2.1. Scalings

The non-dimensionalization is based on the viscous-gravity velocity, $V\equiv \rho g R^{2}/\mu$, and the capillary length, $L=\sigma /\rho g R$. We assume that the radius of the fluid ring, $R$, is much smaller than the characteristic length $L$. The scalings are as follows:

(2.17)\begin{equation} \left.\begin{aligned} r=R r^{\ast},\ z=L z^{\ast},\ t=LV^{-1}t^{\ast},\ w=Vw^{\ast},\ u=\epsilon Vu^{\ast},\ v=\epsilon Vv^{\ast},\\ p=\rho g L p^{\ast},\ S=R S^{\ast},\ a=R a^{\ast},\quad\quad\quad\quad\quad\quad \end{aligned}\right\} \end{equation}

where the aspect ratio parameter $\epsilon =R/L$ is a small number, and ‘$\ast$’ denotes non-dimensional variables. Here, we assumed that the azimuthal velocity is also small, i.e. $v\sim O(\epsilon )$.

For convenience, we drop the $\ast$ decoration and the dimensionless Navier–Stokes equations are expressed as

(2.18)\begin{equation} \partial_r u+\frac{u}{r}+\frac{1}{r}\partial_\theta v+\partial_z w=0, \end{equation}

(2.19)\begin{align}& \epsilon^{4} Re\left(\partial_t u+{u}\partial_r u+\frac{v}{r}\partial_\theta u+{w}\partial_z u-\frac{v^{2}}{r}\right)\nonumber\\ &\quad=-\partial_r p+\Omega_N r-2\epsilon\alpha\Omega_N v+ \epsilon^{2}\left[\partial_{rr}u+\frac{\partial_r u}{r}+\frac{1}{r^{2}}\partial_{\theta\theta}u-\frac{u}{r^{2}}+\epsilon^{2}{\partial_{zz} u}\right], \end{align}

(2.20)\begin{align} & \epsilon^{4} Re\left(\partial_t v+{u}\partial_r v+\frac{v}{r}\partial_\theta v+{w}\partial_z v+\frac{uv}{r}\right)\nonumber\\ &\quad=-\frac{1}{r}\partial_\theta p+2\epsilon\alpha\Omega_N u+ \epsilon^{2}\left[\partial_{rr}v+\frac{\partial_r v}{r}+\frac{1}{r^{2}}\partial_{\theta\theta}v-\frac{v}{r^{2}}+\epsilon^{2}{\partial_{zz} v}\right], \end{align}

(2.21)\begin{align} & \epsilon^{2} Re\left(\partial_t w+{u}\partial_r w+\frac{v}{r}\partial_\theta w+{w}\partial_z w\right)=1-\partial_z\,p + \partial_{rr}w+\frac{\partial_r w}{r}+\frac{1}{r^{2}}\partial_{\theta\theta}w+\epsilon^{2}\partial_{zz}w, \end{align}

where the Reynolds number is defined as $Re=\rho V L/\mu$, and the parameters related to rotation are $\Omega _N=\Omega ^{2} R^{2}/g L$ and $\alpha =V/\Omega R$. This non-dimensionalization naturally results in $\epsilon =\rho g R^{2}/\sigma$, which is also referred to as the Bond number. The choice of small $\epsilon$ implies a small Bond number and surface-tension-dominated case. The full set of dimensionless parameters are $\epsilon$, $a$, $\Omega _N$, $\alpha$ and $Re$.

We choose the set of parameters used in the experiments by Kliakhandler etal. (Reference Kliakhandler, Davis and Bankoff2001), in which castor oil with density $\rho =0.961 \times 10^{3}\ \textrm {kg}\,\textrm {m}^{-3}$, kinematic viscosity $\nu \equiv \mu /\rho =4.44 \times 10^{-4} \ \textrm {m}^{2}\,\textrm {s}^{-1}$, surface tension $\sigma =3.1\times 10^{-2} \ \textrm {kg}\,\textrm {s}^{-2}$, is used for coating. The radius of the fluid ring in initial state, $R$, is approximately $1\ \textrm {mm}$. For this set of physical parameters, the dimensionless parameter $\epsilon$ is less than 0.3 and the Reynolds number $Re\sim 10^{-2}$. We fixed the radius of the initial surface to be approximately $1\ \textrm {mm}$ and change the angular frequency of rotation $\Omega =2{\rm \pi} f$, in which $f$ is the frequency measured in cycles per second or Hertz. As $f$ changes in the range from 10 to 30 which is easily realized in experiments, $\Omega _N=0.1223$, 0.4890, 1.1003, $\alpha =0.3545$, 0.1772, 0.1182 for $f=10$, 20 and 30. When deriving the long-wave evolution equation, we assume the parameter $\Omega _N$ has order $O(1)$.

2.2. Linear stability

In the framework of normal mode analysis, the variables in the full Navier–Stokes equations are decomposed in the form of

(2.22)\begin{equation} [u,v,w,p,S]=[\bar{u},\bar{v},\bar{w},\bar{p},\bar{S}]+[\hat{u},\hat{v},\hat{w},\hat{p},\hat{S}]\exp[\textrm{i}(m\theta+kz-\omega t)], \end{equation}

in which ‘$\bar {\ \ \ }$’, denotes the base state, ‘$\hat {\ \ \ }$’, denotes the Fourier amplitudes of the disturbances, the integer $m$ and the real number $k$ denote the azimuthal and streamwise wavenumbers and $\omega$ denotes the frequency. The basic states of $u$, $w$ and $p$ are

(2.23)\begin{gather} \bar{u}=0, \end{gather}

(2.24)\begin{gather} \bar{w}=\frac{1}{4}(a^{2}-r^{2})+\frac{1}{2}\ln \frac{r}{a}, \end{gather}

(2.25)\begin{gather} \bar{p}=1+\frac{1}{2}\Omega_N(r^{2}-1). \end{gather}

The governing equations for the disturbances are as follows:

(2.26)\begin{equation} \texttt{D}\hat{u}+\frac{\hat{u}}{r}+\frac{\textrm{i}m}{r}\hat{v}+\textrm{i} k \hat{w}=0, \end{equation}

