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

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

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 languageEnglish
Article numberFE-22-1510
JournalJournal of Fluids Engineering, Transactions of the ASME
Volume145
Issue6
Number of pages8
ISSN0098-2202
DOIs
Publication statusPublished - Mar 2023

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