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1. Photospheric Velocities Measured at Mt. Wilson Show Rotational and Poleward Velocity Deviations Compose the Torsional Oscillations

   https://doi.org/10.1007/s11207-023-02215-5  

   Ulrich, Roger K.; Tran, Tham; Boyden, John E. (October 2023, Solar Physics)

   Abstract The methods for reducing the observations from the 150-foot tower telescope on Mt. Wilson are reviewed, and a new method for determining the poleward and rotational velocity deviations is described and applied. The flows we study are smaller than global and change with the solar cycle, so we describe them as poleward and rotational deviations rather than meridional circulation when we discuss solar surface flows. Due to a calibration problem with the data prior to 1983, only observations between 1983 and 2013 are presented at this time. After subtraction of latitude-dependent averages over the 30-year period of observation, the residual deviations in both the poleward and the rotational velocity are well synchronized and correspond to what is widely recognized as torsional oscillations. Both flow components need to be included in any model that replicates the torsional oscillations. 

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2. Lagrangian diffusion properties of a free shear turbulent jet

   https://doi.org/10.1017/jfm.2021.325  

   Viggiano, Bianca; Basset, Thomas; Solovitz, Stephen; Barois, Thomas; Gibert, Mathieu; Mordant, Nicolas; Chevillard, Laurent; Volk, Romain; Bourgoin, Mickaël; Cal, Raúl Bayoán (July 2021, Journal of Fluid Mechanics)

   A Lagrangian experimental study of an axisymmetric turbulent water jet is performed to investigate the highly anisotropic and inhomogeneous flow field. Measurements are conducted within a Lagrangian exploration module, an icosahedron apparatus, to facilitate optical access of three cameras. Stereoscopic particle tracking velocimetry results in three-component tracks of position, velocity and acceleration of the tracer particles within the vertically oriented jet with a Taylor-based Reynolds number $${\textit {Re}}_\lambda \simeq 230$$ . Analysis is performed at seven locations from 15 diameters up to 45 diameters downstream. Eulerian analysis is first carried out to obtain critical parameters of the jet and relevant scales, namely the Kolmogorov and large (integral) scales as well as the energy dissipation rate. Lagrangian statistical analysis is then performed on velocity components stationarised following methods inspired by Batchelor ( J. Fluid Mech. , vol. 3, 1957, pp. 67–80), which aim to extend stationary Lagrangian theory of turbulent diffusion by Taylor to the case of self-similar flows. The evolution of typical Lagrangian scaling parameters as a function of the developing jet is explored and results show validation of the proposed stationarisation. The universal scaling constant $$C_0$$ (for the Lagrangian second-order structure function), as well as Eulerian and Lagrangian integral time scales, are discussed in this context. Constant $$C_0$$ is found to converge to a constant value (of the order of $$C_0 = 3$$ ) within 30 diameters downstream of the nozzle. Finally, the occurrence of finite particle size effects is investigated through consideration of acceleration-dependent quantities. 

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3. Depth‐Dependent Azimuthal Anisotropy Beneath the Juan de Fuca Plate System

   https://doi.org/10.1029/2020JB019477  

   Eilon, Zachary C.; Forsyth, Donald W. (July 2020, Journal of Geophysical Research: Solid Earth)

   Abstract We use surface wave measurements to reveal anisotropy as a function of depth within the Juan de Fuca and Gorda plate system. Using a two‐plane wave method, we measure phase velocity and azimuthal anisotropy of fundamental mode Rayleigh waves, solving for anisotropic shear velocity. These surface wave measurements are jointly inverted with constraints fromSKSsplitting studies using a Markov chain approach. We show that the two data sets are consistent and present inversions that offer new constraints on the vertical distribution of strain beneath the plates and the processes at spreading centers. Anisotropy of the Juan de Fuca plate interior is strongest (~2.4%) in the low‐velocity zone between ~40‐ to 90‐km depth, with ENE direction driven by relative shear between plate motion and mantle return flow from the Cascadia subduction zone. In disagreement withPnmeasurements, weak (~1.1%) lithospheric anisotropy in Juan de Fuca is highly oblique to the expected ridge‐perpendicular direction, perhaps connoting complex intralithospheric fabrics associated with melt or off‐axis downwelling. In the Gorda microplate, strong shallow anisotropy (~1.9%) is consistent withPninversions and aligned with spreading and may be enhanced by edge‐driven internal strain. Weak anisotropy with ambiguous orientation in the low‐velocity zone can be explained by Gorda's youth and modest motion relative to the Pacific. Deeper (≥90 km) fabric appears controlled by regional flow fields modulated by the Farallon slab edge: anisotropy is strong (~1.8%) beneath Gorda, but absent beneath the Juan de Fuca, which is in the strain shadow of the slab. 

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4. Separating Mesoscale and Submesoscale Flows from Clustered Drifter Trajectories

   https://doi.org/10.3390/fluids6010014  

   Oscroft, Sarah; Sykulski, Adam M.; Early, Jeffrey J. (January 2021, Fluids)

   null (Ed.)

   Drifters deployed in close proximity collectively provide a unique observational data set with which to separate mesoscale and submesoscale flows. In this paper we provide a principled approach for doing so by fitting observed velocities to a local Taylor expansion of the velocity flow field. We demonstrate how to estimate mesoscale and submesoscale quantities that evolve slowly over time, as well as their associated statistical uncertainty. We show that in practice the mesoscale component of our model can explain much first and second-moment variability in drifter velocities, especially at low frequencies. This results in much lower and more meaningful measures of submesoscale diffusivity, which would otherwise be contaminated by unresolved mesoscale flow. We quantify these effects theoretically via computing Lagrangian frequency spectra, and demonstrate the usefulness of our methodology through simulations as well as with real observations from the LatMix deployment of drifters. The outcome of this method is a full Lagrangian decomposition of each drifter trajectory into three components that represent the background, mesoscale, and submesoscale flow. 

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5. Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems

   Duruisseaux, Valentin; Duong, Thai; Leok, Melvin; Atanasov, Nikolay. (May 2023, Proceedings of Machine Learning Research)

   Incorporating prior knowledge of physics laws and structural properties of dynamical systems into the design of deep learning architectures has proven to be a powerful technique for improving their computational efficiency and generalization capacity. Learning accurate models of robot dynamics is critical for safe and stable control. Autonomous mobile robots, including wheeled, aerial, and underwater vehicles, can be modeled as controlled Lagrangian or Hamiltonian rigid-body systems evolving on matrix Lie groups. In this paper, we introduce a new structure-preserving deep learning architecture, the Lie group Forced Variational Integrator Network (LieFVIN), capable of learning controlled Lagrangian or Hamiltonian dynamics on Lie groups, either from position-velocity or position-only data. By design, LieFVINs preserve both the Lie group structure on which the dynamics evolve and the symplectic structure underlying the Hamiltonian or Lagrangian systems of interest. The proposed architecture learns surrogate discrete-time flow maps allowing accurate and fast prediction without numerical-integrator, neural-ODE, or adjoint techniques, which are needed for vector fields. Furthermore, the learnt discrete-time dynamics can be utilized with computationally scalable discrete-time (optimal) control strategies. 

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