Unknown

Dataset Information

0

Aerodynamic generation of electric fields in turbulence laden with charged inertial particles.


ABSTRACT: Self-induced electricity, including lightning, is often observed in dusty atmospheres. However, the physical mechanisms leading to this phenomenon remain elusive as they are remarkably challenging to determine due to the high complexity of the multi-phase turbulent flows involved. Using a fast multi-pole method in direct numerical simulations of homogeneous turbulence laden with hundreds of millions of inertial particles, here we show that mesoscopic electric fields can be aerodynamically created in bi-disperse suspensions of oppositely charged particles. The generation mechanism is self-regulating and relies on turbulence preferentially concentrating particles of one sign in clouds while dispersing the others more uniformly. The resulting electric field varies over much larger length scales than both the mean inter-particle spacing and the size of the smallest eddies. Scaling analyses suggest that low ambient pressures, such as those prevailing in the atmosphere of Mars, increase the dynamical relevance of this aerodynamic mechanism for electrical breakdown.

SUBMITTER: Di Renzo M 

PROVIDER: S-EPMC5920100 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

Aerodynamic generation of electric fields in turbulence laden with charged inertial particles.

Di Renzo M M   Urzay J J  

Nature communications 20180426 1


Self-induced electricity, including lightning, is often observed in dusty atmospheres. However, the physical mechanisms leading to this phenomenon remain elusive as they are remarkably challenging to determine due to the high complexity of the multi-phase turbulent flows involved. Using a fast multi-pole method in direct numerical simulations of homogeneous turbulence laden with hundreds of millions of inertial particles, here we show that mesoscopic electric fields can be aerodynamically create  ...[more]

Similar Datasets

| S-EPMC3696777 | biostudies-literature
| S-EPMC5521292 | biostudies-other
| S-EPMC8023798 | biostudies-literature
| S-EPMC3790803 | biostudies-other
| S-EPMC7124953 | biostudies-literature
2006-02-01 | GSE4106 | GEO
2023-11-30 | GSE214387 | GEO
| S-EPMC6279816 | biostudies-other
| S-EPMC6065530 | biostudies-literature
| S-EPMC8126200 | biostudies-literature