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Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography
Timo Lähivaara, Leo Kärkkäinen, Janne M. J. Huttunen +1
We study the feasibility of data based machine learning applied to ultrasound tomography to estimate water-saturated porous material parameters. In this work, the data to train the…
Structure-Preserving Model-Reduction of Dissipative Hamiltonian Systems
Babak Maboudi Afkham, Jan S. Hesthaven
Reduced basis methods are popular for approximately solving large and complex systems of differential equations. However, conventional reduced basis methods do not generally preser…
Structure Preserving Model Reduction of Parametric Hamiltonian Systems
Babak Maboudi Afkham, Jan S. Hesthaven
While reduced-order models (ROMs) have been popular for efficiently solving large systems of differential equations, the stability of reduced models over long-time integration is o…