Zobrazeno 1 - 10
of 264
pro vyhledávání: '"Juniper, Matthew"'
Autor:
Giannotta, Alessandro, Yoko, Matthew, Cherubini, Stefania, De Palma, Pietro, Juniper, Matthew P.
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 containing seven parameters. The experimental rig is a ducted Bunsen flame supp
Externí odkaz:
http://arxiv.org/abs/2407.03701
We formulate and solve a Bayesian inverse Navier-Stokes (N-S) problem that assimilates velocimetry data in order to jointly reconstruct a 3D flow field and learn the unknown N-S parameters, including the boundary position. By hardwiring a generalised
Externí odkaz:
http://arxiv.org/abs/2406.18464
We propose a fast probabilistic framework for identifying differential equations governing the dynamics of observed data. We recast the SINDy method within a Bayesian framework and use Gaussian approximations for the prior and likelihood to speed up
Externí odkaz:
http://arxiv.org/abs/2402.15357
Publikováno v:
IEEE Transactions on Image Processing, 2022
We formulate a physics-informed compressed sensing (PICS) method for the reconstruction of velocity fields from noisy and sparse phase-contrast magnetic resonance signals. The method solves an inverse Navier-Stokes boundary value problem, which permi
Externí odkaz:
http://arxiv.org/abs/2207.01466
Publikováno v:
Journal of Fluid Mechanics, 2022
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 regularize the problem we use a Bayesian framework with Gaussian random fields.
Externí odkaz:
http://arxiv.org/abs/2207.01368
Magnetic resonance velocimetry (MRV) is a non-invasive experimental technique widely used in medicine and engineering to measure the velocity field of a fluid. These measurements are dense but have a low signal-to-noise ratio (SNR). The measurements
Externí odkaz:
http://arxiv.org/abs/2107.07863
Autor:
Sengupta, Ushnish, Waxenegger-Wilfing, Günther, Martin, Jan, Hardi, Justin, Juniper, Matthew P.
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 thermoacoustic instabilities under realistic conditions, representative of smal
Externí odkaz:
http://arxiv.org/abs/2107.06396
Publikováno v:
ICLR 2021 Deep Learning for Simulation Workshop
This paper proposes a Bayesian data-driven machine learning method for the online inference of the parameters of a G-equation model of a ducted, premixed flame. Heteroscedastic Bayesian neural network ensembles are trained on a library of 1.7 million
Externí odkaz:
http://arxiv.org/abs/2104.13201
Publikováno v:
In Computer Methods in Applied Mechanics and Engineering 5 January 2024 418 Part B
Publikováno v:
In Combustion and Flame January 2024 259