scholarly journals Fluctuation-induced force in homogeneous isotropic turbulence

2020 ◽  
Vol 6 (14) ◽  
pp. eaba0461
Author(s):  
Vamsi Spandan ◽  
Daniel Putt ◽  
Rodolfo Ostilla-Mónico ◽  
Alpha A. Lee
Keyword(s):  
Statistical Physics ◽  
Isotropic Turbulence ◽  
Force Generation ◽  
Length Scale ◽  
Nonequilibrium Systems ◽  
Homogeneous Isotropic Turbulence ◽  
Casimir Forces ◽  
Nonmonotonic Function ◽  
Plate Separation ◽  
Reynolds Number Dependence

Understanding force generation in nonequilibrium systems is a notable challenge in statistical physics. We uncover a fluctuation-induced force between two plates immersed in homogeneous isotropic turbulence using direct numerical simulations. The force is a nonmonotonic function of plate separation. The mechanism of force generation reveals an intriguing analogy with fluctuation-induced forces: In a fluid, energy and vorticity are localized in regions of defined length scales. When varying the distance between the plates, we exclude energy structures modifying the overall pressure on the plates. At intermediate plate distances, the intense vorticity structures (worms) are forced to interact in close vicinity between the plates. This interaction affects the pressure in the slit and the force between the plates. The combination of these two effects causes a nonmonotonic attractive force with a complex Reynolds number dependence. Our study sheds light on how length scale–dependent distributions of energy and high-intensity vortex structures determine Casimir forces.

Reynolds number dependence of heavy particles clustering in homogeneous isotropic turbulence

2020 ◽  
Vol 5 (12) ◽  
Author(s):  
Xiangjun Wang ◽  
Minping Wan ◽  
Yan Yang ◽  
Lian-Ping Wang ◽  
Shiyi Chen
Keyword(s):  
Reynolds Number ◽  
Isotropic Turbulence ◽  
Homogeneous Isotropic Turbulence ◽  
Heavy Particles ◽  
Reynolds Number Dependence

Internal Stresses and Breakup of Porous Aggregates in Homogeneous Isotropic Turbulence

2014 ◽  
Author(s):  
Marco Vanni
Keyword(s):  
Numerical Simulation ◽  
Isotropic Turbulence ◽  
Internal Stresses ◽  
Length Scale ◽  
Homogeneous Isotropic Turbulence ◽  
Stokesian Dynamics ◽  
Disordered Structure ◽  
Kolmogorov Length Scale ◽  
Primary Particles ◽  
Internal Forces

The stresses acting on aggregates smaller than the Kolmogorov length scale in homogeneous isotropic turbulence were estimated by a two-scale numerical simulation. The fluid dynamics at the scales larger than the Kolmogorov length scale was calculated by a Direct Numerical Simulation of the turbulent flow, in which the aggregates were modeled as point particles. Then, we adopted Stokesian Dynamics to evaluate the phenomena governed by the smooth velocity field of the smallest scales. At this level the disordered structure of the aggregates was modeled in detail, in order to take into account the role that the primary particles have in generating and transferring the internal stress. From this result, it was possible to evaluate the internal forces acting at intermonomer contacts and determine the occurrence of breakup as a consequence of the failure of intermonomer bonds. The method was applied to disordered aggregates with isostatic and highly hyperstatic structures, respectively.

scholarly journals Reynolds-number dependence of turbulence enhancement on collision growth

2016 ◽  
Vol 16 (19) ◽  
pp. 12441-12455 ◽  
Author(s):  
Ryo Onishi ◽  
Axel Seifert
Keyword(s):  
Reynolds Number ◽  
Isotropic Turbulence ◽  
Reynolds Numbers ◽  
Stokes Number ◽  
Homogeneous Isotropic Turbulence ◽  
Collision Efficiency ◽  
Cloud Droplets ◽  
Clustering Effect ◽  
Reynolds Number Dependence ◽  
Coagulation Kernel

