Turbulence in the intracluster medium: simulations, observables, and thermodynamics

Mohapatra, Rajsekhar; Sharma, Prateek

doi:10.1093/mnras/stz328

Cited by 44 publications

(47 citation statements)

References 60 publications

(87 reference statements)

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“…This discrepancy arises because our simulations are subsonic while their fits are obtained for the transonic regime. A flattening of σ s versus M for M ∼ 1 is also seen in Figure 1 of Mohapatra & Sharma (2019).…”

Section: Density Fluctuation σ S As a Function Of Risupporting

confidence: 57%

“…This implies that thermal SZ fluctuations are easier to convert to velocity fluctuations as compared to X-ray surface brightness fluctuations. This is also true in the presence of thermal instability, as discussed in Mohapatra & Sharma (2019).…”

Section: Discussionmentioning

confidence: 76%

“…(19) as a fitting parameter for Figure 6 and obtain ζ 2 = 0.09 ± 0.02. For Ri = 0 (unstratified turbulence), this reduces to σ 2 s = ln 1 + b 2 M 4 , which reproduces the σρ ∝ M 2 scaling relation in Mohapatra & Sharma (2019). This relation for unstratified turbulence was motivated for subsonic flows by assuming the flow to be close to incompressible.…”

Section: Density Fluctuation σ S As a Function Of Rimentioning

confidence: 72%

“…While the σ s -M fluctuation relation also depends on other parameters such as H P /H S and Ri, the σ ln(P) -M relation is independent of the stratification strength and the pressure and entropy scale heights. In Mohapatra & Sharma (2019), we showed that the σρ-M relation depended on the thermodynamics (heating and cooling) whereas the σP-M relation was independent of the thermodynamics, and still followed the same relation as homogeneous isotropic turbulence. Thus, for subsonic turbulence (M < 1), pressure fluctuations are independent of the thermodynamics and the stratification strength -so they appear more reliable for estimating the velocity dispersion.…”

Section: Pressure Fluctuation σ Ln(p) As a Function Of Rimentioning

confidence: 78%

“…Inspired by the density fluctuation-Mach number relations in Nolan et al (2015); Mohapatra & Sharma (2019) we combine the two rms values of density perturbations and propose a new relation:…”

Section: Density Fluctuation σ S As a Function Of Rimentioning

confidence: 99%

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Turbulence in stratified atmospheres: implications for the intracluster medium

Mohapatra

Federrath

Sharma

2020

Monthly Notices of the Royal Astronomical Society

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The gas motions in the intracluster medium (ICM) are governed by turbulence. However, since the ICM has a radial profile with the centre being denser than the outskirts, ICM turbulence is stratified. Stratified turbulence is fundamentally different from Kolmogorov (isotropic, homogeneous) turbulence; kinetic energy not only cascades from large to small scales, but it is also converted into buoyancy potential energy. To understand the density and velocity fluctuations in the ICM, we conduct high-resolution (1024 2 × 1536 grid points) hydrodynamical simulations of subsonic turbulence (with rms Mach number M ≈ 0.25) and different levels of stratification, quantified by the Richardson number Ri, from Ri = 0 (no stratification) to Ri = 13 (strong stratification). We quantify the density, pressure and velocity fields for varying stratification because observational studies often use surface brightness fluctuations to infer the turbulent gas velocities of the ICM. We find that the standard deviation of the logarithmic density fluctuations (σ s ), where s = ln(ρ/ ρ(z) ), increases with Ri. For weakly stratified subsonic turbulence (Ri 10, M < 1), we derive a new σ s -M-Ri relation, σ 2 s = ln 1 + b 2 M 4 + 0.09M 2 RiH P /H S , where b = 1/3-1 is the turbulence driving parameter, and H P and H S are the pressure and entropy scale heights respectively. We further find that the power spectrum of density fluctuations, P(ρ k / ρ ), increases in magnitude with increasing Ri. Its slope in k-space flattens with increasing Ri before steepening again for Ri 1. In contrast to the density spectrum, the velocity power spectrum is invariant to changes in the stratification. Thus, we find that the ratio between density and velocity power spectra strongly depends on Ri, with the total power in density and velocity fluctuations described by our σ s -M-Ri relation. Pressure fluctuations, on the other hand, are independent of stratification and only depend on M.

