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The role of compressibility and vibrational excitation in hypersonic shock–turbulence interactions

Published online by Cambridge University Press:  27 March 2026

Alberto Cuadra*
Affiliation:
Departamento de Ingeniería Térmica y de Fluidos, Escuela Politécnica Superior, Universidad Carlos III de Madrid , 28911 Leganés, Spain
Christopher Williams
Affiliation:
Center for Turbulence Research, Stanford University, Stanford 94305, USA
Mario Di Renzo
Affiliation:
Center for Turbulence Research, Stanford University, Stanford 94305, USA Department of Engineering for Innovation, University of Salento, Lecce 73100, Italy
César Huete
Affiliation:
Departamento de Ingeniería Térmica y de Fluidos, Escuela Politécnica Superior, Universidad Carlos III de Madrid , 28911 Leganés, Spain
*
Corresponding author: Alberto Cuadra, acuadra@ing.uc3m.es

Abstract

The interaction between turbulence and shock waves significantly modulates the frequency and amplitude of hydrodynamic fluctuations experienced by aerospace vehicles during low-altitude hypersonic flight. In these high-speed flows, intrinsic compressibility effects arise alongside high-enthalpy phenomena manifested through internal-energy excitation. The present study compares direct numerical simulation and linear interaction analysis (LIA) to characterise the influence of solenoidal and dilatational fluctuations, as well as endothermic processes, on a Mach 5 canonical shock–turbulence interaction (STI). Whilst the computational approach involves directly resolving all relevant length scales and potential nonlinear interactions, the LIA framework models the upstream compressible turbulence as a superposition of weakly vortical, entropic and acoustic fluctuations, with the thermal non-equilibrium thickness assumed to be much thinner than the turbulence scales. Both the numerical and theoretical methods reveal that increasing upstream compressibility enhances the turbulent kinetic energy (TKE) across the STI for varying turbulent Mach numbers. The effect of vibrational excitation is shown to further amplify the TKE downstream of the shock. The influence of upstream dilatational disturbances on the postshock turbulent spectra is also analysed, and an improved LIA-based estimate of the Kolmogorov length scale across the shock is obtained.

Information

Type
JFM Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press
Figure 0

Figure 1. Sketch of the interaction of a planar shock wave with an isotropic vorticity–entropy–acoustic field in air at Mach 5, representative of the hypersonic regime. Velocities are presented in the shock reference frame. The variables $u_1$ and $u_2$ denote the bulk flow velocities upstream and downstream of the shock, $\xi_s$ the shock displacement, $\ell$ the characteristic turbulence length scale, and $\ell_T$ the thermochemical non-equilibrium length scale.

Figure 1

Figure 2. Inverse normalised RH-slope parameters as a function of the upstream Mach number $\mathcal{M}_1$ for normal shocks propagating in air at $T_1 = 300$ K and $p_1 = 1$ atm.

Figure 2

Figure 3. Far-field TKE amplification ratio $K$ (a) and its acoustic contribution $K_a$ (b) predicted by LIA as a function of the preshock Mach number $\mathcal{M}_1$ for different intensities of dilatational-to-solenoidal TKE $\eta$. The calculations are provided for the thermally perfect (solid lines) and calorically perfect (dashed lines) models.

Figure 3

Figure 4. Far-field streamwise $K_L$ (a) and transverse $K_T$ (b) components of the TKE amplification ratio predicted by LIA as a function of the preshock Mach number $\mathcal{M}_1$ for different intensities of dilatational-to-solenoidal TKE $\eta$. The calculations are provided for the thermally perfect (solid lines) and calorically perfect (dashed lines) models.

Figure 4

Figure 5. Schematic of the computational set-up showcasing three-dimensional isotropic turbulence generated by a triply periodic box and advecting at a mean Mach number $\mathcal{M}_1$ toward the STI domain.

Figure 5

Table 1. Summary of the numerical simulation set-up for the HIT generator.

Figure 6

Figure 6. Instantaneous slices from the three-dimensional HIT at $x = \pi$ plane, for different turbulent Mach numbers $\mathcal{M}_t = [0.2, 0.4]$ and dilatational-to-solenoidal TKE ratios $\eta = [0.05, 0.1]$, using the calorically perfect model (cases C1–C4). Panel (a) displays the vorticity magnitude, $|\boldsymbol{\nabla }\times \boldsymbol {v}|$, and panel (b) shows the velocity divergence, $\boldsymbol{\nabla }\boldsymbol{\cdot }\boldsymbol {v}$. Colour-bar limits are set by the 99th percentile of the corresponding field in case C4, to highlight the growing intensity and spatial intermittency of turbulent structures with increasing $\mathcal{M}_t$ and $\eta$.

Figure 7

Figure 7. Normalised probability density distributions (p.d.f.s) of vorticity $\varpi / \varpi _{\textit{rms}}$ (a) and velocity divergence $\vartheta / \vartheta _{\textit{rms}}$ (b) for different turbulent Mach numbers $\mathcal{M}_t = [0.2, 0.4]$, dilatational-to-solenoidal TKE ratio $\eta = [0.05, 0.1]$ and the caloric perfect model (cases C1–C4). Calculations were computed in the HIT domain and averaged over different snapshots.

