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A fully one-sided diffuse-interface immersed boundary method for wall-modeled large-eddy simulation

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Pith's one-line read One-sided boundary forcing fixes wall-stress prediction in turbulent flow simulations

desk verdict Solid methodological contribution to diffuse-interface IBM-WMLES coupling. The wall-shear-stress enforcement (Eq. 42) is clean and parameter-free, and the FODIBM one-sided approach genuinely improves on conventional DIBM at low reference heights. The main limitation is scope: everything is validated for attached flows only. read the letter →

arxiv 2607.07443 v1 pith:SJPLSI5U submitted 2026-07-08 physics.flu-dyn

Qian Mao , Yoshiharu Tamaki , Song Zhao , Jérôme Jacob , Pierre Boivin , Julien Favier This is my paper · ORCID
classification physics.flu-dyn PACS 47.11.-j47.27.E47.27.em
keywords immersedboundarymethodwall-modeledlarge-eddysimulationdiffuseinterfacewallshearstresslatticeBoltzmannturbulentchannelflowairfoilaerodynamics
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper addresses a specific failure mode in computational fluid dynamics: when diffuse-interface immersed boundary methods (DIBMs) are combined with wall-modeled large-eddy simulation (WMLES), the numerical diffusion inherent in DIBM contaminates the near-wall flow field and degrades wall-shear-stress prediction. The authors propose a fully one-sided diffuse-interface immersed boundary method (FODIBM) that confines all interpolation and spreading operations strictly inside the immersed body, eliminating cross-boundary diffusion. They then couple the wall-parallel immersed-boundary forcing directly to the wall shear stress predicted by an explicit wall model, without introducing any artificial parameters. To maintain the total shear-stress balance below the reference height where the grid cannot resolve turbulent fluctuations, they introduce a tau-model that adds a modeled turbulent shear-stress tensor with a linear profile from the wall to the reference height. The combined approach is validated in turbulent channel flow at Re_tau = 5200 (skin-friction error below 1%) and in flow over a NACA23012 airfoil (lift coefficient error below 5%).

What carries the argument

FODIBM: one-sided interpolation/spreading confined to body interior; WS: wall-parallel IB force coupled to wall-model stress; tau-model: anisotropic modeled shear-stress tensor with linear profile wall-to-reference-height

What would settle it

If applying the WS+tau-model to a flow with massive separation (e.g., a stalled airfoil or backward-facing step) yields skin-friction or velocity-profile errors substantially larger than the sub-1% channel-flow benchmark, the linear stress-profile assumption would be shown to be regime-dependent rather than universal.

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Extended reading notes

Core claim

The central mechanism is the combination of three ingredients: (1) one-sided interpolation and spreading that removes the diffusion contaminating conventional DIBM near walls, (2) direct coupling of the wall-parallel IB force to the wall-model-predicted wall shear stress so that the forcing enforces the correct stress at the boundary, and (3) a tau-model that injects only the shear component of the modeled turbulent stress (rather than an isotropic eddy viscosity) to preserve the total shear-stress balance below the reference height without suppressing wall-normal turbulent mixing. Together these eliminate the log-layer mismatch that plagues conventional approaches and allow accurate WMLESon

Load-bearing premise

The tau-model assumes the modeled turbulent shear stress varies linearly between the wall (where it equals the wall shear stress) and the reference height (where it vanishes). This linearity is not derived from first principles and has only been tested in attached channel and airfoil flows; if the true stress profile deviates significantly from linear in separated or strongly pressure-gradient-driven flows, the shear-stress balance enforcement would be incorrect.

