M
Michael Emory
Researcher at Stanford University
Publications - 17
Citations - 581
Michael Emory is an academic researcher from Stanford University. The author has contributed to research in topics: Turbulence & Uncertainty quantification. The author has an hindex of 9, co-authored 15 publications receiving 433 citations. Previous affiliations of Michael Emory include Center for Turbulence Research.
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Journal ArticleDOI
Modeling of structural uncertainties in Reynolds-averaged Navier-Stokes closures
TL;DR: In this paper, an approach to model-form uncertainty quantification that does not assume the eddy-viscosity hypothesis to be exact is proposed, and the methodology for estimation of uncertainty is demonstrated for plane channel flow, for a duct with secondary flows, and for the shock/boundary-layer interaction over a transonic bump.
Journal ArticleDOI
Exploiting Active Subspaces to Quantify Uncertainty in the Numerical Simulation of the HyShot II Scramjet
TL;DR: A novel methodology based on active subspaces is employed to characterize the effects of the input uncertainty on the scramjet performance, and this dimension reduction enables otherwise infeasible uncertainty quantification.
Proceedings ArticleDOI
Modeling Structural Uncertainties in Reynolds-Averaged Computations of Shock/Boundary Layer Interactions
TL;DR: In this article, the authors introduce a new approach for addressing epistemic uncertainty which is then demonstrated for the ow over a 2D transonic bump conguration, where the well known SST k! turbulence model is considered.
Proceedings ArticleDOI
Large-eddy simulations of co-annular turbulent jet using a Voronoi-based mesh generation framework
Guillaume A. Brès,Sanjeeb Bose,Michael Emory,Frank Ham,Oliver T. Schmidt,Georgios Rigas,Tim Colonius +6 more
TL;DR: In this paper, large eddy simulations are performed for a cold ideallyexpanded dual-stream jet issued from cylindrical co-axial nozzles, with supersonic primary stream (Mach number M1 = 1.55) and subsonic secondary stream (M2 = 0.9).
Journal ArticleDOI
Epistemic uncertainty quantification for Reynolds-averaged Navier-Stokes modeling of separated flows over streamlined surfaces
TL;DR: In this article, a physics-based approach is proposed to quantify the uncertainty in the Reynolds-averaged Navier-Stokes simulations of separated flows over streamlined surfaces, where perturbations are defined in terms of a decomposition of the Reynolds stress tensor, based on the tensor magnitude and the eigenvalues and eigenvectors of the normalized anisotropy tensor.