88 citations · 876 across the 55 of their papers we have counts for
6 papers · 1 filter
A physical model for indirect noise in non-isentropic nozzles: Transfer functions and stability
Animesh Jain, Luca Magri
We propose a mathematical model from physical principles to predict the sound generated in nozzles with dissipation. The focus is on the sound generated from the acceleration of te…
Gradient-free optimization of chaotic acoustics with reservoir computing
Francisco Huhn, Luca Magri
We develop a versatile optimization method, which finds the design parameters that minimize time-averaged acoustic cost functionals. The method is gradient-free, model-informed, an…
Real-time thermoacoustic data assimilation
Andrea Nóvoa, Luca Magri
Low-order thermoacoustic models are qualitatively correct, but they are typically quantitatively inaccurate. We propose a time-domain bias-aware method to make qualitatively low--o…
Robust Optimization and Validation of Echo State Networks for learning chaotic dynamics
Alberto Racca, Luca Magri
An approach to the time-accurate prediction of chaotic solutions is by learning temporal patterns from data. Echo State Networks (ESNs), which are a class of Reservoir Computing, c…
Short- and long-term prediction of a chaotic flow: A physics-constrained reservoir computing approach
Nguyen Anh Khoa Doan, Wolfgang Polifke, Luca Magri
We propose a physics-constrained machine learning method-based on reservoir computing- to time-accurately predict extreme events and long-term velocity statistics in a model of tur…
Automatic-differentiated Physics-Informed Echo State Network (API-ESN)
Alberto Racca, Luca Magri
We propose the Automatic-differentiated Physics-Informed Echo State Network (API-ESN). The network is constrained by the physical equations through the reservoir's exact time-deriv…