(2.27)\begin{align} & \epsilon^{4} Re(-\textrm{i}\omega \hat{u}+\textrm{i}k\bar{w} \hat{u})\nonumber\\ &\quad =-\texttt{D}\hat{p}-2\epsilon \alpha\Omega_N \hat{v} +\epsilon^{2}\left[\texttt{D}^{2} \hat{u} +\frac{\texttt{D}\hat{u}}{r}-\left(\epsilon^{2}k^{2}+\frac{m^{2}+1}{r^{2}}\right)\hat{u}-\frac{2\textrm{i}m\hat{v}}{r^{2}}\right], \end{align}

(2.28)\begin{align} &\epsilon^{4} Re(-\textrm{i}\omega \hat{v}+\textrm{i}k\bar{w} \hat{v})\nonumber\\ &\quad=-\frac{\textrm{i}m}{r}\hat{p}+2\epsilon \alpha \Omega_N \hat{u} +\epsilon^{2}\left[\texttt{D}^{2} \hat{v}+\frac{\texttt{D}\hat{v}}{r}-\left(\epsilon^{2}k^{2}+\frac{m^{2}+1}{r^{2}}\right)\hat{v}+\frac{2\textrm{i}m\hat{u}}{r^{2}}\right], \end{align}

(2.29)\begin{equation} \epsilon^{2} Re(-\textrm{i}\omega \hat{w}+ \texttt{D}\bar{w}\hat{u}+\textrm{i}k \bar{w}\hat{w})=-\textrm{i}k\hat{p}+\left[\texttt{D}^{2}\hat{w}+\frac{\texttt{D}\hat{w}}{r}-\left(\epsilon^{2}k^{2}+\frac{m^{2}}{r^{2}}\right)\hat{w}\right], \end{equation}

where $\texttt {D}=\textrm {d}/\textrm {d}r$.

At the fibre wall ($r=a$), the boundary conditions are

(2.30)\begin{equation} \hat{u}=\hat{v}=\hat{w}=0. \end{equation}

At the perturbed surface, boundary conditions are projected to $r=1$ and after linearising, we have

(2.31)\begin{gather} \hat{p}-2\epsilon^{2}(\texttt{D} \hat{u}-\textrm{i}k\texttt{D} \bar{w} \hat{S})=-(1+\Omega_N\bar{S})\hat{S}+(m^{2}+\epsilon^{2} k^{2} )\hat{S}, \end{gather}

(2.32)\begin{gather} \texttt{D}\hat{w}+\texttt{D}^{2}\bar{w} \hat{S}+\textrm{i} \epsilon^{2} k \hat{u}=0, \end{gather}

(2.33)\begin{gather} r\texttt{D}\left(\frac{\hat{v}}{r}\right)+\frac{\textrm{i}m}{r}\hat{u}=0, \end{gather}

(2.34)\begin{gather} -\textrm{i} \omega \hat{S}+\textrm{i}k \bar{w}\hat{S}-\hat{u}=0. \end{gather}

The fully linearized Navier–Stokes equations are solved by a Chebyshev collocation method.

Figure 2 shows the dispersion relations of the axisymmetric mode ($m=0$) and the non-axisymmetric mode ($m=1$). At $f=0$, as shown in figure 2(a,d) for $a=0.3$ and 0.8, the axisymmetric mode is the most unstable. As $f=10$ in figure 2(b,e), the non-axisymmetric mode with $m=1$ becomes unstable in the long-wave range, but the maximum growth rate of $m=1$ is less than that of $m=0$. This indicates that the axisymmetric mode dominates the instability when the rotating speed is low. As $f$ increases to 20, as shown in figure 2(c,f) the asymmetric mode $m=1$ becomes the most unstable mode.

Figure 2.

The curves of the dispersion relations predicted by the linearized Navier–Stokes equations (2.23)–(2.31) for ($a) \ a=0.3$, $f=0$; ($b) \ a=0.3$, $f=10$; ($c) \ a=0.3$, $f=20$; ($d) \ a=0.8$, $f=0$; ($e) \ a=0.8$, $f=10$; ($\,f) \ a=0.8$, $f=20$. Here, $f=0$ corresponds the non-rotating case of $\Omega _N=0$. At $f=10$ and $20$, the parameters related to rotation, $(\Omega _N, \alpha )$, are (0.1223, 0.3545) and (0.4890, 0.1772), respectively. The parameter $\epsilon \approx 0.3$.

In figure 3, we compare the dispersion relation of axisymmetric disturbances predicted by the fully linearized Navier–Stokes equations with that of neglecting the Coriolis forces, i.e. setting $\alpha$ to be zero in (2.27) and (2.28). Figure 3 shows that the influence of the Coriolis forces on the stability is negligible when the rotating speed is low such that $\Omega _N\sim O(1)$. Therefore, in the following discussions, the Coriolis effect has been neglected.

Figure 3.

Comparison of the curves of the dispersion relations of axisymmetric modes with $m=0$ predicted by the linearized Navier–Stokes equations (2.26)–(2.34) (solid lines) and the cases without Coriolis force (marked by solid circles). Other parameters are $a=0.3$, $\epsilon \approx 0.3$. The parameter $\Omega _N=0.122$, 0.489, 1.10 corresponds to $f=10$, 20, 30, respectively.

We will examine the nonlinear evolution of the most unstable mode for both low and high frequencies of rotation. At low frequency of rotation, the most unstable is axisymmetric, i.e.$m=0$. In this case, we derive an asymptotic model equation to describe the dynamics of the flow. In the fast rotation case, the results of the linear stability analysis have shown that the $m=0$ is not the most unstable. We should note that there exists different transitional routes in the present system, which depends on the initial conditions. When the rotation is slow, if the initial condition takes the non-axisymmetric form and has no streamwise component (the $m=0$ component), it can develop into a non-axisymmetric state because it is unstable. However, when the initial condition has a streamwise component, we observe fthat the final saturated state is axisymmetric, i.e. the non-axisymmetric mode is suppressed by the axisymmetric mode at small rotation number (see appendix B). When the rotation is fast, if we increase the rotation gradually and allow the axisymmetry mode to appear first, the non-axisymmetric mode $(m=1)$ will be bypassed, which has also been demonstrated by the simulation of a 3-D thin film model in appendix B. However, for a uniform film, if one suddenly rotates the cylinder at a high speed, the non-axisymmetric mode may appear first, which is confirmed by direct numerical simulation in appendices A and B. The axisymmetric state, however, might also be unstable to azimuthal disturbances, when the film is very thin. For example, Rietz etal. (Reference Rietz, Scheid, Gallaire, Kofman, Kneer and Rohlfs2017) observed that axisymmetric ring waves lose instability to a rivulet structure. A similar transitional scenario has also been found in a liquid film flowing underneath an inclined plane (Charogiannis etal. Reference Charogiannis, Denner, van Wachem, Kalliadasis, Scheid and Markides2018). It should be noted that the Rayleigh–Plateau mechanism is very weak and negligible in Rietz etal. (Reference Rietz, Scheid, Gallaire, Kofman, Kneer and Rohlfs2017) due to the small thickness of film. In the present work, both the Rayleigh–Plateau mechanism and the Rayleigh–Taylor instability are important because the film is thick. It will be very challenging to investigate the rivulet instability in the present case because deriving a simple model equation is not possible. However, the present axisymmetric model can be applied to understand the nonlinear wave dynamics on the crests of rivulets formed on the fibre, e.g. the interaction between different waves leading to an oscillating state.

