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首页> 外文期刊>Plasma physics and controlled fusion >Nonlinear dynamic analysis of D-alpha signals for type I edge localized modes characterization on JET with a carbon wall
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Nonlinear dynamic analysis of D-alpha signals for type I edge localized modes characterization on JET with a carbon wall

机译：碳墙射流型I边缘局部模式表征D-alpha信号的非线性动力学分析

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摘要

In this paper, the dynamic characteristics of type-I ELM time-series from the JET tokamak, the world's largest magnetic confinement plasma physics experiment, have been investigated. The dynamic analysis has been focused on the detection of nonlinear structure in D a radiation time series. Firstly, the method of surrogate data has been applied to evaluate the statistical significance of the null hypothesis of static nonlinear distortion of an underlying Gaussian linear process. Several nonlinear statistics have been evaluated, such us the time delayed mutual information, the correlation dimension and the maximal Lyapunov exponent. The obtained results allow us to reject the null hypothesis, giving evidence of underlying nonlinear dynamics. Moreover, no evidence of low-dimensional chaos has been found; indeed, the analysed time series are better characterized by the power law sensitivity to initial conditions which can suggest a motion at the 'edge of chaos', at the border between chaotic and regular non-chaotic dynamics. This uncertainty makes it necessary to further investigate about the nature of the nonlinear dynamics. For this purpose, a second surrogate test to distinguish chaotic orbits from pseudoperiodic orbits has been applied. In this case, we cannot reject the null hypothesis which means that the ELM time series is possibly pseudo-periodic. In order to reproduce pseudo-periodic dynamical properties, a periodic state-of-the-art model, proposed to reproduce the ELM cycle, has been corrupted by a dynamical noise, obtaining time series qualitatively in agreement with experimental time series.
机译：在本文中，研究了来自喷气机Tokamak的I型ELM时间系列的动态特性，是世界上最大的磁监管等离子体物理实验。动态分析专注于D A辐射时间序列中的非线性结构的检测。首先，已经应用了代理数据的方法来评估底层高斯线性过程的静态非线性失真的零假设的统计显着性。已经评估了几个非线性统计数据，这些非线性统计数据延迟了相互信息，相关维度和最大Lyapunov指数。获得的结果允许我们拒绝零假设，以潜在的非线性动力学证据。此外，没有发现低维混乱的证据;实际上，分析的时间序列的特征在于对初始条件的初始条件的敏感性更好，这在混沌和常规非混沌动态之间的边界处建议在“混沌边缘”中的运动。这种不确定性使得有必要进一步调查非线性动力学的性质。为此目的，已经应用了将混沌轨道区分开伪二期轨道的第二替代试验。在这种情况下，我们不能拒绝零假设，这意味着ELM时间序列可能是伪周期性的。为了再现伪周期性动态特性，提出了一种先前的最先进的模型，提出了再现ELM循环，已经通过动态噪声损坏，与实验时间序列相一致地获得定性序列。

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