Large Eddy Simulation Reduced Order Models

Simple item page
dc.contributor.authorXie, Xupingen
dc.contributor.committeechairIliescu, Traianen
dc.contributor.committeememberBorggaard, Jeffrey T.en
dc.contributor.committeememberGugercin, Serkanen
dc.contributor.committeememberRoss, Shane D.en
dc.contributor.departmentMathematicsen
dc.date.accessioned2017-05-13T08:00:12Zen
dc.date.available2017-05-13T08:00:12Zen
dc.date.issued2017-05-12en
dc.description.abstractThis dissertation uses spatial filtering to develop a large eddy simulation reduced order model (LES-ROM) framework for fluid flows. Proper orthogonal decomposition is utilized to extract the dominant spatial structures of the system. Within the general LES-ROM framework, two approaches are proposed to address the celebrated ROM closure problem. No phenomenological arguments (e.g., of eddy viscosity type) are used to develop these new ROM closure models. The first novel model is the approximate deconvolution ROM (AD-ROM), which uses methods from image processing and inverse problems to solve the ROM closure problem. The AD-ROM is investigated in the numerical simulation of a 3D flow past a circular cylinder at a Reynolds number $Re=1000$. The AD-ROM generates accurate results without any numerical dissipation mechanism. It also decreases the CPU time of the standard ROM by orders of magnitude. The second new model is the calibrated-filtered ROM (CF-ROM), which is a data-driven ROM. The available full order model results are used offline in an optimization problem to calibrate the ROM subfilter-scale stress tensor. The resulting CF-ROM is tested numerically in the simulation of the 1D Burgers equation with a small diffusion parameter. The numerical results show that the CF-ROM is more efficient than and as accurate as state-of-the-art ROM closure models.en
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.identifier.othervt_gsexam:11302en
dc.identifier.urihttp://hdl.handle.net/10919/77626en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectReduced Order Modelingen
dc.subjectLarge Eddy Simulationen
dc.subjectApproximate Deconvolutionen
dc.subjectData-Driven Modelingen
dc.subjectStochastic Reduced Order Modelen
dc.subjectSpatial Filteringen
dc.subjectFinite element methoden
dc.subjectNumerical Analysisen
dc.titleLarge Eddy Simulation Reduced Order Modelsen
dc.typeDissertationen
thesis.degree.disciplineMathematicsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Xie_X_D_2017.pdf
Size:
4.73 MB
Format:
Adobe Portable Document Format
Download

Collections

Doctoral Dissertations