A Perspective on the State of Aerospace Computational Fluid Dynamics Technology

Mani, Mori; Dorgan, Andrew J.

doi:10.1146/annurev-fluid-120720-124800

Cited by 35 publications

(16 citation statements)

References 79 publications

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“…LPT method that applies triangulation and subsequent connection of particle positions gained from successive images predict flows and their features by computer simulations, such as for aerodynamical design purposes. At high Reynolds numbers, the resolution requirements in space and time and the nonlinearity of the flow physics involved pose many problems for numerical codes, regarding either the available computer resources or the validity and applicability of established turbulence models or scaling laws (Mani & Dorgan 2023). A very high degree of computational effort is already needed for predicting turbulent flows at moderate Reynolds numbers by direct numerical simulations (DNS).…”

Section: Particle Tracking Velocimetry (Ptv)mentioning

confidence: 99%

3D Lagrangian Particle Tracking in Fluid Mechanics

Schröder

Schanz

2023

Annu. Rev. Fluid Mech.

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In the past few decades various particle image–based volumetric flow measurement techniques have been developed that have demonstrated their potential in accessing unsteady flow properties quantitatively in various experimental applications in fluid mechanics. In this review, we focus on physical properties and circumstances of 3D particle–based measurements and what knowledge can be used for advancing reconstruction accuracy and spatial and temporal resolution, as well as completeness. The natural candidate for our focus is 3D Lagrangian particle tracking (LPT), which allows for position, velocity, and acceleration to be determined alongside a large number of individual particle tracks in the investigated volume. The advent of the dense 3D LPT technique Shake-The-Box in the past decade has opened further possibilities for characterizing unsteady flows by delivering input data for powerful data assimilation techniques that use Navier–Stokes constraints. As a result, high-resolution Lagrangian and Eulerian data can be obtained, including long particle trajectories embedded in time-resolved 3D velocity and pressure fields. Expected final online publication date for the Annual Review of Fluid Mechanics, Volume 55 is January 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Section: Particle Tracking Velocimetry (Ptv)mentioning

confidence: 99%

3D Lagrangian Particle Tracking in Fluid Mechanics

Schröder

Schanz

2023

Annu. Rev. Fluid Mech.

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“…The combined effect of an adverse pressure gradient (APG) and viscosity can cause flow separation. Flow separation can cause significant changes in flow properties and interfere with the force prediction of objects in engineering practice (Mani & Dorgan 2023). Studying APG turbulent boundary layers (TBLs) can elucidate the behaviour of TBLs before flow separation.…”

Section: Introductionmentioning

confidence: 99%

Consistent outer scaling and analysis of adverse pressure gradient turbulent boundary layers

Han,

Ma,

Yan

2024

J. Fluid Mech.

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Under adverse pressure gradient (APG) conditions, the outer regions of turbulent boundary layers (TBLs) are characterized by an increased velocity defect $U_{e}-U$ , an outwards shift of the peak value of the Reynolds shear stress $-\langle uv\rangle$ and an appearance of the outer peak value of the Reynolds normal stress $\langle uu\rangle$ . Here $U_{e}$ is the TBL edge velocity. Scaling APG TBLs is challenging due to the non-equilibrium effects caused by changes in the APG. To address this, the response distance of TBLs to non-equilibrium conditions is utilized to extend the Zagarola–Smits scaling $U_{zs} = U_{e}({\delta ^{*} }/{\delta })$ and ensure that the original properties of the Zagarola–Smits scaling are maintained as $Re \to \infty$ . Here $\delta ^{*}$ is the displacement thickness and $\delta$ is the boundary layer thickness. Based on the established correlation between $U_{e}-U$ and $-\langle uv\rangle$ , the scaling is extended to $-\langle uv\rangle$ . Furthermore, considering the coupling relationship between Reynolds stress components, the scaling is extended to encompass each Reynolds stress component. The proposed consistent scaling is verified using five non-equilibrium databases and five near-equilibrium databases, successfully collapsing the data of the TBL outer region. The pressure gradient parameter $\beta =({\delta ^{*} }/{\rho u_{\tau }^{2} }) ({\mathrm {d} P_{e} }/{\mathrm {d}\kern0.7pt x})$ of these databases spans two orders of magnitude. Here $P_{e}$ is the boundary layer edge pressure, $u_{\tau }$ is the friction velocity and $\rho$ is the density. Finally, the influence of the APG on the inner and outer regions of TBLs is analysed using the mean momentum balance equation. The analysis suggests that the shift of the $-\langle uv\rangle$ peak to the outer region under APG conditions is due to an insufficient inertia term near the inner region to balance the APG. It is observed that the APG promotes interaction between the inner and outer regions of TBLs, but the inner and outer regions still retain distinctive properties.

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“…In fact, the airfoil flow is inevitable in the design and application of all kinds of aircraft, wind and hydroelectric generators, aeronautical and marine propellers, etc For the flow field of flow around airfoil, there are complex flow phenomena such as reverse pressure gradient, vortex flow, and curvature flow [1][2][3]. Since 1970s, the RANS method has gradually become the mainstream method for solving the N-S equations in practical engineering applications [4]. Turbulence models such as the one-equation model (S-A) and the two-equation model (k-ε, MENTER SST) have since been developed [5,6].…”

Section: Introductionmentioning

confidence: 99%

Implementation of a PAFV turbulence model for airfoil flow simulation on OpenFOAM

Yan,

Sun,

Sun

et al. 2024

Phys. Scr.

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To further develop a more effective turbulence model and to improve the calculation accuracy of the flow around airfoil, a new PAFV turbulence model has here been constructed by using a deformation rate tensor and the grouping of an average fluctuation velocity. To evaluate the applicability of the PAFV turbulence model, the numerical calculations of flow around the airfoil have here been implemented, which was based on the OpenFOAM calculation platform. On the basis of grid independence research, the model was used to calculate the low-speed flow-around problem for the plano-convex airfoil NACA4412 and the symmetric airfoil NACA0012. It was also compared with the S-A (Spalart-Allmaras) and SST (Shear Stress Transport) k-ω turbulence models. Firstly, the maximum lift angle-of-attack case of the NACA4412 airfoil was calculated. Thereafter, numerical calculations were performed for the flow around the airfoil in the multi-angle-of-attack case of NACA0012 airfoil. The results showed that the NACA4412 airfoil had an obviously separated vortex at the trailing edge of the airfoil at the maximum lift angle of attack. Also, there was a certain velocity loss downstream of the trailing edge, as was calculated by all three models. However, the results of the PAFV turbulence model were found to be better than those of the S-A and SST turbulence models. The three turbulence models showed comparable accuracies for the calculations of the surface pressure coefficients of the NACA0012 airfoil. However, the S-A and SST k-ω turbulence models were slightly better for the calculations of the mean velocity profiles of the NACA0012 airfoil. Also, the PAFV turbulence model was more accurate for the calculations of the lift and drag coefficients. In conclusion, the PAFV model can make effective predictions for the airfoil low-speed flow around the problem at hand, which in turn preliminarily verifies the applicability of this turbulence model for the low-speed flow around airfoil problems.

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A Perspective on the State of Aerospace Computational Fluid Dynamics Technology

Cited by 35 publications

References 79 publications

3D Lagrangian Particle Tracking in Fluid Mechanics

3D Lagrangian Particle Tracking in Fluid Mechanics

Consistent outer scaling and analysis of adverse pressure gradient turbulent boundary layers

Implementation of a PAFV turbulence model for airfoil flow simulation on OpenFOAM

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