization problem. Therefore, this paper proposes a study of the interaction between hydraulic fractures and different networks of pre-existing natural fractures using a PFM that considers the pressure load on the surface of the hydraulic fractures. Numerical examples are presented to illustrate different possible interactions between the cracks and to explore different initial crack scenarios. All simulations were performed using the INSANE (INteractive Structural ANalysis Environment) software.
Simulation of cohesive fracture method in concrete structures
Authors: Kycianne Rose Alves de Goes Barros  , Rafael Nunes da Cunha  , David Leonardo Nascimento de Figueiredo Amorim
Published: January 2025

The objective of fracture mechanics is to analyze the materials behavior and its failure modes applied to structures. Thereby, it is possible to identify the parameters that impact directly on crack evolution. Geometry, loading, and material properties are examples of crucial failure factors. There are some existing methods to analyze structural collapses, but the cohesive fracture is well known because of its efficiency, being used to calculate many different engineering materials. This paper uses the fundamental concepts of cohesive fracture to link experimental and numerical data. In other words, this paper aims to study two different concrete structures in which were applied cohesive fracture method and then compare the theoretical results with experimental ones. Moreover, some parameters such as crack position, width, thickness, and fracture energy, were defined by finite element analyses. In general, the obtained results show conformity between both simulations.
Checking the coupling between overhead crane hook and steel ladle trunnion in Steelmaking Plant using convolutional neural networks
Authors: Marcelo De Nadai Marcon  , Celso Soares Godoy  , Gustavo Maia de Almeida  , Daniel Cruz Cavalieri  , Cassius Zanetti Resende
Published: January 2025

Overhead cranes are equipment designed for the efficient and safe movement of large loads and are widely used in the industry. They play a very important role in logistics and production by allowing the flow of materials, machinery, and products from one location to another, whether within a factory, warehouse, shipyard, or any other industrial environment. These equipment have a simple mechanical structure, consisting of a main beam equipped with wheels that allow movement along tracks. A hoist is suspended under the main beam, which can also move along it, and is used to lift and lower loads. The element that couples the load to the lifting system varies according to the type of load.In this article, we explore the coupling system commonly used in the steel industry for handling steel ladles through overhead cranes, called hooks and bails. This study proposes the use of artificial intelligence (AI) and machine learning techniques, through computer vision based on convolutional neural networks to detect the coupling, segmenting both the hook and the bail and thereby determining the precise alignment of the assembly before lifting. This contributes to validating the operator's visual information, reducing possible human errors, and promoting greater safety for both the process and the people involved.
A model for predicting temperature and pressure profiles in gas-lifted oil wells
Authors: Luiz Elias da Silva Filho  , Thiago Barbosa da Silva  , Catarina Nogueira de Araújo Fernandes  , William Wagner Matos Lira  , João Paulo Lima Santos  , Charlton Okama de Souza
Published: January 2025

This work presents a methodology for predicting temperature and pressure profiles in oil wells that employ the artificial lift technique through gas-lift. When the reservoir pressure is not sufficient to bring the oil to the surface or when increasing production efficiency is desired, artificial lift techniques are employed. The injection of gas (gas-lift) is one of the most commonly used techniques. In the oil and gas industry, the accurate prediction of temperature profiles during various operations is crucial for ensuring well integrity. These profiles serve as inputs for calculating variations in annular pressures, casing stress, corrosion rates, and other critical parameters. However, calculating these profiles is challenging, requiring data on the well's underground structure, simultaneous resolution of the differential equations governing heat transfer phenomena in the structure, and modeling the hydrodynamic behavior of fluids. In wells where production operations are carried out using gas-lift, the complexity is even greater because the annular fluid, previously static, now circulates downward. This fact increases the number of equations to be solved and the number of fluids to be modeled. Thus, the development of strategies for obtaining these profiles is justified. To achieve the proposed objective, the methodology adopted in this work is based on three main steps: a) description of the mathematical formulation of the problem, considering the energy, momentum, and mass balance in the flow of both the produced fluid and the injected fluid; b) development of a numerical strategy enabling the simultaneous solution of the equations formulated in the previous step, thus allowing the determination of temperature and pressure profiles in the well; and c) verification of the strategy by comparing the results obtained using the procedure described in this work with thermal profiles from wells reported in the literature. The main contribution of this work is to enable the prediction of thermal profiles in oil wells in production operations with artificial lift by gas injection, allowing these profiles to be used in the design and monitoring of wells, thereby adding safety and efficiency to the operation.
Automated Approach for Modeling APB in Oil Wells
Authors: Gleide Karolayne Melo Lins  , Catarina N. A. Fernandes  , Thiago B. da Silva  , João Paulo L. Santos  , William W. M. Lira  , Charlton O. de Souza  , Emilio C. C. M. da Silva
Published: January 2025

