Browsing Physics by Subject "Alaska"
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Interaction of two tributary glacier branches and implications for surge behaviorA glacier surge is a dynamic phenomenon where the glacier after a long period of quiescence, increases its velocities by up to two orders of magnitude. These surges tend to have complex interactions with tributaries, yet the role of these tributary interactions towards glacier surging has yet to be fully investigated. In this work we construct a synthetic glacier with an adjustable tributary intersection angle to study tributary interaction with the trunk glacier. The geometry we choose is loosely based on the main trunk and tributary interaction of Black Rapids Glacier, AK, USA, which last surged in 1936-1937. We investigate surface elevations, medial moraine locations, and erosive power at the bed of the glacier in response to our adjustable domain and relative flux. A nonlinear relationship between tributary flux and surface elevations is found that indicates flow restrictions can occur with geometries like Black Rapids Glacier. These flow restrictions cause increased ice thicknesses up-glacier which can lead to surges via increased stresses.
Risk analysis of Cordova's microgrid from a complex systems viewpointCordova is a town of approximately 2,000 people located on the southern coast of Alaska. A power grid for a town this size, with a large seasonal fishing economy, is considered a moderate to large sized microgrid in terms of power produced. Understanding the vulnerabilities and risks of failures in such a grid is important for planning and operations and investigating these characteristics in the context of complex system dynamics is novel. The analysis of Cordova's microgrid is a case study relevant to a large class of microgrid communities that could benefit from this work. Our analysis of this grid began by looking at the distribution of all outages from 2003 - 2017 by size, followed by splitting up outages based on certain characteristics and again looking at outage size distribution based on different characteristics. Following this we correlated the outages with different weather patterns and then with the hourly load demand on the system. After doing these analyses we developed a risk metric to give a single numerical value to the risk of an outage occurring during certain time periods and under certain conditions. We looked at risk in the summer versus the winter due to the summer having a much larger load demand, and we also looked at the risk before and after all cables in the grid were buried underground. This gives us an idea of when/under what circumstances the most outages are likely to occur and allows us to run our model of the system, make changes, and determine if those changes were beneficial to the system or not.