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Methodology for optimizing electrical grounding grids in stratified soils using advanced calculation techniques and evolutionary algorithms

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Swarm and Evolutionary Computation 2025年 95卷

作者： Silva, Carlos Leandro Borges da Pires, Thyago Gumeratto Silva Filho, Antonio Marcelino Bulhões, Junio Santos Belo, Orlando M. Oliveira Rodrigues, Clóves Gonçalves Coimbra, Antonio Paulo Calixto, Wesley Pacheco Electrical Mechanical & Computer Engineering School Federal University of Goias Goiania Goias PC 74.605-220 Brazil Institute of Systems and Robotics Coimbra University CoimbraPC 3030-290 Portugal Department of Informatics School of Engineering University of Minho BragaPC 4710-057 Portugal Electrical Power Systems Study Group Federal Institute of Tocantins Palmas TocantinsPC 77.021-090 Brazil Graduate Program in Production and Systems Engineering Pontifical Catholic University of Goias Goiania Goias PC 74605-010 Brazil Mato Grosso Brazil Technology Research and Development Center Federal Institute of Goias Goiania Goias PC 74.055-110 Brazil

This paper presents a practical methodology for optimizing the geometry of electrical grounding grids at industrial frequencies of 50Hz and 60Hz, integrating advanced calculation techniques and evolutionary algorithms to improve the safety and operational performance of electrical grounding systems. The proposed approach is particularly beneficial for industrial automation and control systems, where effective grounding is necessary to maintain system reliability and prevent downtime. This methodology employs mathematical modeling and computational tools to optimize grid parameters, ensuring compliance with safety standards while reducing operational costs, thus contributing to the overall efficiency of automated systems in industrial environments. The study reports a reduction of up to 66% in the number of vertical rods and 40% in horizontal conductors compared to traditional methods. These results indicate that the proposed methodology can significantly reduce material usage and costs while maintaining electrical safety in accordance with regulatory standards, making it applicable to a wide range of industrial settings, including substations and automated facilities. © 2025 The Authors

关键词： Electric grounding

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Deep Learning Approach for EEG Classification in Lower-Limb Movement Phases: Towards Enhanced Brain-Computer Interface Control

Deep Learning Approach for EEG Classification in Lower-Limb ...

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IEEE/ASME International Conference on Mechtronic and Embedded systems and Applications, MESA

作者： Cristian Felipe Blanco-Diaz Cristian David Guerrero-Mendez Guilherme Rangel Furtado Teodiano Bastos-Filho Rafhael Milanezi de Andrade Dept. of Excellence and AI The BioRobotics Institute Scuola Superiore Sant’Anna Pisa Italy Dept. Electronics and Biomedical Engineering Universidade Estadual de Campinas Campinas SP Brazil Dept. of Electrical Engineering Universidade Federal do Espírito Santo Vitória ES Brazil Posgraduate Program in Electrical Engineering Universidade Federal do Espírito Santo Vitória ES Brazil Graduate Program in Mechanical Engineering Universidade Federal do Espírito Santo Vitória ES Brazil

ISBN: (数字)9798331516239

ISBN: (纸本)9798331516246

Embedded Brain-Computer Interfaces (BCI) have emerged as an alternative for rehabilitation/assistance of people with neuromotor impairments. Data-driven methods are usually implemented to design controllers to (de)activate these systems using electroencephalography (EEG), which may limit usability and degrees of freedom. Thus, the development of more adaptive classifiers remains a challenge. This study focuses on the implementation of a Deep Learning (DL) method to classify EEG signals during different phases of gait and pedaling. To address this, public and in-house databases were used, which contain information on EEG and kinematic data during walking on a treadmill and pedaling on a minibike. Kinematic labels of the phases were extracted using k-means and classified by a Convolutional Neural Network (CNN), which demonstrated accuracy above 60%. Furthermore, a negative correlation was found between velocities and classifier performance metrics, suggesting that faster movements can hinder EEG decoding. Our proposal is a starting point to identify current states of lower-limb movement, which can be used for designing state machine-based controllers of robotic BCIs with rehabilitation or assistance purposes, such as motorized mini exercise bikes or leg exoskeletons.