Editorial extensions

If this is right

  • The method enables diffuse-interface IBM to achieve accuracy competitive with sharp-interface approaches for WMLES, while retaining the simplicity of Cartesian grids and avoiding complex boundary-cell treatments.
  • The parameter-free coupling between IB forcing and wall shear stress removes a source of tunable arbitrariness that has limited prior diffuse-interface wall-modeling efforts.
  • The tau-model's avoidance of log-layer mismatch suggests that anisotropic stress injection is preferable to isotropic eddy-viscosity enhancement whenever wall-normal mixing must be preserved.
  • The demonstrated robustness across inclination angles up to 45 degrees indicates the method can handle genuinely complex, non-axis-aligned geometries without body-fitted meshes.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The linear stress-profile assumption in the tau-model is untested in separated flows, adverse pressure gradients, and transitional regimes; if the actual profile is strongly nonlinear there, accuracy may degrade in exactly the industrial cases (stalled airfoils, bluff bodies) where IBM is most attractive.
  • The method is validated within a lattice Boltzmann solver, but the authors note it can be extended to Navier-Stokes solvers; whether the one-sided spreading and stress-coupling remain equally accurate on finite-volume or finite-difference discretizations with different numerical dissipation properties is an open question.
  • The airfoil test uses artificial tripping to trigger transition, which sidesteps the known difficulty of predicting laminar-to-turbulent transition in WMLES; the method's performance for natural transition or leading-edge laminar separation bubbles remains unassessed.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

1 major / 6 minor

Summary. This manuscript presents a wall-modeled large-eddy simulation (WMLES) approach built on a fully one-sided diffuse-interface immersed boundary method (FODIBM). The key contributions are: (1) a wall-shear-stress enforcement strategy (WS) that couples the wall-parallel IB forcing directly to the wall shear stress predicted by an explicit wall model, without introducing artificial parameters, and (2) a tau-model adapted from Tamaki and Kawai [22] that introduces a modeled turbulent shear-stress tensor to preserve the total shear-stress balance below the reference height. The method is validated in turbulent channel flow (Re_tau = 1000–10000) with both wall-aligned and wall-unaligned grids, and in flow over a NACA23012 airfoil at Re = 1.88×10^6. The FODIBM is shown to substantially outperform the conventional DIBM, particularly at low reference heights.

Significance. The paper addresses a genuine limitation of diffuse-interface IBMs for WMLES — namely, cross-boundary diffusion that contaminates near-wall flow and degrades wall-shear-stress prediction. The WS coupling (Eq. 42) is parameter-free and well-motivated. The validation is thorough: grid convergence (Table 3), reference height sensitivity (Table 4), inclination angle robustness (Table 5), Reynolds number dependence (Table 6), and a direct DIBM–FODIBM comparison (Tables 7–8). The channel flow results are strong, with skin-friction coefficient errors below 1% for the WS+tau-model at Re_tau = 5200. The airfoil case provides a relevant industrial test case with lift coefficient errors below 5%. The tau-model is adapted from an independent reference [22], grounding the central claim externally rather than circularly.

major comments (1)
  1. §2.4.3, Eqs. (51)–(53): The tau-model relies on two equilibrium assumptions — constant total shear stress in the inner layer (Eq. 51) and a linear profile of modeled turbulent shear stress from tau_w at the wall to zero at the reference height (Eq. 49/50). Both are standard limitations of equilibrium wall models, and the paper explicitly lists separated flows as future work. However, the airfoil validation (§3.2) at alpha=6.2° is also an attached flow, so neither assumption is tested in non-equilibrium conditions. This is a genuine scope limitation rather than an internal inconsistency, but it should be stated more explicitly in the conclusions or the airfoil discussion. As written, the reader may infer broader applicability than is demonstrated. A brief sentence acknowledging that the airfoil case does not exercise the tau-model under adverse pressure gradients or incipient separation,
minor comments (6)
  1. §2.4.2, Eq. (42): The statement that the reciprocity condition is 'no longer required' for the wall-parallel momentum forcing is stated without detailed justification. A brief remark on why the velocity boundary-condition error framework does not apply when the forcing is stress-linked would improve clarity.
  2. §3.2: The tripping parameters (A_t=0.25, delta*_0=2.4*delta_x) are calibrated for this case. The sensitivity of the results to these parameters is not reported. A brief comment on robustness to tripping parameters would strengthen the airfoil validation.
  3. Table 7: The theoretical bulk velocity of 24.85 is described as obtained from 'an empirical formula' but the specific formula or reference is not cited. Please clarify.
  4. Figures 4–9: The axis labels and legends are small and difficult to read. Consider enlarging for the final version.
  5. §2.4.3, Eq. (49): The blending function f_s is described as a 'simple linear form' adopted 'for convenience.' It would help to note that alternative forms (e.g., tanh-based) were not tested, so the sensitivity to this choice is unknown.
  6. Reference [38] is cited as 'J. Comput. Phys. (2026) 114721' — please verify this is published or in press at the time of submission.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the careful reading and the positive assessment. The referee raises one major comment regarding the scope limitation of the tau-model validation, specifically that the airfoil case at α=6.2° is an attached flow and does not exercise the equilibrium assumptions under non-equilibrium conditions. We agree this should be stated more explicitly.

