bluuebunny/crossref_metadata_2025 huggingface dataset:
Reinterpretation of the Cross Method: Gauss-Seidel approximation for the solution of transverse dislocation
Authors: Daniel Gomes de Oliveira  , Rafael Araújo de Sousa
Published: January 2025

The Cross Method was very used for analysis of structures, this was to the agility of the method. But he lose his use by the limitations of metho, such as transversal dislocations. So, a general method was proposed, able of analyzing structures with transversal dislocations and have the classical method as a particular case. The methods found to get these objective was to use displacement method and Gauss-Seidel approximation together and compare with the classical method. The results showed the Gauss-Seidel approximation was able to obtain an approximate solution to for structures with transverse dislocations maintaining part of the agility of the traditional method. With these results, can be concluded that Cross's reinterpretation is able to analysis of structures with transverse dislocation more easily than the classical method.
Ablation study of a non-intrusive data-driven surrogate model for the Rayleigh-Bénard convection problem
Authors: Adriano Cortes  , Roberto Machado Velho  , Gabriel Freguglia Barros  , Fernando Alves Rochinha  , Alvaro Luiz Gayoso de Azeredo Coutinho
Published: January 2025

Non-intrusive data-driven models are promising class of methodologies to build surrogate models for challenging parametric engineering problems. POD-DL [1,2], a method from this class uses deep neural networks as the main data-driven ingredient. Following a first linear dimensionality reduction, based on a POD basis, it applies a second nonlinear dimension reduction, in this case a deep autoencoder, and a nonlinear regression using a forward neural network to account for the temporal and parametric coefficients. This setting generates a large number of hyperparameters, such as the number of modes of the POD basis, the number of layers and amount of neurons per layer for each network (the autoencoder one and the regression one), besides all typical hyperparameters of neural networks, as learning rate, batch size, etc. This all impacts the amount of time for the training process and the surrogate model accuracy.Based on our previous experience with this methodology for coupled transport-fluid problems, we decided to study the Rayleigh-Bénard convection problem [3] with a fixed Prandtl number, a well documented heat transfer problem coupled with fluid flow. Besides the temporal character of the problem, the Rayleigh number serves as a parameter, i.e., each different number generates a different dynamic that is learned by the surrogate model. Then, the regression neural network can predict the dynamics for an unseen Rayleigh number. In order to understand the contribution of each component of the method, we perform an ablation study in this controlled setup. [1] - M. Cracco et al., Deep learning-based reduced-order methods for fast transient dynamics, Arxiv Preprint 2212.07737, 2022.[2] - S. Fresca and A. Manzoni, POD-DL-ROM: Enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition, Comput. Methods Appl. Mech. Engrg., 2022.[3] - R. Kessler, Nonlinear transition in three-dimensional convection, Journal of Fluid Mechanics, 1987.
Reliability of built-up cold-formed steel beams designed by the direct strength method
Authors: Marcelo Borges Pereira  , André Luís Riqueira Brandão  , Marcilio Sousa da Rocha Freitas
Published: January 2025

Built-up cold-formed steel (CFS) beams are composed of two or more sections that are joined together with welds, bolts or screws. Although PFF composite bars are commonly used in bending applications, the structural design of these sections requires further investigation. This study proposed a critical review of research related to the structural behavior and designing methodology of these elements. A review of published articles, encompassing experimental studies and numerical simulations of these elements, was conducted. The safety of built-up beams subjected to bending, designed according to the Direct Strength Method (AISI S100, 2016; NBR 14762, 2010), was evaluated and for the statistical study of the model error variable, beam test results obtained from literature were compared to the resistant capacities obtained by the direct strength method (DSM). The structural safety verification of built-up beams was performed using first-order reliability methods to assess the safety level for different load combinations. A calibration procedure for NBR 14762 (2010) was also presented, obtaining the resistance factor for a target reliability index.
System reliability analysis of cold-formed steel structures for serviceability limit states
Authors: Victor Antônio Moreira de Faria  , Marcílio Sousa da Rocha Freitas  , Danilo Luiz Santana Mapa
Published: January 2025