关键词： Legged locomotion Deep learning Mechatronics Kinematics Electroencephalography Brain-computer interfaces Convolutional neural networks Proposals Usability Robots

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Improve industrial performance based on systematic analyses of manufacturing data

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IFAC-PapersOnLine 2021年第1期54卷 709-716页

作者： M. Lisboa E. Jesus R. Seixas P. Valle F. Deschamps C. Strobel Institute of Applied Technology Solutions (InSTA) Manufacturing Engineering Graduate Program (PPGEM) Department of Mechanical Engineering (DEMEC) Federal University of Paraná (UFPR) Curitiba Brazil

This Article was written based on a systematic review of the literature considering three reference axes, Industry 4.0, Data Analytics and Predictive Maintenance, including specific combination of search terms to ensure a reasonable quantity of articles keeping adherence to the topic that is decision making based on collection and analysis of relevant data on B2B (Business to Business). The study focuses on the area of predictive maintenance, which has been strongly highlighted by the fourth industrial revolution, due to the mechanical and mainly the electronic embedded systems complexity increases in the last decades, as well as network connectivity possibilities for equipment’s data acquisition, enabling technologies for predictive maintenance as a key factor for competitiveness, reducing costs, increasing equipment’s availability, or as a servitization strategy. The article is divided into five parts, starting with the research model and selection of articles, including the proposal for a data analysis framework and the application of systematic analysis of these data, concluding with the opening of a discussion and the indication of future directions.

关键词： Industry 4.0 industrial Internet of things (IIOT) Data Analytics Predictive Maintenance

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Mass Flow Prediction in a Refrigeration Machine Using Artificial Neural Networks

SSRN

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SSRN 2022年

作者： Fonseca, Vinícius David Maia, Antônio Augusto Torres Duarte, Willian Moreira Machado, Luiz Graduate Program in Mechanical Engineering Universidade Federal de Minas Gerais Avenida Antônio Carlos 6627 Pampulha – Minas Gerais Belo Horizonte31270901 Brazil

Measuring mass flow rate in refrigeration systems with flow meters can be expensive when taking into account the cost of the equipment itself and the costs related to installation and maintenance. A model based on Artificial Neural Networks (ANNs) can be used to predict the value of the mass flow, at low cost, through easily observed and measured parameters, like temperatures. Additionally, well-known correlations to calculate parameters that directly influence the mass flow rate can be used as input data for the ANN to improve its accuracy. Within this context, the present study aims to develop a Multilayer Perceptrons (MLP) model to predict the mass flow rate of a refrigeration systems. Later, it is presented an alternative mass flow rate meter, using an ANN model programmed in a microcontrolled circuit with only three temperatures as inputs. To develop the ANN model, experimental data were collected in a refrigeration machine in several operating points. Step disturbances were introduced in the mass flow rate to produce transient data. Two different data set were considered in the training process. The first data set contained only steady-state data and in the second data set there were steady-state plus transient data. The mass flow rate estimated through the ANN presented a maximum error of 0.69% when considering steady-state and transient data in the training process, and 0.75% when considering only steady-state data in the training procedure. The microcontrolled circuit successfully estimated the mass flow rate with an average error of 0.32%. © 2022, The Authors. All rights reserved.

关键词： Neural networks

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Materials’ properties of low temperature deposited Cu/W and Cu/Cr multilayer thin films using high power impulse magnetron sputtering

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Journal of Vacuum Science and Technology A: Vacuum, Surfaces and Films 2024年第3期42卷

作者： Huang, Yu Nguyen, Tra Anh Khoa Dang, Nhat Minh Wang, Hao-Yu Lin, Ming-Tzer Graduate Institute of Precision Engineering National Chung Hsing University Taichung402 Taiwan REMElab Faculty of Mechanical Engineering Ho Chi Minh City University of Technology and Education Ho Chi Minh70000 Viet Nam Taiwan ASML Technology Taiwan Ltd. Hsinchu City300 Taiwan Industrial and Smart Technology Program Academy of Circular Economy National Chung Hsing University Nantou540 Taiwan