Abstract. This study investigates the Reynolds-number dependence of turbulence enhancement on the collision growth of cloud droplets. The Onishi turbulent coagulation kernel proposed in Onishi et al. (2015) is updated by using the direct numerical simulation (DNS) results for the Taylor-microscale-based Reynolds number (Reλ) up to 1140. The DNS results for particles with a small Stokes number (St) show a consistent Reynolds-number dependence of the so-called clustering effect with the locality theory proposed by Onishi et al. (2015). It is confirmed that the present Onishi kernel is more robust for a wider St range and has better agreement with the Reynolds-number dependence shown by the DNS results. The present Onishi kernel is then compared with the Ayala–Wang kernel (Ayala et al., 2008a; Wang et al., 2008). At low and moderate Reynolds numbers, both kernels show similar values except for r2 ∼ r1, for which the Ayala–Wang kernel shows much larger values due to its large turbulence enhancement on collision efficiency. A large difference is observed for the Reynolds-number dependences between the two kernels. The Ayala–Wang kernel increases for the autoconversion region (r1, r2 < 40 µm) and for the accretion region (r1 < 40 and r2 > 40 µm; r1 > 40 and r2 < 40 µm) as Reλ increases. In contrast, the Onishi kernel decreases for the autoconversion region and increases for the rain–rain self-collection region (r1, r2 > 40 µm). Stochastic collision–coalescence equation (SCE) simulations are also conducted to investigate the turbulence enhancement on particle size evolutions. The SCE with the Ayala–Wang kernel (SCE-Ayala) and that with the present Onishi kernel (SCE-Onishi) are compared with results from the Lagrangian Cloud Simulator (LCS; Onishi et al., 2015), which tracks individual particle motions and size evolutions in homogeneous isotropic turbulence. The SCE-Ayala and SCE-Onishi kernels show consistent results with the LCS results for small Reλ. The two SCE simulations, however, show different Reynolds-number dependences, indicating possible large differences in atmospheric turbulent clouds with large Reλ.

Collision statistics of inertial particles in two-dimensional homogeneous isotropic turbulence with an inverse cascade

2014 ◽  
Vol 745 ◽  
pp. 279-299 ◽  
Author(s):  
Ryo Onishi ◽  
J. C. Vassilicos
Keyword(s):  
Reynolds Number ◽  
Isotropic Turbulence ◽  
Particle System ◽  
Stochastic Simulations ◽  
Collision Kernel ◽  
Inertial Particles ◽  
Two Dimensional ◽  
Homogeneous Isotropic Turbulence ◽  
Local Flow ◽  
Reynolds Number Dependence

AbstractThis study investigates the collision statistics of inertial particles in inverse-cascading two-dimensional (2D) homogeneous isotropic turbulence by means of a direct numerical simulation (DNS). A collision kernel model for particles with small Stokes number ($\mathit{St}$) in 2D flows is proposed based on the model of Saffman & Turner (J. Fluid Mech., vol. 1, 1956, pp. 16–30) (ST56 model). The DNS results agree with this 2D version of the ST56 model for $\mathit{St}\lesssim 0.1$. It is then confirmed that our DNS results satisfy the 2D version of the spherical formulation of the collision kernel. The fact that the flatness factor stays around 3 in our 2D flow confirms that the present 2D turbulent flow is nearly intermittency-free. Collision statistics for $\mathit{St}= 0.1$, 0.4 and 0.6, i.e. for $\mathit{St}<1$, are obtained from the present 2D DNS and compared with those obtained from the three-dimensional (3D) DNS of Onishi et al. (J. Comput. Phys., vol. 242, 2013, pp. 809–827). We have observed that the 3D radial distribution function at contact ($g(R)$, the so-called clustering effect) decreases for $\mathit{St}= 0.4$ and 0.6 with increasing Reynolds number, while the 2D $g(R)$ does not show a significant dependence on Reynolds number. This observation supports the view that the Reynolds-number dependence of $g(R)$ observed in three dimensions is due to internal intermittency of the 3D turbulence. We have further investigated the local $\mathit{St}$, which is a function of the local flow strain rates, and proposed a plausible mechanism that can explain the Reynolds-number dependence of $g(R)$. Meanwhile, 2D stochastic simulations based on the Smoluchowski equations for $\mathit{St}\ll 1$ show that the collision growth can be predicted by the 2D ST56 model and that rare but strong events do not play a significant role in such a small-$\mathit{St}$ particle system. However, the probability density function of local $\mathit{St}$ at the sites of colliding particle pairs supports the view that powerful rare events can be important for particle growth even in the absence of internal intermittency when $\mathit{St}$ is not much smaller than unity.

