2

Efficient dynamic modal load reconstruction using physics-informed Gaussian processes based on frequency-sparse Fourier basis functions
An efficient physics-informed Gaussian process method reconstructs dynamic loads from structural response measurements using frequency-sparse Fourier basis functions.
Gledson Rodrigo Tondo, Igor Kavrakov, Guido Morgenthal
Preprint Cite Code Project DOI
Efficient dynamic modal load reconstruction using physics-informed Gaussian processes based on frequency-sparse Fourier basis functions
Stochastic Inference of Plate Bending from Heterogeneous Data: Physics-Informed Gaussian Processes via Kirchhoff–Love Theory
What can noisy measurements tell us about a bending plate? Our physics-informed Gaussian Process model combines different sensor data to infer its stiffness and response—and the code is open source!
Igor Kavrakov, Gledson Rodrigo Tondo, Guido Morgenthal
Preprint Cite Code Project DOI
Stochastic Inference of Plate Bending from Heterogeneous Data: Physics-Informed Gaussian Processes via Kirchhoff–Love Theory
The Lefkandi-Toumba Building as a Timber-Framed Structure
A reconstruction and structural assessment identify the Lefkandi-Toumba building as an early timber-framed structure.
Alexandra Coucouzeli, Allan McRobie, Igor Kavrakov
PDF Cite DOI Journal
The Lefkandi-Toumba Building as a Timber-Framed Structure
Data-driven aeroelastic analyses of structures in turbulent wind conditions using enhanced Gaussian processes with aerodynamic priors
We combine Gaussian Processes with aerodynamic prior knowledge to model buffeting and flutter in turbulent wind. The nonlinear, nondimensional model comes with open-source code—check it out!
Igor Kavrakov, Guido Morgenthal, Allan McRobie
Preprint Cite Code Project DOI
Data-driven aeroelastic analyses of structures in turbulent wind conditions using enhanced Gaussian processes with aerodynamic priors
IABSE Task Group 3.1 Benchmark Results. Numerical Full Bridge Stability and Buffeting Simulations
IABSE Task Group: Bridge Aerodynamics Verification - Part 2, comparison for numerical buffeting and flutter analysis of a full bridge.
Giorgio Diana, and 17 others, including Igor Kavrakov
PDF Cite DOI
IABSE Task Group 3.1 Benchmark Results. Numerical Full Bridge Stability and Buffeting Simulations
Stochastic stiffness identification and response estimation of Timoshenko beams via physics-informed Gaussian processes
The study proposes a new method for inference of beam behaviour using Timoshenko beams and physics-informed Gaussian processes. Additionally, we present physics-informed sensor placement strategy. The method is validated on with experiments.
Gledson Rodrigo Tondo, Sebastian Rau, Igor Kavrakov, Guido Morgenthal
Preprint Cite Code Project DOI
Stochastic stiffness identification and response estimation of Timoshenko beams via physics-informed Gaussian processes
Coupled numerical simulation of liquid sloshing dampers and wind–structure simulation model
The study presents a framework for simulation of the wind-structure interaction mitigated by sloshing dampers
Victor Vîlceanu, Igor Kavrakov, Guido Morgenthal
PDF Cite Project DOI
Coupled numerical simulation of liquid sloshing dampers and wind–structure simulation model
Numerical investigation of the nonlinear interaction between the sinusoidal motion-induced and gust-induced forces acting on bridge decks
The study examines the nonlinear interaction between the buffeting and self-excited forces. We observed new exciting nonlinear features by studying the flowfield.
Samuel Tesfaye, Igor Kavrakov, Guido Morgenthal
Preprint Cite Project DOI
Numerical investigation of the nonlinear interaction between the sinusoidal motion-induced and gust-induced forces acting on bridge decks
Data-driven aerodynamic analysis of structures using Gaussian Processes
We present a new data-driven model using Gaussian Processes for the first time in structural aerodynamics. It is nonlinear, nonparametric, nondimensional and easy to use - check it out, there is an open-source code too!
Igor Kavrakov, Allan McRobie, Guido Morgenthal
Preprint Cite Code Project DOI
Data-driven aerodynamic analysis of structures using Gaussian Processes
Comparison metrics for time-histories: Application to bridge aerodynamics
How to verify/validate/compare your time-dependent model in a phisically meaningful sense? Use our comparison metrics! (incl. code)
Igor Kavrakov, Ahsan Kareem, Guido Morgenthal
PDF Cite Code Project DOI
Comparison metrics for time-histories: Application to bridge aerodynamics