arXiv subjects

Dhrubaditya Mitra

Publications and source records attributed to Dhrubaditya Mitra.

At least 19 recordsLinked to original sources

arXiv2026

Scale-by-scale energy transfers in bubbly flows

Buoyancy-driven bubbly flows naturally have spatially-dependent density fields, which allow for multiple definitions of the scale-dependent (or filtered) energy. A priori, it is not obvious which of these provide the most physically apt scale-by-scale budget. In the present study, we compare two such definitions, based on (a) filtered momentum and filtered velocity (Pandey et al. 2020), and (b) Favre filtered energy (Aluie 2013; Pandey et al. 2023). We also derive a Kármán-Howarth-Monin (KHM) relation using the momentum-velocity correlation function and contrast it with the scale-by-scale energy budget obtained in (a). We find that for the volume fraction and Atwood number explored, irrespective of the definition, energy transfers due to the advective nonlinearity and surface tension are identical. However, discrepancies arise for the buoyancy and pressure contributions. We show that the Favre filtered definition is the more appropriate choice, within which buoyancy injects energy, pressure transfers energy to large scales, and both advective nonlinearity and surface tension transfer energy downscales where it is dissipated by viscosity.

physics.flu-dyn↗

arXiv2026

Intermittency and non-universality of pair dispersion in isothermal compressible turbulence

Statistical properties of the pair dispersion of Lagrangian particles (tracers) in incompressible turbulent flows provide insights into transport and mixing. We explore the same in transonic to supersonic compressible turbulence of an isothermal ideal gas in two dimensions, driven by large-scale solenoidal and irrotational stirring forces, via direct numerical simulations. We find that the scaling exponents of the order-$p$ negative moments of the distribution of exit times -- in particular, the doubling and halving times of pair separations -- are nonlinear functions of $p$. Furthermore, the doubling and halving time statistics are different. The halving-time exponents are universal -- they satisfy their multifractal model-based prediction, irrespective of the nature of the stirring. However, the doubling-time exponents are not. In the solenoidally-stirred flows, the doubling time exponents can be expressed solely in terms of the multifractal scaling exponents obtained from the structure functions of the solenoidal component of the velocity. Moreover, they depend strongly on the Mach number, Ma, as elongated patches of high vorticity emerge along shock fronts at high Ma. In contrast, in the irrotationally-stirred flows, the doubling-time exponents do not satisfy any known multifractal model-based relation, and are independent of Ma. Our findings are of potential relevance to astrophysical disks and molecular clouds wherein turbulent transport and mixing of gases often govern chemical kinetics and the rates of formation of stars and planetesimals.

physics.flu-dyn↗

arXiv2026

The broken link between space and time in elastic turbulence

Elastic turbulence (ET), observed in flows of sufficiently elastic polymer solution at small inertia, is characterized by chaotic motions and power-law scaling of energy spectrum ($E$) in both wavenumber ($k$) and frequency ($ω$): $E(k) \sim k^{-α}$ and $E(ω) \sim ω^{-β}$. Experiments of ET have obtained a vast range of values for the exponent $β$. In inertial turbulence, Taylor's frozen-flow hypothesis implies $α= β$, i.e., spatial and temporal scales are linearly related to each other. In contrast, from high-resolution simulation in three different setups, a tri-periodic box, a channel, and a planar jet, we show that in ET $α\approx 4$ while $β$ varies significantly. Our analysis shows that in general Taylor's hypothesis does not hold in ET as there is no universal relation, linear or otherwise, between space and time. We thus clear the confusion of the different scaling exponents found in ET, and focus the attention of future research on understanding $α$. Our analysis also implies that waves-like dynamics with a linear dispersion relation (e.g., Alfvén waves) can not play a role in determining the scaling behavior of ET. The techniques introduced here can be useful for studying smooth chaotic flows in general, e.g., active turbulence.

physics.flu-dyn↗

arXiv2025

Vector Differential Operators in arbitrary coordinates: a general approach

We present a method for calculating the results of operation of differential operators operating on components of vector in generalized coordinates not restricted to orthogonal one. For this we use the relationships between covariant, contravariant and physical components of a vector and the idea of covariant differentiation. This not only simplifies vector calculus in common curvilinear coordinates, e.g., cylindrical or spherical polar, but also provides a deeper understanding of these operators in coordinate independent form.

