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Delamination area quantification in composite structures using Gaussian process regression and auto-regressive models
(2020-01-01)
After detecting initial delamination damage in a hotspot region of a composite structure monitored through a data-driven approach, the user needs to decide if there is an imminent structural failure or if the system can ...
Probabilistic machine learning for detection of tightening torque in bolted joints
(2022-01-01)
Observing the loss of tightening torque using modal parameters is challenging due to the variability and nonlinear effects in bolted joints. Thus, this paper proposes a combined application of two probabilistic machine ...
Forecast and evaluation of COVID-19 spreading in USA with reduced-space Gaussian process regression
In this report, we analyze historical and forecast infections for COVID-19 death based on Reduced-Space
Gaussian Process Regression associated to chaotic Dynamical Systems with information obtained in 82
days with ...
Gapped Gaussian smoothing technique for debonding assessment with automatic thresholding
(John Wiley and Sons Ltd, 2019)
© 2019 John Wiley & Sons, Ltd.Sandwich structures are subjected to imperfect bonding or debonding caused by defects during the manufacturing process, by fatigue, or by impact loads. In this context, their safety and ...
Predicting EHL film thickness parameters by machine learning approaches
(2022)
Non-dimensional similarity groups and analytically solvable proximity equations can be used to estimate integral fluid film parameters of elastohydrodynamically lubricated (EHL) contacts. In this contribution, we demonstrate ...