This paper presents an automated approach for modeling APB (Annular Pressure Build-up) in vertical oil wells. The APB phenomenon is characterized by an increase in pressure in the annular spaces of wells due to the variation in temperature of confined fluids, resulting in significant loading differentials on the casings. Therefore, to ensure the wells structural integrity, it is essential to consider the effects of APB in the design of equipment and casings. However, the calculation of pressure buildup is complex and lacks a closed (or analytical) solution, requiring the use of computational tools. In the literature, some successful works can be identified that model the APB phenomenon in finite element-based software, such as ABAQUS, for example. However, creating models through the graphical interface is a slow and limited process. To achieve the proposed objective, a work methodology is developed based on the following steps: a) development of a strategy for modeling APB in ABAQUS; b) creation of Python scripts to automate all tasks (pre-processing and solving) of the developed strategy; and c) validation of the proposed strategy through scenarios with results available in the literature. In the developed approach, all scenario data is described in a JSON structured file. To model the APB, the main Python file is executed, and thus, the entire developed strategy is automatically executed in ABAQUS. Finally, the ABAQUS graphical interface is opened, displaying all results. All annular fluid modeling is performed using ABAQUS's own fluid cavity interaction. Compared to another approach available in the literature, the developed strategy shows relative errors of up to 10% in predicting APB. This discrepancy can be justified by the simplifications in calculations adopted by the reference work and by considering the Fluid Cavity at a constant temperature throughout the annulus, as done in this study. Despite the differences found this study contributes by providing an additional tool to assist studies related to the APB phenomenon and in predicting its corresponding effects on casings. Furthermore, the proposed automation adds speed to modeling and prevents errors in scenario construction or strategy reproduction.
Deep Learning-Based Reservoir Simulation Proxy Models
Authors: Alexandre de Souza Jr.  , Juan A. R. Tueros  , Matheus G. Machado  , Rafael F. V. C. Santosa  , Ramiro B. Willmersdorf  , Silvana B. Afonso  , Leonardo C. Oliveira  , Bernardo Horowitz
Published: January 2025

