arXiv subjects

Ryo Araki

Publications and source records attributed to Ryo Araki.

9 recordsLinked to original sources

arXiv2026

Information-Preserving SGS model based on the local inter-scale equilibrium hypothesis

Large eddy simulation has been widely used to simulate turbulence at balanced computational cost and accuracy. Many Subgrid-Scale (SGS) models have been proposed over the years, where data-driven and machine learning-aided approaches set the recent trend. To address the problem of extrapolation in these models, we propose a new data-driven SGS model based on an information-theoretic picture of turbulence. To this end, we estimate the model parameters by maximizing mutual information, which correspond to the scale-by-scale local equilibrium hypothesis in developed turbulence or "information preservation." An a priori test confirmed that the estimated parameters are in good agreement with the previously reported empirical values. Furthermore, a posteriori tests on periodic box turbulence and channel turbulence exhibited accuracy comparable to the existing models. These results suggest the utility of the information-theoretic picture of turbulence for constructing more generic SGS models without the need for empirically prescribed model parameters, while enhancing physical interpretability beyond black-box approaches.

physics.flu-dyn↗

arXiv2026

Convolutional causal learning for aerodynamic flows

This study aims to capture aerodynamic causality from snapshot data with a time-varying mode decomposition technique referred to as information-theoretic machine learning. The current approach extracts time-dependent informative vortical structures, contributing to the future evolution of the aerodynamic coefficients. The present decomposition is employed with a convolutional neural network, enabling the identification of the spatial continuous mode. In addition, a low-order representation, characterizing the informative vortical structures and their corresponding aerodynamic coefficients, can also be identified by considering autoencoder-based data compression. The present technique is applied to a range of aerodynamic examples, including extreme vortex-gust airfoil interactions, experimentally measured transverse jet-wing interaction, and a turbulent separated wake across different Reynolds numbers. For the cases of gust-wing interaction, the time-varying gust effect on the lift response is extracted in an interpretable manner. With the example of a turbulent wake, the relationship between large-scale vortical motion and lift force is identified without any spatial length-scale information. The proposed approach could serve as a foundation for data-driven causal modeling and control for a range of unsteady flows.

physics.flu-dyn↗

arXiv2025

Information-theoretic machine learning for time-varying mode decomposition of separated aerodynamic flows

We perform an information-theoretic mode decomposition for separated aerodynamic flows. The current data-driven approach based on a neural network referred to as deep sigmoidal flow enables the extraction of an informative component from a given flow field snapshot with respect to a target variable at a future time stamp, thereby capturing the causality as a time-varying modal structure. We consider four examples of separated flows around a wing, namely, 1. laminar periodic wake at post-stall angles of attack, strong gust-wing interactions of 2. numerical and 3. experimental measurements, and 4. a turbulent wake in a spanwise-periodic domain. The present approach reveals informative vortical structures associated with a time-varying lift response. For the periodic shedding cases, the informative structures vary in time corresponding to the fluctuation level from their mean values. With the examples of gust-wing interactions, how the effect of gust on a wing emerges in the lift response over time is identified in an interpretable manner. Furthermore, for the case of turbulent wake, the present model highlights structures near the wing and vortex cores as informative components based solely on the information metric without any prior knowledge of aerodynamics and length scales. This study provides causality-based insights into a range of unsteady aerodynamic problems.

physics.flu-dyn↗

arXiv2024

Scale-to-Scale Information Flow Amplifies Turbulent Fluctuations

In three-dimensional turbulence, information of turbulent fluctuations at large scales is propagated to small scales. Here, we investigate the relation between the information flow and turbulent fluctuations described by a shell model. We first establish a connection between the information flow and phase-space contraction rate. From this relation, we then prove an inequality between the information flow and turbulent fluctuations, which suggests that the information flow from large to small scales amplifies turbulent fluctuations at small scales. This inequality can also be interpreted as a quantification of Landau's objection to the universality of turbulent fluctuations. We also discuss differences between the information flow and the Kolmogorov-Sinai entropy.

