An official website of the United States government
Abstract The question of whether a dynamo can be triggered by gravitational collapse is of great interest, especially for the early Universe. Here, we employ supercomoving coordinates to study the magnetic field amplification from decaying turbulence during gravitational collapse. We perform 3D simulations and show that for large magnetic Reynolds numbers, there can be exponential growth of the comoving magnetic field with conformal time before the decay of turbulence impedes further amplification. The collapse dynamics only affect the nonlinear feedback from the Lorentz force, which diminishes more rapidly for shorter collapse times, allowing nearly kinematic continued growth. We confirm that helical turbulence is more efficient in driving dynamo action than nonhelical turbulence, but this difference decreases for larger collapse times. We also show that for nearly irrotational flows, dynamo amplification is still possible, but it is always associated with a growth of vorticity—even if it still remains very small. In nonmagnetic runs, the growth of vorticity is associated with viscosity and grows with the Mach number. In the presence of magnetic fields, vorticity emerges from the curl of the Lorentz force. During a limited time interval, an exponential growth of the comoving magnetic field with conformal time is interpreted as clear evidence of dynamo action.
more »
« less
A universal scaling law for Lagrangian snowflake accelerations in atmospheric turbulence
We use a novel experimental setup to obtain the vertical velocity and acceleration statistics of snowflakes settling in atmospheric surface-layer turbulence, for Taylor microscale Reynolds numbers (Reλ) between 400 and 67 000, Stokes numbers (St) between 0.12 and 3.50, and a broad range of snowflake habits. Despite the complexity of snowflake structures and the non-uniform nature of the turbulence, we find that mean snowflake acceleration distributions can be uniquely determined from the value of St. Ensemble-averaged snowflake root mean square (rms) accelerations scale nearly linearly with St. Normalized by the rms value, the acceleration distribution is nearly exponential, with a scaling factor for the (exponent) of −3/2 that is independent of Reλ and St; kurtosis scales with Reλ, albeit weakly compared to fluid tracers in turbulence; gravitational drift with sweeping is observed for St < 1. Surprisingly, the same exponential distribution describes a pseudo-acceleration calculated from fluctuations of snowflake terminal fall speed in still air. This equivalence suggests an underlying connection between how turbulence determines the trajectories of particles and the microphysics determining the evolution of their shapes and sizes.
more »
« less
- Award ID(s):
- 2210179
- PAR ID:
- 10613541
- Publisher / Repository:
- AIP Publishing
- Date Published:
- Journal Name:
- Physics of Fluids
- Volume:
- 35
- Issue:
- 12
- ISSN:
- 1070-6631
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
The mechanisms driving the transition to turbulence in pulsatile flows are not well understood. Prior studies in this domain have noted the dynamics of this flow regime to depend on the mean Reynolds number, pulsation frequency (i.e., Womersley number), and inflow pulsatile waveform shape. Conflicting findings, particularly regarding the role of the Womersley number on the critical Reynolds number and the development of turbulence, have been reported. The discord has primarily been observed for flows, with Womersley numbers ranging from 4 to 12. Hence, in this work, we use particle image velocimetry to explore the effects of the Womersley number within this 4–12 range on the dynamics of the pulsatile transition. Eighteen test cases were captured using six mean Reynolds numbers (range 800–4200) and five Womersley numbers. Turbulent kinetic energy, turbulence intensity (TI), and phase lag were computed. Our results indicated that the critical Reynolds number was roughly independent of the Womersley number. At high Womersley numbers, the TI trend maintained lower pulsatility, and the flow was observed to mimic a steady transitional flow regime. A plateau of the TI-velocity and TI-acceleration phase lag was observed at a Womersley number of 8, highlighting that this may be the critical value where further increases to the Womersley number do not alter the transition dynamics. Furthermore, this suggests that the phase lag may provide a universal indicator of the specific influence of the Womersley number on transition for a given flow. Overall, these findings elucidate critical details regarding the role of the Womersley number in the transition to turbulence.more » « less
-
Abstract Numerical model predictions of precipitation rates rely heavily on representations of how fast hydrometeors fall, assuming settling is determined only by the opposing force balance of gravity and drag. Here, we use a novel suite of ground‐based winter measurements to show large departures of the mean snowflake settling speed from the terminal fall speed of a particle falling broadside. Where is lower than the air root‐mean‐square turbulent velocity fluctuation , settling is sub‐terminal by up to a factor of five, and if it is higher, then settling is super‐terminal by up to a factor of three. Mean winds and aerodynamic lift appear to play an unexpectedly important role, by tilting snowflake orientations edge‐on while slowing their mean rate of descent. New parameterizations are provided for relating winds and small‐scale turbulence to hydrometeor orientations, drift angles, and precipitation rate reductions and enhancements.more » « less
-
ABSTRACT In star-forming clouds, high velocity flow gives rise to large fluctuations of density. In this work, we explore the correlation between velocity magnitude (speed) and density. We develop an analytic formula for the joint probability distribution function (PDF) of density and speed, and discuss its properties. In order to develop an accurate model for the joint PDF, we first develop improved models of the marginalized distributions of density and speed. We confront our results with a suite of 12 supersonic isothermal simulations with resolution of $1024^3$ cells in which the turbulence is driven by 3 different forcing modes (solenoidal, mixed, and compressive) and 4 rms Mach numbers (1, 2, 4, 8). We show, that for transsonic turbulence, density and speed are correlated to a considerable degree and the simple assumption of independence fails to accurately describe their statistics. In the supersonic regime, the correlations tend to weaken with growing Mach number. Our new model of the joint and marginalized PDFs are a factor of 3 better than uncorrelated, and provides insight into this important process.more » « less
-
null (Ed.)The effect of turbulence on snow precipitation is not incorporated into present weather forecasting models. Here we show evidence that turbulence is in fact a key influence on both fall speed and spatial distribution of settling snow. We consider three snowfall events under vastly different levels of atmospheric turbulence. We characterize the size and morphology of the snow particles, and we simultaneously image their velocity, acceleration and relative concentration over vertical planes approximately $$30\ \textrm {m}^2$$ in area. We find that turbulence-driven settling enhancement explains otherwise contradictory trends between the particle size and velocity. The estimates of the Stokes number and the correlation between vertical velocity and local concentration are consistent with the view that the enhanced settling is rooted in the preferential sweeping mechanism. When the snow vertical velocity is large compared to the characteristic turbulence velocity, the crossing trajectories effect results in strong accelerations. When the conditions of preferential sweeping are met, the concentration field is highly non-uniform and clustering appears over a wide range of scales. These clusters, identified for the first time in a naturally occurring flow, display the signature features seen in canonical settings: power-law size distribution, fractal-like shape, vertical elongation and large fall speed that increases with the cluster size. These findings demonstrate that the fundamental phenomenology of particle-laden turbulence can be leveraged towards a better predictive understanding of snow precipitation and ground snow accumulation. They also demonstrate how environmental flows can be used to investigate dispersed multiphase flows at Reynolds numbers not accessible in laboratory experiments or numerical simulations.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1063/5.0173359
