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ORCIDFelipe A. C. Viana
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- affiliation: University of Central Florida, Orlando, FL, USA
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Journal Articles
- 2024
[j15]Yigit A. Yucesan, Felipe A. C. Viana
:
Physics-informed digital twin for wind turbine main bearing fatigue: Quantifying uncertainty in grease degradation. Appl. Soft Comput. 149(Part A): 110921 (2024)- [j14]Augusto Delavald Marques, Lara Werncke Vieira, Paulo Smith Schneider, Felipe A. C. Viana:
Steam generator efficiency optimization under uncertainty through multi-fidelity modeling. J. Comput. Sci. 79: 102307 (2024) - [j13]Francesco Piccialli, Maziar Raissi, Felipe A. C. Viana, Giancarlo Fortino, Huimin Lu, Amir Hussain:
Guest Editorial: Special Issue on Physics-Informed Machine Learning. IEEE Trans. Artif. Intell. 5(3): 964-966 (2024) - 2023
- [j12]Andre Von Zuben, Luigi E. Perotti, Felipe A. C. Viana:
Anatomically-guided deep learning for left ventricle geometry generation with uncertainty quantification based on short-axis MR images. Eng. Appl. Artif. Intell. 121: 106012 (2023) - [j11]Andre Von Zuben, Felipe A. C. Viana:
Generative adversarial networks for extrapolation of corrosion in automobile images. Expert Syst. Appl. 213(Part): 118849 (2023) - 2022
- [j10]Arinan Dourado, Felipe A. C. Viana:
Ensemble of hybrid neural networks to compensate for epistemic uncertainties: a case study in system prognosis. Soft Comput. 26(13): 6157-6173 (2022) - 2021
- [j9]Yigit A. Yucesan, Arinan Dourado, Felipe A. C. Viana:
A survey of modeling for prognosis and health management of industrial equipment. Adv. Eng. Informatics 50: 101404 (2021) - [j8]Yigit A. Yucesan, Felipe Antonio Chegury Viana:
Hybrid physics-informed neural networks for main bearing fatigue prognosis with visual grease inspection. Comput. Ind. 125: 103386 (2021) - [j7]Arinan Dourado, Felipe Antonio Chegury Viana:
Early life failures and services of industrial asset fleets. Reliab. Eng. Syst. Saf. 205: 107225 (2021) - 2020
- [j6]Renato Giorgiani Nascimento, Kajetan Fricke, Felipe Antonio Chegury Viana:
A tutorial on solving ordinary differential equations using Python and hybrid physics-informed neural network. Eng. Appl. Artif. Intell. 96: 103996 (2020) - [j5]Arinan Dourado, Felipe Antonio Chegury Viana:
Physics-Informed Neural Networks for Missing Physics Estimation in Cumulative Damage Models: A Case Study in Corrosion Fatigue. J. Comput. Inf. Sci. Eng. 20(6) (2020) - 2016
- [j4]Felipe Antonio Chegury Viana:
A Tutorial on Latin Hypercube Design of Experiments. Qual. Reliab. Eng. Int. 32(5): 1975-1985 (2016) - 2013
- [j3]Ping Zhu, Feng Pan, Wei Chen, Felipe Antonio Chegury Viana:
Lightweight design of vehicle parameters under crashworthiness using conservative surrogates. Comput. Ind. 64(3): 280-289 (2013) - [j2]Felipe Antonio Chegury Viana, Raphael T. Haftka, Layne T. Watson:
Efficient global optimization algorithm assisted by multiple surrogate techniques. J. Glob. Optim. 56(2): 669-689 (2013) - 2009
- [j1]Felipe Antonio Chegury Viana, Valder Steffen, Sergio Butkewitsch, Marcus de Freitas Leal:
Optimization of aircraft structural components by using nature-inspired algorithms and multi-fidelity approximations. J. Glob. Optim. 45(3): 427-449 (2009)
Conference and Workshop Papers
- 2023
- [c3]Andre Von Zuben, Emily Whitt, Felipe A. C. Viana, Luigi E. Perotti:
Long Axis Cardiac MRI Segmentation Using Anatomically-Guided UNets and Transfer Learning. FIMH 2023: 274-282 - 2021
- [c2]Andre Von Zuben, Kylie Heckman, Felipe A. C. Viana, Luigi E. Perotti:
A Multi-step Machine Learning Approach for Short Axis MR Images Segmentation. FIMH 2021: 122-133 - 2006
- [c1]Felipe Antonio Chegury Viana, Giovanni Iamin Kotinda, Domingos Alves Rade, Valder Steffen Jr.:
Can Ants Design Mechanical Engineering Systems? IEEE Congress on Evolutionary Computation 2006: 831-837
Informal and Other Publications
- 2019
- [i1]Renato Giorgiani Nascimento, Felipe Antonio Chegury Viana:
Fleet Prognosis with Physics-informed Recurrent Neural Networks. CoRR abs/1901.05512 (2019)
Coauthor Index
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