23 citations · 65 across the 8 of their papers we have counts for
3 papers · 1 filter
Stochastic stiffness identification and response estimation of Timoshenko beams via physics-informed Gaussian processes
Gledson Rodrigo Tondo, Sebastian Rau, Igor Kavrakov +1
Machine learning models trained with structural health monitoring data have become a powerful tool for system identification. This paper presents a physics-informed Gaussian proces…
A physics-informed machine learning model for reconstruction of dynamic loads
Gledson Rodrigo Tondo, Igor Kavrakov, Guido Morgenthal
Long-span bridges are subjected to a multitude of dynamic excitations during their lifespan. To account for their effects on the structural system, several load models are used dur…
Physics-informed Gaussian process model for Euler-Bernoulli beam elements
Gledson Rodrigo Tondo, Sebastian Rau, Igor Kavrakov +1
A physics-informed machine learning model, in the form of a multi-output Gaussian process, is formulated using the Euler-Bernoulli beam equation. Given appropriate datasets, the mo…