read point-by-point responses

  1. Referee: §2.4.3, Eqs. (51)–(53): The tau-model relies on two equilibrium assumptions — constant total shear stress in the inner layer (Eq. 51) and a linear profile of modeled turbulent shear stress from τ_w at the wall to zero at the reference height (Eq. 49/50). Both are standard limitations of equilibrium wall models, and the paper explicitly lists separated flows as future work. However, the airfoil validation (§3.2) at α=6.2° is also an attached flow, so neither assumption is tested in non-equilibrium conditions. This is a genuine scope limitation rather than an internal inconsistency, but it should be stated more explicitly in the conclusions or the airfoil discussion. As written, the reader may infer broader applicability than is demonstrated. A brief sentence acknowledging that the airfoil case does not exercise the tau-model under adverse pressure gradients or incipient separation.

    Authors: We fully agree with this observation. The airfoil case at α=6.2° is indeed an attached-flow configuration, and the tau-model's equilibrium assumptions — constant total shear stress in the inner layer and the linear profile of the modeled turbulent shear stress — are not tested under adverse pressure gradients or incipient separation. We will add an explicit statement in both the airfoil discussion (§3.2) and the conclusions (§4) acknowledging this scope limitation. Specifically, we will note that the NACA23012 case at α=6.2° does not exercise the tau-model under non-equilibrium conditions, and that validation under adverse pressure gradients and separated flows remains necessary future work. This is consistent with the existing mention of flow separation as future work in the conclusions, but we agree it should be stated more precisely in the airfoil section as well. revision: yes

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity; one standard self-citation to prior methodology that is independently published and not load-bearing for the central claim.

full rationale

The paper's derivation chain is self-contained against external benchmarks. The FODIBM formulation (Eqs. 22–25) cites the authors' prior work [38] (Mao et al., J. Comput. Phys. 2026) for the derivation of the scaling factor ϕ_l and improved Lagrangian weight W_l, but this is a published, independently verifiable derivation — not an unverified self-citation chain. The WS coupling (Eq. 42) is derived in the present paper from the integral constraint (Eq. 37) in a parameter-free manner. The explicit wall model (Eqs. 33–36) uses standard blending constants (κ=0.41, E=11.27) adopted from Cai et al. [27], an independent reference. The tau-model (Eqs. 49–54) is adapted from Tamaki and Kawai [22] (independent) with a mixing-length closure from Baldwin-Lomax [49] (independent); the linear stress-profile assumption (Eq. 49) is openly stated as a modeling choice, not presented as a derived result. All validation cases compare against independent DNS data (Lee and Moser [51], Oberlack et al. [53]) and experimental data (Broeren et al. [55]). No step in the derivation reduces to its own inputs by construction, and no 'prediction' is a renamed fit. The single self-citation to [38] is standard methodological referencing and does not raise the circularity score beyond a minor 1.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The paper introduces no new physical entities, particles, forces, or dimensions. All modeled quantities (tau_model, mu_RANS, eddy viscosity) are standard turbulence modeling constructs. The FODIBM is a numerical method, not a new physical entity. The free parameters are either standard values from the literature (kappa, Cs, wall model constants) or empirically chosen for the tripping strategy (At, delta*_0). The linear tau_model profile assumption is the most significant ad hoc element.