physics.gen-ph↗

arXiv2025

Renormalization group analysis of noisy neural field

Neurons in the brain show great diversity in their individual properties and their connections to other neurons. To develop an understanding of how neuronal diversity contributes to brain dynamics and function at large scales we start with a linearized version of the Wilson-Kowan model and introduce a random anisotropy to inter-neuron connection. The resultant model is Edwards-Wilkinson model with a random anisotropic term. Averaging over the quenched randomness with the replica method we obtain a bi-quadratic nonlinearity. We use Wilsonian dynamic renormalization group to analyze this model. We find that, up to one loop order, for dimensions higher than two, the effect of the noise is to change dynamic exponent from two to one.

cond-mat.dis-nn↗

arXiv2024

Anisotropic Magnetized Asteroseismic Waves

We solve for waves in a polytropic, stratified plasmas with a spatially varying background magnetic field that points along a horizontal $x$-direction, and with gravity that is directed along the vertical $z$-direction. Force balance determines the magnitude of the background magnetic field, $B_0^2 \sim z^{n+1}$, where $n$ is the polytropic index. Using numerical and asymptotic methods, we deduce an explicit dispersion relation for fast pressure-driven waves: $Ω^2 \sim K\left(2m+n\right) \left[1 + (1/M_\mathrm{A})^2 (4-2γ+\cos^2θ-3\cos^4θ)/4 \right]$. Here, $Ω$ is the frequency, $K$ the wavenumber, $θ$ the angle the wave-vector makes with the background magnetic field, $M_\mathrm{A}$ the Alfvénic Mach number, and $m$ an integer representing the eigenstate. We discuss roles of such an explicit formula in asteroseismology.

astro-ph.SR↗

arXiv2024

Estimate of entropy generation rate can spatiotemporally resolve the active nature of cell flickering

We use the short-time inference scheme (Manikandan, Gupta and Krishnamurthy, Phys. Rev. Lett. 124, 120603, 2020), obtained within the framework of stochastic thermodynamics, to infer a lower-bound to entropy generation rate from flickering data generated by Interference Reflection Microscopy of HeLA cells. We can clearly distinguish active cell membranes from their ATP depleted selves and even spatio-temporally resolve activity down to the scale of about one $μ$m. Our estimate of activity is model--independent.

cond-mat.soft↗

arXiv2024

Intermittency in the not-so-smooth elastic turbulence

Elastic turbulence is the chaotic fluid motion resulting from elastic instabilities due to the addition of polymers in small concentrations at very small Reynolds ($\mbox{Re}$) numbers. Our direct numerical simulations show that elastic turbulence, though a low $\mbox{Re}$ phenomenon, has more in common with classical, Newtonian turbulence than previously thought. In particular, we find power-law spectra for kinetic energy $E(k) \sim k^{-4}$ and polymeric energy $E_{\rm p}(k) \sim k^{-3/2}$, independent of the Deborah ($\mbox{De}$) number. This is further supported by calculation of scale-by-scale energy budget which shows a balance between the viscous term and the polymeric term in the momentum equation. In real space, as expected, the velocity field is smooth, i.e., the velocity difference across a length scale $r$, $δu \sim r$ but, crucially, with a non-trivial sub-leading contribution $r^{3/2}$ which we extract by using the second difference of velocity. The structure functions of second difference of velocity up to order $6$ show clear evidence of intermittency/multifractality. We provide additional evidence in support of this intermittent nature by calculating moments of rate of dissipation of kinetic energy averaged over a ball of radius $r$, $\varepsilon_{r}$, from which we compute the multifractal spectrum.

physics.flu-dyn↗

arXiv2024

Anomalous diffusion and effective shear modulus in a semi-solid membrane

From the perspective of physical properties, the cell membrane is an exotic two-dimensional material that has a dual nature: it exhibits characteristics of fluids, i.e., lipid molecules show lateral diffusion, while also demonstrating properties of solids, evidenced by a non-zero shear modulus. We construct a model for such a $\textit{semi-solid}$ $\textit{membrane}$. Our model is a fluctuating randomly triangulated mesh with two different kinds of nodes. The solid nodes never change their neighbors, while the fluid nodes do. As the area fraction occupied by the solid nodes ($Φ$) is increased the motion of fluid nodes transition from diffusion to localization via subdiffusion. Next, the solid nodes are pinned to mimic the pinning of the plasma membrane to the cytoskeleton. For the pinned membrane, there exists a range of $Φ$ over which the model has both a non-zero shear modulus and a non-zero lateral diffusivity. The bending modulus, measured through the spectrum of height fluctuations remains unchanged.