The adoption of numerical analyses in structural design practice has ensured greater control over the actual behavior of structures. Design-by-analysis approaches deviate from traditional methods by directly considering the load-bearing capacity of the entire system rather than individual element checks. These approaches can even incorporate inherent nonlinearities into the analysis, such as second-order effects, material inelasticity, geometric imperfections, and semi-rigid connections. These advanced analysis models may produce results closer to the actual behavior of the structure in service, enabling the safe utilization of lighter structural systems. In this context, the evaluation of serviceability limit states becomes relevant, particularly for cold-formed steel structures, which are typically assembled using slender elements. This paper presents the application of a reliability-based procedure to assess the compliance of cold-formed steel frames with serviceability limit state criteria for excessive lateral displacement. Considering two groups of cold-formed steel structures based on their functions: single-story building frames and industrial storage rack frames, the lateral drift limits are extracted from the AISI S100, ASCE/SEI 7, ANSI MH 16.1, and Brazilian NBR 14762 and NBR 15524-2 standards, along with the target reliability indices for the corresponding limit state. The subsequent step involves evaluating system reliability, considering typical load cases for these structures (dead and wind loads for single-story frames and dead and product loads for racks) selected from the mentioned specifications, accounting for the uncertainties in loads and in the material and geometric parameters of the steel members. For this purpose, a MATLAB reliability framework is presented, coupling the First Order Reliability Method (FORM) to the MASTAN2 finite-element package, in order to apply the structural analysis results in each evaluation of the limit state functions. Conclusions regarding reliability indices and the potential adequacy of resistance factors are presented.
Investigation of the structural behaviour of non-conventional beams designed using a Topology Optimisation procedure
Authors: Guilherme Marcelo  , Thomaz Eduardo Teixeira Buttignol  , Hugo Luiz Oliveira  , Maiara Gomes Montaute
Published: January 2025

In this research we use topology optimisation to design statically determinate rectangular beams with different heights. For the sake of simplification, the constitutive material is assumed to be homogeneous. The aim is to verify the efficiency level that topology optimisation procedure has in removing material from the structural member still preserving the bending strength capacity. Topology optimisation is based on the Bi-directional Evolutionary Structural Optimisation (BESO) and Solid Isotropic Material with Penalisation (SIMP) methods. To use the SIMP method, a 3D parametric model of the beams was implemented in the Rhinoceros3D (Computer-Aided Design) software with the aid of the Grasshopper (Algorithm-Aided Design) plugin. The optimization was performed using the tOpos plugin. For the BESO method, the BESO 2D code developed in RMIT Univervity was used. The output for both codes are compared, highlighting the coherence of the results based on computational time efficiency and physically plausible generated shapes. After Topology Optimization, the structural behaviour was investigated using Karamba3D plugin. To obtain the maximum load for the beams with different heights and their final volume coming from topology optimisation, an additional optimisation method based on genetic algorithms was adopted to maximise an objective function based on deformation. This analysis was performed for local maximum displacement respecting limiting state serviceability criteria considering increasing distributed load and different volume fractions. In all the cases analysed, the width and span are fixed. The results of the optimisation procedure for beams with different heights are compared based on economic-sustainability criteria (volume of material) and load-bearing capacity (maximum bearing moment).
A numerical study on the critical bending moment for distortional buckling of cold-formed lipped C-sections
Authors: Vinícius Nogueira Magalhães  , Adenilcia Fernanda Groberio Calenzani  , João Victor Fragoso Dias
Published: January 2025

Applications of cold-formed profiles have become more common in the civil construction industry. In particular, the cold-formed lipped C-sections are frequently used. Mostly, these channels are submitted to bend about the major principal axis and, consequently, they get subjected to compression stresses that, due to their considerable local slenderness, can provoke instability. Particularly complex, the distortional buckling is one of those failure modes and may occur in cold-formed lipped C-sections causing translation of the edges. Thus, this article intends to evaluate theoretical design procedures, from the perspective of accuracy and implementation, when used to calculate the critical bending moment of distortional buckling. Four formulae were selected and, for comparison, two computational approaches were employed to determine, numerically, the critical moments in different lipped C-sections: the finite element method (FEM) and the finite strip method (FSM). The Hancocks and Schafers formulations proved to be highly precise when confronted with the numerical data. An adapted procedure presented by AISI, based primarily on local buckling designs, showed itself imprecise, returning both unsafe and conservative results depending on the cross-section. The last one was the simplified method, also available on AISI standard, and as expected, it was conservative when predicting the distortional buckling moment. Conclusions regarding the critical moment and buckling modes with changes in geometrical parameters were also extracted. Thickness increase led the critical moment to grow, as expected, due to the reduction of local slenderness provided. Likewise, as the lip width gets larger, the critical moment rises, however the profile tends to fail by local buckling mode, evidencing the need for attention when using channels with too narrow or too wide lips.
Assessment of the Tall Buildings Dynamic Response Considering the Geometric Nonlinearity and the Aerodynamic Damping
Authors: Jean Carlos Mota Silva  , George Lucas da Silva Quintanilha  , José Guilherme Santos da Silva
Published: January 2025

