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Maxwell–Cattaneo double-diffusive convection: the general case

Published online by Cambridge University Press:  30 March 2026

D.W. Hughes*
Affiliation:
School of Mathematics, University of Leeds , Leeds LS2 9JT, UK
M.R.E. Proctor
Affiliation:
DAMTP, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA, UK
I.A. Eltayeb
Affiliation:
Faculty of Mathematical Sciences and Informatics, University of Khartoum, POB 321, Khartoum, Sudan
*
Corresponding author: D.W. Hughes, d.w.hughes@leeds.ac.uk

Abstract

Double-diffusive convection, in which the density of a fluid is dependent on two fields that diffuse at different rates (such as temperature and salinity), has been widely studied in areas as diverse as the oceans and stellar atmospheres. Under the assumption of classical Fickian diffusion for both heat and salt, the evolution of temperature and salinity is governed by parabolic advection–diffusion equations. In reality, there are small additional terms in these equations that render them hyperbolic (the Maxwell–Cattaneo (M–C) effect). Although these corrections are nominally small, they represent a singular perturbation, and hence can lead to significant effects when the underlying differences of salinity and temperature are large. In an earlier paper (Hughes, Proctor & Eltayeb, J. Fluid Mech., vol. 927, 2021, p. A13), we investigated the linear stability of a double-diffusive fluid layer subject to the M–C effect in either the temperature or the salinity equation (but not both). Here we consider the general, and much more complicated, case in which the M–C effect influences both temperature and salinity. We find that, as in the earlier paper, oscillatory instability is indeed facilitated (and in fact made possible when the salinity gradient is destabilising, where the classical problem has no oscillatory instability) when the salinity gradients are sufficiently large. The scalings that emerge from the earlier paper, however, are not necessarily representative of those in the general case, thus justifying the present study. In addition, we have found a remarkable singular situation when the ratio of the M–C effects is equal to the ratio between the heat and salinity diffusivities, near which the critical wavenumber is sharply reduced. In addition to determining the stability boundaries we have also investigated the growth rates of unstable modes and shown that these are on a par with those of classical double-diffusive convection.

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Copyright
© The Author(s), 2026. Published by Cambridge University Press
Figure 0

Figure 1. (a–c) The real parts of the roots of (A6) for $k_s^2$ as a function of $\widetilde {Rs}$ for $ 0 \lt n \leqslant 1$; blue lines denote real roots, the red line denotes the real part of a conjugate pair; $\sigma = 1$, $\tau = 0.1$, with (a) $\lambda =-0.8$, (b) $\lambda =0$, (c) $\lambda =0.8$. (d–f) Corresponding plots of the oscillatory stability boundary (grey solid line), together with the zeroth-order asymptotic expression (A3) (magenta dashed line) and the first-order correction (A5) (magenta squares); for the numerical results, $\varGamma = 10^{-3}$, $Rs = 1.5 \times 10^4$ (corresponding to $\widetilde {Rs}=15$). For comparison, the cyan line shows ${\textit{Ra}}^{(o)}$ for the classical problem, given by (2.25).

Figure 1

Figure 2. Plots of $Ra^{(o)}$ versus $k^2$ for $\varGamma =10^{-3}$, $Rs=10^6$ ($n=2$), $\tau =0.5$. In (a–c), $\sigma = 10$, with (a) $\lambda =-0.8$ (black), $\lambda =-1$ (red); (b) $\lambda =0$; (c) $\lambda =0.8$ (black), $\lambda =1$ (red). In (d–f), $\sigma = 0.1$, with (d) $\lambda =-0.8$ (black), $\lambda =-1$ (red); (e) $\lambda =0$; ( f) $\lambda =0.8$ (black), $\lambda =1$ (red). The cyan lines show ${\textit{Ra}}^{(o)}$ for the classical problem, given by (2.25).