2.3. A long-wave model

The linear stability analysis shows that the Coriolis effect is negligible at small rotation frequency, $\Omega _N=O(1)$. The axisymmetric unstable mode dominates the primary instability when the rotating frequency is low $f\le 10$ and surface tension effect is dominant (small $\epsilon$). Assuming $\epsilon ^{2}\ll 1$, $Re\sim O(1)$ and slow rotation, we can neglect the inertial terms and the Coriolis force.

Under the assumption of axisymmetry, the leading-order Navier–Stokes equation is given by

(2.35)\begin{gather} 0=-\partial_r p+\Omega_N r, \end{gather}

(2.36)\begin{gather} \partial_{rr}w+\frac{\partial_r w}{r}=\partial_z p-1. \end{gather}

At the fibre wall $r=a$,

(2.37)\begin{equation} w=0. \end{equation}

The leading-order tangential and normal stress balances at the surface ($r=S$) are

(2.38)\begin{gather} \partial_r w=0, \end{gather}

(2.39)\begin{gather} p=\frac{1}{S}-\epsilon^{2} \partial_{zz}S. \end{gather}

It is notable that the term, $\epsilon ^{2}S_{zz}$, which involves the highest derivative of $S$ is included in (2.39). In a linear analysis, the inclusion of this term is vital to give the correct cutoff wavenumber. Conventionally, this term is kept in long-wave theories of the problem with a cylindrical free surface, such as jets, threads and liquid bridges (Eggers & Dupont Reference Eggers and Dupont1994; Craster & Matar Reference Craster and Matar2006). An understandable explanation for the inclusion of this term is that the streamwise curvature is sufficiently large in some regions at the interface such as the steep front edge of a solitary hump. So, the term which contains the highest derivative of $S$ is sufficiently large and cannot be neglected even though it is multiplied by $\epsilon ^{2}$. For more justification of the inclusion of this term, we refer the reader to Craster & Matar (Reference Craster and Matar2006). An alternative choice is to keep the full curvature in the equation of the balance of the normal stresses in other related topics, for example, free-surface flows with large slopes (Snoeijer Reference Snoeijer2006) and rim or coating flows (Lopes, Thiele & Hazel Reference Lopes, Thiele and Hazel2018).

From (2.35) and (2.36), we obtain the pressure

(2.40)\begin{equation} p=\frac{1}{S}-\epsilon^{2} \partial_{zz}S+\frac{1}{2}\Omega_N(r^{2}-S^{2}), \end{equation}

and the velocity $w(r,z,t)$

(2.41)\begin{equation} w=(1-\partial_z p)\left[\frac{1}{4}(a^{2}-r^{2})+\frac{1}{2}S^{2}\ln \frac{r}{a}\right]. \end{equation}

Substituting $w$ into the kinematic boundary condition yields an evolution equation for $S(z,t)$ given by

(2.42)\begin{align} \partial_t S=-\frac{1}{16 S}\partial_z\left\{ \left(1+\frac{\partial_z S}{S^{2}}+\Omega_N S \partial_zS+\epsilon^{2} \partial_{zzz}S\right)\left[4S^{4}\log \frac{S}{a}+(3S^{2}-a^{2})(a^{2}-S^{2})\right]\right\}. \end{align}

Equation (2.42) is identical to Craster & Matar (Reference Craster and Matar2006) when the rotation is turned off.

2.4. Thin film limit

For the case in which the film is thin relative to the fibre, i.e. $S(z,t)=a+h(z,t)$, where the film thickness $h\ll a$, expanding equation (2.42) for small $h$ results in the evolution equation for the thin film

(2.43)\begin{align} &\left(1+\frac{h}{a}\right)\partial_t h+\frac{1}{3}\frac{\partial}{\partial z}\nonumber\\ &\quad\times\left\{ h^{3}\left(1+\frac{h}{a}\right)\left[1+\frac{\partial_z h}{a^{2}(1+h/a)^{2}}+\Omega_Na(1+h/a)\partial_z h+\epsilon^{2} \partial_{zzz} h\right]\right\}=0. \end{align}

For very thin fluid films, $a\rightarrow 1$ and $1+h/a\rightarrow 1$, the evolution equation can be further simplified as

(2.44)\begin{equation} \partial_t h+\frac{\partial}{\partial z}\left\{ \frac{h^{3}}{3}\left[1+(1+\Omega_N)\partial_z h+\epsilon^{2} \partial_{zzz} h\right]\right\}=0. \end{equation}

At $\Omega _N=0$, (2.44) is reduced to the evolution equation of thin film by some authors (Frenkel Reference Frenkel1992; Kalliadasis & Chang Reference Kalliadasis and Chang1994). The roles of capillary forces and rotation on the stability of the film are manifested in (2.44). The terms $\partial _z h$, $\Omega _N \partial _z h$, $\epsilon ^{2} \partial _{zzz}h$ denote the contributions of azimuthal curvature, the rotation and the streamwise curvature, respectively. It is well known that the azimuthal curvature and the streamwise curvature are destabilizing and stabilizing, respectively (Kliakhandler etal. Reference Kliakhandler, Davis and Bankoff2001; Craster & Matar Reference Craster and Matar2006). From (2.44) for the thin film limit, it can be seen that the rotation is destabilizing the interface through the azimuthal curvature.

3.1. Dispersion relations

Let us now consider the linear stability of the problem. A small periodic disturbance in the streamwise direction is imposed on the film such that the film thickness can be decomposed into a base state component $\bar {S}$, and a small disturbance of normal mode with amplitude $\hat {S}$,

(3.1)\begin{equation} S=\bar{S}+\hat{S}{\rm e}^{ \textrm{i}(kz-\omega t) }, \end{equation}

in which $\omega$ is the complex frequency and $k$ is the wavenumber, and $\bar {S}=1$.