This research work aims to evaluate the dynamic structural behaviour of tall buildings when subjected to wind loads considering the effect of the geometric nonlinearity and also the aerodynamic damping, due to the relative movement between the structure and the wind action. This way, the project associated to a steel-concrete composite building with 48 floors and 172.8 m height is investigated, when subjected to wind nondeterministic dynamic actions. The composite building finite element model was developed based on the use of the Finite Element Method (FEM), utilising the ANSYS computational program, and considering the soil-structure interaction effect, aiming to obtain a realistic representation of the dynamic behaviour. The building dynamic response was obtained based on the displacements and accelerations values, determined having in mind a wind velocity range between 5 m/s [18 km/h] and 45 m/s [162 km/h]. The conclusions of this investigation pointed out to the fact that when the geometric nonlinearity effect was considered in the analysis the investigated building dynamic response presented relevant differences, with maximum differences up to 30% to horizontal translational displacements and up to 45% to accelerations. On the other hand, when the aerodynamic damping was considered the contribution was not significant to the structure dynamic response, with maximum differences up to 5% for the displacements and up to 10% for the accelerations.
Contributions to the analysis of prestressed steel and concrete composite beams using machine learning algorithms
Authors: João Batista Marques de Sousa Junior  , Beatriz M. Meneses
Published: January 2025

In the practice of civil construction, one of the structural alternatives used so that beams can withstand the required loads in a more efficient and economical way are the prestressed composite beams, especially steel and reinforced concrete. Posttensioned composite steel-concrete beams (PSCCB) have a greater range of elastic behavior, as well as yield and ultimate load values. In continuous beams, there is a reduction of cracking in the hogging moment region. They may also have better fatigue performance and employ lighter steel sections. The present paper aims to create a large database for the analysis of PSCCB, based on a previously developed nonlinear finite element model, which performs static non-linear analysis of PSCCBs, considering the partial interaction between steel and concrete. With a database developed from a variation of the parameters in the numerical models, three Machine Learning models are developed and trained with the objective of predicting the beam ultimate load, deflection, and final tendon force. The implemented procedures is compared, whenever possible, with experimental and numerical results available in classic literature, mainly as a reference of test data to evaluate the success of Machine Learning algorithms.
On the numerical simulation of two-phase flow in shale gas reservoirs
Authors: Gillyan Macario da Silva  , Mayksoel Medeiros de Freitas  , Grazione de Souza  , Helio Pedro Amaral Souto
Published: January 2025

In the past two decades, the scientific and technological community dedicated to oil and gas production has demonstrated a growing interest in unconventional reservoirs containing natural gas, such as shale reservoirs. These deposits typically contain significant volumes of gas, but their low intrinsic permeability is a drawback. For example, technological advances using horizontal well drilling have led to economically viable production from such reservoirs, and in this context, numerical simulations are relevant in planning natural gas recovery. In this paper, we carry out numerical simulations of isothermal two-phase gas-water flow in shale gas reservoirs. We considered the effects of slippage and adsorption employing the Klinkenberg model and the Langmuir isotherm for the gas phase. It also incorporates a pressure-dependent correction in determining effective permeability for both phases and horizontal wells for production. The Control Volume-Finite Difference method is applied to discretize the governing flow equations, employing centered block grids and fully implicit numerical formulations. We linearize the discretized equation for gas phase pressure using the Picard method, while we use the Newton method for the discretized equation for water phase saturation. The results are analyzed in terms of the pressure at the production well, leading to an evaluation of how the effects considered for the effective permeabilities of the phases influence pressure variation and the times of occurrence of the flow regimes for the considered well-reservoir system.
Asymptotic homogenization of a mechanical equilibrium problem of a functionally-graded Euler-Bernoulli beam with non-periodic microstructure
Authors: Leslie Darien Pérez Fernández  , Douglas Machado da Silva  , Julián Bravo-Castillero
Published: January 2025

To the best of our knowledge, the few classical applications of Keller's two-space method of non-periodic asymptotic homogenization are related to the effective behavior of heterogeneous media in the context of poroelasticity considering fluid flow and saturation. We believe that this is due to the alternative common approach of approximating random or non-periodic microstructures via the periodic replication of a representative volume element, as periodic structures are, generally speaking, much more tractable mathematically and computationally. However, more than 40 years later, a number of preliminary results of applications of the two-space method has arisen on various areas, namely, effective behavior of composite or functionally-graded bars, approximate solution of the electroencephalogram forward problem for neural imaging activity, and modeling of atmospheric pollutant dispersion. These recent applications deal with second-order elliptic or parabolic equations. In this contribution, we present the application of the two-space method to a mechanical equilibrium problem of a functionally-graded Euler-Bernoulli beam with non-periodic microstructure, which relies on a fourth-order elliptic equation. To the best of our knowledge, homogenization of fourth-order equations has been considered only in the periodic case.
Development of a Python Software for the Cardiovascular System Segmentation such as Arteries and Left Ventricle
Authors: Luísa Maria Pimenta Abreu Costa Sousa  , João Filipe Vieira Festas  , Samuel  Sousa Silva  , Sónia Isabel SIlva Pinto
Published: January 2025

