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Noise-stabilized random attractor.

J M Finn1, E R Tracy, W E Cooke

  • 1T-15, Plasma Theory, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|April 12, 2006
PubMed
Summary

A new model simulates edge-localized modes in tokamaks using a two-dimensional flow system. Adding noise to the system bounds burst amplitudes and intervals, offering insights into plasma behavior.

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Area of Science:

  • Plasma physics
  • Nonlinear dynamics
  • Fluid dynamics

Background:

  • Edge-localized modes (ELMs) are crucial phenomena in tokamak fusion devices.
  • Understanding ELM dynamics is key to stable plasma confinement.
  • Deterministic models often fail to capture the complex, noisy behavior of ELMs.

Purpose of the Study:

  • To introduce a novel two-dimensional flow model for simulating ELMs.
  • To investigate the effect of additive noise on burst dynamics.
  • To explore symmetry breaking in the model and its impact on ELM-like behavior.

Main Methods:

  • Development of a deterministic two-dimensional flow model with symmetric bursts.
  • Introduction of additive noise in a specific direction to the model.
  • Analysis of burst amplitude and interburst interval statistics.
  • Study of symmetry breaking effects on model behavior.
  • Comparison with experimental observations from a nonlinear circuit.

Main Results:

  • Deterministic model exhibits successively larger bursts with increasing interburst intervals.
  • Additive noise bounds burst amplitudes and intervals, leading to bounded behavior.
  • Noise allows bursts to switch between positive and negative values.
  • Probability distributions of burst heights and periods are dependent on noise variance.
  • Slight symmetry breaking in the system shows qualitatively similar behavior.

Conclusions:

  • The proposed noisy two-dimensional flow model effectively captures key features of edge-localized modes.
  • Noise plays a critical role in bounding ELM-like burst dynamics.
  • The model's predictions align well with experimental observations from a nonlinear circuit.

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