free parameters (6)
  • Smagorinsky constant Cs = standard (Cs~0.1, C~2.5*Cs^2)
    Used in the Vreman SGS model (Eq. 9). Standard value from the literature, not fitted to the present results.
  • Wall model constants (s, p, E, kappa) = s=180.8, p=0.789, E=11.27, kappa=0.41
    Constants in the blended wall model (Eq. 33). Standard values from Cai et al. [27], not fitted to the present results.
  • Tripping force amplitude At = 0.25
    Amplitude of the artificial tripping force for the NACA23012 case (Section 3.2). Chosen empirically; not derived.
  • Tripping displacement thickness delta*_0 = 2.4*dx
    Set to 2.4*dx for the tripping strategy (Section 3.2) because the actual Blasius displacement thickness is too small relative to grid resolution. Ad hoc choice.
  • Hybrid recursive collision parameter tau = 0.98
    Weighting free parameter in the hybrid recursive collision model (Eq. A.7). Set to 0.98 following Jacob et al. [57].
  • Delta function radius d = 2
    Radius of the regularized delta function (Eq. 27). Standard choice for 4-point stencil.
assumptions (5)
  • domain assumption The total shear stress is approximately constant and equal to the wall shear stress in the near-wall region of a turbulent boundary layer.
    Invoked in Eq. (44) and Eq. (51) to justify the shear-stress balance and the tau-model formulation. Standard boundary layer assumption, valid for equilibrium flows but questionable in strong pressure gradients or separated flows.
  • ad hoc to paper The profile of the modeled turbulent shear stress (tau_model) is linear between the wall and the reference height.
    Stated in Section 2.4.3: 'the profile of tau_model_xi_eta between the wall and the reference height is assumed to be linear, following the study of Tamaki and Kawai [22].' This is a modeling assumption not derived from first principles.
  • domain assumption The inertial terms and pressure gradient are negligible in the near-wall region.
    Invoked to simplify Eq. (43) to Eq. (44). Standard thin-shear-layer approximation, valid for attached boundary layers but not for separated or strongly accelerated flows.
  • domain assumption The velocity gradient at the reference point can be approximated by the local gradient under the assumption of a linear velocity profile below the reference height.
    Used in deriving Eq. (53) from Eq. (52). The linear profile assumption below the reference height is a standard wall-model approximation.
  • domain assumption The isotropic contribution of the SGS stress tensor is negligible except near shocks.
    Stated after Eq. (8): 'The isotropic contribution is neglected, as it becomes significant only in the vicinity of shocks.' Standard for low-Mach LES.

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Pith. "Pith review of A fully one-sided diffuse-interface immersed boundary method for wall-modeled large-eddy simulation." pith.science (2026). https://pith.science/paper/SJPLSI5U

@misc{pith2026260707443,
  author       = {Pith},
  title        = {Pith review of: A fully one-sided diffuse-interface immersed boundary method for wall-modeled large-eddy simulation},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/SJPLSI5U}},
  note         = {Machine review of arXiv:2607.07443}
}
read the original abstract

Diffuse-interface immersed boundary methods (DIBMs) provide a simple and robust approach for simulating flows involving complex geometries. However, their inherent diffusion effect can contaminate the near-wall flow field and significantly degrade wall-shear-stress prediction in wall-modeled large-eddy simulation (WMLES). To address this limitation, we develop a WMLES approach based on a fully one-sided diffuse-interface immersed boundary method (FODIBM). By performing interpolation and spreading exclusively inside the immersed body, the proposed method removes the cross-boundary diffusion effect that adversely affects wall modeling in conventional DIBMs. A wall-shear-stress enforcement strategy is developed by coupling the wall-parallel immersed-boundary forcing with the wall shear stress predicted by an explicit wall model. In addition, a tau-model based on the modeled turbulent shear-stress tensor is introduced to preserve the total shear-stress balance below the reference height. The method is first validated in high-Reynolds-number turbulent channel flows, showing good agreement with DNS data for the mean velocity, Reynolds shear stress, and skin-friction coefficient. Sensitivity studies with respect to grid resolution, reference height, wall inclination angle, and Reynolds number demonstrate the robustness of the method. Compared with the conventional DIBM, the proposed method substantially improves the overall prediction accuracy, particularly at low reference heights. The approach is further assessed for turbulent flow over a NACA23012 airfoil, where the predicted pressure distribution and lift coefficient agree well with experimental data.

Figures

Figures reproduced from arXiv: 2607.07443 by the authors.