J. Festas, L.C. Sousa, S.S. Siusa, S.I.S. PintoCardiovascular diseases (CVDs) are the leading cause of death globally, accounting for approximately 17.9 million deaths annually, with coronary artery disease (CAD) as a major contributor. CAD results from the build-up of atherosclerotic plaques, reducing myocardial perfusion and leading to conditions like angina and myocardial infarctions, severely affecting the left ventricles function. Advanced diagnostic tools are being developed to enhance the segmentation of cardiovascular structures, improving diagnostic accuracy and treatment outcomes.Accurate segmentation is crucial for analyzing coronary behavior via Computed Tomography Angiography (CTA), a non-invasive alternative to coronary angiography, and for planning surgical interventions. Furthermore, the models retrieved after segmentation can be enlarged simulating hyperemia for further hemodynamic simulations. Similarly, segmenting the left ventricle in dynamic CT scans is vital for assessing cardiac health through measurements like ventricular volume and ejection fraction.However, manual segmentation is time-consuming and suffers from variability, which can lead to significant diagnostic errors [1]. As such, there is a pressing need for more automated tools that enhance accuracy while reducing manual labor.Most common advancements are in the realms of deep learning. These have propelled automated medical image segmentation, achieving results with high efficiency and reliability [2]; however, these require extensive data sets and high variability. In scenarios where such datasets are limited or exhibit low variance, these models risk developing biases or failing to achieve accurate results in cases that are very different then the norm of the training dataset.To mitigate these risks, we are developing a Python-based semi-automatic algorithm that relies on existing open-source libraries, enhancing them with custom developments tailored to our specific needs, while relying on technician input to enhance classical image processing, ensuring adaptability to varied clinical conditions. We are testing this tool with patient data, with results that are very promising: segmentation similarity results of around 85%. We plan to release it as open-source software, encouraging a community-driven approach for continuous improvement and adaptation to clinical needs.The initial tests allows to believe this tool can be a robust and accurate software that can be used in hospital or for investigation purposes. The semi-automatic nature allows for user input and post processing tailoring of the segmentation.[1] Tavakoli, V. et al. (2013) A survey of shaped-based registration and segmentation techniques for cardiac images. Computer Vision and Image Understanding 117, no. 9: 966-989.[2] Litjens, G. et al. (2017) A survey on deep learning in medical image analysis. Medical Image Analysis 42: 60-88.
Use of hyperelastic models and sliding connections to model the mechanical behavior of musculoskeletal structures
Authors: Gabriel de Bessa Spínola  , Humberto Breves Coda  , Rodrigo Ribeiro Paccola
Published: January 2025

The generation of movement and force produced by the musculoskeletal system in various parts of the body is a topic of high interest in academic research. The increasingly detailed and precise knowledge of the biomechanical behavior of these structures is required to meet the demands of health care and human well-being. The use of structural analysis tools is essential for that purpose. In some situations, in vivo or in vitro tests present a series of inconveniences; therefore, computational simulations prove to be complementary to experimental tests to analyze human movements and generally offer advantages in terms of cost and time. To contribute to the construction of a more precise understanding of the mechanical behavior of biological structures, this work aims to numerically simulate the planar behavior of the upper limb of the human body through the action of skeletal muscles and the movement of adjacent joints. The mechanical simulation is performed through a computational code developed based on the Positional Finite Element Method (PFEM), capable of performing geometric nonlinear analyses directly in its formulation. The proposed modeling treats the muscle tissue as a composite material made of a three-dimensional matrix and embedded simple bar elements, which represent the muscle fibers. Despite the three-dimensional nature of the model, it is important to emphasize that the work aims at a two-dimensional application, simulating the mechanical behavior of musculoskeletal structures on a single plane. The Saint-Venant-Kirchhoff hyperelastic constitutive model is used to define the relationship between stresses and strains in the materials, highlighting its potential and limitations. Additionally, the active muscle behavior is considered through a numerical strategy that represents fiber contraction by allows controlling the initial length of the bar element. The joint studied in the model is the elbow, modeled through the formulation of sliding connections, allowing relative movement between connected surfaces. Since the mechanical simulation is planar, only flexion and extension movements are reproduced. The kinematic conditions imposed on the system to promote sliding are introduced into the problem using Lagrange multipliers. The proposed model has the potential to describe the mechanical response of human body members in a simplified manner.
Efficient evaluation of near-singular integrals of the eXtended Isogeometric Boundary Element Method for three-dimensional fracture mechanics
Authors: Matheus Rocha  , Jon Trevelyan  , Edson Denner Leonel
Published: January 2025