cond-mat.soft↗

arXiv2023

Uncovering the multifractality of Lagrangian pair dispersion in shock-dominated turbulence

Lagrangian pair dispersion provides insights into mixing in turbulent flows. By direct numerical simulations (DNS) we show that the statistics of pair dispersion in the randomly forced two-dimensional Burgers equation, which is a typical model of shock-dominated turbulence, is very different from its incompressible counterpart because Lagrangian particles get trapped in shocks. We develop a heuristic theoretical framework that accounts for this -- a generalization of the multifractal model -- whose prediction of the scaling of Lagrangian exit times agrees well with our DNS.

physics.flu-dyn↗

arXiv2023

Flow driven interfacial waves: an inviscid asymptotic study

Motivated by wind blowing over water, we use asymptotic methods to study the evolution of short wavelength interfacial waves driven by the combined action of these flows. We solve the Rayleigh equation for the stability of the shear flow, and construct a uniformly valid approximation for the perturbed streamfunction, or eigenfunction. We then expand the real part of the eigenvalue, the phase speed, in a power series of the inverse wavenumber and show that the imaginary part is exponentially small. We give expressions for the growth rates of the Miles (1957) and rippling (e.g., Young & Wolfe 2013) instabilities that are valid for an arbitrary shear flow. The accuracy of the results is demonstrated by a comparison with the exact solution of the eigenvalue problem in the case when both the wind and the current have an exponential profile.

physics.flu-dyn↗

arXiv2023

Kolmogorov Turbulence Coexists with Pseudo-Turbulence in Buoyancy-Driven Bubbly Flows

We investigate spectral properties of buoyancy driven bubbly flows. Using high-resolution numerical simulations and phenomenology of homogeneous turbulence, we identify the relevant energy transfer mechanisms. We find: (a) At high enough Galilei number (ratio of the buoyancy to viscous forces) the kinetic energy spectrum shows the Kolmogorov scaling with a power law exponent $-5/3$ for the range of scales between the bubble diameter and the dissipation scale ($η$). (b) For scales smaller than $η$, the physics of pseudo-turbulence is recovered.

physics.flu-dyn↗

arXiv2023

Active buckling of pressurized spherical shells : Monte Carlo Simulation

We study the buckling of pressurized spherical shells by Monte Carlo simulations in which the detailed balance is explicitly broken -- thereby driving the shell active, out of thermal equilibrium. Such a shell typically has either higher (active) or lower (quiescent) fluctuations compared to one in thermal equilibrium depending on how the detailed balance is broken. We show that for the same set of elastic parameters, a shell that is not buckled in thermal equilibrium can be buckled if turned active. Similarly, a shell that is buckled in thermal equilibrium can unbuckle if turned quiescent. Based on this result, we suggest that it is possible to experimentally design microscopic elastic shells whose buckling can be optically controlled.

cond-mat.soft↗

arXiv2023

Large is different: non-monotonic behaviour of elastic range scaling in polymeric turbulence at large Reynolds and Deborah numbers

We use direct numerical simulations to study homogeneous, and isotropic turbulent flows of dilute polymer solutions at high Reynolds and Deborah numbers. We find that for small wavenumbers $k$, the kinetic energy spectrum shows Kolmogorov--like behavior which crosses over at a larger $k$ to a novel, elastic scaling regime, $E(k) \sim k^{-ξ}$, with $ξ\approx 2.3$. We study the contribution of the polymers to the flux of kinetic energy through scales, and find that it can be decomposed into two parts: one increase in effective viscous dissipation, and a purely elastic contribution that dominates over the nonlinear flux in the range of $k$ over which the elastic scaling is observed. The multiscale balance between the two fluxes determines the crossover wavenumber which depends non-monotically on the Deborah number. Consistently, structure functions also show two scaling ranges, with intermittency present in both of them in equal measure.

physics.flu-dyn↗

arXiv2022

A Comparative Analysis of Machine-learning Models for Solar Flare Forecasting: Identifying High-performing Active Region Flare Indicators