Substituting (3.1) into (2.42) yields the dispersion relation

(3.2)\begin{align} -\textrm{i}\omega+\left\{\frac{1}{16}k^{2}(k^{2}\epsilon^{2}-(1+\Omega_N)) \left(4 \ln \frac{1}{a}-a^{4}+4a^{2}-3\right)+\frac{\textrm{i}k}{2}(a^{2}-1-2\ln a) \right\}=0. \end{align}

At $\Omega _N=0$, this dispersion relation is identical to that of Craster & Matar (Reference Craster and Matar2006) for a coating flow down a fibre. In the thin film limit as $a\rightarrow 1$, the dispersion relation corresponding to (2.44) tends to

(3.3)\begin{equation} -\textrm{i}\omega\sim \frac{1}{3}k^{2}[(1+\Omega_N)-k^{2}\epsilon^{2}] (1-a)^{3}-\textrm{i}k(1-a)^{2}. \end{equation}

We use $\omega _r$ and $\omega _i$ to denote the real part and imaginary part of $\omega$. Here, $\omega _i$ and $\omega _r$ correspond to its growth or decay rate and the frequency of the disturbance. The phase speed of the disturbance is defined as $c={k}^{-1}{\omega _r}$. From (3.2), the phase speed

(3.4)\begin{equation} c=\frac{1}{2}(a^{2}-1-2\ln a), \end{equation}

is positive and independent of the wavenumber $k$ and the rotation parameter $\Omega _N$. This means all disturbances with different wavenumbers propagate downstream at a same speed.

Craster & Matar (Reference Craster and Matar2006) have tested the validity of their model by comparing the results of the dispersion relation predicted by the long-wave model and the linear stability characteristics of the Stokes flow equations. The result showed that the model equation provides a reasonably good approximation of the full Navier–Stokes equations. In the present paper, we will test the validity of the model (2.42) with the presence of rotation. The details of the stability analysis of the full Navier–Stokes equations are presented in § 2.2. In order to know quantitatively the effect of rotation, in figure 4 we plot the curves of the dispersion relations (3.2) of the long-wave model and those via fully linear stability analysis.

Figure 4.

Comparisons of the real growth rate of the axisymmetric mode $m=0$ versus the wavenumber in the range of $0<k<k_c$ for various $\Omega _N$ between the stability analysis of the Navier–Stokes equations (solid lines) and the long-wave model (dashed lines). Other parameters are $\epsilon =0.2$, ($a) \ a=0.5$, ($b) \ a=0.9$.

We compared the dispersion relations for both models for two typical cases, thick film with $a=0.5$ and thin film with $a=0.9$. Inspection of the dispersion curves indicates that the prediction of the long-wave model is in reasonable agreement with that predicted by the Navier–Stokes equations for various $\Omega _N$. For a fixed $k$, both models predict that the growth rate $\omega _i$ increases with the increase of $\Omega _N$. In figure 4(a), we observed that for thick film the time growth rate predicted by the long-wave model is obviously higher than that predicted by the linear stability analysis. However, in figure 4(b), the agreement between both models is excellent for the case of thin film.

3.2. Absolute and convective instabilities

For a general hydrodynamics stability problem, the wavenumber and frequency satisfy a dispersion relation in the form of

(3.5)\begin{equation} \mathcal{D}(k,\omega)=0. \end{equation}

In this subsection, we carry out a spatio-temporal stability analysis and both the wavenumber $k$ and the frequency $\omega$ are complex numbers.

The stability properties of the perturbations are determined by the long-time behaviour of an impulsive response to a localized excitation. The solution of the impulsive response can be expressed in the form of

(3.6)\begin{equation} G(z,t)=\frac{1}{2{\rm \pi}}\int_A\int_F\frac{{\rm e}^{\textrm{i}(kz-\omega t)}}{\mathcal{D}(k,\omega)}\,\textrm{d}\omega\,\textrm{d}k, \end{equation}

where the Bromwich contour $F$ in the $\omega$-plane is a horizontal line lying above all the singularities to satisfy causality, and the integration path $A$ lies inside the analyticity band around the $k$-axis.

The nature of CI and AI can be identified by examining the long-time behaviour of the wavenumber $k_0$ along the ray $z/t$ at a fixed spatial location. This complex $k_0$ has, by definition, a zero group velocity

(3.7)\begin{equation} \frac{\partial \omega}{\partial k}(k_0)=0, \end{equation}

and $\omega _0=\omega (k_0)$ is called the absolute frequency. If ${\rm Im} (\omega _0)>0$/${\rm Im} (\omega _0)<0$, the flow is said to be absolutely/convectively unstable. It should be noted that the saddle point $k_0$ must be identified by the Briggs–Bers collision criterion (Briggs Reference Briggs1964; Bers Reference Bers, DeWitt and Peyraud1975), i.e. the saddle point must be a pinch point produced by the collision of two distinct spatial branches of solutions coming from the upper and lower half-$k$-planes. In the pinching process, when $\omega$ moves from above along the vertical line down to $\omega _0$, the two spatial branches $k_1(\omega )$ and $k_2(\omega )$ originate in this movement on opposite sides of the real $k$-axis and collide at $k=k_0$ and $\omega =\omega _0$. For more details on the topics related to AI–CI problems, we refer the reader to a good review article by Huerre & Monkewitz (Reference Huerre and Monkewitz1990). The most relevant work to the present problem is the study on the AI–CI characteristics of an exterior coating film down a vertical fibre (Duprat etal. Reference Duprat, Ruyer-Quil, Kalliadasis and Giorgiutti-Dauphiné2007). Very recently, an experimental study by Sadeghpour etal. (Reference Sadeghpour, Zeng, Ji, Ebrahimi, Bertozzi and Ju2019) also showed that the water–vapour transfer rate in the coating flow is dependent on the AI–CI characteristics. For example, when the flow is absolutely unstable, the water–vapour transfer rate is generally promoted by increasing the liquid flow rate. However, in the convectively unstable situation, the water–vapour transfer rate does not increase with the liquid flow rate due to the occurrence of irregular beads.