cond-mat.stat-mech↗

arXiv2024

Piezomagnetism in the Ising ferromagnet URhGe

Piezomagnetism, linear response between strain and magnetic field, is relatively unexplored cross-correlation but has promising potential as a novel probe of time-reversal-symmetry breaking in various classes of materials. Interestingly, there has been no report of piezomagnetism in ferromagnets, most archetypal time-reversal-symmetry-broken materials. This half-century absence of piezomagnetic ferromagnets is attributable to complications originating from multiple-domain states, as well as from changes in the magnetic point group by rotation of magnetic moment. Here, we report characteristic V-shaped magnetostriction in the Ising itinerant ferromagnet URhGe, observed by simultaneous multi-axis strain measurement technique utilizing optical fiber Bragg grating sensors. This novel magnetostriction occurs only under fields along the c axis and does not scale with the square of magnetization. Such unconventional feature indicates piezomagnetism as its origin. Our observation, marking the first report of piezomagnetism in ferromagnets, is owing to the mono-domain switching and the Ising magnetization. The obtained piezomagnetic coefficients are fairly large, implying that Ising ferromagnets are promising frontiers when seeking for materials with large piezomagnetic responses.

cond-mat.str-el↗

arXiv2023

Information-Thermodynamic Bound on Information Flow in Turbulent Cascade

We investigate the nature of information flow in turbulence from an information-thermodynamic viewpoint. For the fully developed three-dimensional fluid turbulence described by the fluctuating Navier-Stokes equation, we prove that information of large-scale eddies is transferred to small scales along with the energy cascade. We numerically illustrate our findings using a shell model and further show that in the inertial range, the intensity of the information flow is nearly constant and can be scaled by the large-eddy turnover time. Our numerical results also suggest that the corresponding information-thermodynamic efficiency is quite low compared to other typical information processing systems such as Maxwell's demon. These findings provide a new perspective on how universality and intermittency of turbulent fluctuations emerge at small scales.

cond-mat.stat-mech↗

arXiv2023

Space-local Navier--Stokes turbulence

We investigate the physical-space locality of interactions in three-dimensional incompressible turbulent flow. To that, we modify the nonlinear terms of the vorticity equation such that the vorticity field is advected and stretched by the locally induced velocity. This space-local velocity field is defined by the truncated Biot--Savart law, where only the neighboring vorticity field in a sphere of radius $R$ is integrated. We conduct direct numerical simulations of the space-local system to investigate its statistics in the inertial range. We observe a standard $E(k) \propto k^{-5/3}$ scaling of the energy spectrum associated with an energy cascade for scales smaller than the space-local domain size $k \gg R^{-1}$. This result is consistent with the assumption Kolmogorov's 1941 paper made for the space-locality of the nonlinear interactions. The enstrophy amplification is suppressed for larger scales $k \ll R^{-1}$, and for these scales, the system exhibits a scaling consistent with a conservative enstrophy cascade.

physics.flu-dyn↗

arXiv2022

Inertial range scaling of inhomogeneous turbulence

We investigate how inhomogeneity influences the $k^{-5/3}$ inertial range scaling of turbulent kinetic energy spectra (with $k$ the wavenumber). For weak statistical inhomogeneity, the energy spectrum can be described as an equilibrium spectrum plus a perturbation. Theoretical arguments suggest that this latter contribution scales as $k^{-7/3}$. This prediction is assessed using direct numerical simulations of three-dimensional Kolmogorov flow.

physics.flu-dyn↗

arXiv2021

Minimal model of quasi-cyclic behaviour in turbulence driven by Taylor--Green forcing

We attempt to formulate the simplest possible model mimicking turbulent dynamics, such as quasi-cyclic behaviour (QCB), using only three variables. To this end, we first conduct direct numerical simulations of three-dimensional flow driven by the steady Taylor--Green forcing to find a similarity between a stable periodic orbit (SPO) at a small Reynolds number ($Re$) and turbulent QCB at higher $Re$. A close examination of the SPO allows the heuristic formulation of a three-equation model, representing the evolution of Fourier modes in three distinct scales. The model reproduces the continuous bifurcation from SPO to turbulence with QCB when $Re$ is varied. We also demonstrate that, by changing model parameters, the proposed model exhibits a discontinuous transition from steady to chaotic solutions without going through an SPO.

physics.flu-dyn↗