Figure 1
Figure 1. Schematic of the DIBM and FODIBM. Each boundary point is associated with [PITH_FULL_IMAGE:figures/full_fig_p009_1.png] view at source ↗
Figure 2
Figure 2. Schematic of the shear-stress balance. in [PITH_FULL_IMAGE:figures/full_fig_p013_2.png] view at source ↗
Figure 3
Figure 3. Visualization of the computational domain for turbulent channel flow using (a) [PITH_FULL_IMAGE:figures/full_fig_p019_3.png] view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: Comparison of different wall-modeling strategies. (a) Mean wall-parallel velocity [PITH_FULL_IMAGE:figures/full_fig_p021_4.png]
Figure 5
Figure 5. Figure 5: Grid convergence test (∆x). (a) Mean wall-parallel velocity in wall-viscous units and (b) Reynolds shear stress (FODIBM, WS+τ -model, Reτ = 5200, θ0 = 30◦ , dref = 3∆x). Cf (×10−3 ) ∆ϵ (%) Lee and Moser (DNS) 3.442 - Present ∆x = H/8 3.332 3.19 Present H/16 3.493 1.48 …
Figure 6
Figure 6. Figure 6: Effect of the reference height (dref). (a) Mean wall-parallel velocity in wall￾viscous units and (b) Reynolds shear stress (FODIBM, WS+τ -model, Reτ = 5200, θ0 = 30◦ , ∆x = H/32). Cf (×10−3 ) ∆ϵ (%) Lee and Moser (DNS) 3.442 - Present dref = 2.0∆x 3.313 3.75 Present 2.…
Figure 7
Figure 7. Figure 7: Effect of the inclination angle (θ0). (a) Mean wall-parallel velocity in wall-viscous units and (b) Reynolds shear stress (FODIBM, WS+τ -model, Reτ = 5200, dref = 3∆x, ∆x = H/32). Cf (×10−3 ) ∆ϵ (%) Lee and Moser (DNS) 3.442 - Present θ0 = 0◦ 3.445 0.08 Present 30◦ 3.4…
Figure 8
Figure 8. Figure 8: Reynolds number dependence (Reτ ). (a) Mean wall-parallel velocity in wall￾viscous units and (b) Reynolds shear stress (FODIBM, WS+τ -model, θ0 = 30◦ , dref = 3∆x, ∆x = H/32). 26 [PITH_FULL_IMAGE:figures/full_fig_p026_8.png]
Figure 9
Figure 9. Figure 9: Effect of the reference height (dref) in DIBM. (a) Mean wall-parallel velocity in wall-viscous units and (b) Reynolds shear stress for different reference height (WS+τ - model, Reτ = 5200, θ0 = 30◦ , ∆x = H/32). dependence of the present method. As shown in [PITH_FULL…
Figure 10
Figure 10. Figure 10: Visualization of the computational mesh in the vicinity of the NACA23012 [PITH_FULL_IMAGE:figures/full_fig_p029_10.png]
Figure 11
Figure 11. Figure 11: Distributions of (a) pressure coefficient [PITH_FULL_IMAGE:figures/full_fig_p031_11.png]
Figure 12
Figure 12. Figure 12: Isosurfaces of the Q-criterion (Qc2/u2 ∞ = 1000) colored by velocity magnitude for (a) the fine grid with tripping, (b) the coarse grid with tripping, and (c) the coarse grid without tripping. 32 [PITH_FULL_IMAGE:figures/full_fig_p032_12.png]

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Works this paper leans on

57 extracted references · 57 canonical work pages

  1. [22]

    Tamaki, S

    Y. Tamaki, S. Kawai, Wall modeling for large-eddy simulation on non- body-conforming Cartesian grids, Phys. Rev. Fluids 6 (2021) 114603

    work page 2021

  2. [1]

    Piomelli, Wall-layer models for large-eddy simulations, Prog

    U. Piomelli, Wall-layer models for large-eddy simulations, Prog. Aero- naut. Sci. 44 (2008) 437–446

    work page 2008

  3. [2]

    S. T. Bose, G. I. Park, Wall-modeled large-eddy simulation for complex turbulent flows, Annu. Rev. Fluid Mech. 50 (2018) 535–561

    work page 2018

  4. [3]

    Mittal, G

    R. Mittal, G. Iaccarino, Immersed boundary methods, Annu. Rev. Fluid Mech. 37 (2005) 239–261

    work page 2005

  5. [4]

    Peskin, Flow patterns around hear valves: A numerical method, J

    C. Peskin, Flow patterns around hear valves: A numerical method, J. Comput. Phys. 10 (1972) 252–271

    work page 1972

  6. [5]

