SearcharxivSearch

arXiv subjects

Steven M. Tobias

Publications and source records attributed to Steven M. Tobias.

At least 19 recordsLinked to original sources

Diffusion-Free Dynamics in Rotating Spherical Shell Convection Driven By Internal Heating and Cooling

The bulk properties of convection in stellar and giant planet interiors are often assumed to be independent of the molecular diffusivities, which are very small. By contrast, simulations of this process in rotating, spherical shells, which are typically driven by conductive boundary heat fluxes, generally yield results that depend on the diffusivity. This makes it challenging to extrapolate these simulation results to real objects. However, laboratory models and Cartesian-box simulations suggest that diffusion-free dynamics are more readily obtained if convection is driven using prescribed internal heating and cooling instead of boundary fluxes. Here, we apply this methodology to simulations of Boussinesq, hydrodynamic rotating spherical shell convection. We find that this set-up unambiguously yields diffusion-free behaviour for some bulk properties of the convection, such as the radial temperature contrast and the convective heat transport. Moreover, the transition from prograde to retrograde equatorial zonal flow is diffusion-free and only depends on the convective Rossby number. The diffusivity dependence of other bulk properties is regime-dependent. In simulations that are rotationally constrained, the convective velocities, and the strength and structure of the zonal flow, are diffusion-dependent, although the zonal flow appears to approach a diffusion-free state for sufficiently high supercriticality. In simulations that are uninfluenced by rotation, or are only influenced by rotation at large scales, diffusion-free convective velocities and zonal flows are obtained. The result that many aspects of our idealised simulations are diffusion-free has promising implications for the development of realistic stellar and giant planet convection models that can access diffusion-free regimes.

astro-ph.SR

On nonlinear transitions, minimal seeds and exact solutions for the geodynamo

Nearly fifty years ago, Roberts (1978) postulated that Earth's magnetic field, which is generated by turbulent motions of liquid metal in its outer core, likely results from a subcritical (finite-amplitude) dynamo instability characterised by a dominant balance between Coriolis, pressure and Lorentz forces. Here we numerically explore subcritical convective dynamo action in a spherical shell, using techniques from optimal control and dynamical systems theory to uncover the nonlinear dynamics of magnetic field generation. Through nonlinear optimisation, via direct-adjoint looping, we identify the minimal seed - the smallest magnetic field that attracts to a nonlinear dynamo solution. Additionally, using the Newton-hookstep algorithm, we converge stable and unstable travelling wave solutions to the governing equations. By combining these two techniques, complex nonlinear pathways between attracting states are revealed, providing insight into a potential subcritical origin of the geodynamo. This paper showcases these methods on the widely studied benchmark of Christensen et al. (2001), laying the foundations for future studies in more extreme and realistic parameter regimes. We show that the minimal seed reaches a nonlinear dynamo solution by first approaching an unstable travelling wave solution, which acts as an edge state separating a hydrodynamic solution from a magnetohydrodynamic one. Furthermore, by carefully examining the choice of cost functional, we establish a robust optimisation procedure that can systematically locate dynamo solutions on short time horizons with no prior knowledge of its structure.

physics.flu-dyn

Data-driven discovery of the equations of turbulent convection

We compare the efficiency and ease-of-use of the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm and Sparse Physics-Informed Discovery of Empirical Relations (SPIDER) framework in recovering the relevant governing equations and boundary conditions from data generated by direct numerical simulations (DNS) of turbulent convective flows. In the former case, a weak-form implementation pySINDy is used. Time-dependent data for two- (2D) and three-dimensional (3D) DNS simulation of Rayleigh-Benard convection and convective plane Couette flow is generated using the Dedalus PDE framework for spectrally solving differential equations. Using pySINDy we are able to recover the governing equations of 2D models of Rayleigh-Benard convection at Rayleigh numbers, R, from laminar, through transitional to moderately turbulent flow conditions, albeit with increasing difficulty with larger Rayleigh number, especially in recovery of the diffusive terms (with coefficient magnitude proportional to 1/R^0.5). SPIDER requires a much smaller library of terms and we are able to recover more easily the governing equations for a wider range of R in 2D and 3D convection and plane flow models and go on to recover constraints (the incompressibility condition) and boundary conditions, demonstrating the benefits and capabilities of SPIDER to go beyond pySINDy for these fluid problems governed by second-order PDEs. [We] demonstrat[e] the potential of machine-learning methods to validate numerical solvers and solutions for such flow problems. We also find that properties of the flow, specifically the correlation time and spatial scales, should inform the initial selection of spatiotemporal subdomain sizes [abbreviated]