The Boundary Element Method (BEM) has proven to be a suitable method for the numerical assessment of numerous engineering problems in both two-dimensional and three-dimensional forms. In particular, BEM robustly handles discontinuities in the mechanical response present in fracture mechanics applications. Additionally, its boundary-only nature simplifies the re-meshing process during crack growth modelling. Furthermore, coupling BEM with isogeometric analysis (IgA) is straightforward, as both strategies rely on boundary representation, enabling the direct use of Computer-Aided Design (CAD) geometry as the mesh for the method. IgA basis functions can accurately represent complex surfaces such as spheres and toroids. In this context, the Isogeometric Boundary Element Method (IGABEM) emerges as a reliable tool for solving engineering problems, combining the advantages of BEM with the improved geometric accuracy provided by IgA. In addition, a relevant approach in fracture mechanics is using enrichment functions that incorporate known solution fields, addressing response aspects that standard isogeometric basis functions cannot capture. Combining the enrichment strategy with IGABEM leads to the eXtended IGABEM (XIGABEM) method. Specifically, enriching functions that account for the square-root inverse behaviour on crack surfaces promotes several improvements, such as improved convergence rate and removal of a non-physical jump displacement in the crack front. Another advantage is the direct extraction of Stress Intensity Factors (SIF) as system variables, eliminating the need for costly extraction techniques in three-dimensional problems. However, near-singular integrals appear after the Singularity Subtraction Technique (SST) of the enriching terms in 3D XIGABEM. This study proposes using the hyperbolic sine transformation for the near singular surface integrals that arise from the SST to evaluate them efficiently. Numerical applications demonstrate a reduction in the required integration points for these integrals compared to traditional methods. Therefore, this advancement in the XIGABEM framework reduces the computational cost of this strategy while maintaining accuracy.
Multiscale Modelling of the Two-Dimensional Problem Using the Boundary Element Method
Authors: Gabriela Rezende Fernandes  , Guilherme Bassi da Silva Pontes  , Vitor Nascimento Oliveira
Published: January 2025

A full coupled multi-scale modelling using the Boundary Element Method for analysing the 2D problem of stretched plates composed of heterogeneous materials, where dissipative phenomena can be considered, is presented. Both the macro-scale and the micro-scale are modelled by BEM formulations where the consistent tangent operator (CTO) is used to achieve the equilibrium of the iterative procedures (see [1]). The equilibrium equation of the plate (macro-continuum) is written in terms of in-plane strains while the equilibrium problem of the microstructure, which is defined by the RVE (Representative Volume Element), is solved in terms of displacements fluctuations (see [2]-[5]). In this kind of modelling, the mechanical behaviour of the material is governed by the homogenized response of the RVE, obtained after solving its equilibrium problem. As this kind of modelling is expensive computationally, it is important to investigate other numerical methods to have faster formulations, but which are still accurate. To validate the presented model, the numerical results are compared to the ones where the material microstructure (RVE) is modelled by the FEM.REFERENCES[1] G. R. Fernandes and E. A. de Souza Neto, Self-consistent linearization of non-linear BEM formulations with quadratic convergence, Computational Mechanics, vol. 52, pp. 1125-1139, 2013.[2] G. R. Fernandes, L. H. R. Crozariol, A. S. Furtado and M. C. Santos, A 2D boundary element method to model the constitutive behavior of heterogeneous microstructures considering dissipative phenomena Engineering Analysis with Boundary Elements, vol. 99, pp. 1-22, 2019.[3] G. R. Fernandes, J. J. C. Pituba and E. A. de Souza Neto, FEM/BEM formulation for multi-scale analysis of stretched plates, Engineering Analysis with Boundary Elements, vol. 54, pp. 47-59, 2015.[4] D. Peric, E. A. de Souza Neto, R. A. Feijóo, M. Partovi and A. J. C. Molina, On micro to macro transitions for multi scale analysis of non linear heterogeneous materials: unified variational basis and finite element implementation, Numerical Methods in Engineering, vol. 87, pp. 149-170, 2011.[5] Somer D.D., de Souza Neto E.A., Dettmer W.G., Peric D., A sub-stepping scheme for multi-scale analysis of solids, Comput. Methods Appl. Mech. Engrg., v. 198, p. 10061016, 2009.
Damage detection in 2D beams using wavelet and boundary elements
Authors: Rafael Alan de Sá  , Gilberto Gomes  , Ramon Silva
Published: January 2025

Damage detection in structures is crucial to prevent the collapse of structural elements. Research suggests using numerical methods to aid in damage detection in structures, typically based on finite element modeling (FEM) and comparisons of modal responses of structures before and after damage. This article proposes a new approach to identify damage using Wavelet Transform (WT) and Boundary Element Method (BEM), these methods can detect singularities present in displacement parameters caused by damage and, consequently, do not require the condition of the structure before damage. To validate the methodology, a simply supported and bi-supported beam with damage will be modeled using the open-source programs Bemlab2d and Bemcracker2d, along with an algorithm in Matlab language for manipulation of wavelet coefficients and damage localization. The results indicate that WT is a useful tool for identification and monitoring of structural damage.
Fast semi-analytic sequential explicit coupling analysis of 3D planar hydraulic fracturing
Authors: Luis Fernando Paullo Muñoz  , Cristian Eleazar Mejía Sánchez  , Julio Alberto Rueda Cordero  , Deane Roehl
Published: January 2025