The behavior of oil reservoirs, characterized by geophysical, geochemical, and geological properties, can be understood through the simulation of computational models, involving the construction of meshes of finite volume elements with equations derived from fundamental principles. However, the execution of multiple simulations for activities such as optimization and uncertainty assessment results in substantial computational costs.To overcome this challenge, proxy models are proposed, aiming to replace reservoir simulators with adequate precision. This work proposes the implementation of data-based proxies for reservoir simulators using Artificial Neural Networks (ANNs). This approach utilizes time series of well controls as inputs, generating responses for Bottom Hole Pressures (BHPs) and/or flow rates.In recent years, proxy models based on neural networks have been applied to obtain predictions of flows and/or pressures in reservoirs. For example, Recurrent Neural Networks (RNNs), specialized in handling sequential data, were used by [1] to predict water flows in the Xiluodu hydroelectric reservoir in China. Convolutional Neural Networks (CNNs), specialized in pattern recognition in images and videos, were also employed by [2] to predict pressures and flow rates of injector and producer wells, respectively.In the scope of this study, distinct neural network architectures were evaluated to predict outputs of a synthetic two-phase model with partial faults. Given the adoption of mixed controls, where producer wells are controlled by BHP and injector wells by flow rate, the use of Multihead Neural Networks [3] was also investigated. This approach allows differentiated processing of input data, contributing to more robust and efficient learning.For each considered architecture, the impact of the number of timesteps in the samples and their size on the accuracy of predictions was analyzed. The results indicate that parallel hybrid architectures exhibit the best performance, forming a complementary mutual network where each architecture contributes with different learning approaches. Additionally, a higher number of samples contributes to reducing result dispersion, while an increase in the number of timesteps does not show a significant contribution to reducing mean error.We gratefully acknowledge the support provided by PETROBRAS, ANP, FINEP, PRH, EMBRAPII, FACEPE, CNPq, and CAPES, which has been instrumental in the successful execution of this work.
On the generation of submarine landslide models for Material Point Method simulations through bathymetric data
Authors: Christian Frantz Ruff  , Tiago Peixoto da Silva Lôbo  , Lorran Ferreira Oliveira  , Luciana Correira Laurindo Martins Vieira  , Adeildo Soares Ramos Júnior  , Ricardo Garske Borges
Published: January 2025

Submarine landslides are natural phenomena that can cause economic problems and environmental disasters, as the force of the sliding mass can break pipes, interrupting production and destroying whole ecosystems. By simulating these landslides using bathymetric data, one can optimize the design and construction of subsea equipment to minimize its risks. This work aims to create a wizard that, using bathymetric data, guides the engineer through the process of creation of the simulation input for the submarine landslide study. The simulator used was developed in-house and uses the material point method to solve continuum mechanics momentum conservation equations for a vast library of constitutive models. The wizard objective is to streamline numerical parameters by automating and optimizing model choices inherent to the computational method, allowing the engineer to focus on the physical problem rather than the numerical details. Furthermore, it will be possible to configure a vast range of physical parameters, such as the definition of the sliding mass, the constitutive model and its parameters.
Assessment of the uncertainties' impact of relative permeability curves on mature field oil production: a case study in unisim-i-h
Authors: Lucas de Lima Felix  , Thatianne de Araujo Lins da Silva  , Caroline Henrique Dias  , Felipe Moreira Eler  , Paulo Couto
Published: January 2025

Relative permeability is a crucial parameter in reservoir characterization as it directly influences the behavior of the rock-fluid system and, consequently, oil production. However, estimating this parameter is difficult due to uncertainties that can originate from various sources, such as geological, parametrical modelling, computational, and so on. If not properly examined, these uncertainties might undermine prediction accuracy and impair final production. Over time, several correlations were created to estimate relative permeability better. Although no parametrical correlation can adequately predict the exact shape of the curve, most of them reasonably approximate it within specific uncertainty limits. For mature oil fields, a novel kind of industry for Brazil, the research of relative permeability and associated uncertainties is still in its early stages. The main objective of this study is to numerically investigate the effects of uncertainties on relative permeability curves via software CMG® and the geological model UNISIM-I-H developed by UNICAMP. The LET correlation was used to estimate the relative permeability curves. Initially, a base case known as UNISIM-I-H was simulated, upon which the remaining analyses were built. This case consisted of a 15-year production phase followed by a 5-year production pause, a 10-year production restart, the abandonment of the three less productive wells and the drilling of the three new wells to represent a mature oil field better. Four cases were created with relative permeability parameter uncertainties increased by 5%, 10%, 15%, and 20%. The effects of these uncertainties on the relative permeability curve, production curve, net product value, and recovery factor were then examined. The data analysis revealed that these uncertainties mostly affect the forecasts relating to net product value, reservoir recovery factor, and cumulative production, with the latter being the most impacted. Every uncertainty case increased the maximum and minimum values of the curves. Compared to the base case, an intriguing pattern also showed up, where the maximum increased much more quickly than the minimum, suggesting that the risk of estimating the values for each curve above the actual is significantly higher with increasing uncertainty than the opposite.
Permeability estimation from rock digital images segmented through deep learning
Authors: Vivian de Carvalho Rodrigues  , Maira da Costa Oliveira Lima Santo  , José Guilherme Santos da Silva  , Paulo Couto  , Elisabeth May Braga Dulley Pontedeiro  , Leonardo Coelho
Published: January 2025