    C. S. Peskin, The immersed boundary method, Acta Numer. 11 (2002) 479–517

    work page 2002

  7. [6]

    Q. Mao, Y. Liu, H. J. Sung, Snap-through dynamics of a buckled flexible filament in a uniform flow, J. Fluid Mech. 969 (2023) A33

    work page 2023

  8. [7]

    Q. Mao, U. D’Ortona, J. Favier, Hydrodynamic coupling of a cilia– mucus system in herschel–bulkley flows, J. Fluid Mech. 994 (2024) A8. 39

    work page 2024

Show all 57 references
  1. [8]

    Huang, C

    W. Huang, C. Chang, H. Sung, An improved penalty immersed bound- ary method for fluid–flexible body interaction, J. Comput. Phys. 230 (2011) 5061–5079

    2011

  2. [9]

    Q. Mao, J. Zhao, Y. Liu, H. J. Sung, Hydrodynamic benefits of protrud- ing eyes and mouth in a self-propelled flexible stingray, Phys. Fluids. 33 (2021)

    2021

  3. [10]

    Pinelli, I

    A. Pinelli, I. Naqavi, U. Piomelli, J. Favier, Immersed-boundary meth- ods for general finite-difference and finite-volume Navier–Stokes solvers, J. Comput. Phys. 229 (2010) 9073–9091

    2010

  4. [11]

    Q. Mao, U. D’Ortona, J. Favier, Fluid transport by a single active filament in a three-dimensional two-phase flow, Phys. Rev. Fluids 11 (2026) 013102

    2026

  5. [12]

    K. Luo, Z. Wang, J. Fan, K. Cen, Full-scale solutions to particle-laden flows: Multidirect forcing and immersed boundary method, Phys. Rev. E 76 (2007) 066709

    2007

  6. [13]

    Zhang, G

    Y. Zhang, G. Pan, Y. Zhang, S. Haeri, A relaxed multi-direct-forcing immersed boundary-cascaded lattice Boltzmann method accelerated on GPU, Comput. Phys. Commun. 248 (2020) 106980

    2020

  7. [14]

    Mittal, H

    R. Mittal, H. Dong, M. Bozkurttas, F. Najjar, A. Vargas, A. V. Loebbecke, A versatile sharp interface immersed boundary method for incompressible flows with complex boundaries, J. Comput. Phys. 227 (2008) 4825–4852

    2008

  8. [15]

    A. Jost, S. Glockner, Direct forcing immersed boundary methods: Im- provements to the ghost-cell method, J. Comput. Phys. 438 (2021) 110371

    2021

  9. [16]

    Ingram, D

    D. Ingram, D. Causon, C. Mingham, Developments in Cartesian cut cell methods, Math. Comput. Simul. 61 (2003) 561–572

    2003

  10. [17]

    Schneiders, D

    L. Schneiders, D. Hartmann, M. Meinke, W. Schröder, An accurate moving boundary formulation in cut-cell methods, J. Comput. Phys. 235 (2013) 786–809. 40

    2013

  11. [18]

    Li, An overview of the immersed interface method and its applica- tions, Taiwan

    Z. Li, An overview of the immersed interface method and its applica- tions, Taiwan. J. Math. 7 (2003) 1–49

    2003

  12. [19]

    Brehm, H

    C. Brehm, H. Fasel, A novel concept for the design of immersed interface methods, J. Comput. Phys. 242 (2013) 234–267

    2013

  13. [20]

    J. H. Seo, R. Mittal, A sharp-interface immersed boundary method with improved mass conservation and reduced spurious pressure oscillations, J. Comput. Phys. 230 (2011) 7347–7363

    2011

  14. [21]

    S.-G. Cai, J. Degrigny, J.-F. Boussuge, P. Sagaut, Coupling of tur- bulence wall models and immersed boundaries on Cartesian grids, J. Comput. Phys. 429 (2021) 109995

    2021

  15. [23]

    Z. L. Chen, S. Hickel, A. Devesa, J. Berland, N. A. Adams, Wall model- ing for implicit large-eddy simulation and immersed-interface methods, Theor. Comput. Fluid Dyn. 28 (2014) 1–21

    2014

  16. [24]