Hydraulic fracturing is a relevant issue in Geomechanics, especially when analyzing hydrocarbon production activities and their physical phenomena. Several numerical, analytic, and semi-analytic methods have been developed to predict fluid-driven fracture propagation response. Tradicional continuum-based numerical coupling methods, such as FEM or XFEM, allow the study of complex and realistic scenarios. However, they frequently require enormous computational effort, which is more evident in 3D modeling. On the other hand, most analytic solutions provide fast solutions but are limited to basic conditions, such as the analysis of the fracture domain only. In this context, semi-analytic methods are an alternative that can provide solutions faster than traditional numerical methods. In addition, those methods apply to more realistic scenarios than analytic solutions. This work proposes a sequential explicit two-way coupling methodology to analyze planar hydraulic fracture propagation in pressurized rock formations. The coupling methodology associates the Finite Element Method, used to solve the fluid flow problem, with the semi-analytical Displacement Discontinuity Method to solve the mechanical problem. The proposed approach allows predicting fluid-driven fracture propagation in a planar domain considering arbitrary in-situ stress and fluid flow conditions into the surrounding porous medium. The numerical results are compared to asymptotic analytical and numerical solutions showing good accuracy and expressively lower computational cost than traditional numerical schemes.
Impact of cold fluid injection on caprock integrity
Authors: Julio Rueda Cordero  , Cristian Mejia Sanchez  , Deane Roehl
Published: January 2025

In Brazilian pre-salt fields, the extracted carbon dioxide (CO2) is reinjected with lower temperatures into the reservoirs to maintain reservoir pressure, improve oil recovery and reduce greenhouse gas emissions. The cold CO2 injection can alter the mechanical and hydraulic properties of the subsurface and induce variations in formation stresses. Stress changes can be sufficiently high to generate undesirable fracture propagation, damage the caprock, and activate natural fractures or geological faults. Consequently, they can induce seismicity, leaks, and contamination of shallower aquifers and CO2 release into the atmosphere. This work investigates the thermo-hydro-mechanical effect of cold fluid injection on caprock integrity. To this end, a fully coupled thermo-hydro-mechanical (THM) finite element model governs the rock formation behavior. The proposed model considers poroelasticity, fluid flow, and convection/diffusion heat transfer within the permeable rock formation under single-phase fluid flow conditions. The temperature diffusion, pore-pressure buildup, and stress variation under isothermal or non-isothermal injection scenarios are investigated. The results show reservoir expansion in the isothermal scenario due to fluid injection, which is expected in the pressurization process. In the non-isothermal scenario, the thermally disturbed region throughout the reservoir resulted in compaction rather than expansion, even though it was subjected to injection. The instantaneous drop in temperature induces a hard drop in pore pressure and plastic deformations in the reservoir. The lower interval of the caprock presents critical horizontal tension stresses compromising its integrity. Finally, the study adds valuable insight to better understand the complex cold fluid injection process, considering hydraulic, mechanical, and thermal coupling.
Numerical simulation of the lateral load test on piles through a parametric analysis
Authors: Tatyanne Pacifico dos Santos  , Aline da Silva Ramos Barboza
Published: January 2025

Pile foundations are utilized to transfer load from the superstructure to the soil mass when the surface layer of the ground exhibits low load-bearing capacity. For an axially loaded pile, the load is transmitted to the soil through lateral friction at the soil-pile interface and via tip resistance. However, these elements are subject to significant lateral forces in addition to vertical ones. The resistance of piles to lateral loads depends on boundary conditions, stiffness, and concrete strength of the pile, as well as soil type, soil stiffness, and soil strength. Several models are employed to analyse laterally loaded piles, including soil modelling using nonlinear springs, commonly known as p-y curves. This article aims to investigate the impact of pile geometric properties, soil type, and the chosen model on simulating soil-pile interaction on the structural performance of a pile embedded in soil subjected to a transverse load. The study encompasses the variation of three pile diameters (60 cm, 80 cm, and 100 cm), three pile lengths (5.5 m, 10.5 m, and 15.5 m), and three soil types (soft clay, stiff clay, and moderately compacted sand). The effects of diameter (D), pile length (L), slenderness ratio (L/D), and soil type on the lateral response of the pile are examined. Additionally, an analysis is conducted regarding the influence of linear and nonlinear (p-y curves) Winkler models on simulating soil-pile interaction. The presented results indicate that the foundation behaviour, when considering soil-pile interaction, is contingent upon various factors and should be rigorously assessed by designers. It is noteworthy that, depending on the soil type, soil modelling using horizontal linear springs yields acceptable results, obviating the need for a nonlinear model. However, when soil particles exhibit friction or low cohesion, a careful analysis of soil parameters and the chosen model for simulating soil-pile interaction is warranted, with numerical simulation via FEM in conjunction with lateral load testing recommended to determine the optimal method.
Comparing Transformers and Linear models for precipitation forecast in Rio de Janeiro
Authors: Mauro Sérgio dos Santos Moura  , Fabio Andre Machado Porto
Published: January 2025

