Felipe A. C. Viana
Felipe A. C. Viana
Other namesFelipe Antonio Chegury Viana, Felipe Viana
Head of Applied Research
Verified email at
Cited by
Cited by
Multiple surrogates: how cross-validation errors can help us to obtain the best predictor
FAC Viana, RT Haftka, V Steffen
Structural and Multidisciplinary Optimization 39 (4), 439-457, 2009
Metamodeling in Multidisciplinary Design Optimization: How Far Have We Really Come?
FAC Viana, TW Simpson, V Balabanov, V Toropov
AIAA Journal 52 (4), 670-690, 2014
Design and analysis of computer experiments in multidisciplinary design optimization: a review of how far we have come or not
TW Simpson, V Toropov, V Balabanov, FAC Viana
12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, AIAA …, 2008
An algorithm for fast optimal Latin hypercube design of experiments
FAC Viana, G Venter, V Balabanov
International Journal for Numerical Methods in Engineering 82 (2), 135-156, 2010
Efficient global optimization algorithm assisted by multiple surrogate techniques
FAC Viana, RT Haftka, LT Watson
Journal of Global Optimization 56 (2), 669-689, 2013
A Tutorial on Latin Hypercube Design of Experiments
FAC Viana
Quality and Reliability Engineering International, 2015
SURROGATES toolbox user’s guide
FAC Viana
Users manual, http://fchegury. googlepages. com, 2009
Things you wanted to know about the Latin hypercube design and were afraid to ask
FAC Viana
10th World Congress on Structural and Multidisciplinary Optimization …, 2013
Multimodal vibration damping through piezoelectric patches and optimal resonant shunt circuits
FAC Viana, V Steffen Jr
Journal of the Brazilian Society of Mechanical Sciences and Engineering 28 …, 2006
Making the most out of surrogate models: tricks of the trade
FAC Viana, C Gogu, RT Haftka
ASME 2010 International Design Engineering Technical Conferences & Computers …, 2010
A tutorial on solving ordinary differential equations using Python and hybrid physics-informed neural network
RG Nascimento, K Fricke, FAC Viana
Engineering Applications of Artificial Intelligence 96, DOI: 10.1016/j …, 2020
Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis
RG Nascimento, M Corbetta, CS Kulkarni, FAC Viana
Journal of Power Sources 513, 230526, 2021
Physics-informed neural networks for missing physics estimation in cumulative damage models: a case study in corrosion fatigue
A Dourado, FAC Viana
ASME Journal of Computing and Information Science in Engineering, 2020
A physics-informed neural network for wind turbine main bearing fatigue
YA Yucesan, FAC Viana
International Journal of Prognostics and Health Management 11 (1), 2020
Tuning dynamic vibration absorbers by using ant colony optimization
FAC Viana, GI Kotinda, DA Rade, V Steffen Jr
Computers & Structures 86 (13-14), 1539-1549, 2008
Surrogate-based optimization with parallel simulations using the probability of improvement
FAC Viana, RT Haftka
13th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, AIAA …, 2010
Fleet Prognosis with Physics-informed Recurrent Neural Networks
RG Nascimento, FAC Viana
The 12th International Workshop on Structural Health Monitoring, 2019
Estimating model inadequacy in ordinary differential equations with physics-informed neural networks
FAC Viana, RG Nascimento, A Dourado, YA Yucesan
Computers and Structures 245, 106458 (DOI: 10.1016/j.compstruc.2020.10, 2021
Why not run the efficient global optimization algorithm with multiple surrogates?
FAC Viana, RT Haftka, LT Watson
51st AIAAASMEASCEAHSASC Structures Structural Dynamics and Materials …, 2010
Using multiple surrogates for metamodeling
FAC Viana, RT Haftka
7th ASMO-UK/ISSMO International Conference on Engineering Design Optimization, 2008
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