Uncertainty Analysis for Autonomous Entry at Titan
Open Access
- Author:
- Hale, Kendra
- Area of Honors:
- Aerospace Engineering
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Puneet Singla, Thesis Supervisor
Philip John Morris, Thesis Honors Advisor - Keywords:
- aerospace
Monte Carlo
Conjugate Unscented Transformation
Titan
uncertainty analysis
parachute - Abstract:
- Titan, Saturn’s largest moon, is an intriguing subject in space exploration. With its rich atmosphere, and similarities to prebiotic Earth, it is of particular interest in the study of how life begins, in our solar system and in general. In the forty years since the first Titan fly-by, completed by Voyager 1 in 1980, intrigue surrounding the nature of the distant moon’s surface has catalyzed iconic missions; notably, the European Space Agency’s Huygens Probe, which landed on Titan's surface in 2005. Though Huygens is, so far, the only vehicle to land on Titan, there are plans to visit again in the future; Johns Hopkins Applied Physics Laboratory’s Dragonfly is scheduled to land on Titan 2034. The Huygens Probe’s principal objective was to gather atmospheric data during descent. Although Dragonfly also intends to take atmospheric measurements, it will focus primarily on exploring the moon's surface, and therefore has a designated landing site. This significant difference in objectives introduces a variety of constraints to the Dragonfly mission and, in fact, any future missions with predetermined landing targets. Requiring a specific landing target restricts the landing window, the entry state, the craft geometry, the parachute geometry, the parachute deployment scheme, and so on. The primary objective of this thesis is to identify which of the aforementioned parameters have the most predictable influence on some quantities of interest, which include the final state vector, as well as the peak deceleration and maximum stagnation point heat rate. The utility of ideas developed in the analysis will be showcased with numerical simulations. The analysis will use a state-of-the-art uncertainty quantification method known as the Conjugate Unscented Transformation (CUT) method. This method will be used to quantify the effects of variations in the entry state vector, lift-to-drag ratio, and vehicle parameters. The CUT method provides a numerically efficient means of quantifying the variation of multiple parameters, as opposed to traditional methods such as the Monte-Carlo method, which may be computationally inefficient. The CUT method is used to derive a polynomial surrogate model to capture the relationship between input parameters and quantities of interest; input parameters include the entry state and vehicle characteristics, and quantities of interest include the maximum stagnation point heat rate, maximum deceleration, impact velocity, flight path angle at impact, descent time, and total downrange distance. