Analytic slowing-down distributions as modified by turbulent transport

The effect of electrostatic microturbulence on fast particles rapidly decreases at high energy, but can be significant at moderate energy. Previous studies found that, in addition to changes in the energetic particle density, this results in nontrivial changes to the equilibrium velocity distribution. These effects have implications for plasma heating and the stability of Alfv\'en eigenmodes, but make multiscale simulations much more difficult without further approximations. Here, several related analytic model distribution functions are derived from first principles with reasonable approximations. A single dimensionless parameter characterizes the relative strength of turbulence relative to collisions, and this parameter appears as an exponent in the model distribution functions. Even the most simple of these models reproduces key features of the numerical phase-space transport solution and provides a useful a priori heuristic for determining how strong the effect of turbulence is on the redistribution of energetic particles in toroidal plasmas.Comment: 13 pages; 6 figure

Validating modelling assumptions of alpha particles in electrostatic turbulence

To rigorously model fast ions in fusion plasmas, a non-Maxwellian equilibrium distribution must be used. In the work, the response of high-energy alpha particles to electrostatic turbulence has been analyzed for several different tokamak parameters. Our results are consistent with known scalings and experimental evidence that alpha particles are generally well-confined: on the order of several seconds. It is also confirmed that the effect of alphas on the turbulence is negligible at realistically low concentrations, consistent with linear theory. It is demonstrated that the usual practice of using a high-temperature Maxwellian gives incorrect estimates for the radial alpha particle flux, and a method of correcting it is provided. Furthermore, we see that the timescales associated with collisions and transport compete at moderate energies, calling into question the assumption that alpha particles remain confined to a flux surface that is used in the derivation of the slowing-down distribution.Comment: 23 pages, 13 figures, submitted to the Journal of Plasma Physic

Autonomic Sonar Sensor Fault Manager for Mobile Robots

NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earth-based control and more dependent on self-configuration and self-decision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and self-adaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining 'enabled' sonars sensors to compensate for those sonar sensors that are 'disabled'. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability

Mobile Robots and Autonomic Ambient Assisted Living

The use of Smart Environments in the delivery of pervasive care is a research topic that has witnessed increasing interest in recent years. These environments aim to deliver pervasive care through ubiquitous sensing by monitoring the occupants Activities of Daily Living. In order for these environments to succeed in achieving their goal, it is crucial that sensors deployed in the environment perform faultlessly. In this research we investigate addressing anomalous sensor behavior through the utilization of a mobile robot. The robot’s role is twofold; it must provide substitution in the presence of suspected sensor faults and act as an observer of anomalous sensor behavior in order to understand the changes that occur in the behavior of sensors deployed within the environment over time. The aim of this work is to explore a paradigm shift to the use of Autonomic Ambient Assisted Living.We have discovered that the use of a mobile robot is a viable means of introducing this paradigm to a Smart Environment