astro-ph.SR

Run-away transition to turbulent strong-field dynamo

Planets and stars are able to generate coherent large-scale magnetic fields by helical convective motions in their interiors. This process, known as hydromagnetic dynamo, involves nonlinear interaction between the flow and magnetic field. Nonlinearity facilitates existence of bi-stable dynamo branches: a weak field branch where the magnetic field is not strong enough to enter into the leading order force balance in the momentum equation at large flow scales, and a strong field branch where the field enters into this balance. The transition between the two with enhancement of convection can be either subcritical or supercritical, depending on the strength of magnetic induction. In both cases, it is accompanied by topological changes in velocity field across the system; however, it is yet unclear how these changes are produced. In this work, we analyse transitions between the weak and strong dynamo regimes using a data-driven approach, separating different physical effects induced by dynamically active flow scales. Using Dynamic Mode Decomposition, we decompose the dynamo data from direct numerical simulations into different components (modes), identify the ones relevant for transition, and estimate relative magnitudes of their contributions Lorentz force and induction term. Our results suggest that subcritical transition to a strong dynamo is facilitated by a subharmonic instability, allowing for a more efficient mode of convection, and provide a modal basis for reduced-order models of this transition.

physics.flu-dyn

Radiatively-Cooled Moist Convection under an Idealised Climate Change Scenario: Linear Analysis

In order to explore the effects of climate change on atmospheric convection and the water cycle, we develop and analyse an extension of the Rainy-Bénard model, which is itself a moist version of the Rayleigh-Bénard model of dry convection. Including moisture changes the character of the convection, with condensation providing a source of buoyancy via latent heating. The climate change model is set up by imposing a variable radiative cooling rate, prescribing surface temperature and relative humidity, and imposing a moist-pseudoadiabatic profile at the top boundary (a flux boundary condition). The model is analysed across the climate parameter space by examining diagnostics of the model's basic state, and its stability, with Convective Available Potential Energy (CAPE) calculations and a linear stability analysis. We use the linear stability results to identify new parameters relevant for this moist convective system, and to understand how the linear instability responds to the climate parameters. In particular, we define the "Rainy number" as a scaled ratio of positive-area CAPE and diffusion parameters. An alternative radiative-based Rainy number also is shown to describe the parameter space, especially for problems relating to changes in flux conditions. The analysis provides a novel theoretical understanding of how the dynamics and scales of moist convection and hence precipitation will change under climate change.

physics.flu-dyn

Local stability of differential rotation in magnetised radiation zones and the solar tachocline

We study local magnetohydrodynamical (MHD) instabilities of differential rotation in magnetised, stably-stratified regions of stars and planets using a Cartesian Boussinesq model. We consider arbitrary latitudes and general shears (with gravity direction misaligned from this by an angle $ϕ$), to model radial ($ϕ=0$), latitudinal ($ϕ=\pm 90^\circ$), and mixed differential rotations, and study both non-diffusive (including magnetorotational, MRI, and Solberg-Høiland instabilities) and diffusive instabilities (including Goldreich-Schubert-Fricke, GSF, and MRI with diffusion). These instabilities could drive turbulent transport and mixing in radiative regions, including the solar tachocline and the cores of red giant stars, but their dynamics are incompletely understood. We revisit linear axisymmetric instabilities with and without diffusion and analyse their properties in the presence of magnetic fields, including deriving stability criteria and computing growth rates, wavevectors and energetics, both analytically and numerically. We present a more comprehensive analysis of axisymmetric local instabilities than prior work, exploring arbitrary differential rotations and diffusive processes. The presence of a magnetic field leads to stability criteria depending upon angular velocity rather than angular momentum gradients. We find MRI operates for much weaker differential rotations than the hydrodynamic GSF instability, and that it typically prefers much larger lengthscales, while the GSF instability is impeded by realistic strength magnetic fields. We anticipate MRI to be more important for turbulent transport in the solar tachocline than the GSF instability when $ϕ>0$ in the northern (and vice versa in the southern) hemisphere, though the latter could operate just below the convection zone when MRI is absent for $ϕ<0$.