In this study, copper/tungsten (Cu/W) and copper/chromium (Cu/Cr) multilayers were created by stacking bilayer films in a 3:1 ratio, with layer thicknesses ranging from 400 to 800 nm, deposited on Si (100) substrates using high power impulse magnetron sputtering (HiPIMS). The microstructural and surface properties of these films were examined through x-ray diffraction, atomic force microscopy, and scanning electron microscopy. Electrical properties were assessed using a four-point probe, while mechanical properties were measured via nanoindentation. Both multilayer systems showed a decrease in the hardness accompanied by an increase in the elastic modulus with each stacking bilayer. The Cu/W system experienced a gradual hardness reduction (down to 19%), compared to the Cu/Cr system, which exhibited a similar decrease (14.5%). The Cu/W and Cu/Cr multilayer film samples consistently demonstrate a softer nature compared to their bilayer counterparts due to the influence of the underlying Cu soft layers. A distinctive surface smoothness in these multilayer systems correlates with the elastic modulus in a manner unlike that with hardness. These multilayer films also demonstrated altered electrical resistivity, enhancing our understanding and capabilities in fabricating films with an increased number of layers. © 2024 Author(s).

关键词： Multilayer films

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Droplet digital quantification of nucleic acids with Cas13a 25

Droplet digital quantification of nucleic acids with Cas13a

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25th International Conference on Miniaturized systems for Chemistry and Life Sciences, MicroTAS 2021

作者： Liu, Frank X. Cui, Johnson Q. Yao, Shuhuai Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Bioengineering Graduate Program Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)9781733419031

The isothermal amplification coupled with CRISPR detection has attracted tremendous interest for the sensitive, specific, and qualitative detection of nucleic acids. We report here a Microfluidics Enabled Digital Isothermal CRISPR-cas13a Assay (MEDICA) which leverages the droplet microfluidics technology to enable recombinase polymerase amplification (RPA) and Cas13a trans-cleavage reporting in individual droplet partitions for absolute quantification. The optimal one-pot MEDICA achieved single nucleic acid molecule detection within 30 min. We applied MEDICA to quantify HPV 16 and 18 viral loads in clinical samples, indicating complete accordance with quantitative polymerase chain reaction (qPCR) results. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized systems for Chemistry and Life Sciences. All rights reserved.

关键词： Drops

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MICROFLUIDIC PLATFORM FOR MULTI-FREQUENCY VISCOELASTIC PHENOTYPING OF SINGLE CELLS 25

MICROFLUIDIC PLATFORM FOR MULTI-FREQUENCY VISCOELASTIC PHENO...

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25th International Conference on Miniaturized systems for Chemistry and Life Sciences, MicroTAS 2021

作者： Lai, Andre Dong, Alan Lustig, Michael Sohn, Lydia L. UC Berkeley-UC San Francisco Graduate Program in Bioengineering University of California BerkeleyCA United States Electrical Engineering and Computer Sciences University of California BerkeleyCA United States Department of Mechanical Engineering University of California BerkeleyCA United States

ISBN: (纸本)9781733419031

Biomechanics plays an integral role in cancer development and progression. Accurately quantifying the mechanical properties of cells would enable a more comprehensive understanding of cancer, complementing conventional biochemical and genetic analyses. Here, we introduce a microfluidic platform for measuring single cell viscoelasticity at multiple frequencies in a high-throughput and label-free manner. Using the Coulter principal and a unique microfluidic channel geometry, our device records resistance pulses in order to estimate a cell's viscoelastic phenotype. We demonstrate our platform's capabilities by measuring three breast epithelial cell lines. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized systems for Chemistry and Life Sciences. All rights reserved.

关键词： Biomechanics

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All-Electric Ship On-Board Continuous Sustainable H2 Generation from Aluminum Scrap and Seawater

All-Electric Ship On-Board Continuous Sustainable H2 Generat...

