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Quasilinear modelling of supersonic turbulent channel flow using incompressible flow data.

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Title: Quasilinear modelling of supersonic turbulent channel flow using incompressible flow data.
Authors: Zou, Zecheng1 (AUTHOR) zecheng.zou19@imperial.ac.uk, Ceci, Alessendro2,3 (AUTHOR), Jiao, Yuxin1,3,4 (AUTHOR), Pirozzoli, Sergio3,4 (AUTHOR), Hwang, Yongyun1 (AUTHOR)
Source: Journal of Fluid Mechanics. 6/25/2026, Vol. 1037, p1-45. 45p.
Subjects: Compressible flow, Incompressible flow, Eddy viscosity, Supersonic flow, Mach number, Navier-Stokes equations, Turbulence
Abstract: Content of image described in text. This study extends the data-driven quasilinear approximation (DQLA) (Holford, Lee & Hwang 2024 J. Fluid Mech. , vol. 980 , A12) to compressible turbulent channel flow. The DQLA employs the eddy viscosity enhanced linearised compressible Navier–Stokes operator (Chen et al. 2023 J. Fluid Mech. , vol. 962 , A7), driven by stochastic forcing whose streamwise weights are determined through self-similarity assimilated from an incompressible direct numerical simulation (DNS) database, and spanwise weights are obtained by minimising discrepancies in the Reynolds stresses between the mean and the fluctuation equations. Without any compressible DNS input, the extended DQLA reproduces turbulence intensities and energy spectra in close quantitative agreement with DNS up to bulk Mach number italic Ma Subscript b Baseline equals 1.5 Ma b = 1.5 $\textit{Ma}_b=1.5$ , and exhibits a consistent collapse of turbulence statistics across Mach numbers when expressed in semilocal units at the same centreline semilocal friction Reynolds number italic Re Subscript tau c Superscript asterisk Re τ c ∗ $\textit{Re}_{\tau c}^*$. This collapse is largely inherited from the scaling properties of the mean flow and is preserved through DQLA, consistent with Morkovin's hypothesis. At higher Mach number (italic Ma Subscript b Baseline equals 3.0 Ma b = 3.0 $\textit{Ma}_b=3.0$), systematic deviations emerge, reflecting the limitations of the present modelling assumptions, particularly the neglect of nonlinear terms associated with density fluctuations. The results demonstrate the predictive capability of DQLA up to moderate Mach numbers, and establish its potential as a physically interpretable and computationally efficient framework for exploring compressible wall-bounded turbulence at high Reynolds numbers. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Fluid Mechanics is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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An: 194751995
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  Data: Quasilinear modelling of supersonic turbulent channel flow using incompressible flow data.
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  Data: <searchLink fieldCode="AR" term="%22Zou%2C+Zecheng%22">Zou, Zecheng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zecheng.zou19@imperial.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Ceci%2C+Alessendro%22">Ceci, Alessendro</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiao%2C+Yuxin%22">Jiao, Yuxin</searchLink><relatesTo>1,3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pirozzoli%2C+Sergio%22">Pirozzoli, Sergio</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hwang%2C+Yongyun%22">Hwang, Yongyun</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Fluid+Mechanics%22">Journal of Fluid Mechanics</searchLink>. 6/25/2026, Vol. 1037, p1-45. 45p.
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  Data: <searchLink fieldCode="DE" term="%22Compressible+flow%22">Compressible flow</searchLink><br /><searchLink fieldCode="DE" term="%22Incompressible+flow%22">Incompressible flow</searchLink><br /><searchLink fieldCode="DE" term="%22Eddy+viscosity%22">Eddy viscosity</searchLink><br /><searchLink fieldCode="DE" term="%22Supersonic+flow%22">Supersonic flow</searchLink><br /><searchLink fieldCode="DE" term="%22Mach+number%22">Mach number</searchLink><br /><searchLink fieldCode="DE" term="%22Navier-Stokes+equations%22">Navier-Stokes equations</searchLink><br /><searchLink fieldCode="DE" term="%22Turbulence%22">Turbulence</searchLink>
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  Data: Content of image described in text. This study extends the data-driven quasilinear approximation (DQLA) (Holford, Lee & Hwang 2024 J. Fluid Mech. , vol. 980 , A12) to compressible turbulent channel flow. The DQLA employs the eddy viscosity enhanced linearised compressible Navier–Stokes operator (Chen et al. 2023 J. Fluid Mech. , vol. 962 , A7), driven by stochastic forcing whose streamwise weights are determined through self-similarity assimilated from an incompressible direct numerical simulation (DNS) database, and spanwise weights are obtained by minimising discrepancies in the Reynolds stresses between the mean and the fluctuation equations. Without any compressible DNS input, the extended DQLA reproduces turbulence intensities and energy spectra in close quantitative agreement with DNS up to bulk Mach number italic Ma Subscript b Baseline equals 1.5 Ma b = 1.5 $\textit{Ma}_b=1.5$ , and exhibits a consistent collapse of turbulence statistics across Mach numbers when expressed in semilocal units at the same centreline semilocal friction Reynolds number italic Re Subscript tau c Superscript asterisk Re τ c ∗ $\textit{Re}_{\tau c}^*$. This collapse is largely inherited from the scaling properties of the mean flow and is preserved through DQLA, consistent with Morkovin's hypothesis. At higher Mach number (italic Ma Subscript b Baseline equals 3.0 Ma b = 3.0 $\textit{Ma}_b=3.0$), systematic deviations emerge, reflecting the limitations of the present modelling assumptions, particularly the neglect of nonlinear terms associated with density fluctuations. The results demonstrate the predictive capability of DQLA up to moderate Mach numbers, and establish its potential as a physically interpretable and computationally efficient framework for exploring compressible wall-bounded turbulence at high Reynolds numbers. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Fluid Mechanics is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1017/jfm.2026.11696
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 45
        StartPage: 1
    Subjects:
      – SubjectFull: Compressible flow
        Type: general
      – SubjectFull: Incompressible flow
        Type: general
      – SubjectFull: Eddy viscosity
        Type: general
      – SubjectFull: Supersonic flow
        Type: general
      – SubjectFull: Mach number
        Type: general
      – SubjectFull: Navier-Stokes equations
        Type: general
      – SubjectFull: Turbulence
        Type: general
    Titles:
      – TitleFull: Quasilinear modelling of supersonic turbulent channel flow using incompressible flow data.
        Type: main
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            NameFull: Zou, Zecheng
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            NameFull: Ceci, Alessendro
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            NameFull: Jiao, Yuxin
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            NameFull: Pirozzoli, Sergio
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            NameFull: Hwang, Yongyun
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            – D: 25
              M: 06
              Text: 6/25/2026
              Type: published
              Y: 2026
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              Value: 1037
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            – TitleFull: Journal of Fluid Mechanics
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