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Section: Density Fluctuation σ S As a Function Of Risupporting

confidence: 57%

Section: Discussionmentioning

confidence: 76%

Section: Density Fluctuation σ S As a Function Of Rimentioning

confidence: 72%

Section: Pressure Fluctuation σ Ln(p) As a Function Of Rimentioning

confidence: 78%

Section: Density Fluctuation σ S As a Function Of Rimentioning

confidence: 99%

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Turbulence in stratified atmospheres: implications for the intracluster medium

Mohapatra

Federrath

Sharma

2020

Monthly Notices of the Royal Astronomical Society

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Numerical modeling of two‐phase flows in the presence of dynamic and thermal interactions

Tulegenov,

Kamalova,

Bekenova

et al. 2023

Heat Trans

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The study of turbulent flow in mixtures consisting of gas and particulate matter is a current area of research among modern scientists. The main objective of this area is to prevent the reduction of burnout in flow‐through systems. Therefore, the purpose of this research is to develop a mathematical model of turbulent gas flow with solids to explore the structure of the combustion region in a channel with a partially open boundary to determine the interfacial interaction of the injection of a flat heterogeneous flow in a confined area and the influence of regime parameters on the ignition process. For this purpose, a modeling method was used, which involved using the fundamental laws of continuity of flow, conservation of energy, and the quantity of motion and matter, and an experiment was conducted to reconcile the proposed model with theoretical data. As a result of this work, a model based on the averaged Reynolds Navier–Stokes equations and an algorithm for solving a turbulent subsonic two‐dimensional flow in a heterogeneous medium based on an Euler–Lagrange representation have been developed. Thus, the effects of the parameters of entrainment, temperature, and component concentration on the combustion range and mixing intensity were determined. The proposed methodology can be applied to solve application problems of various kinds, for example, in the design of thermal power plants. The scope of the mathematical and numerical models developed is sufficiently broad that they are universal.

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Investigating the turbulent hot gas in X-COP galaxy clusters

Dupourqué¹,

Clerc²,

Pointecouteau³

et al. 2023

A&A

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Context. Turbulent processes at work in the intracluster medium perturb this environments, impacting its properties, displacing gas, and creating local density fluctuations that can be quantified via X-ray surface brightness fluctuation analyses. Improved knowledge of these phenomena would allow for a more accurate determination of the mass of galaxy clusters, as well as a better understanding of their dynamic assembly. Aims. In this work, we aim to set constraints on the structure of turbulence using X-ray surface brightness fluctuations. We seek to consider the stochastic nature of this observable and to constrain the structure of the underlying power spectrum. Methods. We propose a new Bayesian approach, relying on simulation-based inference to account for the whole error budget. We used the X-COP cluster sample to individually constrain the power spectrum in four regions and within R500. We spread the analysis on the entire set of 12 systems to alleviate the sample variance. We then interpreted the density fluctuations as the result of either gas clumping or turbulence. Results. For each cluster considered individually, the normalisation of density fluctuations correlate positively with the Zernike moment and centroid shift, but negatively with the concentration and the Gini coefficient. The spectral index within R500 and evaluated over all clusters is consistent with a Kolmogorov cascade. The normalisation of density fluctuations, when interpreted in terms of clumping, is consistent within 0.5R500 with the literature results and numerical simulations; however, it is higher between 0.5 and 1R500. Conversely, when interpreted on the basis of turbulence, we deduce a non-thermal pressure profile that is lower than the predictions of the simulations within 0.5 R500, but still in agreement in the outer regions. We explain these results by the presence of central structural residues that are remnants of the dynamical assembly of the clusters.

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Turbulence in the intracluster medium: simulations, observables, and thermodynamics

Cited by 44 publications

References 60 publications

Turbulence in stratified atmospheres: implications for the intracluster medium

Turbulence in stratified atmospheres: implications for the intracluster medium

Numerical modeling of two‐phase flows in the presence of dynamic and thermal interactions

Investigating the turbulent hot gas in X-COP galaxy clusters

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