USING AUTO- AND CROSS-CORRELATIONS FROM SEISMIC NOISE TO MONITOR VELOCITY CHANGES AT VILLARRICA VOLCANO, CHILE

We used the Green's functions from auto-correlations and cross-correlations of seismic ambient noise to monitor temporal velocity changes in the subsurface at Villarrica volcano in the Southern Andes of Chile. Campaigns were conducted from March to October 2010 and February to April 2011 with 8 broadband and 6 short-period stations, respectively. We prepared the data by removing the instrument response, normalizing with a root-mean-square method, whitening the spectra, and filtering from 1 to 10 Hz. This frequency band was chosen based on the relatively high background noise level in that range. Hour-long auto- and cross-correlations were computed and the Green's functions stacked by day and total time. To track the temporal velocity changes we stretched a 24 hour moving window of correlation functions from 90% to 110% of the original and cross correlated them with the total stack. All of the stations' auto-correlations detected what is interpreted as an increase in velocity in 2010, with an average increase of 0.13%. Cross-correlations from station V01, near the summit, to the other stations show comparable changes that are also interpreted as increases in velocity. We attribute this change to the closing of cracks in the subsurface due either to seasonal snow loading or regional tectonics. In addition to the common increase in velocity across the stations, there are excursions in velocity on the same order lasting several days. Amplitude decreases as the station's distance from the vent increases suggesting these excursions may be attributed to changes within the volcanic edifice. In at least two occurrences the amplitudes at stations V06 and V07, the stations farthest from the vent, are smaller. Similar short temporal excursions were seen in the auto-correlations from 2011, however, there was little to no increase in the overall velocity.

Muffler characterization with implementation of the finite element method and experimental techniques

Determining how an exhaust system will perform acoustically before a prototype muffler is built can save the designer both a substantial amount of time and resources. In order to effectively use the simulation tools available it is important to understand what is the most effective tool for the intended purpose of analysis as well as how typical elements in an exhaust system affect muffler performance. An in-depth look at the available tools and their most beneficial uses are presented in this thesis. A full parametric study was conducted using the FEM method for typical muffler elements which was also correlated to experimental results. This thesis lays out the overall ground work on how to accurately predict sound pressure levels in the free field for an exhaust system with the engine properties included. The accuracy of the model is heavily dependent on the correct temperature profile of the model in addition to the accuracy of the source properties. These factors will be discussed in detail and methods for determining them will be presented. The secondary effects of mean flow, which affects both the acoustical wave propagation and the flow noise generation, will be discussed. Effective ways for predicting these secondary effects will be described. Experimental models will be tested on a flow rig that showcases these phenomena.