    Roman, V

    F. Roman, V. Armenio, J. Fröhlich, A simple wall-layer model for large eddy simulation with immersed boundary method, Phys. Fluids 21 (2009)

    2009

  17. [25]

    L. Wang, Z. Liu, B. R. Jin, Q. Huang, J. Young, F.-B. Tian, Wall- modeled large eddy simulation in the immersed boundary-lattice Boltz- mann method, Phys. Fluids 36 (2024)

    2024

  18. [26]

    van Noordt, S

    W. van Noordt, S. Ganju, C. Brehm, An immersed boundary method for wall-modeled large-eddy simulation of turbulent high-Mach-number flows, J. Comput. Phys. 470 (2022) 111583

    2022

  19. [27]

    S.-G. Cai, J. Jacob, P. Sagaut, Immersed boundary based near-wall modelingforlargeeddysimulationofturbulentwall-boundedflow, Com- put. Fluids 259 (2023) 105893

    2023

  20. [28]

    De Vanna, G

    F. De Vanna, G. Baldan, F. Picano, E. Benini, On the coupling between wall-modeled LES and immersed boundary method towards applicative compressible flow simulations, Comput. Fluids 266 (2023) 106058. 41

    2023

  21. [29]

    Capizzano, Turbulent wall model for immersed boundary methods, AIAA J

    F. Capizzano, Turbulent wall model for immersed boundary methods, AIAA J. 49 (2011) 2367–2381

    2011

  22. [30]

    Tamaki, M

    Y. Tamaki, M. Harada, T. Imamura, Near-wall modification of Spalart– Allmaras turbulence model for immersed boundary method, AIAA J. 55 (2017) 3027–3039

    2017

  23. [31]

    Tamaki, S

    Y. Tamaki, S. Kawai, Wall-modeled large-eddy simulation of transonic buffet over NASA-CRM using FFVHC-ACE, AIAA J. 62 (2024) 2489– 2504

    2024

  24. [32]

    Cheylan, J

    I. Cheylan, J. Favier, P. Sagaut, Immersed boundary conditions for moving objects in turbulent flows with the lattice-Boltzmann method, Phys. Fluids 33 (2021)

    2021

  25. [33]

    K. Yan, Y. Wu, Q. Zhu, Y. Cui, B. C. Khoo, Efficient wall-modeling diffused-interfaceimmersedboundarymethodforsolvingturbulentflows with high-order finite difference schemes, Phys. Fluids 36 (2024)

    2024

  26. [34]

    B. Shi, X. Yang, G. Jin, G. He, S. Wang, Wall-modeling for large- eddy simulation of flows around an axisymmetric body using the diffuse- interface immersed boundary method, Appl. Math. Mech. 40 (2019) 305–320

    2019

  27. [35]

    Ma, W.-X

    M. Ma, W.-X. Huang, C.-X. Xu, A dynamic wall model for large eddy simulation of turbulent flow over complex/moving boundaries based on the immersed boundary method, Phys. Fluids 31 (2019)

    2019

  28. [36]

    B. Shi, Z. Xu, S. Wang, A non-equilibrium slip wall model for large-eddy simulation with an immersed boundary method, AIP Adv. 12 (2022)

    2022

  29. [37]

    Ma, W.-X

    M. Ma, W.-X. Huang, C.-X. Xu, G.-X. Cui, A hybrid immersed boundary/wall-model approach for large-eddy simulation of high- Reynolds-number turbulent flows, Int. J. Heat Fluid Flow 88 (2021) 108769

    2021

  30. [38]

    Q. Mao, J. E. C. Cabezas, S. Zhao, P. Boivin, J. Favier, An explicit fully one-sided diffuse-interface immersed boundary method for compressible flows, J. Comput. Phys. (2026) 114721. 42

    2026

  31. [39]

    Farag, T

    G. Farag, T. Coratger, G. Wissocq, S. Zhao, P. Boivin, P. Sagaut, A unified hybrid lattice-Boltzmann method for compressible flows: Bridg- ing between pressure-based and density-based methods, Phys. Fluids 33 (2021)

    2021

  32. [40]

    Wissocq, T

    G. Wissocq, T. Coratger, G. Farag, S. Zhao, P. Boivin, P. Sagaut, Restoring the conservativity of characteristic-based segregated models: Application to the hybrid lattice Boltzmann method, Phys. Fluids 34 (2022)