An accurate estimation of permeability is very important for the development and management of petroleum reservoirs. Knowledge of petrophysical properties is essential to achieve profitability in production in the oil and gas (O&G) industry. Modeling of flow properties at pore scales has gained great prominence in oil industry projects with the advances achieved with digital transformation. From digital images of reservoir rocks, it is possible to extract information from the porous system, in order to obtain petrophysical properties such as porosity, permeability, and, make suitable the comprehension of the connectivity of this system. The feasibility of acquiring three-dimensional images of these rocks, the industry began to use machine learning tools to assist the rock characterizations, thus, the entire modeling process is more efficient. And with high-performance computers, both the optimization and expansion of porous network have led to increasingly real flow calculations, which contributes to the knowledge of these properties. The objective of this research is to estimate the absolute permeability of rocks using micro tomography (microCT) images segmented using deep learning. It was used 12 samples of coquinas from the Morro do Chaves formation (Sergipe-Alagoas Basin), these samples are similar to those from the Itapema formation (Santos Basin). The images, with 42-micron resolution and in gray scale. Data were separated into training, validation and testing. Each batch of training images has 32 sub-images with 64x64 pixels (patch) and the stride ratio equal to 1. It was used 100 learning epochs with an early stopping criterion. The model used for segmentation will be U-net convolutional neural network with cross entropy as cost function and Adadelta ([1]) optimization algorithm. Additionally, sensitivities were made regarding the use or not of the data augmentation technique and also regarding the use of input images with and without denoising filters. Deep learning models were generated in the Dragonfly program ([2]), and the modeling of the pore network, using the PNM algorithm (Pore Network Modeling).[1] Zeiler, Matthew D.. Adadelta: an adaptive learning rate method [Online] Available: https://doi.org/10.48550/arXiv.1212.5701[2] Dragonfly: commercial software [online] Available: https://dragonfly.comet.tech/
Conjugated Heat Transfer of the stator of an synchrounous electrical machine
Authors: Augusto Salomão Bornschlegell  , Thiago Antonini Alves  , Gerson Bessa Gibelli
Published: January 2025

Electrical energy generation in remote islands and ships are mainly due the energy conversion from chemical (fuel) to mechanical by an engine and converted from mechanical to electrical by an alternator. The losses in the alternator during the energy conversion are responsible for the increase of its temperature. In order to control the temperature level of the equipment, it is necessary to control how heat is evacuated. The present work numerically evaluates the heat dissipation in the stator of an electrical machine and its temperature maximum levels. Heat is generated in the cooper (windings) and steel (stator main body) during the energy conversion and is evacuated due the forced airflow throughout the stator. In order to reduce computational costs, due geometrical symmetry, one quarter of the machine was modeled. In addition to symmetry, the momentum boundary conditions consist in inlet, outlet and noslip at the walls and the thermal boundary conditions consist in imposed heat fluxes. In order to isolate the inlet and outlet boundary conditions, they were positioned at least 10 times the respective channel height far from the stator. The model is transient and the initial flow field is at rest (0 m/s) and at ambient temperature (300 K). The geometry was constructed using Salome-Meca software and the mesh was generated using the snappyHexMesh solver from OpenFOAM v11. The foamMultiRun solver from OpenFOAM was employed to create the numerical model. It solves the mass, momentum and energy equations in transient regime. The numerical schemes employed were linearUpwind (second order) for the advective terms, Gauss for the diffusive terms (linear) and the backward time discretization (second order). The turbulence model employed was the K-omega SST. The model predicted where were the regions inside the stator with intese heat transfer, which implies in lower temperature magnitudes and also where there were temperature peaks. Then correlation between the temperature and flow fields were discussed.
Problematika Kesaksian Talak dalam Pengadilan Agama Menurut Fiqih Islam dan KHI
Authors: Umar Umar  , Mhd. Amar Adly  , Heri Firmansyah
Published: January 2025