astro-ph.SR

Weakly nonlinear analysis of the onset of convection in rotating spherical shells

A weakly nonlinear study is numerically conducted to determine the behaviour near the onset of convection in rotating spherical shells. The mathematical and numerical procedure is described in generality, with the results presented for an Earth-like radius ratio. Through the weakly nonlinear analysis a Stuart--Landau equation is obtained for the amplitude of the convective instability, valid in the vicinity of its onset. Using this amplitude equation we derive a reduced order model for the saturation of the instability via nonlinear effects and can completely describe the resultant limit cycle without the need to solve initial value problems. In particular the weakly nonlinear analysis is able to determine whether convection onsets as a supercritical or subcritical Hopf bifurcation through solving only linear 2D problems, specifically one eigenvalue and two linear boundary value problems. Using this, we efficiently determine that convection can onset subcritically in a spherical shell for a range of Prandtl numbers if the shell is heated internally, confirming previous predictions. Furthermore, by examining the weakly nonlinear coefficients we show that it is the strong zonal flow created through Reynolds and thermal stresses that determines whether convection is supercritical or subcritical.

physics.flu-dyn

Ordering of timescales predicts applicability of quasi-linear theory in unstable flows

We discuss the applicability of quasilinear-type approximations for a turbulent system with a large range of spatial and temporal scales. We consider a paradigm fluid system of rotating convection with a vertical and horizontal temperature gradients. In particular, the interaction of rotating with the horizontal temperature gradient drives a ``thermal wind'' shear flow whose strength is controlled by a horizontal temperature gradient. Varying the parameters systematically alters the ordering of the shearing timescale, the convective timescale, and the correlation timescale. We demonstrate that quasilinear-type approximations work well when the shearing timescale or the correlation timescale is sufficiently short. In all cases, the Generalised Quasilinear approximation (GQL) systematically outperforms the Quasilinear approximation (QL). We discuss the consequences for statistical theories of turbulence interacting with mean gradients. We conclude with comments about the general applicability of these ideas across a wide variety of non-linear physical systems.

physics.flu-dyn

Linear and nonlinear properties of the Goldreich-Schubert-Fricke instability in stellar interiors with arbitrary local radial and latitudinal differential rotation

We investigate the linear and nonlinear properties of the Goldreich-Schubert-Fricke (GSF) instability in stellar radiative zones with arbitrary local (radial and latitudinal) differential rotation. This instability may lead to turbulence that contributes to redistribution of angular momentum and chemical composition in stars. In our local Boussinesq model, we investigate varying the orientation of the shear with respect to the 'effective gravity', which we describe using the angle $ϕ$. We first perform an axisymmetric linear analysis to explore the effects of varying $ϕ$ on the local stability of arbitrary differential rotations. We then explore the nonlinear hydrodynamical evolution in three dimensions using a modified shearing box. The model exhibits both the diffusive GSF instability, and a non-diffusive instability that occurs when the Solberg-H\{o}iland criteria are violated. We observe the nonlinear development of strong zonal jets ("layering" in the angular momentum) with a preferred orientation in both cases, which can considerably enhance turbulent transport. By varying $ϕ$ we find the instability with mixed radial and latitudinal shears transports angular momentum more efficiently (particularly if adiabatically unstable) than cases with purely radial shear $(ϕ= 0)$. By exploring the dependence on box size, we find the transport properties of the GSF instability to be largely insensitive to this, implying we can meaningfully extrapolate our results to stars. However, there is no preferred length-scale for adiabatic instability, which therefore exhibits strong box-size dependence. These instabilities may contribute to the missing angular momentum transport required in red giant and subgiant stars and drive turbulence in the solar tachocline.

astro-ph.SR

Jupiter's cloud-level variability triggered by torsional oscillations in the interior