    2022

  33. [41]

    E.Garnier, N.Adams, P.Sagaut, Largeeddysimulationforcompressible flows, Springer Science & Business Media, 2009

    2009

  34. [42]

    Vreman, An eddy-viscosity subgrid-scale model for turbulent shear flow: Algebraic theory and applications, Phys

    A. Vreman, An eddy-viscosity subgrid-scale model for turbulent shear flow: Algebraic theory and applications, Phys. Fluids 16 (2004) 3670– 3681

    2004

  35. [43]

    Gsell, J

    S. Gsell, J. Favier, Direct-forcing immersed-boundary method: A simple correction preventing boundary slip error, J. Comput. Phys. 435 (2021) 110265

    2021

  36. [44]

    Cheylan, T

    I. Cheylan, T. Fringand, J. Jacob, J. Favier, Analysis of the immersed boundary method for turbulent fluid-structure interaction with lattice Boltzmann method, J. Comput. Phys. 492 (2023) 112418

    2023

  37. [45]

    Lerogeron, P

    H. Lerogeron, P. Boivin, V. Faucher, J. Favier, A numerical framework for fast transient compressible flows using lattice Boltzmann and im- mersed boundary methods, Int. J. Numer. Methods Eng. 126 (2025) e7647

    2025

  38. [46]

    Davidson, M

    L. Davidson, M. Billson, Hybrid LES-RANS using synthesized turbulent fluctuations for forcing in the interface region, Int. J. Heat Fluid Flow 27 (2006) 1028–1042

    2006

  39. [47]

    Davidson, S.-H

    L. Davidson, S.-H. Peng, Hybrid LES-RANS modelling: a one-equation SGS model combined with ak–ωmodel for predicting recirculating flows, Int. J. Numer. Methods Fluids 43 (2003) 1003–1018

    2003

  40. [48]

    Hamba, A hybrid RANS/LES simulation of turbulent channel flow, Theor

    F. Hamba, A hybrid RANS/LES simulation of turbulent channel flow, Theor. Comput. Fluid Dyn. 16 (2003) 387–403. 43

    2003

  41. [49]

    Baldwin, H

    B. Baldwin, H. Lomax, Thin-layer approximation and algebraic model for separated turbulentflows, in: 16th aerospace sciences meeting, 1978, p. 257

    1978

  42. [50]

    R. B. Dean, Reynolds number dependence of skin friction and other bulk flow variables in two-dimensional rectangular duct flow, J. Fluids Eng. 100 (1978) 215–223

    1978

  43. [51]

    M. Lee, R. D. Moser, Direct numerical simulation of turbulent channel flow up toReτ = 5200, J. Fluid Mech. 774 (2015) 395–415

    2015

  44. [52]

    Kawai, J

    S. Kawai, J. Larsson, Wall-modeling in large eddy simulation: Length scales, grid resolution, and accuracy, Phys. Fluids 24 (2012)

    2012

  45. [53]

    Oberlack, S

    M. Oberlack, S. Hoyas, S. Kraheberger, F. Alcántara-Ávila, J. Laux, DNS channel dataRe tau = 10000high moments, https://doi.org/10.48328/tudatalib-670 (2021)

    2021 doi

  46. [54]

    Schlatter, R

    P. Schlatter, R. Örlü, Turbulent boundary layers at moderate Reynolds numbers: inflow length and tripping effects, J. Fluid Mech. 710 (2012) 5–34

    2012

  47. [55]

    A. P. Broeren, H. E. Addy, S. Lee, M. C. Monastero, Validation of 3-D ice accretion measurement methodology for experimental aerody- namic simulation, in: 6th AIAA Atmospheric and space environments conference, 2014, p. 2614

    2014

  48. [56]

    M. D. Hussain, A. D. Deshpande, C. Brehm, J. Larsson, Leading-edge treatments for wall-modeled large-eddy simulation of an airfoil, AIAA J. (2025) 1–14

    2025

  49. [57]

    Jacob, O

    J. Jacob, O. Malaspinas, P. Sagaut, A new hybrid recursive regularised Bhatnagar–Gross–Krook collision model for lattice Boltzmann method- based large eddy simulation, J. Turbul. 19 (2018) 1051–1076. 44

    2018

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