Data-Driven Dynamical System Models of Roughness-Induced Secondary Flows in Thermally Stratified Turbulent Boundary Layers

Christoffer Hansen; Xiang I. A. Yang; Mahdi Abkar

doi:10.1115/1.4057016

Data-Driven Dynamical System Models of Roughness-Induced Secondary Flows in Thermally Stratified Turbulent Boundary Layers

Christoffer Hansen, Xiang I. A. Yang, Mahdi Abkar^*

^*Corresponding author for this work

Department of Mechanical and Production Engineering - Fluids and Energy

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

3 Citations (Scopus)

Abstract

The goal of this work is to investigate the feasibility of constructing data-driven dynamical system models of roughness-induced secondary flows in thermally stratified turbulent boundary layers. Considering the case of a surface roughness distribution which is homogeneous and heterogeneous in the streamwise and spanwise directions, respectively, we describe the streamwise averaged in-plane motions via a stream function formulation, thereby reducing the number of variables to the streamwise velocity component, an appropriately introduced stream function, and the temperature. Then, from the results of large eddy simulations, we perform a modal decomposition of each variable with the proper orthogonal decomposition and further utilize the temporal dynamics of the modal coefficients to construct a data-driven dynamical system model by applying the sparse identification of nonlinear dynamics (SINDy). We also present a novel approach for enforcing spanwise reflection symmetry within the SINDy framework to incorporate a physical bias.

Original language	English
Article number	FE-22-1510
Journal	Journal of Fluids Engineering, Transactions of the ASME
Volume	145
Issue	6
Number of pages	8
ISSN	0098-2202
DOIs	https://doi.org/10.1115/1.4057016
Publication status	Published - 1 Jun 2023

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title = "Data-Driven Dynamical System Models of Roughness-Induced Secondary Flows in Thermally Stratified Turbulent Boundary Layers",

abstract = "The goal of this work is to investigate the feasibility of constructing data-driven dynamical system models of roughness-induced secondary flows in thermally stratified turbulent boundary layers. Considering the case of a surface roughness distribution which is homogeneous and heterogeneous in the streamwise and spanwise directions, respectively, we describe the streamwise averaged in-plane motions via a stream function formulation, thereby reducing the number of variables to the streamwise velocity component, an appropriately introduced stream function, and the temperature. Then, from the results of large eddy simulations, we perform a modal decomposition of each variable with the proper orthogonal decomposition and further utilize the temporal dynamics of the modal coefficients to construct a data-driven dynamical system model by applying the sparse identification of nonlinear dynamics (SINDy). We also present a novel approach for enforcing spanwise reflection symmetry within the SINDy framework to incorporate a physical bias.",

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Data-Driven Dynamical System Models of Roughness-Induced Secondary Flows in Thermally Stratified Turbulent Boundary Layers. / Hansen, Christoffer; I. A. Yang, Xiang; Abkar, Mahdi.
In: Journal of Fluids Engineering, Transactions of the ASME, Vol. 145, No. 6, FE-22-1510, 01.06.2023.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

TY - JOUR

T1 - Data-Driven Dynamical System Models of Roughness-Induced Secondary Flows in Thermally Stratified Turbulent Boundary Layers

AU - Hansen, Christoffer

AU - I. A. Yang, Xiang

AU - Abkar, Mahdi

PY - 2023/6/1

Y1 - 2023/6/1

N2 - The goal of this work is to investigate the feasibility of constructing data-driven dynamical system models of roughness-induced secondary flows in thermally stratified turbulent boundary layers. Considering the case of a surface roughness distribution which is homogeneous and heterogeneous in the streamwise and spanwise directions, respectively, we describe the streamwise averaged in-plane motions via a stream function formulation, thereby reducing the number of variables to the streamwise velocity component, an appropriately introduced stream function, and the temperature. Then, from the results of large eddy simulations, we perform a modal decomposition of each variable with the proper orthogonal decomposition and further utilize the temporal dynamics of the modal coefficients to construct a data-driven dynamical system model by applying the sparse identification of nonlinear dynamics (SINDy). We also present a novel approach for enforcing spanwise reflection symmetry within the SINDy framework to incorporate a physical bias.

AB - The goal of this work is to investigate the feasibility of constructing data-driven dynamical system models of roughness-induced secondary flows in thermally stratified turbulent boundary layers. Considering the case of a surface roughness distribution which is homogeneous and heterogeneous in the streamwise and spanwise directions, respectively, we describe the streamwise averaged in-plane motions via a stream function formulation, thereby reducing the number of variables to the streamwise velocity component, an appropriately introduced stream function, and the temperature. Then, from the results of large eddy simulations, we perform a modal decomposition of each variable with the proper orthogonal decomposition and further utilize the temporal dynamics of the modal coefficients to construct a data-driven dynamical system model by applying the sparse identification of nonlinear dynamics (SINDy). We also present a novel approach for enforcing spanwise reflection symmetry within the SINDy framework to incorporate a physical bias.

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Data-Driven Dynamical System Models of Roughness-Induced Secondary Flows in Thermally Stratified Turbulent Boundary Layers

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