Publicações - engenharias
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SCAPINELLO AQUINO, LUIZA;
RODRIGUES AGOTTANI, LUIS FERNANDO;
SEMAN, LAIO ORIEL;
Viviana Cocco Mariani;
LEANDRO DOS SANTOS COELHO;
GONZALEZ, GABRIEL VILLARRUBIA
Palavra-chave:
distribuição de energia elétrica;
aprendizado profundo;
Redes Neurais Artificiais;
detecção de falhas
Áreas do conhecimento:
Engenharias; Engenharia Elétrica; Inteligência Artificial;
Engenharias; Engenharia Elétrica; sistemas de potência
resumo ...
Ensuring the reliability of power transmission systems depends on the accurate detection of defects in insulators, which are subject to environmental degradation and mechanical stress. Traditional inspection methods are time-consuming and often ineffective, particularly in complex aerial environments. This paper presents a fault detection framework that integrates the YOLOv8 object detection model with an Adaptive Context Refinement (ACR) mechanism. YOLOv8 provides real-time detection, while ACR incorporates multi-scale contextual information surrounding detected objects to improve classification and localization. The system is evaluated across 25 YOLO model variants (YOLOv8 to YOLOv12) using high-resolution UAV datasets from operational power distribution networks. Results show that ACR improves mean Average Precision (mAP) in all cases, with gains of up to 22.9% for YOLOv10n (from 0.556 to 0.684 mAP) and average improvements of 12.6% for YOLOv10, 8.6% for YOLOv12, 5.6% for YOLOv9, and 4.0% for YOLOv8. The method maintains computational efficiency and performs consistently under varied environmental and fault conditions, making it suitable for the real-time UAV-based inspection of power systems.
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CABRAL, LUCAS LACERDA;
DE CARVALHO, KARINA QUERNE;
BOTTINI, RÚBIA CAMILA RONQUI;
GONÇALVES, ALEXANDRE JOSÉ;
JUNIOR, MILTON MANZONI;
RIZZO-DOMINGUES, ROBERTA CAROLINA PELISSARI;
Marcelo Kaminski Lenzi;
NAGALLI, ANDRÉ;
PASSIG, FERNANDO HERMES;
DOS SANTOS, POLIANA MACEDO
Palavra-chave:
Sorption;
mathematical modeling;
Design of experiments
Áreas do conhecimento:
Engenharias; Engenharia Química; Bioprocessos
resumo ...
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Alexandre Marques de Almeida;
Marcelo Kaminski Lenzi;
Ervin Kaminski Lenzi;
Thiago Dalgalo de Quadros
Revista Tecnológica,
v. 1,
p. 34-50,
2025
Palavra-chave:
Controle Fracionário;
Módulo Experimental
Áreas do conhecimento:
Engenharias; Engenharia Química; Bioprocessos
resumo ...
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GUERRA, HENRIQUE P.;
giuliana sardi venter;
ORDONEZ, J.C.;
Jóse Viriato Coelho Vargas;
RAIMUNDO, RODRIGO C.;
TAHER, DHYOGO M.;
MARTINS, LAUBER S.;
OCH, STEPHAN H.;
PITZ, DIOGO B.;
MARIANO, ANDRÉ B.;
CARDOZO-FILHO, LUCIO
Palavra-chave:
Green hydrogen;
fuel cell;
renewable energy;
Aluminum-to-Hydrogen;
Catalysis
Áreas do conhecimento:
Ciências Exatas e da Terra; Química; Físico-Química; Eletroquímica;
Engenharias; Engenharia Mecânica; Engenharia Térmica; Aproveitamento da Energia
resumo ...