Divorce (Talak) is an act that dissolves the marital bond between husband and wife. Divorce is categorized into two types: Talak Raj’i and Talak Bain. In Islamic law, the dissolution of marriage does not necessarily require the presence of a third-party witness. This discrepancy p This study aims to examine the legal foundation of Islamic jurisprudence and KHI concerning the dissolution of marriage, focusing on the differences between these two legal frameworks. Employing the Library Research method, the researcher gathered data related to this issue. The findings reveal significant differences between Islamic jurisprudence and the KHI regarding This difference arises because the two legal frameworks are based on distinct legal foundations, resulting in varied applications. From the discussion, it is clear that divorce declarations should not need to be repeated in front of a judge in religious courts. Based on the consensus (ijma’) of Islamic scholars, the involvement of third parties is unnecessary to validate a divorce. Institsbat) the divorce, meaning the husban This approach aligns with other cases, such as unregistered marriages (nikah siri), where the marriage.
Realizing Quality Health Services through Ergonomic Re-Design of the Medical Records Room at the Kedungkandang Community Health Center
Authors:   Department of Business Administration, Sekolah Tinggi Ilmu Administrasi Malang, East Java, Indonesia, Adiba Farah , Hanafiah Ali ,   Department of Administration, Sekolah Tinggi Ilmu Administrasi Malang, East Java, Indonesia, Oktoriani Ervita Nindy ,   Department of Medical Record, Sekolah Tinggi Ilmu Administrasi Malang, East Java, Indonesia
Published: January 2025

This community service activity aims to redesign the medical records room at the Kedungkandang Community Health Center by applying ergonomic principles. The main goal of this redesign is to improve the quality of health services by creating a more comfortable and efficient work environment for medical records staff, as well as improving service flow to reduce patient waiting times. The methods used include in-depth interviews with staff, direct observation in the medical records room, and needs analysis based on ergonomic principles. Based on the data collected, various problems were found, such as non-optimal layout and inefficient equipment placement. The result of this activity was a new, more ergonomic design, which included reorganizing the registration counter, improving lighting, and improving ventilation. Although this design has not yet been implemented, the results of the service are expected to increase staff work efficiency and patient satisfaction after implementation. It is also hoped that this design can become a model for other health centers to improve the quality of health services.
Healthcare Services and its Impact on Women's Health: A Study of Chitral District
Authors: Saif Aimen , Butt Huma
Published: January 2025

The present study was about healthcare services and their impacts on women's health. This study explored the problem faced by women in accessing healthcare services, and the reasons for their poor health. The research was carried out in the Istangol Valley of District Chitral by married women. The primary objective of this research was to unveil the major health problems of women and how healthcare facilities affect women's health in their daily lives. This study was conducted under a quantitative research design by using social survey method. Data was collected through a detailed questionnaire. A sample size of 103 respondents was selected from the targeted population through simple random sampling. The researcher then analyzed the data by employing a statistical package for social science (SPSS). Through the results, the researcher found that the unavailability of female specialties was a major reason that became a hurdle for women to access healthcare services. The situation of the poor basic health of women showed the failure of health ministries/departments to provide basic healthcare in rural areas. It is recommended that the government take action to upgrade facilities, supply infrastructure, and hire physicians to address women's health concerns in rural regions in order to enhance the health of women there. It is also suggested that non-governmental organizations should spread awareness about healthy diets and the importance of better health.
Factores asociados a la interrupción del embarazo y el consentimiento de las mujeres en Ecuador
Authors: Guanoquiza Toapanta Kevin Ariel , Rodriguez Lucas Roderick Denzel
Published: January 2025

