39 citations · 77 across the 5 of their papers we have counts for
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Bayesian inference of physics-based models of acoustically-forced laminar premixed conical flames
Alessandro Giannotta, Matthew Yoko, Stefania Cherubini +2
We perform twenty experiments on an acoustically-forced laminar premixed Bunsen flame and assimilate high-speed footage of the natural emission into a physics-based model containin…
Joint reconstruction and segmentation of noisy velocity images as an inverse Navier-Stokes problem
Alexandros Kontogiannis, Scott V. Elgersma, Andrew J. Sederman +1
We formulate and solve a generalized inverse Navier-Stokes problem for the joint velocity field reconstruction and boundary segmentation of noisy flow velocity images. To regulariz…
Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning
Ushnish Sengupta, Günther Waxenegger-Wilfing, Jan Martin +2
The 100 MW cryogenic liquid oxygen/hydrogen multi-injector combustor BKD operated by the DLR Institute of Space Propulsion is a research platform that allows the study of thermoaco…
Adjoint-based linear analysis in reduced-order thermo-acoustic models
Luca Magri, Matthew Juniper
This paper presents the linear theory of adjoint equations as applied to thermo-acoustics. The purpose is to describe the mathematical foundations of adjoint equations for linear s…
Global modes, receptivity, and sensitivity analysis of diffusion flames coupled with duct acoustics
Luca Magri, Matthew Juniper
In this theoretical and numerical paper, we derive the adjoint equations for a thermo-acoustic system consisting of an infinite-rate chemistry diffusion flame coupled with duct aco…