Precipitation represents a critical meteorological phenomenon that exerts a substantial influence on different geographic regions, as well as playing a fundamental role in various human activities. Notably, Rio de Janeiro experiences unstable weather conditions that lead to sudden and intense rainfall. Consequently, forecasting such precipitation patterns, particularly extreme events, is of fundamental importance in mitigating adverse impacts. Artificial Neural Networks (ANNs) present a promising path for predicting time series data, with transformer architectures emerging as an efficient option. Recognized for their versatility across diverse tasks, transformers have demonstrated effectiveness in time series forecasting, with the Autoformer model emerging as a standout performer, achieving state-of-the-art performance levels. However, the computational demands inherent in transformer-based models, including significant time and memory requirements, have led to the exploration of simpler alternatives. Linear models, such as DLinear, have been proposed as computationally efficient alternatives, capable of providing predictive performance comparable or superior to transformers. The objective of this study was to evaluate and contrast the predictive effectiveness of the linear model with the transformer-based approach in precipitation forecasting tasks for data from Rio de Janeiro. The dataset was obtained through the INMET meteorological system, covering historical records from 2002 to 2023, from four meteorological stations distributed in Rio de Janeiro, Brazil. When it comes to precipitation forecasting, the presence of data imbalance, particularly with regard to extreme events characterized by precipitation exceeding 25 mm, represents a significant challenge. In the scope of this work, the dataset was used in unbalanced form. To train the models, the dataset was partitioned into training (60%), validation (20%) and test (20%) subsets. Both models were instantiated with equal parameters, including sequence length and prediction length of 96, batch size of 32, 20 epochs, and utilizing EarlyStopping and ReduceLROnPlateau callbacks with a patience parameter of 3. The mean squared error (MSE) served as the primary metric for optimizing the loss function during training and evaluating predictive performance. Finally, the study seeks to evaluate the quality of models for predicting precipitation in the Rio de Janeiro region. By evaluating meteorological data, the study attempts to contribute to the understanding of models performance in precipitation forecasting tasks. Our analysis sought to demonstrate insights into which architecture to choose when it comes to precipitation with an unbalance dataset.
Detecting Hate Speech on Brazilian Social Media: New Dataset and Analysis
Authors: Felipe Ramos de Oliveira  , Victoria Dias Reis  , Nelson Francisco Favilla Ebecken
Published: January 2025

Social media plays a crucial role in human interaction, facilitating communication and self-expression. However, the proliferation of hate speech on these platforms poses significant risks to individuals and communities. Detecting and addressing hate speech is particularly challenging in languages like Portuguese due to its rich vocabulary, complex grammar, and regional variations. To address this challenge, we introduce TuPy-E, the largest annotated Portuguese corpus dedicated to hate speech detection. Through a comprehensive analysis utilizing advanced techniques such as BERT and GPT-2 models, our research contributes to both academic understanding and practical applications in this field.
Monitoring and diagnosis of cardiac anomalies in hospitalized patients using IoT and LSTM neural networks
Authors: João Victor Tavares Santos  , Márcio Guilherme Silvestrini Júnior  , Thabatta Moreira Alves de Araujo  , Eduardo Habib Bechelane Maia  , Lucas Silva de Oliveira
Published: January 2025