Figure 2

Figure 3. $\text{Plots of }Ra^{(o)}_c$, $k_c^2$ and $\omega _c^2$ versus $\lambda$ for $\varGamma =10^{-3}$, $Rs=10^6$ ($n=2$). In (a–c), $\sigma = 10$, $\tau =0.5$; in (d–f), $\sigma =0.1$, $\tau =0.5$; in (g–i), $\sigma =10$, $\tau =0.9$; in (j–l), $\sigma =0.1$, $\tau =0.9$. The blue dashed line shows ${\textit{Ra}}^{(o)}_c$ for the classical problem, given by (2.28).

Figure 3

Figure 4. $\text{Plots of }Ra^{(o)}_c$, $k_c^2$ and $\omega _c^2$ versus $\lambda$ for $\varGamma =10^{-3}$, $\sigma =1$, $\tau =0.5$. In (a–c), $Rs=10^9$ ($n=3$); in (d–f), $Rs=10^{12}$ ($n=4$); in (g–i), $Rs=10^{15}$ ($n=5$). The asymptotic results (3.11) are marked as dashed red lines.

Figure 4

Figure 5. $\text{Plots of }k_c^2$ versus $\lambda$, for a restricted range of $\lambda$, with $\varGamma =10^{-3}$, $\sigma =1$, $\tau =0.5$. In (a), $Rs=10^9$ ($n=3$); in (b), $Rs=10^{12}$ ($n=4$); in (c), $Rs=10^{15}$ ($n=5$). In (b) the asymptotic result (3.25) is marked as a red line.

Figure 5

Figure 6. $\text{Plots of }Ra^{(o)}$ versus $k^2$ with $\varGamma =10^{-3}$, $Rs=10^{12}$ ($n=4$), $\sigma =1$, $\tau =0.5$. In (a), $\lambda =-0.34$ (just to the left of the dip); in (b), $\lambda =-0.3335$ (in the middle of the dip); in (c), $\lambda =-0.33$ (just to the right of the dip).

Figure 6

Figure 7. $\text{Plots of }Ra^{(o)}_c$, $k_c^2$ and $\omega _c^2$ versus $\lambda$ for $\varGamma =10^{-3}$, $Rs=10^9$, $\sigma =1$, with $\tau =0.2$ (red), $\tau =0.5$ (black), $\tau =0.8$ (blue).

Figure 7

Figure 8. Surface plots of (a) ${\textit{Ra}}^{(o)}_c$ and (b) $k_c^2$ versus $\lambda$ and $\tau$ for $\varGamma =10^{-3}$, $Rs=10^9$, $\sigma =1$. The range $0.05 \leqslant \tau \leqslant 0.95$ is plotted.

Figure 8

Figure 9. $\text{Plots of }Ra^{(o)}_c$, $k_c^2$ and $\omega _c^2$ versus $\lambda$ for $\varGamma =10^{-3}$, $Rs=10^9$, $\tau =0.5$, with $\sigma =1$ (black), $\sigma =5$ (red), $\sigma =100$ (blue).

Figure 9

Figure 10. Surface plots of (a,c) ${\textit{Ra}}^{(o)}_c$ and (b,d) $k_c^2$ versus $\lambda$ and $\tau$ for $\varGamma =10^{-3}$, $Rs=10^9$. In (a,b), $\sigma =0.075$; in (c,d), $\sigma =0.01$. The range $0.05 \leqslant \tau \leqslant 0.95$ is plotted.

Figure 10

Figure 11. $\text{Plot of }\sigma$ versus $\lambda$ for the line ${\mathcal{L}}$, defined by (4.15), denoting the parameter values at which the loop of oscillatory solutions first appears on the steady branch. The curves show $\tau =0.9$ (top), $0.8$, $0.7$, $0.6$, $0.5$, $0.4$, $0.3$ (bottom).

Figure 11

Figure 12. Plots of $Ra$ versus $k^2$ for the steady (red) and oscillatory (blue) stability boundaries, with $\varGamma =10^{-4}$, $\sigma =0.2$, $\tau =0.5$, $\lambda =0.3$. In (a), $Rs=-10^9$ ($\widetilde {Rs}=-10$); in (b), $Rs=-3.148 \times 10^9$ ($\widetilde {Rs}=-31.48)$; in (c), $Rs=-4 \times 10^9$ ($\widetilde {Rs}=-40$).