A general self-preservation analysis for decaying homogeneous isotropic turbulence

2015 ◽  
Vol 773 ◽  
pp. 345-365 ◽  
Author(s):  
L. Djenidi ◽  
R. A. Antonia
Keyword(s):  
Velocity Structure ◽  
Isotropic Turbulence ◽  
Initial Conditions ◽  
Longitudinal Velocity ◽  
Length Scale ◽  
Grid Turbulence ◽  
Homogeneous Isotropic Turbulence ◽  
Kolmogorov Length Scale ◽  
Velocity Structure Function ◽  
Turbulence Data

A general framework of self-preservation (SP) is established, based on the transport equation of the second-order longitudinal velocity structure function in decaying homogeneous isotropic turbulence (HIT). The analysis introduces the skewness of the longitudinal velocity increment, $S(r,t)$ ($r$ and $t$ are space increment and time), as an SP controlling parameter. The present SP framework allows a critical appraisal of the specific assumptions that have been made in previous SP analyses. It is shown that SP is achieved when $S(r,t)$ varies in a self-similar manner, i.e. $S=c(t){\it\phi}(r/l)$ where $l$ is a scaling length, and $c(t)$ and ${\it\phi}(r/l)$ are dimensionless functions of time and $(r/l)$, respectively. When $c(t)$ is constant, $l$ can be identified with the Kolmogorov length scale ${\it\eta}$, even when the Reynolds number is relatively small. On the other hand, the Taylor microscale ${\it\lambda}$ is a relevant SP length scale only when certain conditions are met. The decay law for the turbulent kinetic energy ($k$) ensuing from the present SP is a generalization of the existing laws and can be expressed as $k\sim (t-t_{0})^{n}+B$, where $B$ is a constant representing the energy of the motions whose scales are excluded from the SP range of scales. When $B=0$, SP is achieved at all scales of motion and ${\it\lambda}$ becomes a relevant scaling length together with ${\it\eta}$. The analysis underlines the relation between the initial conditions and the power-law exponent $n$ and also provides a link between them. In particular, an expression relating $n$ to the initial values of the scaling length and velocity is developed. Finally, the present SP analysis is consistent with both experimental grid turbulence data and the eddy-damped quasi-normal Markovian numerical simulation of decaying HIT by Meldi & Sagaut (J. Turbul., vol. 14, 2013, pp. 24–53).

517 Reynolds Number Dependence of Coherent Fine Scale Eddies in Homogeneous Isotropic Turbulence

2001 ◽  
Vol 2001.14 (0) ◽  
pp. 567-568
Author(s):  
Mamoru TANAHASHI ◽  
Shinichiro KIKUCHI ◽  
Shiki IWASE ◽  
Toru YANAGAWA ◽  
Toshio MIYAUCHI
Keyword(s):  
Reynolds Number ◽  
Isotropic Turbulence ◽  
Fine Scale ◽  
Homogeneous Isotropic Turbulence ◽  
Reynolds Number Dependence

scholarly journals Kármán–Howarth theorem for the Lagrangian-averaged Navier–Stokes–alpha model of turbulence

