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Turbulence Model Development for Hyp...

Jordan, Cyrus Joshua.

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Turbulence Model Development for Hypersonic Shock Wave Boundary Layer Interactions.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Turbulence Model Development for Hypersonic Shock Wave Boundary Layer Interactions./
Author:	Jordan, Cyrus Joshua.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:	146 p.
Notes:	Source: Dissertations Abstracts International, Volume: 84-12, Section: A.
Contained By:	Dissertations Abstracts International84-12A.
Subject:	Kinematics. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30463916
ISBN:	9798379649579

Turbulence Model Development for Hypersonic Shock Wave Boundary Layer Interactions.
Jordan, Cyrus Joshua.

Turbulence Model Development for Hypersonic Shock Wave Boundary Layer Interactions. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 146 p.

Source: Dissertations Abstracts International, Volume: 84-12, Section: A.

Thesis (Ph.D.)--North Carolina State University, 2023.

This item must not be sold to any third party vendors.

The 21st century has sparked interest in hypersonic applications not seen since X-series planes were designed and tested in the early 1960s. These applications demand accurate and cost-effective tools for predicting and modeling hypersonic (M >5) conditions. Conventional wind tunnels cannot recreate hypersonic flight conditions limiting testing to specialized facilities. Shock and expansion tunnels provide high enthalpy conditions but are restricted to finite test time, while hypersonic blow-down tunnels exist but are costly and difficult to maintain. Often engineers turn to computational fluid dynamics (CFD) to simulate rather than test hypersonic applications. Turbulent flow is described by a broad spectrum of time and length scales, which must be resolved or modeled. Scale-resolving methods such as Direct Numerical Simulations (DNS) or Large Eddy Simulation (LES) require full or partial resolution of the turbulent scales. As hypersonic flows are described by Reynolds numbers (Re) of the order 106 per meter, and grid size requirements for DNS and LES roughly scale as Re3 and Re2 , scale-resolving methods often exceed computational resources. However, lower-fidelity methods model rather than resolve turbulence, with the current state-of-the-practice being Reynolds-averaged Navier Stokes (RANS) modeling.RANS predictions using Menter's baseline (BSL) and shear stress transport (SST) models show significant deviations from hypersonic experiments with shock wave boundary layer interactions (SBLIs), with BSL failing to predict axial separation and SST generally over-predicting the degree of separation. The LES-type methods improve upon these results, predicting the level of upstream influence more correctly for the stronger (more compressed) interactions while accurately capturing off-body structures in upstream boundary layers.In this work, we utilize high-fidelity datasets generated using scale-resolving methods (wallresolved LES or hybrid LES-RANS) to evaluate the model assumptions underpinning modern RANS practices. We show the Boussinesq hypothesis for the Reynolds shear stress and the gradient-diffusion assumption for the turbulent heat flux does not hold very well in the region of strong shock / boundary layer interaction but improve as the boundary layer reaches more of an equilibrium state. The extraction of turbulent momentum and thermal diffusivities reveals that the turbulent Prandtl number is not constant, reaching sub-unity values through much of the interaction region. The shear-stress structure factor (a key model constant in Menter's SST model) also varies significantly within the interaction region, rising above its equilibrium level near shock waves.Following this, a novel equation-learning neural net strategy was used to develop functional descriptions of turbulent Prandtl number and structure factor. Utilizing the high-fidelity hypersonic SBLI test suite and two additional, physically unique hypersonic test cases, we benchmark our developed models' performance. In general, for applications where SST over-predicts and BSL under-predicts experimental values, our modifications provided significant gains in accuracy in terms of separation and surface measurements. However, our model trended towards BSL predictions in weakly separated applications, typically over-predicting surface heat transfer, performing worse than unmodified SST. Overall, we have revealed physical inaccuracy in the fundamental assumptions underpinning RANS models in hypersonic SBLI applications. Our work demonstrates the potential of data-driven methods to develop model improvements with LES / LES-RANS simulations as truth models.

ISBN: 9798379649579Subjects--Topical Terms:

571109
Kinematics.

Turbulence Model Development for Hypersonic Shock Wave Boundary Layer Interactions.
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245 1 0 $a Turbulence Model Development for Hypersonic Shock Wave Boundary Layer Interactions.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2023
300 $a 146 p.
500 $a Source: Dissertations Abstracts International, Volume: 84-12, Section: A.
500 $a Advisor: Gremaud, Pierre;Narayanaswamy, Venkateswaran;Subbareddy, Pramod;Edwards, Jack.
502 $a Thesis (Ph.D.)--North Carolina State University, 2023.
506 $a This item must not be sold to any third party vendors.
520 $a The 21st century has sparked interest in hypersonic applications not seen since X-series planes were designed and tested in the early 1960s. These applications demand accurate and cost-effective tools for predicting and modeling hypersonic (M >5) conditions. Conventional wind tunnels cannot recreate hypersonic flight conditions limiting testing to specialized facilities. Shock and expansion tunnels provide high enthalpy conditions but are restricted to finite test time, while hypersonic blow-down tunnels exist but are costly and difficult to maintain. Often engineers turn to computational fluid dynamics (CFD) to simulate rather than test hypersonic applications. Turbulent flow is described by a broad spectrum of time and length scales, which must be resolved or modeled. Scale-resolving methods such as Direct Numerical Simulations (DNS) or Large Eddy Simulation (LES) require full or partial resolution of the turbulent scales. As hypersonic flows are described by Reynolds numbers (Re) of the order 106 per meter, and grid size requirements for DNS and LES roughly scale as Re3 and Re2 , scale-resolving methods often exceed computational resources. However, lower-fidelity methods model rather than resolve turbulence, with the current state-of-the-practice being Reynolds-averaged Navier Stokes (RANS) modeling.RANS predictions using Menter's baseline (BSL) and shear stress transport (SST) models show significant deviations from hypersonic experiments with shock wave boundary layer interactions (SBLIs), with BSL failing to predict axial separation and SST generally over-predicting the degree of separation. The LES-type methods improve upon these results, predicting the level of upstream influence more correctly for the stronger (more compressed) interactions while accurately capturing off-body structures in upstream boundary layers.In this work, we utilize high-fidelity datasets generated using scale-resolving methods (wallresolved LES or hybrid LES-RANS) to evaluate the model assumptions underpinning modern RANS practices. We show the Boussinesq hypothesis for the Reynolds shear stress and the gradient-diffusion assumption for the turbulent heat flux does not hold very well in the region of strong shock / boundary layer interaction but improve as the boundary layer reaches more of an equilibrium state. The extraction of turbulent momentum and thermal diffusivities reveals that the turbulent Prandtl number is not constant, reaching sub-unity values through much of the interaction region. The shear-stress structure factor (a key model constant in Menter's SST model) also varies significantly within the interaction region, rising above its equilibrium level near shock waves.Following this, a novel equation-learning neural net strategy was used to develop functional descriptions of turbulent Prandtl number and structure factor. Utilizing the high-fidelity hypersonic SBLI test suite and two additional, physically unique hypersonic test cases, we benchmark our developed models' performance. In general, for applications where SST over-predicts and BSL under-predicts experimental values, our modifications provided significant gains in accuracy in terms of separation and surface measurements. However, our model trended towards BSL predictions in weakly separated applications, typically over-predicting surface heat transfer, performing worse than unmodified SST. Overall, we have revealed physical inaccuracy in the fundamental assumptions underpinning RANS models in hypersonic SBLI applications. Our work demonstrates the potential of data-driven methods to develop model improvements with LES / LES-RANS simulations as truth models.
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