Odd Erik Garcia

The study of large amplitude-fluctuations is relevant to many different fields of science. It is vital to know that the methods used to analyze them are robust and provide reliable results. Conditional sampling and averaging is one such method that is used to extract and estimate various characteristics of large-amplitude events. Former studies analyzing the properties of this method have only concerned themselves with well-separated events, both in time and space. This is not always a guaranty in real-life data as large-amplitude fluctuations may be closely spaced or overlap to the point where underlying small-amplitude events result in large fluctuations. In this study, we examine the conditional sampling and averaging method to identify where its outputs are reliable for different degrees of pulse overlap. To do this, we analyze synthetic test-signals from a superposition of overlapping pulses that were fed through the conditional averaging scheme to unveil the routines limitations in recovering the underlying statistics and metrics of the original signal. Different sampling conditions and input parameters were examined to discover where and how they affect the outputs in the face of pulse overlap. We found that the waveform-estimates of the method are generally reliable for low and moderate degrees of pulse overlap. The amplitude distributions were discovered to break down with increasing pulse overlap. The waiting time distributions were not reliable under any level of pulse overlap. We use our findings to provide recommendations for input parameters and for interpreting the validity of the outputs in combination with other methods.

The impact of sheath dissipation on scrape-off layer (SOL) turbulence and transport in magnetically confined plasmas is investigated using numerical simulations of a reduced two-field fluid model. By varying the sheath dissipation parameter over nearly two orders of magnitude while keeping the parallel particle loss rate fixed, the effects of sheath currents on blob dynamics, radial transport, and plasma profiles are isolated. Linear stability analysis shows that increasing sheath dissipation reduces the growth rate of interchange modes and shifts fluctuations to smaller spatial scales. Across the parameter scan, the simulations exhibit comparatively robust relative fluctuation levels of density across the SOL in the turbulence simulations. The scaling of transport-weighted poloidal blob size and radial velocities with the sheath dissipation parameter is accurately described by a blob velocity scaling theory. The simulation results are analyzed using a stochastic model, which describes the SOL fluctuations as a superposition of uncorrelated radially propagating pulses. The model captures the statistical properties of the simulated fluctuations and predicts an exponential mean-density profile with scale length Ln=V/σn, determined by the blob velocity V and parallel particle loss rate σn. The radial particle density profile steepens with increasing sheath dissipation, consistent with the change in blob propagation. Within the present reduced two-field model, these results demonstrate that effective sheath dissipation strongly influences filament scales, radial propagation, and the resulting SOL density profile. They provide a controlled reference for interpreting how changes in current closure may affect intermittent SOL transport, while motivating future three-dimensional studies with self-consistent parallel dynamics.

Far scrape-off layer fluctuations, also known as blobs/filaments, are compared for the first time across six tokamaks: Alcator C-Mod, DIII-D, TCV, KSTAR, MAST, and MAST-U, under the context of stochastic modeling in Ohmic and low confinement mode scenarios. In this model, which well describes these fluctuations, measurements from Langmuir probes are modeled as a superposition of uncorrelated, two-sided exponential temporal pulses. The key parameters of this model are the mean waiting times between consecutive pulses, the pulse duration times and the mean of the pulse amplitudes. The study examines the influence of line-averaged density, plasma current, magnetic field and aspect ratio. The mean amplitudes and pulse waiting times increase with the line-averaged density across devices, while the pulse duration times remain constant. Whereas the variation in waiting times is gradual across the density scan, the mean amplitudes increase abruptly as the density profile broadens and flattens for Alcator C-Mod. The blob waiting times decrease with increasing plasma current and the toroidal magnetic field, while they increase with aspect ratio for conventional tokamaks. The duration times follow the same trends as the waiting times in these parameters but vary more slowly, resulting in the trends in the waiting times dominating the intermittency level of the fluctuations.

Blob sizes and velocities in the scrape-off layer of the Alcator C-Mod tokamak are analysed using gas puff imaging diagnostics for a series of Ohmically heated, lower single-null diverted plasmas with varying core plasma densities. Results reveal that both average blob size and radial velocity increase gradually with core plasma density, transitioning from sheath-connected to resistive velocity scaling regimes as the empirical discharge density limit is approached. The normalized blob sizes and velocities are comparable to those reported from other devices but the regime transitions differs. The findings presented here provide new insights into the role of collisionality in scrape-off layer transport and its implications for plasma–surface interactions. Predictions for blob parameters in the SPARC tokamak suggest similar scaling regimes, emphasizing the relevance of these results for next-generation fusion devices.

Methods for analyzing the motion of coherent structures in coarse-grained imaging data often face challenges due to the barber pole effect, arising when elongated and tilted structures move at an angle with respect to their axis of symmetry. This study presents a velocity estimation technique that overcomes the barber pole effect while remaining well-suited for coarse-grained imaging data. The proposed method employs two-dimensional conditional averaging to characterize the typical shape and motion of large-amplitude structures passing through a reference point, followed by a maximum tracking or contouring approach to estimate the average trajectory, from which the velocity is calculated. The method is validated using synthetic datasets, demonstrating its accuracy and potential applicability to gas puff imaging and beam emission spectroscopy measurements in magnetically confined plasmas.

This study investigates cross-field particle transport and intermittent fluctuations in the boundary region of magnetically confined plasmas using numerical turbulence simulations based on a reduced two-field fluid model. The model captures turbulent dynamics and blob-like structures in the drift plane perpendicular to the magnetic field, while parametrizing parallel losses in the scrape-off layer through sheath interactions at material surfaces. A systematic analysis of fluctuation statistics is performed by varying the parallel loss rate parameter. Results show that increasing parallel losses steepens the radial particle density profile, enhances the linear growth rate, reduces the dominant fluctuation length scale, increases the relative fluctuation level, and amplifies the intermittency of fluctuations. Despite these changes, the statistical properties of the fluctuations remain consistent across all parallel loss rates. Large-amplitude bursts are well described by a two-sided exponential pulse function, with peak amplitudes and waiting times following exponential distributions, fluctuations obeying Gamma distributions, and frequency spectra exhibiting a Lorentzian shape. These features are accurately captured by a stochastic model based on the superposition of uncorrelated pulses. The methodology presented here offers a robust framework for verifying fluctuation statistics in more advanced boundary turbulence simulation codes.

Fluctuations in the boundary region of the Alcator C-Mod device are investigated with mirror Langmuir probe and gas puff imaging measurements in a series of experiments with a scan in core plasma density. This reveals the familiar broadening and flattening of the radial electron density profile in the scrape-off layer (SOL). A time delay estimation method is applied to deduce blob velocities at various radial positions within the boundary region. In discharges characterized by low core plasma density, the dynamics of blobs manifest in the far SOL, exhibiting radial velocities reaching up to 0.5 km s − 1 . As the core plasma density approaches the empirical discharge density limit, blob dynamics come to dominate the entire SOL, extending even inside the last closed magnetic flux surface with radial velocities exceeding 1 km s − 1 . The fluctuations measured at any given location within the gas puff imaging field-of-view display pronounced intermittency in the region primarily governed by blob structures. Both the radial profiles and the fluctuations are in agreement with a stochastic model describing the blobs as a super-position of uncorrelated pulses moving radially outwards, predicting a particle density profile e-folding length given by the product of the radial blob velocity and the parallel loss time. With increasing core plasma density, the blobs move faster, the average particle density in the far SOL increases and the fluctuations become more intermittent, which will result in enhanced plasma–surface interactions.

In the frequency power spectral density, periodic oscillations appear as a Dirac comb at integer multiples of the frequency of the period. In weakly nonlinear systems or systems close to the primary instability threshold, the periodicity may be perturbed, resulting in deviations from the Dirac comb. We review and discuss a stochastic model of such semiperiodic fluctuations, while also providing several new results which widen the applicability of the model. The fluctuations are described as a superposition of pulses with a fixed shape. Closed form expressions are derived for the frequency power spectral density in the case of periodic pulse arrivals and a random distribution of pulse amplitudes. In general, the spectrum is a Dirac comb located at multiples of the inverse periodicity time and modulated by the pulse spectrum. Deviations from strict periodicity in the arrivals are considered in two ways: either as a random offset to each periodic arrival (jitter) or as independently distributed waiting times between arrivals (renewal). In this contribution, we show that both ways of including deviations from periodicity remove the Dirac comb with remarkable efficiency, leaving mainly the spectrum of the pulse function. Where the jitter process modulates the mass of the higher harmonics, the renewal process leads to spectral broadening. We clarify the effects of random pulse amplitudes on the frequency power spectrum and demonstrate the applicability of normally distributed waiting times to modeling. Contrary to the previous literature, we argue that negative waiting times do not pose problems for the theory, broadening the applicability of the normal approximation. Randomness in the pulse arrival times is investigated by numerical realizations of the process, and the model is used to describe time series of kinetic energy of fluctuating motions in two-dimensional thermal convection.

A stochastic model for a superposition of uncorrelated pulses with a random distribution of and correlations between amplitudes and velocities is analyzed. The pulses are assumed to move radially with fixed shape and amplitudes decreasing exponentially in time due to linear damping. The pulse velocities are taken to be time-dependent with a power law dependence on the instantaneous amplitudes, as suggested by blob velocity scaling theories. In accordance with experimental measurements, the pulse function is assumed to be exponential, and the amplitudes are taken to be exponentially distributed. As a consequence of linear damping and time-dependent velocities, it is demonstrated that the pulses stagnate during their radial motion. This makes the average pulse waiting time increase radially outwards in the scrape-off layer of magnetically confined plasmas. In the case that pulse velocities are proportional to their amplitudes, the mean value of the process decreases exponentially with radial coordinate, similar to the case when all pulses have the same, time-independent velocity. The profile e-folding length is then given by the product of the average pulse velocity and the parallel transit time. Moreover, both the average pulse amplitude and the average velocity are the same at all radial positions due to stagnation of slow and small-amplitude pulses. In general, an increasing average pulse velocity results in a flattened radial profile of the mean value of the process as well as a higher relative fluctuation level, strongly enhancing plasma–surface interactions.