La interrupción del embarazo en Ecuador es un fenómeno influido por factores legales, socioculturales y éticos que perpetúan desigualdades de género y afectan gravemente la salud de las mujeres. Este estudio tiene como objetivo analizar las implicaciones de la criminalización del aborto en el país, sus impactos sociales y sanitarios, y las barreras para avanzar hacia un marco legal inclusivo. Se utilizó un diseño documental exploratorio basado en la revisión de literatura científica y normativa, abarcando casos de Ecuador y comparaciones con marcos legales de otros países latinoamericanos como Uruguay y Argentina. Los resultados evidencian que la penalización del aborto refuerza estigmas, limita la autonomía de las mujeres y fomenta prácticas clandestinas con altos riesgos sanitarios. Además, se identifica un vacío en las políticas públicas que no integran la educación sexual integral ni garantizan el acceso a servicios de salud reproductiva. La discusión destaca cómo el debate ético polarizado entre sectores conservadores y feministas dificulta las reformas legales necesarias. En conclusión, superar estas limitaciones requiere un enfoque integral que priorice los derechos reproductivos, incorpore la perspectiva de género y garantice la equidad en salud, contribuyendo así a una justicia social más inclusiva.
THE IMPACT OF GOVERNMENT POLICIES AND FOREIGN DIRECT INVESTMENT ON THE GROWTH DYNAMICS OF THE INDIAN CONSUMER DURABLES MARKET: A COMPREHENSIVE ANALYSIS
Authors: Mahida Rinkeshkumar
Published: January 2025

The present research aims to examine the effects of technical improvements, FDI, and government regulations on the growth dynamics of the consumer durables industry in India. Through an examination of current patterns, market division, output capacities, and the function of foreign direct investment, the study seeks to provide a thorough grasp of the industry's share of India's GDP and the forces influencing consumer demand. The results show that higher FDI inflows and supportive government policies greatly accelerate market expansion, while technical developments also further improve consumer preferences. Raising disposable incomes and evolving lifestyles appear as crucial factors influencing consumer demand, and the industry's division into brown and white items impacts the allocation of market share among major competitors. The research uses regression analysis to find important correlations between these factors, emphasizing how innovation, e-commerce, and government regulations work together to create a strong market environment. The enhancement of market dynamics via trade policies and the Production-Linked Incentive (PLI) Scheme highlights the need to implement strategic policies. To maintain development in the consumer durables industry, the report closes with recommendations for bolstering regulatory frameworks, encouraging foreign direct investment (FDI), and funding technical innovation. Policymakers, business stakeholders, and investors who want to take advantage of new possibilities and solve problems in an ever-changing market need to know these insights. Because of the study's thorough methodology, it is possible to find strategic avenues for future growth and get a helpful foundation for comprehending the many impacts on the Indian consumer durables industry.
Peacekeeping and Nation-Branding: The Case of Bangladesh's Contributions to The UN Peacekeeping
Authors: Biplob Khalid Bin Ismot
Published: January 2025

Ever since the dawn of its statehood, Bangladesh is committed to maintaining global peace and security through multilateralism. Bangladesh's commitment to multilateralism is aptly radiated through its peacekeeping endeavour. Peacekeeping has endowed Bangladesh with a special niche in the society of nations. Despite of being a small actor, Bangladesh could attain leading position among scores of powerful contenders in the competitive peacekeeping undertakings by virtue of its peacekeepers' impartiality, dedication and extraordinary professionalism. Bangladesh is a trend-setter, a 'staying power' and above all a reliable partner in global peacekeeping. Furthermore, Bangladesh has proved itself to be a responsible 'global citizen' unequivocally through peacekeeping. The contribution of Bangladesh in peacekeeping is fairly visible', well-regarded and undisputed. These have built up the image and identity of the country as a role model in the competitive realm of peacekeeping. The credibility and reputation as the largest peacekeeper have bestowed Bangladesh an attractive power which can better be translated as 'nation-branding'. Indeed, peacekeeping is a unique attribute of the country, a charm offensive. Thus, to give Bangladesh a brand name-The Peacekeeper.