Figure 12

Figure 13. Plots of $Ra$ versus $k^2$ for the steady (red) and oscillatory (blue) stability boundaries, with $\varGamma =10^{-4}$, $\sigma =0.2$, $\tau =0.5$. In (a–c), $\lambda =0.5$; in (d–f), $\lambda =0.8$. In (a), $\widetilde {Rs}=-10.5$ ($Rs=-1.05 \times 10^9$); in (b), $\widetilde {Rs}=-10.945$ ($Rs=-1.0945 \times 10^9$); in (c), $\widetilde {Rs}=-15$ ($Rs=-1.5 \times 10^9$); in (d), $\widetilde {Rs}=-10$ ($Rs=-10^9$); in (e), $\widetilde {Rs}=-10.466$ ($Rs=-1.0466 \times 10^9$); in ( f), $\widetilde {Rs}=-12$ ($Rs=-1.2 \times 10^9$).

Figure 13

Figure 14. Plots of (a) $n_c$ and (b) $k_{oc}^2$ versus $\lambda$ for $\varGamma =10^{-4}$, $\tau =0.5$. The black lines denote $\sigma =0.2$ ($\sigma \lt \sigma _c$), the red dashed lines $\sigma =1$ ($\sigma \gt \sigma _c$).

Figure 14

Figure 15. $\text{Plots of }Ra_c$, $k_c^2$ and $\omega _c^2$ versus $\lambda$; $\tau =0.5$. In (a–c), $\sigma = 1$, $\varGamma =10^{-3}$, $Rs=-10^9$ ($n=3$); in (d–f), $\sigma =0.2$, $\varGamma =10^{-3}$, $Rs=-10^9$ ($n=3$); in (g–i), $\sigma =1$, $\varGamma =10^{-3}$, $Rs=-10^{12}$ ($n=4$). Numerical results are shown as solid lines; black (magenta) denotes oscillatory (steady) solutions. The asymptotic results of § 4.4 are shown as dashed red lines.

Figure 15

Figure 16. $\text{Plots of }Ra_c$, $k_c^2$ and $\omega _c^2$ versus $\lambda$; $\tau =0.5$, $\varGamma =10^{-3}$, $Rs=-10^{12}$ ($n=4$). (a–c) Region near $\lambda =-1$ for $\sigma =1$; (d–f) region near $\lambda =-1$ for $\sigma =0.2$; (g–i) region near $\lambda =1$ for $\sigma =1$. Numerical results are shown as solid lines; black (magenta) denotes oscillatory (steady) solutions. The asymptotic results of § 4.4 are shown as dashed red lines.

Figure 16

Figure 17. Surface plots of (a) ${\textit{Ra}}_c$ and (b) $k_c^2$ versus $\lambda$ and $\tau$ for $\varGamma =10^{-3}$, $Rs=-10^9$, $\sigma =1$. The range $0.05 \leqslant \tau \leqslant 0.95$ is plotted.

Figure 17

Figure 18. Contour plots as functions of $\lambda$ and ${\textit{Ra}}/|Rs|$ for (a,d) growth rate, (b,e) frequency and (c, f) $k^2$ for the gravest mode in the first quadrant; $\sigma =1$, $\tau =0.5$, for the case of $n=3$. In the top row, $\varGamma =10^{-3}$, $Rs=10^9$; in the bottom row, $\varGamma =10^{-4}$, $Rs=10^{12}$. In plots (b) and (e), the red dotted region denotes where the gravest mode is steady. The blue dashed line shows the oscillatory stability boundary for the classical problem, given by (2.28).

Figure 18

Figure 19. Contour plots as functions of $\lambda$ and ${\textit{Ra}}/|Rs|$ for (a,d) growth rate, (b,e) frequency and (c, f) $k^2$ for the gravest mode; $\sigma =1$, $\tau =0.5$, for the case of $n=3$ in the third quadrant. In the top row, $\varGamma =10^{-3}$, $Rs=-10^9$; in the bottom row, $\varGamma =10^{-4}$, $Rs=-10^{12}$. In plots (b) and (e), the red dotted region denotes where the gravest mode is steady.

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