Jupiter's weather layer exhibits long-term and quasi-periodic cycles of meteorological activity that can completely change the appearance of its belts and zones. There are cycles with intervals from 4 to 9 years, dependent on the latitude, which were detected in 5$μ$m radiation, which provides a window into the cloud-forming regions of the troposphere; however, the origin of these cycles has been a mystery. Here we propose that magnetic torsional oscillations/waves arising from the dynamo region could modulate the heat transport and hence be ultimately responsible for the variability of the tropospheric banding. These axisymmetric waves are magnetohydrodynamic waves influenced by the rapid rotation, which have been detected in Earth's core, and have been recently suggested to exist in Jupiter by the observation of magnetic secular variations by Juno. Using the magnetic field model JRM33, together with the density distribution model, we compute the expected speed of these waves. For the waves excited by variations in the zonal jet flows, their wavelength can be estimated from the width of the alternating jets, yielding waves with a half period of 3.2-4.7 years in 14-23$^\circ$N, consistent with the intervals with the cycles of variability of Jupiter's North Equatorial Belt and North Temperate Belt identified in the visible and infrared observations. The nature of these waves, including the wave speed and the wavelength, is revealed by a data-driven technique, dynamic mode decomposition, applied to the spatio-temporal data for 5$μ$m emission. Our results imply that exploration of these magnetohydrodynamic waves may provide a new window to the origins of quasi-periodic patterns in Jupiter's tropospheric clouds and to the internal dynamics and the dynamo of Jupiter.

astro-ph.EP

Direct statistical simulation of Lorenz96 system in model reduction approaches

Direct statistical simulation (DSS) of nonlinear dynamical systems bypasses the traditional route of accumulating statistics by lengthy direct numerical simulations (DNS) by solving the equations that govern the statistics themselves. DSS suffers, however, from the curse of dimensionality as the statistics (such as correlations) generally have higher dimension than the underlying dynamical variables. Here we investigate two approaches to reduce the dimensionality of DSS, illustrating each method with numerical experiments with the Lorenz-96 dynamical system. The forms of DSS chosen here involve approximate closures at second and third order in the equal time cumulants. We demonstrate significant reduction in computational effort that can be achieved without sacrificing the accuracy of DSS. The methods developed here can be applied to turbulent fluid and magnetohydrodynamical systems.

physics.flu-dyn

Transition to chaos and modal structure of magnetized Taylor-Couette flow

Taylor-Couette flow is often used as a simplified model for complex rotating flows in the interior of stars and accretion disks. The flow dynamics in these objects is influenced by magnetic fields. For example, quasi-Keplerian flows in Taylor-Couette geometry become unstable to a travelling or standing wave in an external magnetic field if the fluid is conducting; there is an instability even when the flow is hydrodynamically stable. This magnetorotational instability leads to the development of chaotic states and, eventually, turbulence, when the cylinder rotation is sufficiently fast. The transition to turbulence in this flow can be complex, with the coexistence of parameter regions with spatio-temporal chaos and regions with quasi-periodic behaviour, involving one or two additional modulating frequencies. Although the unstable modes of a periodic flow can be identified with Floquet analysis, here we adopt a more flexible equation-free data-driven approach. We analyse the data from the transition to chaos in the magnetized Taylor-Couette flow and identify the flow structures related to the modulating frequencies with Dynamic Mode Decomposition; this method is based on approximating nonlinear dynamics with a linear infinite-dimensional Koopman operator. With the use of these structures, one can construct a nonlinear reduced model for the transition.

physics.flu-dyn

Magnetoclinicity Instability

In strongly compressible magnetohydrodynamic turbulence, obliqueness between the large-scale density gradient and magnetic field gives an electromotive force mediated by density variance (intensity of density fluctuation). This effect is named ``magnetoclinicity'', and is expected to play an important role in large-scale magnetic-field generation in astrophysical compressible turbulent flows. Analysis of large-scale instability due to the magnetoclinicity effect shows that the mean magnetic-field perturbation is destabilised at large scales in the vicinity of strong mean density gradient in the presence of density variance.

astro-ph.SR

Can neural networks predict dynamics they have never seen?

