Understanding volcanic processes using UV camera measurements of sulfur dioxide and coincident infrasound and seismicity

The exsolution of volatiles from magma maintains an important control on volcanic eruption styles. The nucleation, growth, and connectivity of bubbles during magma ascent provide the driving force behind eruptions, and the rate, volume, and ease of gas exsolution can affect eruptive activity. Volcanic plumes are the observable consequence of this magmatic degassing, and remote sensing techniques allow us to quantify changes in gas exsolution. However, until recently the methods used to measure volcanic plumes did not have the capability of detecting rapid changes in degassing on the scale of standard geophysical observations. The advent of the UV camera now makes high sample rate gas measurements possible. This type of dataset can then be compared to other volcanic observations to provide an in depth picture of degassing mechanisms in the shallow conduit. The goals of this research are to develop a robust methodology for UV camera field measurements of volcanic plumes, and utilize this data in conjunction with seismoacoustic records to illuminate degassing processes. Field and laboratory experiments were conducted to determine the effects of imaging conditions, vignetting, exposure time, calibration technique, and filter usage on the UV camera sulfur dioxide measurements. Using the best practices determined from these studies, a field campaign was undertaken at Volcán de Pacaya, Guatemala. Coincident plume sulfur dioxide measurements, acoustic recordings, and seismic observations were collected and analyzed jointly. The results provide insight into the small explosive features, variations in degassing rate, and plumbing system of this complex volcanic system. This research provides useful information for determining volcanic hazard at Pacaya, and demonstrates the potential of the UV camera in multiparameter studies.

Kalman Filter approaches on crane swing

The purpose of this study is to explore a Kalman Filter approach to estimating swing of crane-suspended loads. Measuring real-time swing is needed to implement swing damping control strategies where crane joints are used to remove energy from a swinging load. The typical solution to measuring swing uses an inertial sensor attached to the hook block. Measured hook block twist is used to resolve the other two sensed body rates into tangential and radial swing. Uncertainty in the twist measurement leads to inaccurate tangential and radial swing calculations and ineffective swing damping. A typical mitigation approach is to bandpass the inertial sensor readings to remove low frequency drift and high frequency noise. The center frequency of the bandpass filter is usually designed to track the load length and the pass band width set to trade off performance with damping loop gain. The Kalman Filter approach developed here allows all swing motions (radial, tangential and twist) to be measured without the use of a bandpass filter. This provides an alternate solution for swing damping control implementation. After developing a Kalman Filter solution for a two-dimensional swing scenario, the three-dimensional system is considered where simplifying assumptions, suggested by the two-dimensional study, are exploited. One of the interesting aspects of the three-dimensional study is the hook block twist model. Unlike the mass-independence of a pendulum's natural frequency, the twist natural frequency depends both on the pendulum length and the load’s mass distribution. The linear Kalman Filter is applied to experimental data demonstrating the ability to extract the individual swing components for complex motions. It should be noted that the three-dimensional simplifying assumptions preclude the ability to measure two "secondary" hook block rotations. The ability to segregate these motions from the primary swing degrees of freedom was illustrated in the two-dimensional study and could be included into the three-dimensional solution if they were found to be important for a particular application.