Figure 8

Table 2. Comparison of postshock turbulence statistics from DNS and LIA. The DNS quantities $K$, $R_{11}$ and $R_{\textit{TT}}$ are evaluated at the local maximum of $R_{11}$, whereas $K^*$ denotes the TKE amplification extrapolated to infinite Reynolds number using (5.1). All cases are conducted at $\mathcal{M}_1 = 5$ and ${Re}_\lambda = 40$. The parameters $\Delta \mathcal{Q}^{\textit{LIA}}$ denote the percentage differences between LIA and DNS statistics, where $\mathcal{Q} = K, R_{11}$ and $R_{\textit{TT}}$.

Figure 9

Figure 8. Panel (a) displays the distribution of the streamwise $R_{11}(x)$ component of the TKE amplification ratio for case C3. Panel (b) presents the instantaneous field of the vorticity magnitude $|\boldsymbol{\nabla }\times \boldsymbol {v}|$ in the $x$–$z$ plane. Both panels cover 50 % of the total streamwise domain. The simulation parameters are: preshock Mach number $\mathcal{M}_1 = 5$, turbulent Mach number $\mathcal{M}_t = 0.4$, Taylor-scale Reynolds number ${Re}_{\lambda } = 40$, dilatational-to-solenoidal TKE ratio $\eta = 0.05$ and calorically perfect model. The spatial coordinates are normalised with the Taylor microscale $\lambda$.

Figure 10

Figure 9. Evolution of the TKE amplification, $K$, for the C-series (upper panels) and G-series (lower panels) caloric models at two different turbulent Mach numbers: $\mathcal{M}_t=0.2$ (left panels) and $\mathcal{M}_t=0.4$ (right panels). The turbulent kinetic dilatational to solenoidal energy is varied in each panel for $\eta =0.05$ (dashed line) and $\eta =0.1$ (solid line). Panel (a) includes a case with $\eta = 0.001$ (dotted line).

Figure 11

Figure 10. Comparison of the C-series (dashed line) and G-series (solid line) caloric models for the evolution of TKE amplification, $K$, for $\eta =0.05$ (upper panels) and $\eta =0.1$ (lower panels) at two different turbulent Mach numbers: $\mathcal{M}_t=0.2$ (left panels) and $\mathcal{M}_t=0.4$ (right panels).

Figure 12

Figure 11. Evolution of the streamwise TKE amplification, $R_{11}$, for the C-series (upper panels) and G-series (lower panels) caloric models at two different turbulent Mach numbers: $\mathcal{M}_t=0.2$ (left panels) and $\mathcal{M}_t=0.4$ (right panels). The turbulent kinetic dilatational to solenoidal energy is varied in each panel for $\eta =0.05$ (dashed line) and $\eta =0.1$ (solid line).

Figure 13

Figure 12. Evolution of the transverse TKE amplification, $R_{\textit{TT}}$, for the C-series (upper panels) and G-series (lower panels) caloric models at two different turbulent Mach numbers: $\mathcal{M}_t=0.2$ (left panels) and $\mathcal{M}_t=0.4$ (right panels). The turbulent kinetic dilatational to solenoidal energy is varied in each panel for $\eta =0.05$ (dashed line) and $\eta =0.1$ (solid line).

Figure 14

Figure 13. Normalised one-dimensional power spectra of the kinetic energy in the HIT domain for two different turbulent Mach numbers: $\mathcal{M}_t = 0.2$ (left panels) and $\mathcal{M}_t = 0.4$ (right panels). Panels (a,b) show the normalised spectra for different values of $\eta$, while panels (c,d) show the decomposition of the spectra into solenoidal, dilatational, and total contributions at fixed $\eta = 0.1$. The dashed line represents the reference VK spectrum.

Figure 15

Figure 14. Normalised one-dimensional power spectra of the kinetic energy in the transverse directions for the C-series at preshock and far-field locations (see figure 9 for reference).

Figure 16

Figure 15. Normalised one-dimensional power spectra of the streamwise (a) and transverse (b) kinetic energy as a function of the transverse wavenumber for cases C3–C4 in the far field. The solid lines represent DNS results, while dashed lines denote LIA predictions.

Figure 17

Figure 16. Normalised Kolmogorov length scale ratio across the shock. Panel (a) shows the distribution of $\ell _{k} / \ell _{k,1}$ as a function of the normalised streamwise coordinate $\lambda ^{-1}(x - x_s)$. Panel (b) presents the postshock jump $\mathcal{L} = \ell _{k,2} / \ell _{k,1}$ against the upstream Mach number $\mathcal{M}_1$, with LIA predictions (black lines), RDT (grey lines), DNS data from Larsson et al. (2013) (triangles), DNS data from Grube & Martín (2023) (star) and the present simulations (circles), for both calorically perfect and thermally perfect assumptions. Solid and dashed lines correspond to Sutherland-law dynamic viscosity, while dotted lines assume a power-law scaling. Linear theory curves correspond to upstream dilatational-to-solenoidal TKE ratio of $\eta =0$.

Figure 18

Figure 17. Normalised one-dimensional power spectra of the kinetic energy in the transverse directions for the G-series at preshock and far-field locations (see figure 9 for reference).

Figure 19

Table 3. Grid-resolution metrics in the STI domain.

Figure 20

Figure 18. Normalised one-dimensional power spectra of the streamwise (left panels) and transverse (right panels) kinetic energy as a function of the transverse wavenumber for G-series in the far field. The solid lines represent DNS results, while dashed lines denote LIA predictions.

Figure 21

Figure 19. Comparison of the evolution of the TKE amplification $K$ obtained in this work with the DNS data of Larsson et al. (2013) for $\mathcal{M}_1 \approx 3.5$, $\mathcal{M}_t \approx 0.16$, ${Re}_\lambda \approx 40$ and $\eta \approx 0$.