From the dispersion relation, (3.2), the complex frequency $\omega$ can be expressed as a polynomial of $k$:

(3.8)\begin{equation} \omega=\frac{\textrm{i}}{16} k^{2}[(1+\Omega_N)-\epsilon^{2}k^{2}]\,f_1+k f_2, \end{equation}

in which

(3.9)\begin{gather} f_1=4 \ln \frac{1}{a}-a^{4}+4a^{2}-3, \end{gather}

(3.10)\begin{gather} f_2=\frac{1}{2}(a^{2}-1-2\ln a). \end{gather}

Through the transformation $k=\alpha \tilde {k}$, $\beta =(1+\Omega _N)(\alpha \epsilon )^{-2}$, $\tilde {\omega }=\omega (\alpha f_2)^{-1}$, where $\alpha =[(16f_2)/(3f_1 \epsilon ^{2})]^{1/3}$, the dispersion relation reduces to a standard form as

(3.11)\begin{equation} \tilde{\omega}=\tilde{k}+\frac{\textrm{i}\tilde{k}^{2}}{3}({\beta}-\tilde{k}^{2}). \end{equation}

A straightforward analysis based on (3.11) then shows that the instability becomes absolute when ${\beta }>{\beta }_c= [(9/4)(-17+7\sqrt {7})]^{1/3}\approx 1.5$ (Duprat etal. Reference Duprat, Ruyer-Quil, Kalliadasis and Giorgiutti-Dauphiné2007). Therefore, applying $\beta =(1+\Omega _N)(\alpha \epsilon )^{-2}$ to the condition ${\beta }>{\beta }_c$ yields the following implicit condition for absolute instability:

(3.12)\begin{equation} (1+\Omega_N)\left(\frac{3f_1}{16 \epsilon f_2 }\right)^{2/3}>{\beta}_c . \end{equation}

In figure 5(a,b), we present the AI–CI boundaries for various $\Omega _N$ in the $\epsilon\hbox{--}a$ plane and for various $a$ in the $\epsilon\hbox{--}\Omega _N$ plane, respectively. The range of parameter $a$ is ($0,1$). The model is valid for small $\epsilon$, however, when presenting the results we extend the range of $\epsilon$ to 0.5. As shown in figure 5(a), for each curve with the decrease of $a$ or $\epsilon$ the flow regime can switch from convective instability to absolute instability. With the increase of $\Omega _N$, the absolutely unstable regime extends in the $\epsilon\hbox{--}a$ plane. In figure 5(a), as $\Omega _N=0$ the convective regime occupies a large portion of area in the $\epsilon\hbox{--}a$ plane. With the increase of $\Omega _N$, some CI regimes become absolutely unstable and the boundary extends counterclockwise in the $\epsilon\hbox{--}a$ plane. In figure 5(b), it is shown that for each value of $a$ with the increase of $\Omega _N$ the flow switches from the CI to the AI regime. The results of figure 5 indicate that the increase of rotation promotes the absolute instability.

Figure 5.

The boundaries between CI and AI, ($a$) in the $\epsilon\hbox{--}a$ plane for various $\Omega _N$, ($b$) in the $\epsilon\hbox{--}\Omega _N$ plane for various $a$.

4.1. AI–CI instability

In this subsection, we performed numerical simulations on the nonlinear evolution of (2.42) to examine the effect of rotation on the transition from CI to AI regimes. We choose the set of parameters of $a=0.3$ and $\epsilon =0.4$ which lies in the CI regime for $\Omega _N=0$ and in the AI regime for $\Omega _N=0.5$. The initial condition is seeded with $S(z,0)=0.1 \exp [-(z -20)^{2}/{2}]$ and the length of computational domain $l=100$.

In figure 6, we present the spatio-temporal diagram for various $\Omega _N$, which may be helpful for us to understand the effect of rotation on the AI–CI characteristics. For $\Omega _N=0$, the flow is linearly convectively unstable. In figure 6(a) it is obvious that the disturbance propagates downstream and decays at $z=20$. As $\Omega _N$ increases to 0.5, as shown in figure 5, the flow is absolutely unstable as the point of (0.4, 0.3) in the $\epsilon\hbox{--}a$ plane is below the AI–CI boundary of $\Omega _N=0.5$. In figure 6(b), as $\Omega _N=0.5$, the flow becomes absolutely unstable as the disturbance is amplified both downstream and upstream.

Figure 6.

Spatial-temporal diagram for $a=0.3$, $\epsilon =0.4$. The values of $S(z,t)$ are marked by different colours. ($a) \ \Omega _N=0$; ($b) \ \Omega _N=0.5$.

4.2. Transient simulations in long domains

In order to know the properties of the solutions which are naturally selected, we performed numerical simulations in long domains subject to a pseudo-random initial condition. Two typical sets of parameters of $a$ and $\epsilon$ are chosen. Kliakhandler etal. (Reference Kliakhandler, Davis and Bankoff2001) and Craster & Matar (Reference Craster and Matar2006) have performed simulations on the nonlinear evolution for three regimes in Kliakhandler etal. (Reference Kliakhandler, Davis and Bankoff2001) and all of them are in the absolute instability regime. The first set of parameters, $a=0.255$ and $\epsilon =0.292$ chosen in this paper, which falls in the absolute instability regime, is identical to that used by Kliakhandler etal. (Reference Kliakhandler, Davis and Bankoff2001) and Craster & Matar (Reference Craster and Matar2006). The second set of parameters, $a=0.55$ and $\epsilon =0.3$, however, is picked from the convectively unstable regime when $\Omega _N=0$, which becomes absolutely unstable when $\Omega _N>0.2$.

The system becomes saturated after long-time evolution. In figure 7, we present the results of the first set of parameters, which is in the absolutely unstable regime. In figure 7(a–d), similar-sized large droplets are moving as a bound state. The heights of these droplets are very close but the gaps between them can vary. The increase of $\Omega _N$ leads to the formation of more pronounced and closely spaced beads with smaller sizes. Moreover, the gaps between different beads become flatter and thinner.

Figure 7.

The profiles of the interface via transient numerical simulations for various $\Omega _N$. Other parameters are $a = 0.2551$, $\epsilon = 0.2915$. The instant time is $t=100$. The coordinate $\zeta =z/\epsilon$. Here, $\Omega _N=0$, 0.2, 0.5 for ($a$), ($b$) and ($c$), respectively.