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IEEE Electric Ship Technologies Symposium, ESTS

作者： Dhyogo M. Taher Wellington Balmant Stephan H. Och Diogo B. Pitz Giuliana S. Venter Lucio C. Filho Lauber S. Martins José V. C. Vargas Juan C. Ordonez Graduate Program in Mechanical Engineering and Sustainable Energy Research and Development Center Federal University of Paraná UFPR Curitiba PR Brazil Department of Chemical Engineering Maringá State University UEM Maringá PR Brazil Department of Health and Biomedical Sciences Advent Health University AHU Orlando FL USA Department of Mechanical Engineering Center for Advanced Power Systems and Energy and Sustainability Center Florida State University FSU Tallahassee FL USA

A mathematical model of a sustainable H2 generation reactor that utilizes aluminum and seawater is introduced. Conservation of species and the kinetics of the H2 production reaction from aluminum and seawater allowed for obtaining the process transient response in a batch reactor. Continuous steady state production was assessed by adding a balance of energy, allowing for reactants inlet mass flow rates, and calculating the outlet H2 mass flow (generation) rate. The theoretical H2 production curve data showed good quantitative and qualitative agreement with experimental data. The validated mathematical model was then used to optimize the continuous reactor. The maximum was sharp, since an 85% variation between the maximum and the smallest H2 generation rate value as a function of the inlet NaOH solution volumetric flow rate tested range was verified. Such fundamental result stresses the importance of operating the system at the optimal condition, no matter how complex the actual reactor design may be. Since aluminum is inexpensive, abundant, and fully recyclable, in situ sustainable H2 production could allow for fuel cell stacks to become all electric ships (AES) power sources.

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Drivetrain simulation using variational autoencoders

arXiv

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arXiv 2025年

作者： Sharma, Pallavi Urrea-Quintero, Jorge-Humberto Bogdan, Bogdan Ciotec, Adrian-Dumitru Vasilie, Laura Wessels, Henning Skull, Matteo Porsche Engineering Etzelstraße 1 Bietigheim-Bissingen74321 Germany Graduate Program Computational Sciences in Engineering Technische Universität Braunschweig Braunschweig Germany Fraunhofer Institute for Energy Economics and Energy System Technology Joseph-Beuys-Straße 8 Kassel34117 Germany Institute of Applied Mechanics Division Data-Driven Modeling of Mechanical Systems Technische Universität Braunschweig Pockelsstraße 3 Braunschweig38106 Germany

This work proposes variational autoencoders (VAEs) to predict a vehicle’s jerk from a given torque demand, addressing the limitations of sparse real-world datasets. Specifically, we implement unconditional and conditional VAEs to generate jerk signals that integrate features from different drivetrain scenarios. The VAEs are trained on experimental data collected from two variants of a fully electric SUV, which differ in maximum torque delivery and drivetrain configuration. New meaningful jerk signals are generated within an engineering context through the interpretation of the VAE’s latent space. A performance comparison with baseline physics-based and hybrid models confirms the effectiveness of the VAEs. We show that VAEs bypass the need for exhaustive manual system parametrization while maintaining physical plausibility by conditioning data generation on specific inputs. © 2025, CC BY.

关键词： Signal encoding

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A lightweight pedestrian detection model for edge computing systems 17th

A lightweight pedestrian detection model for edge computing ...

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17th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2020

作者： Chen, Wen-Hui Kuo, Han-Yang Lin, Yu-Chen Tsai, Cheng-Han Graduate Institute of Automation Technology National Taipei University of Technology Taipei Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Mechanical and Mechatronics Systems Laboratories Industrial Technology Research Institute Hsinchu Taiwan

ISBN: (纸本)9783030530358

Most vision-based pedestrian detection systems adopted deep learning approaches with the framework of convolutional neural networks (CNNs) to reach the state-of-the-art detection accuracy. As CNN-based approaches are computationally intensive, the deployment of those systems to a resource-limited edge device is a challenging task, especially for a real-time application such as intelligent vehicles. In this study, we proposed a lightweight high-performance edge computing solution to achieve rapid and accurate performance in pedestrian detection. Experimental results showed that the proposed framework can effectively reduce the miss rate of the YOLO-tiny detection model from 48.8% to 26.2% while achieving an inference speed of 31 frames per second (FPS) tested on the Caltech pedestrian dataset. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Edge computing

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