Solar flares create adverse space weather impacting space and Earth-based technologies. However, the difficulty of forecasting flares, and by extension severe space weather, is accentuated by the lack of any unique flare trigger or a single physical pathway. Studies indicate that multiple physical properties contribute to active region flare potential, compounding the challenge. Recent developments in machine learning (ML) have enabled analysis of higher-dimensional data leading to increasingly better flare forecasting techniques. However, consensus on high-performing flare predictors remains elusive. In the most comprehensive study to date, we conduct a comparative analysis of four popular ML techniques (k-nearest neighbor, logistic regression, random forest classifier, and support vector machine) by training these on magnetic parameters obtained from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) for the entirety of solar cycle 24. We demonstrate that the logistic regression and support vector machine algorithms perform extremely well in forecasting active region flaring potential. The logistic regression algorithm returns the highest true skill score of $0.967 \pm 0.018$, possibly the highest classification performance achieved with any strictly parametric study. From a comparative assessment, we establish that the magnetic properties like total current helicity, total vertical current density, total unsigned flux, R_VALUE, and total absolute twist are the top-performing flare indicators. We also introduce and analyze two new performance metrics, namely, severe and clear space weather indicators. Our analysis constrains the most successful ML algorithms and identifies physical parameters that contribute most to active region flare productivity.

astro-ph.SR↗

arXiv2022

Flexible filament in time-periodic viscous flow: shape chaos and period three

We study a single, freely--floating, inextensible, elastic filament in a linear shear flow: $\mathbf{U}_{0}(x,y) = \dotγ y \hat{x}$. In our model: the elastic energy depends only on bending; the rate-of-strain, $\dotγ = S \sin(ωt)$ is a periodic function of time, $t$; and the interaction between the filament and the flow is approximated by a local isotropic drag force. Based on the shape of the filament we find five different dynamical phases: straight, buckled, periodic (with period two, period three, period four, etc), chaotic, and one with chaotic transients. In the chaotic phase, we show that the iterative map for the angle, which the end-to-end vector of the filament makes with the tangent its one end, has period three solutions; hence it is chaotic. Furthermore, in the chaotic phase the flow is an efficient mixer.

cond-mat.soft↗

arXiv2022

Chaos and irreversibility of a flexible filament in periodically-driven Stokes flow

The flow of Newtonian fluid at low Reynolds number is, in general, regular and time-reversible due to absence of nonlinear effects. For example, if the fluid is sheared by its boundary motion that is subsequently reversed, then all the fluid elements return to their initial positions. Consequently, mixing in microchannels happens solely due to molecular diffusion and is very slow. Here, we show, numerically, that the introduction of a single, freely-floating, flexible filament in a time-periodic linear shear flow can break reversibility and give rise to chaos due to elastic nonlinearities, if the bending rigidity of the filament is within a carefully chosen range. Within this range, not only the shape of the filament is spatiotemporally chaotic, but also the flow is an efficient mixer. Overall, we find five dynamical phases: the shape of a stiff filament is time-invariant -- either straight or buckled; it undergoes a period-two bifurcation as the filament is made softer; becomes spatiotemporally chaotic for even softer filaments but, surprisingly, the chaos is suppressed if bending rigidity is decreased further.

cond-mat.soft↗

arXiv2022

Asymptotic interpretation of the Miles mechanism of wind-wave instability

When wind blows over water, ripples are generated on the water surface. These ripples can be regarded as perturbations of the wind field, which is modelled as a parallel inviscid flow. For a given wavenumber $k$, the perturbed streamfunction of the wind field and the complex phase speed are the eigenfunction and the eigenvalue of the so-called Rayleigh equation in a semi-infinite domain. Because of the small air-water density ratio, $ρ_{\rm{a}}/ρ_{\rm{w}}\equivε<<1$, the wind and the ripples are weakly coupled, and the eigenvalue problem can be solved perturbatively. At the leading order, the eigenvalue is equal to the phase speed $c_0$ of surface waves. At order $ε$, the eigenvalue has a finite imaginary part, which implies growth. Miles (1957) showed that the growth rate is proportional to the square modulus of the leading-order eigenfunction evaluated at the so-called critical level $z=z_c$, where the wind speed is equal to $c_0$ and the waves extract energy from the wind. Here, we construct uniform asymptotic approximations of the leading-order eigenfunction for long waves, which we use to calculate the growth rate as a function of $k$. In the strong wind limit, we find that the fastest growing wave is such that the aerodynamic pressure is in phase with the wave slope. The results are confirmed numerically.

physics.flu-dyn↗