This study introduces a mathematical model of a sustainable electricity generation system whose energy source is from aluminum and water. The system is composed by a batch reactor for greenhouse gas-free hydrogen (H2) generation, a gas dehumidifier, a 5 kW Proton Exchange Membrane Fuel Cell (PEMFC) stack and ancillary equipment. A transient mathematical model for hydrogen and electricity generation was conceived based on mass, energy and species conservation principles, and was experimentally validated. The mobile system prototype was mounted on an automotive trailer with the intention to be applied as a range extender (REX) device to electric vehicles (EV) or even provide total independence of battery charging stations, assuming that aluminum, water and catalyst (NaOH) are available. The numerical results were shown to be in good qualitative and quantitative agreement with experimental data and give insight on the main operating parameters that must be considered to control the system. Notably, the approach contributes to mitigate adverse environmental effects associated with fossil fuel use, leveraging residual aluminum—an abundant global waste. In essence, the herein sustainable, in situ production of green hydrogen and electricity places the hydrogen generation & fuel cell system technology in the category of a clean and renewable energy source. Therefore, the system is expected to be applicable to electric vehicles, all electric ships and stationary distributed power generation.
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G. OLIVEIRA, ANGÉLICA;
JOSÉ GOMES, GLAUCIO;
SPESSATO, LUCAS;
S. BITTENCOURT, PAULO RODRIGO;
Janine Padilha Botton;
C. S. GONÇALVES, CAROLINE
Palavra-chave:
biocomposites;
Environmental Management;
pyrolysis;
Hazardous waste;
Toxic gas;
CO2 adsorption
resumo ...
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ALMEIDA, ALEXANDRE MARQUES DE;
DAGA, ALISSON LUAN;
LANZARINI, RAFAEL PALMA SETTI PENTEADO;
E. K. Lenzi;
Marcelo Kaminski Lenzi
Palavra-chave:
Identificacao de Processos;
Sistemas Multivariáveis;
Cálculo Fracionário
Áreas do conhecimento:
Engenharias; Engenharia Química; Bioprocessos
resumo ...
This paper focuses on the application of fractional calculus techniques in the identification and control of multivariable (multiple input—multiple output) systems (MIMO). By considering a previously reported experimental set-up similar to a greenhouse, this study proposes the open-loop identification of fractional order transfer functions relating to the controlled and manipulated variables, which were validated by experimental data. Afterward, the theoretical analysis of Fractional-order Proportional and Integral (FOPI) closed-loop control for this MIMO system was carried out. An important aspect concerns the use of Particle Swarm Optimization (PSO) metaheuristic algorithm for optimization tasks, both in parameter estimation and controller tuning. Moreover, comparisons with integer order models and controllers (IOPID-IMC) were performed. The results demonstrate the superior performance and robustness of the FOPI-PSO fractional control, which achieves up to 79.6% reduction in ITAE and 72.1% reduction in ITSE criteria. Without the need for explicit decouplers, the decentralized FOPI-PSO control structure demonstrated effective handling of interactions between the temperature and humidity control loops, simplifying the control design while maintaining performance. The fractional-order controllers exhibited robustness to measurement noise, as evidenced by stable and precise control responses in the presence of experimental uncertainties. Additionally, the optimized tuning of FOPI controllers implicitly compensated for disturbances and setpoint changes without requiring additional feedforward mechanisms. This study contributes to a better understanding of fractional calculus applications in designing FO–MIMO systems and provides a practical framework for addressing the identified gaps in the field.
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AMARAL, MARCELLA;
AGUIAR OLIVEIRA, ISAAC;
DE BEM, DIOGO HENRIQUE;
COSTA RÉUS, GIOVANA;
MACIOSKI, GUSTAVO;
MIRANDA FARIAS, MARCELO;
Marcelo Henrique Farias de Medeiros
Palavra-chave:
sílica ativa;
Corrosão de armaduras;
Concreto - durabilidade
Áreas do conhecimento:
Engenharias; Engenharia Civil; Inovação
resumo ...