2002 ◽  
Vol 467 ◽  
pp. 205-214 ◽  
Author(s):  
DARRYL D. HOLM
Keyword(s):  
Energy Spectrum ◽  
Dissipation Rate ◽  
Isotropic Turbulence ◽  
Energy Dissipation Rate ◽  
Navier Stokes ◽  
Length Scale ◽  
Two Dimensional ◽  
Homogeneous Isotropic Turbulence ◽  
Third Order ◽  
Kinetic Energy Spectrum

The Lagrangian averaged Navier–Stokes–alpha (LANS-α) model of turbulence is found to possess a Kármán–Howarth (KH) theorem for the dynamics of its second-order autocorrelation functions in homogeneous isotropic turbulence. This KH result implies that alpha-filtering in the LANS-α model of turbulence does not affect the exact Navier–Stokes relation between second and third moments at separation distances large compared to the model's length scale α. Moreover, at separations r that are smaller than α, the KH scaling between energy dissipation rate and longitudinal third-order autocorrelation changes to match the scaling found in two-dimensional incompressible flow. This is consistent with the corresponding change in scaling of the kinetic energy spectrum from k−5/3 for larger scales with kα < 1, which switches to k−3 for smaller scales with kα > 1, as discovered in Foias, Holm & Titi (2001).

scholarly journals Reynolds-number dependence of turbulence enhancement on collision growth

2016 ◽  
Author(s):  
Ryo Onishi ◽  
Axel Seifert
Keyword(s):  
Reynolds Number ◽  
Isotropic Turbulence ◽  
Reynolds Numbers ◽  
Stokes Number ◽  
Homogeneous Isotropic Turbulence ◽  
Collision Efficiency ◽  
Cloud Droplets ◽  
Clustering Effect ◽  
Reynolds Number Dependence ◽  
Coagulation Kernel

Abstract. This study investigates the Reynolds-number dependence of turbulence enhancement on the collision growth of cloud droplets. The Onishi turbulent coagulation kernel proposed in Onishi et al. (2015) is updated by using the direct numerical simulation (DNS) results for the Taylor-microscale-based Reynolds number (Reλ) up to 1,140. The DNS results for particles with a small Stokes number (St) show a consistent Reynolds-number dependence of the so-called clustering effect with the locality theory proposed by Onishi et al. (2015). It is confirmed that the present Onishi kernel is more robust for a wider St range and has better agreement with the Reynolds-number dependence shown by the DNS results. The present Onishi kernel is then compared with the Ayala-Wang kernel (Ayala et al. (2008a); Wang et al. (2008)). At low and moderate Reynolds numbers both kernels show similar values except for r2 ∼ r1, for which the Ayala-Wang kernel shows much larger values due to its large turbulence enhancement on collision efficiency. A large difference is observed for the Reynolds-number dependences between the two kernels. The Ayala-Wang kernel increases for the autoconversion region (r1, r2 < 40 μm) and for the accretion region (r1 < 40 μm and r2 > 40 μm; r1 > 40 μm and r2 < 40 μm) as Reλ increases. In contrast, the Onishi kernel decreases for the autoconversion region and increases for the rain-rain self-collection region (r1, r2 > 40 μm). Stochastic collision-coalescence equation (SCE) simulations are also conducted to investigate the turbulence enhancement on particle size evolutions. The SCE with the Ayala-Wang kernel (SCE-Ayala) and that with the present Onishi kernel (SCE-Onishi) are compared with results from the Lagrangian Cloud Simulator (LCS, Onishi et al. (2015)), which tracks individual particle motions and size evolutions in homogeneous isotropic turbulence. The SCE-Ayala and SCE-Onishi kernels show consistent results with the LCS results for small Reλ. The two SCE simulations, however, show different Reynolds-number dependences, indicating possible large differences in atmospheric turbulent clouds with large Reλ.

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