Neural networks have proven to be remarkably successful for a wide range of complicated tasks, from image recognition and object detection to speech recognition and machine translation. One of their successes is the skill in prediction of future dynamics given a suitable training set of data. Previous studies have shown how Echo State Networks (ESNs), a subset of Recurrent Neural Networks, can successfully predict even chaotic systems for times longer than the Lyapunov time. This study shows that, remarkably, ESNs can successfully predict dynamical behavior that is qualitatively different from any behavior contained in the training set. Evidence is provided for a fluid dynamics problem where the flow can transition between laminar (ordered) and turbulent (disordered) regimes. Despite being trained on the turbulent regime only, ESNs are found to predict laminar behavior. Moreover, the statistics of turbulent-to-laminar and laminar-to-turbulent transitions are also predicted successfully, and the utility of ESNs in acting as an early-warning system for transition is discussed. These results are expected to be widely applicable to data-driven modelling of temporal behaviour in a range of physical, climate, biological, ecological and finance models characterized by the presence of tipping points and sudden transitions between several competing states.

cs.LG

Ion Heat and Parallel Momentum Transport by Stochastic Magnetic Fields and Turbulence

The theory of turbulent transport of parallel momentum and ion heat by the interaction of stochastic magnetic fields and turbulence is presented. Attention is focused on determining the kinetic stress and the compressive energy flux. A critical parameter is identified as the ratio of the turbulent scattering rate to the rate of parallel acoustic dispersion. For the parameter large, the kinetic stress takes the form of a viscous stress. For the parameter small, the quasilinear residual stress is recovered. In practice, the viscous stress is the relevant form, and the quasilinear limit is not observable. This is the principal prediction of this paper. A simple physical picture is developed and shown to recover the results of the detailed analysis.

physics.plasm-ph

Direct statistical simulation of the Lorenz63 system

We use direct statistical simulation (DSS) to find the low-order statistics of the well-known dynamical system, the Lorenz63 model. Instead of accumulating statistics from numerical simulation of the dynamical systems, we solve the equations of motion for the statistics themselves after closing them by making several different choices for the truncation. Fixed points of the statistics are obtained either by time evolving, or by iterative methods. Statistics so obtained are compared to those found by the traditional approach.

cond-mat.stat-mech

Optimizing the control of transition to turbulence using a Bayesian method

The nonlinear robustness of laminar plane Couette flow is considered under the action of in-phase spanwise wall oscillations by computing properties of the edge of chaos, i.e., the boundary of its basin of attraction. Three measures are used to quantify the chosen control strategy on laminar-to-turbulent transition: the kinetic energy of edge states (local attractors on the edge of chaos), the form of the minimal seed (least energetic perturbation on the edge of chaos), and the laminarization probability (the probability that a random perturbation from the laminar flow of given kinetic energy will laminarize). A novel Bayesian approach is introduced to enable the accurate computation of the laminarization probability at a fraction of the cost of previous methods. While the edge state and the minimal seed provide useful information about the dynamics of transition to turbulence, neither measure is particularly useful to judge the effectiveness of the control strategy since they are not representative of the global geometry of the edge. In contrast, the laminarization probability provides global information about the edge and can be used to evaluate the control effectiveness by computing a laminarization score (the expected laminarization probability) and the associated expected dissipation rate of the controlled flow. These two quantities allow for the determination of optimal control parameter values subject to desired constraints. The results discussed in the paper are expected to be applied to a wide range of transitional flows and control strategies aimed at suppressing or triggering transition to turbulence.

physics.flu-dyn

Characterising the shape, size and orientation of cloud-feeding coherent boundary layer structures

This paper presents two techniques for characterisation of cloud-feeding coherent boundary layer structures through analysis of large-eddy simulations of shallow cumulus clouds, contrasting conditions with and without ambient shear. The first technique is a generalisation of the two-point correlation function where the correlation length-scale as well as orientation can be extracted. The second technique decomposes the vertical transport by coherent structures by the shape, size and orientation of these structures. It is found that the structures dominating the vertical flux are plume-like in character (extending from the surface into cloud), show small width/thickness asymmetry and rise near-vertically in the absence of ambient wind. The planar stretching and tilting of boundary layer structures caused by the introduction of ambient shear is also quantified, demonstrating the general applicability of the techniques for future study of other boundary layer patterns.

physics.ao-ph