Research

This PhD research focuses on the creation of a statistically-derived and historically-based risk analysis methodology for small satellites with an application to the designing, building and flying of CubeSats. Based on experience in the Texas Spacecraft Laboratory (TSL) at the University of Texas at Austin, I developed a Risk Management Plan for CubeSats which became the basis for the statistical risk analysis completed afterwards. Realizing that the traditional Likelihood and Consequence scales, as defined by NASA and the DoD, were highly subjective, I decided to create a more statistical and more objective method of analyzing a CubeSat mission's risks. In order to do this, I needed to gather data from the CubeSat community then analyze it using regression techniques to obtain, what I now call, Risk Estimating Relationships. All this information would then need to be transformed into a useful tool for mission designers, systems engineers, and program managers to be able to use effectively and easily. This tool became known as the CubeSat Risk Tool. These areas of research were initially developed in the order listed below (links have more detail), but are now updated in a cyclic nature.

This research continues thanks to the generous support of the National Defense Science and Engineering Graduate Fellowship (NDSEG) beginning September 2013.

My role in the TSL has been primarily in the systems engineering role and program management. I led the ARMADILLO 3U CubeSat from initial design to winning the University Nanosatellite Program Flight Competition Review. My Master's Thesis developed metrics by which to measure the reusability of satellite design and processes as well as investigated and compared the existing cost models for use on a CubeSat mission.