Stochastic structures in the low-frequency plasma turbulence: measurement of characteristics and determination of general features

Results are presented from the experimental and statistical studies of low-frequency turbulence in a magnetized plasma. It is shown that, for all types of driving instability (drift, ion-acoustic, MHD instability), this turbulence is accompanied by the formation of stochastic structures demonstratin...

Повний опис

Збережено в:
Бібліографічні деталі
Опубліковано в: :Вопросы атомной науки и техники
Дата:2000
Автори: Skvortsova, N.N., Sarksyan, K.A., Kharchev, N.K.
Формат: Стаття
Мова:Англійська
Опубліковано: Національний науковий центр «Харківський фізико-технічний інститут» НАН України 2000
Теми:
Онлайн доступ:https://nasplib.isofts.kiev.ua/handle/123456789/78503
Теги: Додати тег
Немає тегів, Будьте першим, хто поставить тег для цього запису!
Назва журналу:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Цитувати:Stochastic structures in the low-frequency plasma turbulence: measurement of characteristics and determination of general features / N.N. Skvortsova, K.A. Sarksyan, N.K. Kharchev // Вопросы атомной науки и техники. — 2000. — № 6. — С. 24-26. — Бібліогр.: 8 назв. — англ.

Репозитарії

Digital Library of Periodicals of National Academy of Sciences of Ukraine
Опис
Резюме:Results are presented from the experimental and statistical studies of low-frequency turbulence in a magnetized plasma. It is shown that, for all types of driving instability (drift, ion-acoustic, MHD instability), this turbulence is accompanied by the formation of stochastic structures demonstrating a statistically consistent behavior and similar correlation, spectral, probability characteristics. The stochastic structures that are existing in the state of dynamic equilibrium and non-random interaction determine all common features of very different turbulent processes: ionacoustic nonlinear solitons, drift vortices, and MHD spatial structures. It follows that the structural turbulence is a non-Gaussian probability process with the long memory, i.e., a self-similar probability process.
ISSN:1562-6016