Trinity: A Unified Treatment of Turbulence, Transport, and Heating in Magnetized Plasmas

To faithfully simulate ITER and other modern fusion devices, one must resolve electron and ion fluctuation scales in a five-dimensional phase space and time. Simultaneously, one must account for the interaction of this turbulence with the slow evolution of the large-scale plasma profiles. Because of the enormous range of scales involved and the high dimensionality of the problem, resolved first-principles global simulations are very challenging using conventional (brute force) techniques. In this thesis, the problem of resolving turbulence is addressed by developing velocity space resolution diagnostics and an adaptive collisionality that allow for the confident simulation of velocity space dynamics using the approximate minimal necessary dissipation. With regard to the wide range of scales, a new approach has been developed in which turbulence calculations from multiple gyrokinetic flux tube simulations are coupled together using transport equations to obtain self-consistent, steady-state background profiles and corresponding turbulent fluxes and heating. This approach is embodied in a new code, Trinity, which is capable of evolving equilibrium profiles for multiple species, including electromagnetic effects and realistic magnetic geometry, at a fraction of the cost of conventional global simulations. Furthermore, an advanced model physical collision operator for gyrokinetics has been derived and implemented, allowing for the study of collisional turbulent heating, which has not been extensively studied. To demonstrate the utility of the coupled flux tube approach, preliminary results from Trinity simulations of the core of an ITER plasma are presented.Comment: 187 pages, 53 figures, Ph.D. thesis in physics at University of Maryland, single-space versio

Polarised light stress analysis and laser scatter imaging for non-contact inspection of heat seals in food trays

This paper introduces novel non-contact methods for detecting faults in heat seals of food packages. Two alternative imaging technologies are investigated; laser scatter imaging and polarised light stress images. After segmenting the seal area from the rest of the respective image, a classifier is trained to detect faults in different regions of the seal area using features extracted from the pixels in the respective region. A very large set of candidate features, based on statistical information relating to the colour and texture of each region, is first extracted. Then an adaptive boosting algorithm (AdaBoost) is used to automatically select the best features for discriminating faults from non-faults. With this approach, different features can be selected and optimised for the different imaging methods. In experiments we compare the performance of classifiers trained using features extracted from laser scatter images only, polarised light stress images only, and a combination of both image types. The results show that the polarised light and laser scatter classifiers achieved accuracies of 96\% and 90\%, respectively, while the combination of both sensors achieved an accuracy of 95\%. These figures suggest that both systems have potential for commercial development

University ombuds: issues for fair and equitable complaints resolution

Increasingly, universities around Australia are appointing university ombuds to assist in the resolution of student complaints against academics. This paper explores a number of key issues relevant to the dispute resolution practice of university ombuds, particularly in relation to ensuring fair and equitable process and outcomes

Intrinsic rotation in tokamaks: theory

Self-consistent equations for intrinsic rotation in tokamaks with small poloidal magnetic field $B_p$ compared to the total magnetic field $B$ are derived. The model gives the momentum redistribution due to turbulence, collisional transport and energy injection. Intrinsic rotation is determined by the balance between the momentum redistribution and the turbulent diffusion and convection. Two different turbulence regimes are considered: turbulence with characteristic perpendicular lengths of the order of the ion gyroradius, $\rho_i$, and turbulence with characteristic lengths of the order of the poloidal gyroradius, $(B/B_p) \rho_i$. Intrinsic rotation driven by gyroradius scale turbulence is mainly due to the effect of neoclassical corrections and of finite orbit widths on turbulent momentum transport, whereas for the intrinsic rotation driven by poloidal gyroradius scale turbulence, the slow variation of turbulence characteristics in the radial and poloidal directions and the turbulent particle acceleration can be become as important as the neoclassical and finite orbit width effects. The magnetic drift is shown to be indispensable for the intrinsic rotation driven by the slow variation of turbulence characteristics and the turbulent particle acceleration. The equations are written in a form conducive to implementation in a flux tube code, and the effect of the radial variation of the turbulence is included in a novel way that does not require a global gyrokinetic formalism.Comment: 88 pages, 4 figure

Boosting minimalist classifiers for blemish detection in potatoes

This paper introduces novel methods for detecting blemishes in potatoes using machine vision. After segmentation of the potato from the background, a pixel-wise classifier is trained to detect blemishes using features extracted from the image. A very large set of candidate features, based on statistical information relating to the colour and texture of the region surrounding a given pixel, is first extracted. Then an adaptive boosting algorithm (AdaBoost) is used to automatically select the best features for discriminating between blemishes and nonblemishes. With this approach, different features can be selected for different potato varieties, while also handling the natural variation in fresh produce due to different seasons, lighting conditions, etc. The results show that the method is able to build “minimalist” classifiers that optimise detection performance at low computational cost. In experiments, minimalist blemish detectors were trained for both white and red potato varieties, achieving 89.6% and 89.5% accuracy respectively

The Impact of Vein Mechanical Compliance on Arteriovenous Fistula Outcomes

© 2016 Elsevier Inc. Background Arteriovenous fistulae (AVFs) are the preferred access for hemodialysis but suffer a high early failure rate. The aim of this study was to determine how venous distensibility, as measured in vitro, relates to early outcomes of AVF formed with the sampled vein. Methods Ethical approval was obtained for all aspects of this study. During AVF formation a circumferential segment of the target vein was sampled. Mechanical stress testing of the venous segments was undertaken using a dynamic mechanical analyzer, with progressive stress loading at 2 N/min to a maximum of 10 N or until sample disruption. Stress-strain curves were obtained for vein samples and Young's modulus (YM) calculated. Duplex assessment of the fistulae was undertaken at 30 days. Results Thirty patients consented to participate with 29 samples obtained for analysis. Statistical comparison of YM demonstrated no relationship with common cardiovascular risk factors or dialysis status. Subject age greater than 65 was the only patient factor which showed a significant difference in YM (P = 0.05). Furthermore, a negative correlation was confirmed between age and YM (Pearson's r = -0.465, P < 0.05). Nine of the 29 subjects suffered an early AVF failure. Mann-Whitney U testing for differences in distribution reported that YM was significantly higher in those fistulas which failed (P < 0.005). Conclusions Reduced venous compliance appears to result in higher failure rates of AVFs. With the advancement of clinical tools such as speckle tracing ultrasound identification of vessel compliance in vivo may produce valuable additional information for clinicians planning AVF surgery

Considerate Approaches to Achieving Sufficiency for ABC model selection

For nearly any challenging scientific problem evaluation of the likelihood is problematic if not impossible. Approximate Bayesian computation (ABC) allows us to employ the whole Bayesian formalism to problems where we can use simulations from a model, but cannot evaluate the likelihood directly. When summary statistics of real and simulated data are compared --- rather than the data directly --- information is lost, unless the summary statistics are sufficient. Here we employ an information-theoretical framework that can be used to construct (approximately) sufficient statistics by combining different statistics until the loss of information is minimized. Such sufficient sets of statistics are constructed for both parameter estimation and model selection problems. We apply our approach to a range of illustrative and real-world model selection problems