Measurement of particle accelerations in fully developed turbulence

By Gregory A. Voth, A. Porta, A. Crawford, Eberhard Bodenschatz, James C. Alexander. Journal of Fluid Mechanics, 2001

456 citations recorded by the source corpus.

We use silicon strip detectors (originally developed for the CLEO III high-energy particle physics experiment) to measure fluid particle trajectories in turbulence with temporal resolution of up to 70000 frames per second. This high frame rate allows the Kolmogorov time scale of a turbulent water flow to be fully resolved for 140 [ges ] Rλ [ges ] 970. Particle trajectories exhibiting accelerations up to 16000 m s −2 (40 times the r.m.s. value) are routinely observed. The probability density function of the acceleration is found to have Reynolds-number-dependent stretched exponential tails. The moments of the acceleration distribution are calculated. The scaling of the acceleration component variance with the energy dissipation is found to be consistent with the results for low-Reynolds-number direct numerical simulations, and with the K41-based Heisenberg–Yaglom prediction for Rλ [ges ] 500. The acceleration flatness is found to increase with Reynolds number, and to exceed 60 at Rλ = 970. The coupling of the acceleration to the large-scale anisotropy is found to be large at low Reynolds number and to decrease as the Reynolds number increases, but to persist at all Reynolds numbers measured. The dependence of the acceleration variance on the size and density of the tracer particles is measured. The autocorrelation function of an acceleration component is measured, and is found to scale with the Kolmogorov time τη.

Subfields: Aerospace Engineering, Computational Mechanics, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/a4c90e86d5bf237759b7cad45353e74fd616bf3e

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Citations in the corpus

Dynamics and statistics of heavy particles in turbulent flows (2006, background): “One of the most striking features that characterize tracers is the very intermittent distribution of the acceleration [28, 29, 31, 35] ; fluctuations as strong as 80 times the root mean square acceleration arms reflect the tendency of tracers to be trapped into vortical structures [28, 50, 51].”
Clustering of aerosol particles in isotropic turbulence (2005, methodology): “and experiments (Yeung 2001; Voth et al. 2002).”
Acceleration statistics of finite-sized particles in turbulent flow: the role of Faxén forces (2008, methodology): “…assess the statistical signature of ‘large’ spherical particles, i.e. whose diameter d is larger than the smallest turbulence scale η. Recent studies (Voth et al. 2002; Qureshi et al. 2007) and detailed comparison between experiments and numerical simulations (Volk et al. 2008a) have shown that…”
The effect of Reynolds number on inertial particle dynamics in isotropic turbulence. Part 1. Simulations without gravitational effects (2015, background): “…In this section, we analyse fluid and inertial particle accelerations ap(t) ≡ dvp(t)/dt. Fluid particle accelerations are known to be strongly intermittent (e.g. see Voth et al. 2002; Ishihara et al. 2007), with the probability of intense acceleration events increasing with the Reynolds number.”
The effect of Reynolds number on inertial particle dynamics in isotropic turbulence. Part 2. Simulations with gravitational effects (2015, unknown): “ the third mechanism to kp( St)=kwith increasing Reynolds number at small values of . 3.3. Particle accelerations In this section, we analyze uid and inertial particle accelerations ap(t) dvp(t)=dt. Voth et al. 2002;Ishihara et al. 2007), with the probability of intense acceleration events increasin”
A random-jet-stirred turbulence tank (2008, background): “Anisotropy in the turbulent intensity (wrms/urms = 1) is common for tanks without symmetric forcing, and for some SF systems as well (Voth et al. 2002).”
Dissipation rate estimation from PIV in zero-mean isotropic turbulence (2009, methodology): “The direct method calculates velocity gradients by differentiating the PIV data in one or two dimensions (Saarenrinne and Piirto 2000; Baldi and Yianneskis 2003; Tanaka and Eaton 2007), while several indirect methods rely on inertial subrange scaling to infer the energy dissipation rate (Sheng et al”
Large-eddy simulation of particle-laden turbulent flows (2008, background): “Measurements, by mean of optical devices, of the acceleration experienced by particles in a turbulent flow (e.g. Mordant et al. 2001; La Porta et al. 2002; Voth et al. 2002), provide evidence that particles are likely to experience accelerations which are many times higher than the acceleration stan”
Bubbly and Buoyant Particle–Laden Turbulent Flows (2020, background): “…〈 a2p 〉 i can be expressed as an enhancement over the fluid acceleration variance 〈 a2f 〉 : 〈 a2p 〉 i〈 a2f 〉 ' 1 + κi( StFr )2 , 8. where κx = 2/(15a0) for the horizontal component, and κy = 1/(15a0) for the vertical component, with a0 the so-called Heisenberg-Yaglom constant (Voth et al. 2002).”
Motion of inertial particles with size larger than Kolmogorov scale in turbulent flows (2008, unknown): “[12].”
Experimental Lagrangian acceleration probability density function measurement (2003, background): “ar X iv :p hy si cs /0 30 30 03 v2 [ ph ys ic s. fl udy We report experimental results on the acceleration component probability distribution function at Rλ = 690 to probabilities of less than 10 −7.”
A quantitative study of three-dimensional Lagrangian particle tracking algorithms (2006, methodology): “The axial velocity component (not shown) is less Gaussian, as noted in Voth et al. (2002) for this flow.”
Two-Particle Dispersion in Isotropic Turbulent Flows (2009, methodology): “[The value of L = 7.1 cm was taken from an earlier paper characterizing this facility (Voth et al. 2002).]”
The three-dimensional Euler equations : Where do we stand? (2008, background): “The second area where quaternions have an application lies in the recent experimental advances that have made in the detection of the trajectories of tracer and other particles in fluid flows [90–99].”