Figure 8 shows the film profiles for different values of $\Omega _N$, which demonstrates that the rotation has a significant influence on the flow pattern. In these figures, the height of the beads increases with the increase of $\Omega _N$. Comparing with figure 8(a,c), in which $\Omega _N$ increases from $\Omega _N=0$ to $\Omega _N=0.5$, the height of the beads in figure 8(c) is obviously larger than that in figure 8(a). However, the large droplet numbers are reduced from six to two. Hence, the gap between the large drops in figure 8(c) is much longer than that in figure 8(a). This long film between the two large droplets in figure 8(c) is unstable and breaks into several tiny beads. The large droplet, however, will catch up with and consume these small beads ahead and leave behind a flat film where small beads will regenerate again.

Figure 8.

The profiles of the interface via transient numerical simulations for various $\Omega _N$. Other parameters $a = 0.55$, $\epsilon = 0.3$. The instant time is $t=500$. The coordinate $\zeta =z/\epsilon$. Here, $\Omega _N=0$, 0.2, 0.5 for $(a),(b),(c)$, respectively.

5.1. Travelling-wave solutions

Experiments have shown different types of steadily propagating solutions in the form of highly organized droplets or bead-like solutions separated by long space (Kliakhandler etal. Reference Kliakhandler, Davis and Bankoff2001). In this subsection, we will examine how rotation influences the characteristics of these steady travelling-wave solutions.

We solve the governing equations by moving to a travelling-wave coordinate. In the moving system, it is convenient to define

(5.1)\begin{gather} \tau=t, \end{gather}

(5.2)\begin{gather} \xi=z-ct, \end{gather}

where $c$ is the wave speed of the moving coordinate. The derivatives with respective to $t$ and $z$ can be expressed as

(5.3)\begin{gather} \partial_t=\partial_\tau-c\partial_\xi, \end{gather}

(5.4)\begin{gather} \partial_z=\partial_\xi. \end{gather}

For a travelling-wave solution, the time derivation of $S$ with respect to $\tau$ is zero, and the profile of the interface has the form of $S=S(\xi )$. The nonlinear equation (2.42) becomes

(5.5)\begin{equation} -c\partial_\xi S^{2}+2\partial_\xi Q(S)=0, \end{equation}

where

(5.6)\begin{equation} Q(S)=\frac{1}{16}\left(1+\frac{\partial_\xi S}{S^{2}}+\Omega_N S \partial_\xi S+\epsilon^{2} \partial_{\xi\xi\xi}S\right)\left[4S^{4}\log \frac{S}{a}+(3S^{2}-a^{2})(a^{2}-S^{2})\right]. \end{equation}

Integrating equation (5.5) once, we have

(5.7)\begin{equation} -c S^{2}+2 Q(S)=q, \end{equation}

where $q$ is an integral constant. Equation (5.7) subject to periodic boundary conditions will be solved in the region of $-l/2<\xi \leq l/2$, where the length of the computational domain, $l$, is the wavelength of the travelling-wave solution. To fix $c$, we impose the mass conservative condition

(5.8)\begin{equation} \int_{-l/2}^{l/2}(S^{2}(\xi)-a^{2})\,\textrm{d}\xi=l(1-a^{2}). \end{equation}

To break the translational symmetry, one can enforce the real (or imaginary) part of the first Fourier mode to zero such that $q$ can be determined. A code for Newton iteration based on Ding & Willis (Reference Ding and Willis2019) was developed to solve the present problem. The solution can be tracked from the Hopf bifurcation point ($\omega _i=0$) with branch continuation.

Typical profiles of the travelling-wave solutions are shown in figure 9. As shown in figure 9, the droplet height is increased by the axial rotation. In Craster & Matar (Reference Craster and Matar2006) and Ding & Willis (Reference Ding and Willis2019), an observation is that higher droplets are moving faster than lower droplets. However, in the present study, it is found that this conclusion holds only if the axial rotation is slow (see figure 10a, in which the wave speed $c$ increases with $\Omega _N$). When the rotation becomes fast ($\Omega _N>0.5$), we observe that large droplets can move slower than small droplets (see figure 10b), which is contrary to the conclusions of Craster& Matar (Reference Craster and Matar2006) and Ding & Willis (Reference Ding and Willis2019).

Figure 9.

Interface profile for the travelling-wave solution for various $\Omega _N$. Other parameters are $\epsilon = 0.2$ and $a=0.25$. ($a) \ l=2$; ($b) \ l=6$.

Figure 10.

Travelling-wave solution for one-hump solutions: spacings $l$ and propagating speeds $c$ for various $\Omega _N$ at $\epsilon = 0.2$ and $a=0.25$.

To account for the physical mechanism of the abnormal phenomenon, we plot the flow field in figure 11 in the moving frame. It indicates that the reversal flow in the wave hump becomes stronger as $\Omega _N$ increases. This reversal flow can significantly increase the viscous dissipation effect. In their work, Ruyer-Quil etal. (Reference Ruyer-Quil, Treveleyan, Giorgiutti-Dauphiné, Dupat and Kalliadasis2008) derived a weighted residual model, which considered the streamwise dissipation effect, and they found that the wave speed of the travelling-wave solution in flow regime ‘c’ is lower than Craster & Matar (Reference Craster and Matar2006). As also discussed by Ding & Willis (Reference Ding and Willis2019) that viscous dissipation effect can slow the droplet motion, it is suggestive that the motion of large droplets is retarded by this strong reversal flow in the hump.

Figure 11.

The flow field in the moving frame at $\Omega _N=0.5,\,0.8,\,1$ for ($a$), ($b$) and ($c$), respectively.

5.2. Stability of the travelling-wave solution

Numerical simulations of the present problem showed that not all the travelling waves can be obtained through the evolution of an initial condition. It is natural to examine whether the travelling-wave solutions with different wavelengths are stable.

We performed a linear stability analysis on the travelling-wave solutions in the moving frame at the wave speed $c$. The profile of the interface is the travelling-wave solutions perturbed by an infinitesimal disturbance

(5.9)\begin{equation} S(\xi,\tau)=\bar{S}(\xi)+S'(\xi,\tau), \end{equation}

in which $S'(\xi ,\tau )=\hat {S}(\xi ){\rm e}^{-\textrm {i}\omega \tau }$.