Continuous monitoring of patients in hospital settings is essential for preventing cardiac disease, representing a crucial measure to ensure the safety of hospitalized patients. However, current monitoring methods have significant limitations, such as patients only being monitored for short periods, which complicates the identification of changes in health status. This article presents a proof of concept for successfully implementing a continuous vital signs monitoring system using the Internet of Things (IoT), coupled with a Long Short-Term Memory (LSTM) neural network for detecting cardiac anomaly events.The development of the neural network hinged on a meticulously labeled database. This database, composed of 12-lead electrocardiogram (ECG) signals from 45,152 patients, was a labor of expertise. Collected at a sampling rate of 500 Hz, these data were labeled by experts, ensuring their high quality and reliability. This resource is fundamental for training machine learning models with high diagnostic precision, enabling accurate identification of cardiac rhythm patterns that indicate potential adverse conditions or those that deviate from a normal or stable electrocardiogram pattern. To make practical use of this extensive data, a robust system architecture was necessary to handle and analyze the data effectively.Microcontrollers played a crucial role in our system, facilitating the transmission of data to a web server. This was achieved using the Message Queuing Telemetry Transport (MQTT) protocol, a highly efficient and fast method for message transmission. The MQTT server, acting as a central hub, received the information and distributed it to two destinations. First, it sent the data to the real-time monitoring site, ensuring immediate access to patient vital signs. Second, it forwarded the data to the system hosting the neural network model. In this environment, the model processed the information and promptly identified any irregularities detected in the data.The results demonstrate that the model achieved high precision in identifying these conditions, enabling the issuance of alerts and the implementation of preventive measures with a high efficacy rate. Such actions reduce patients' health risks, allowing real-time detection and remote communication of vital signs to healthcare professionals.
Simulation of working memory using neural field equations
Authors: Pedro Miguel R. Trindade Lima  , Tiago Sequeira
Published: January 2025

Neural field equations are intended to model the synaptic interactions between neurons in a continuous neural network, called a neural field .This kind of integro-differential equations proved to be a useful tool for the spatiotemporal modeling of the neuronal activity from a macroscopic point of view, allowing the study of a wide variety of neurobiological phenomena, such as the processing of sensory stimuli. In particular, they are a perfect tool for the simulation of working memory, which makes them very useful in Robotics.The aim of the present talk is to study the effects of additive noise in one- and two-dimensional neural fields, while taking into account finite signal transmission speed.A Galerkin-type method to approximate such models is presented, which applies the Fast Fourier Transformation to optimise the computational effort required to solve this type of equations. Numerical simulations obtained by this algorithm are presented and discussed.
Comprehensive reliability-based well integrity analysis: application to worst case discharge (WCD) scenario
Authors: Thiago Barbosa da Silva  , Eduardo Toledo de Lima Junior  , Charlton Okama de Souza  , Emilio Cesar Cavalcante Melo da Silva
Published: January 2025

The global increase in energy demand, combined with the availability of hydrocarbons, positions oil and gas among the main non-renewable sources in the world's energy matrix. In the scope of well design, ensuring their structural integrity under increasingly severe conditions, especially in deep and ultra-deep water, has become a critical factor for the oil and gas industry. Consequently, there has been an investment in modeling extreme environmental scenarios found in challenging wells to ensure their integrity throughout their lifecycle. This work proposes a new methodology for probabilistic analysis of structural integrity during the construction and operation phases of wells, taking into account the uncertainties associated with variables related to the behavior of tubulars, cement sheath, formation, and applied loads . It aims to analyze well integrity through safety barrier failure events in a scenario of severe blowout known as Worst Case Discharge (WCD), using structural reliability theory. The calculation of failure probability will be carried out using the First Order Reliability Method (FORM) and Monte Carlo simulation. It is understood that the proposed methodology can be applied in the design and monitoring stages of wells, contributing to decision-making process.
Predictive Characterization of Fracture and Absorption Tests in Halite Formations: an integrated approach of numerical modeling and field data
Authors: Themisson dos Santos Vasconcelos  , Catarina Nogueira de Araújo Fernandes  , João Paulo Lima Santos  , Luis Philipe Ribeiro Almeida  , Antônio Paulo Amâncio Ferro  , João Fyllipy de Lima Nunes  , Rafael Dias  , Bruno Sergio Pimentel de Souza  , Fabio Sawada Cutrim
Published: January 2025

This study introduces a predictive model based on field data from oil wells in the pre-salt region, focusing on the analysis of fractures in saline rocks and the simulation of leak-off tests through integration with the finite element method. The analysis utilized a variety of techniques, including the construction of a correlation matrix, statistical testing, linear adjustment methods, and numerical modeling. Utilizing specific field data from halite formations, the study identified overburden stress and sediment depth as the most critical variables for minimum stress. Three linear adjustment methodsleast squares, genetic algorithms, and Bayesian methodswere employed. All methods demonstrated a strong correlation among the variables, with Bayesian methods exhibiting the lowest percentage error relative to experimental data. Residual analysis showed that the regression models provided accurate predictions, with most points closely matching the actual values. Numerical modeling further allowed for the assessment of rock behavior under different fluid conditions, indicating that the compositional fluid provides a more realistic simulation and adheres more closely to theoretical expectations and field data. The results affirm the efficacy of the proposed models, particularly highlighting the use of Bayesian methods and mathematical modeling integrated with the finite element method, in predicting the dynamics of fractures and fluid absorption in saline formations. This model significantly enhances the characterization of fractures and absorption pressures in oil wells, improving its utility in predicting behaviors in formations associated with pre-salt fields.