Efficient modeling of incompressible flows with moderate large Reynolds numbers using a deconvolution-based Leray model: analysis, uncertainty quantification and application in aortic dissections

Xu, Huijuan

Title:

Efficient modeling of incompressible flows with moderate large Reynolds numbers using a deconvolution-based Leray model: analysis, uncertainty quantification and application in aortic dissections

dc.contributor.advisor	Veneziani, Alessandro
dc.contributor.advisor	Robert, Nerem M.
dc.contributor.author	Xu, Huijuan
dc.contributor.committeeMember	Alexeev, Alexander
dc.contributor.committeeMember	Gleason, Rudolph
dc.contributor.committeeMember	Taylor, Robert
dc.contributor.committeeMember	Leshnower, Bradley
dc.contributor.department	Mechanical Engineering
dc.date.accessioned	2020-05-20T16:58:28Z
dc.date.available	2020-05-20T16:58:28Z
dc.date.created	2020-05
dc.date.issued	2020-01-09
dc.date.submitted	May 2020
dc.date.updated	2020-05-20T16:58:28Z
dc.description.abstract	Progressive false lumen aneurysmal degeneration in the acute uncomplicated type B aortic dissection is a complex process with a combination of mechanical and biological etiologies. Patient-specific Computational Fluid Dynamics (CFD) provides spatial and temporal hemodynamic quantities that facilitate understanding of this disease progression. However, due to the moderate large Reynolds number and complex geometries, Direct Numerical Simulation (DNS) could be intimidatingly computational expensive. As a Large Eddy Simulation (LES) model, the Leray model solves the flow structure at large scales while models the effect of the small-scale flows using a deconvolution-based differential filter, whose efficiency and accuracy make it a promising candidate for the hemodynamic problem in human aortas. In order to evaluate the robustness of the model prediction, Uncertainty Quantification (UQ) and sensitivity analysis are necessary for understanding the effects of the model parameter and patients' data. The goal of this work is to develop and analyze the deconvolution-based Leray model for the incompressible flow problem in the hemodynamics of aortic dissections, to quantify the model uncertainty, and to apply the model to investigate the prognostic factors for the late complication of the originally uncomplicated type B aortic dissection in order to facilitate the decision of the less invasive early surgical intervention. The specific aims are: Aim 1, development and implementation of the deconvolution-based Leray model using the Finite Element Method. Aim 2, analysis of using the Leray model for suppressing the backflow instability, a common numerical instability in hemodynamic simulations. Aim 3, sensitivity analysis and uncertainty quantification of the influence of the Leray model parameter and patients' data. Aim 4, investigation of the hemodynamic indication factors of early surgical intervention for the acute uncomplicated type B aortic dissection by correlating the hemodynamic factors and false lumen degeneration in time.
dc.description.degree	Ph.D.
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/62729
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	Deconvolution-based Leray Model
dc.subject	Aortic dissection
dc.subject	Backflow stabilization
dc.subject	Large Eddy simulation
dc.subject	Uncertainty quantification
dc.subject	Global sensitivity analysis
dc.title	Efficient modeling of incompressible flows with moderate large Reynolds numbers using a deconvolution-based Leray model: analysis, uncertainty quantification and application in aortic dissections
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.corporatename	George W. Woodruff School of Mechanical Engineering
local.contributor.corporatename	College of Engineering
relation.isOrgUnitOfPublication	c01ff908-c25f-439b-bf10-a074ed886bb7
relation.isOrgUnitOfPublication	7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level	Doctoral