The linearized evolution equation is written as

(5.10)\begin{equation} \bar{S}\partial_\tau S'-c\partial_\xi(\bar{S}S')+\partial_\xi\{(1-\partial_\xi \bar{p})\mathcal{F}_S S'-{\mathcal{F}}\partial_\xi p'\}=0, \end{equation}

in which

(5.11)\begin{gather} \partial_\xi \bar{p}=-\frac{\bar{S}_\xi}{\bar{S}^{2}}-\epsilon^{2}\partial_{\xi\xi\xi}\bar{S}-\Omega_N \bar{S} \partial_\xi\bar{S}, \end{gather}

(5.12)\begin{gather} \partial_\xi p'=-\frac{\partial_\xi S'}{\bar{S}^{2}}+2\partial_\xi\bar{S}\frac{S'}{\bar{S}^{3}}-\epsilon^{2} \partial_{\xi\xi\xi}S'-\Omega_N(\bar{S}\partial_\xi S'+\partial_\xi \bar{S}S'), \end{gather}

(5.13)\begin{gather} \mathcal{F}_S=\bar{S}^{3}\ln \frac{\bar{S}}{a} +\frac{\bar{S}(a^{2}-\bar{S}^{2})}{2}, \end{gather}

(5.14)\begin{gather} \mathcal{F}=\frac{\bar{S}^{4}}{4}\ln \frac{\bar{S}}{a} +\frac{(3\bar{S}^{2}-a^{2})(a^{2}-\bar{S}^{2})}{16}. \end{gather}

The curves of the leading eigenvalue of the travelling-wave solutions versus the wavelength are shown in figure 12. For $\Omega _N=0$, there exists a critical wavelength $l_c\approx 3.5$ beyond which the travelling-wave solutions are unstable. As $l >l_c$, a conjugate complex pair of eigenvalues are found. In figure 12(a), the curves of the growth rate consists of several segments, indicating that mode switching occurs as $l$ increases. This is also reflected by the non-continuous curves of temporal frequency $\omega _r$ as shown in figure 12(b). As shown in figure 12(a), with the increase of $\Omega _N$ the critical wavelength $l_c$ increases. As $\Omega _N$ increases from 0 to 0.2, the growth rate decreases as $l<12$ and increases as $l>12$. As $\Omega _N$ increases from 0.2 to 0.6, the effect of rotation is stabilizing. In figure 12(a), for $\Omega _N=0.6$ the unstable region is confined in a limited band of $l$. When $\Omega _N$ increases further, the travelling-wave solutions become completely stable. In figure 12(b), the frequency of the most unstable mode increases with the increase of $\Omega _N$. The results in figure 12 showed that the effect of rotation on the travelling-wave solution is adverse to the linear stability of the trivial base state $\bar {S}=1$ in which the rotation is destabilizing.

Figure 12.

The curves of the leading eigenvalue for the travelling-wave solutions versus the wave length $l$. ($a$) The time growth rate $\omega _i$, ($b$) the frequency $\omega _r$. Other parameters are $\epsilon = 0.2$ and $a=0.25$.

It is interesting to examine the structures of the most unstable mode of different segments in figure 12(a). In figure 13, the profiles of the most unstable mode are plotted for two typical sets of parameters. The structures of the disturbances are similar in these two figures. The disturbance consists of a series of ripples occupying the whole spatial domain. The disturbed surface is in the form of a large bead accompanied by a series of smaller beads. We also examine the structures of the most unstable mode for various parameters of $l$ and $\Omega _N$. The results of the linear stability analysis indicate that the structures of different segments are similar. The slight difference is that the numbers of small ripples may increase with $l$. It is obvious that the profiles in figure 13 provide initial states involving the interaction between a large bead and several smaller ones.

Figure 13.

The profile of the leading unstable mode with $L=5$. ($a) \ \Omega _N=0$; ($b) \ \Omega _N=0.4$. The dashed line denotes the basic state. Other parameters are $\epsilon = 0.2$ and $a=0.25$.

In the experiments by Kliakhandler etal. (Reference Kliakhandler, Davis and Bankoff2001), the flow regime ‘c’ presents dynamic behaviours different from the steady travelling waves, in which a complicated interaction between a large droplet and several small droplets causes an oscillatory flow. It is interesting to investigate how the rotation influences the dynamics of the oscillatory flow, i.e. flow regime ‘c’. To answer this question, we perform numerical simulations on the evolution initiated by a travelling-wave solution superposed of the most unstable mode. Before we study the nonlinear evolution by numerical simulations, it is helpful to discuss the nature of the stability of travelling-wave solutions. We classify the stability of travelling-wave solutions as being either convectively unstable or absolutely unstable. If the travelling-wave solutions are convectively unstable, they can tolerate localized disturbances and the flow ultimately evolves into a state in which the travelling waves interact with small ripples. If the travelling-wave solutions are absolutely unstable, these solutions can be destroyed by localized disturbances and evolve into a new state after a long time of evolution. As discussed in figure 13, the eigenvalues corresponding to the most unstable modes are in the form of a pair of conjugated complex numbers. This means the most unstable mode is convectively unstable and can escape the travelling wave downstream or upstream. For related discussion on the stability of a two-dimensional pulse on electrified falling films, see Blyth etal. (Reference Blyth, Tseluiko, Lin and Kalliadasis2018).

In figure 14, the space–time diagrams of a long-time evolution are plotted for several typical cases. In figure 14(a) for $l=4$ and $\Omega _N=0$ in which the travelling-wave solution is unstable as shown in figure 12, the oscillatory behaviour of the height of the large droplets is obvious. In this space–time diagram, it is observed that the oscillation is both temporally and spatially periodic. In figure 14(b) for $l=4$ and $\Omega _N=0.4$, there is no oscillation in the space–time diagram, indicating the system is a steady travelling wave. In figure 14(c,d), the space–time diagrams are plotted for two typical cases with $l=7$ in which the travelling-wave solutions are unstable. The characteristics of the structures in figure 14(a,c,d) are qualitatively similar. In these figures, smaller ripples arrange periodically in the $z\hbox{--}t$ plane, and the loci of the large droplets oscillate periodically. The flow can be considered as an oscillatory travelling wave, which conforms to the fact that the travelling-wave solutions are convectively unstable. The numerical simulations suggest that the time-periodic state is a relative periodic orbit (RPO), which has been reported by Ding & Willis (Reference Ding and Willis2019) in a non-rotating system. However, it is unclear how the rotation affects the mean speed and the period of the RPO. We will proceed to § 5.3 to answer this question.

Figure 14.

The space–time diagrams for the travelling waves perturbed by the most unstable mode. The contours of $S(z,t)$ are marked by different colours. $(a)\ L=4$, $\Omega _N=0$; $(b)\ L=4$, $\Omega _N=0.4$; $(c)\ L=7$, $\Omega_N=0.2$; $(d)L=7$, $\Omega _N=0.4$. Other parameters are $\epsilon = 0.2$ and $a=0.25$.