Corrosion is one of the causes of failure in reinforced concrete structures, and forming a passive film on the steel is essential for protection. Although several studies have looked at passive film formation in concrete pore solutions, few have considered its formation in hardened concrete and the influence of silica fume (SF) in the binder composition. This study aims to evaluate the influence of the SF content on passive film formation time in concrete. Periodic measurements assessed the electrical resistivity and corrosion current density of concrete samples containing 5%, 10%, 15%, and 20% SF. The alkalinity of the mixtures and the kinetics of the pozzolanic reaction were also monitored by XRD and titration tests. The control mixtures exhibited susceptibility to corrosion, regardless of the curing age evaluated. In contrast, the partial replacement of cement with SF accelerated the formation of the passive film on the steel surface, suggesting a delayed onset of corrosion due to modifications in the physical properties of the concrete. Also, the portlandite content and pH can predict passive film formation, with SF significantly accelerating this process.
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GOMES, ANDREAS ANAEL PEREIRA;
Leandra Ulbricht;
GANACIM, FRANCISCO;
FERNANDES, LEONARDO GÖBEL;
Pombeiro, Anselmo;
BOBKO, NARA;
ROMANELI, E F R
Palavra-chave:
Substation Automation;
Computer Vision;
object detection;
infrared imaging;
Image Rectification
Áreas do conhecimento:
Ciências Exatas e da Terra; Ciência da Computação; Metodologia e Técnicas da Computação; Engenharia de Software;
Engenharias; Engenharia Elétrica; Telecomunicações
resumo ...
Abstract Energy losses in transmission lines can be aggravated by contact deterioration and...
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MAMADOU, A. F. I.;
IDRISSOU, M. O. K.;
SANYA, S. A. O.;
Jóse Viriato Coelho Vargas;
ALEXANDRA, A. R.
Palavra-chave:
Absorption Refrigeration;
optimal parameters;
Machine learning
Áreas do conhecimento:
Engenharias; Engenharia Mecânica; Engenharia Térmica; Aproveitamento da Energia
resumo ...
Optimal control of Heating, Ventilation, and Air Conditioning Absorption Refrigeration (HVAC-AR) systems based on Finite-Time Thermodynamics (FTT) represents a major challenge in modern engineering application. Indeed, the solution procedure currently used to solve the thermodynamic optimization problem of static thermodynamic systems like HVAC-AR is based on the analytical-geometric technique and the variational principle. Hence, the need to explore numerical optimization methods to generate a set of optimal solutions and ultimately use them to maintain the device at its optimal operating point, through statistical machine learning methods, when operating conditions change. This manuscript therefore presents a novel approach combining FTT and Linear Programming Programing (LPP) to solve Optimal Thermal Conductance Allocation Problems (OTCAP) in R4 (four heat exchangers), as well as a Supervised Machine Learning (SML) for the maximum refrigeration heat load and associated coefficient of performance (COP) prediction of a practical single-effect HVAC-AR system under real operating condition. Five models of regression algorithms (Random Forest Regressor, Gradient Boosting Regressor, Decision Trees Regressor, K-Nearest Neighbors Regressor and Tweedie Regressor) were used. After the model evaluations, the nonlinear Gradient Boosting Regressor (GrBR) model was identified as suitable for predicting COP and maximum refrigeration heat load with an r2_score of 96.34% and 85.04% respectively. The obtained results demonstrate that generator fuel flow rate is a key variable that has a considerable effect on the performance parameters of the HVAC-AR system. FTT-LPP-SML has been proven to be suitable and reliable for solving optimization problems and estimating the performance of single-effect HVAC-AR system after experimental validation.
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Marienne do Rocio de Mello Maron da Costa;
Rafaella Salvador Paulino
Palavra-chave:
alvenaria de vedação;
bloco cerâmico
Áreas do conhecimento:
Engenharias; Engenharia Civil; Construção Civil; Tecnologia da Informação na Construção Civil
resumo ...
Abstract The use of rationalized masonry in building construction is increasing due to process...
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