Joao Paulo Eguea

DsC in Aeronautical Engineering at the School of Engineering of São Carlos (EESC-USP). Temporary teacher at Aeronautical Engineering Department at EESC-USP. João has expertise on fluid dynamics, aerodynamics, multidisciplinary design, wind tunnel testing and instrumentation.

EDUCATION

Aeronautical Engineer - São Carlos School of Engineering - University of São Paulo
MSc in Mechanical Engineering - Area: Aeronautics - São Carlos School of Engineering - University of São Paulo
DSc in Aeronautical Engineering - Area: Aeronautics - São Carlos School of Engineering - University of São Paulo

RESEARCH, TEACHING, or OTHER INTERESTS

Aerospace Engineering

Scopus Publications

Developing a compact load cell to measure thrust and torque in small propeller testing
Gabriel Pereira Gouveia da Silva, João Paulo Eguea, Lucas Miasiro Ciaramicoli, Hernán Darío Cerón-Muñoz, Fernando Martini Catalano
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2025
Experimental investigation of natural laminar-to-turbulent transition in straight and swept wings at low Reynolds numbers
Caio Roberto Botter, Odenir de Almeida, João Paulo Eguea, Fernando Martini Catalano
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2025
Temperature compensation of a load cell under heterogeneous heating
Lucas Miasiro Ciaramicoli, João Paulo Eguea, Fernando Martini Catalano, Gabriel Pereira Gouveia da Silva
Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2025
Noise source separation in low-Reynolds multi-propeller systems: experimental techniques and post-processing approaches
Gabriel Pereira Gouveia da Silva, João Paulo Eguea, Fernando Martini Catalano
54th International Congress and Exposition on Noise Control Engineering Internoise 2025, 2025
Small propellers and rotors operating at low Reynolds numbers exhibit predominantly broadband noise, so that the tonal noise at the blade passing frequency and its higher harmonics (more significant in large-scale propellers and rotors) is masked by broadband noise in acoustic spectra obtained from reduced-scale wind tunnel tests. Thus, to evaluate the decay of blade passing frequency harmonics in rotating noise sources obtained from reduced-scale tests, it is necessary to apply techniques capable of synchronously measuring the angular position of each blade along with the acoustic pressure. In this context, techniques such as ensemble averaging can be employed to enable the measurement of noise associated with the blade passing frequency and its higher harmonics even when broadband noise predominates. This work describes the experimental setup and post-processing techniques used at the Experimental Aerodynamics Laboratory of the São Carlos School of Engineering, University of São Paulo, to perform noise source separation in small, low-Reynolds-number propellers and rotors in multi-propeller and multi-rotor systems.
Optimization of Structures and Composite Materials: A Brief Review
André Ferreira Costa Vieira, Marcos Rogério Tavares Filho, João Paulo Eguea, Marcelo Leite Ribeiro
Eng, 2024
Neural networks (NNs) have revolutionized various fields, including aeronautics where it is applied in computational fluid dynamics, finite element analysis, load prediction, and structural optimization. Particularly in optimization, neural networks and deep neural networks are extensively employed to enhance the efficiency of genetic algorithms because, with this tool, it is possible to speed up the finite element analysis process, which will also speed up the optimization process. The main objective of this paper is to present how neural networks can help speed up the process of optimizing the geometries and composition of composite structures (dimension, topology, volume fractions, reinforcement architecture, matrix/reinforcement composition, etc.) compared to the traditional optimization methods. This article stands out by showcasing not only studies related to aeronautics but also those in the field of mechanics, emphasizing that the underlying principles are shared and applicable to both domains. The use of NNs as a surrogate model has been demonstrated to be a great tool for the optimization process; some studies have shown that the NNs are accurate in their predictions, with an MSE of 1×10−5 and MAE of 0.007%. It has also been observed that its use helps to reduce optimization time, such as up to a speed 47.5 times faster than a full aeroelastic model.
PUSHER PROPELLER INFLUENCE ON A LAMINAR WING TRANSITION LOCATION USING INFRARED THERMOGRAPHY
33rd Congress of the International Council of the Aeronautical Sciences Icas 2022, 2022
EXPERIMENTAL INVESTIGATION OF A NEXT-GENERATION AIRLINER WITH BOUNDARY LAYER INGESTION
Icas Proceedings, 2022
EXPERIMENTAL INVESTIGATION OF A NEXT-GENERATION AIRLINER WITH BOUNDARY LAYER INGESTION
33rd Congress of the International Council of the Aeronautical Sciences Icas 2022, 2022
EXPERIMENTAL STUDIES ON THE INTERACTION BETWEEN PROPELLERS AND WING
33rd Congress of the International Council of the Aeronautical Sciences Icas 2022, 2022
Camber morphing winglet influence on aircraft drag breakdown and tip vortex structure
João Paulo Eguea, Pedro David Bravo-Mosquera, Fernando Martini Catalano
Aerospace Science and Technology, 2021
HIGH-LIFT NOISE REDUCTION USING PLASMA ACTUATORS
32nd Congress of the International Council of the Aeronautical Sciences Icas 2021, 2021
Slat aerodynamic noise reduction using dielectric barrier discharge plasma actuators
Gabriel Pereira Gouveia da Silva, João Paulo Eguea, José Antônio Garcia Croce, Fernando Martini Catalano
Aerospace Science and Technology, 2020
Fuel efficiency improvement on a business jet using a camber morphing winglet concept
João Paulo Eguea, Gabriel Pereira Gouveia da Silva, Fernando Martini Catalano
Aerospace Science and Technology, 2020
Study on a camber adaptive winglet
João Paulo Eguea, Fernando Martini Catalano, Alvaro Martins Abdalla, Leandro D. de Santana, Cornelis H. Venner, André Luiz Fontes Silva
2018 Applied Aerodynamics Conference, 2018