5.3. Exact RPOs

To find the exact RPOs of the present problem, we search for the recurrent solutions in the system

(5.15)\begin{equation} S(z,t)=S(z+s,t+T), \end{equation}

where $s$ is the spatial shift along the axis of the fibre and $T$ is the time period. Each RPO has its own particular period $T$, while a travelling wave has arbitrary period $T$. Given an initial guess of $\boldsymbol {X}_0=[S_0,s_0,T_0]^{\textrm {T}}$, we can obtain a better guess $\boldsymbol {X}_0+\delta \boldsymbol {X}_0$ by solving

(5.16)\begin{equation} \frac{\partial \boldsymbol{F}}{\partial S_0}\delta S_0+ \frac{\partial \boldsymbol{F}}{\partial s}\delta s+ \frac{\partial \boldsymbol{F}}{\partial T}\delta T=-\boldsymbol{F}, \end{equation}

where $\boldsymbol {F}=S(z+s,t+T)-S_0$. The solution $S_0$ is approximated by a Fourier expansion of $2N$ modes. Plus two other unknown parameters $T$ and $s$, there are $2N+2$ unknowns. To close the system, we require the update $\delta \boldsymbol {X}_0$ has no component in the $z$ direction and the $t$ direction (Ding & Willis Reference Ding and Willis2019):

(5.17)\begin{gather} \frac{\partial S^{T}_0}{\partial z}\delta S_0 =0, \end{gather}

(5.18)\begin{gather} \frac{\partial S^{T}_0}{\partial t}\delta S_0 =0. \end{gather}

Equation (5.16) and the two constraints constitute the following linear algebra problem:

(5.19)\begin{equation} \boldsymbol{A} \delta \boldsymbol{X}=\boldsymbol{b}, \end{equation}

where $\boldsymbol {b}=[\boldsymbol {F},0,0]^{\textrm {T}}$. It is impossible to write down the explicit Jacobian $\boldsymbol {A}$ but an alternative way to solve this problem is to work in the Krylov subspace spanned by $\mathcal{K}_n=\{\boldsymbol {b},\boldsymbol {A}\boldsymbol {b},\boldsymbol {A}\boldsymbol {b}^{2},\ldots ,\boldsymbol {A}\boldsymbol {b}^{n-1}\}$. To evaluate the result of multiplication by the Jacobian, we use the approximation

(5.20)\begin{equation} \frac{\partial S}{\partial S_0}\delta S_0\approx \frac{S(z,T;S_0+\varepsilon\delta{S}_0)- {S}(z,T;S_0)}{\varepsilon}, \end{equation}

in which $\varepsilon$ is an empirical small parameter and typically $\varepsilon =10^{-4}\|S_0\|/\|\delta S_0\|$. The generalized minimal residual method (GMRES) iterations are continued until

(5.21)\begin{equation} \frac{\parallel \boldsymbol{A} \delta \boldsymbol{X}_n-\boldsymbol{b}\parallel}{\parallel\boldsymbol{b}\parallel}\leq tol, \end{equation}

where $tol$ is the tolerance chosen in the range of $10^{-3}\text {--}10^{-4}$. Typically, it takes 10 to 20 GMRES iterations to get a converged solution to $\delta \boldsymbol {X}_0$. The Newton iteration is terminated when

(5.22)\begin{equation} \frac{\|S-S_0\|}{\|S_0\|}\leq 10^{-6}. \end{equation}

Failure of the Newton iteration is commonplace when the initial guess is poor. To improve the convergence domain, a hookstep method is applied to move $\delta {\boldsymbol {X}_0}$ into the trust region. We adapted the Newton–Krylov-hookstep algorithm by Ding & Willis (Reference Ding and Willis2019) and implemented the pseudo-arclength continuation technique to it for the present problem. The RPO is tracked from the Hopf bifurcation of the steady travelling-wave solutions, which is continued to other parameters via the pseudo-arclength continuation technique.

In figure 15(a), for $\Omega _N=0$ the first RPO branch bifurcates from the travelling-wave branch at $l\approx 3.5$, which corresponds to the first unstable mode as shown in figure 12. The bifurcation point of the second RPO branch locates at $l\approx 4.5$. As the parameter $\Omega _N=0.3$, as shown in figure 15(a), the first RPO branch bifurcates from the travelling-wave branch at $l\approx 4.0$ with $c\approx 1.5$. As shown in figure 15(a), at a given wavelength $l$, the RPO solution propagates slower than the travelling-wave solution. In this figure, it is found that both the first and the second branches of RPO propagate faster when $\Omega _N=0.3$. This indicates that rotation can not only promote the mean wave speed of travelling-wave solutions but also the RPO. In figure 15(b), at a given domain size $l$, the time period of the second RPO solution is obviously smaller than that of the first RPO solution. In figure 15(b), it is found that the value of $T$ of $\Omega _N=0.3$ is much smaller than the case of $\Omega _N=0$. The decreasing of the period means that the coalescence and breakup between a large droplet and a small droplet becomes faster. This suggests that the droplet coalescence and breakup process in flow regime ‘c’ can be promoted by the axial rotation.

Figure 15.

($a$) The bifurcation diagrams for RPOs in the $c\hbox{--}l$ plane. The propagating speed is defined by $c=s/T$ for RPOs. ($b$) The curves of the period $T$ versus the domain size $l$ for RPOs. Other parameters are $\epsilon = 0.2$ and $a=0.25$. The bifurcation points are marked by circles. TW, travelling wave.

For higher rotation speed, the travelling waves become more stable due to the rotation as discussed in § 5.2. Thus as $\Omega _N$ exceeds a critical value, the RPO branch will disappear because the travelling waves are stable. As shown in figure 16, the first PRO branch is plotted for $\Omega _N=0.5$. The relation between the RPO branch and the travelling-wave branch is similar to that in figure 15(a). In this figure, the wave speed $c$ of the RPO is closer to that of travelling-wave solution than the cases of lower rotations in figure 15(a). We have not tracked the RPOs at higher rotating speeds because, with the increase of $\Omega _N$, the oscillation becomes weak and the RPOs are very close to the travelling waves.

Figure 16.

The bifurcation diagrams for RPOs in the $c\hbox{--}l$ plane at high rotation with $\Omega _N=0.5$. Other parameters are $\epsilon = 0.2$ and $a=0.25$. TW, travelling wave.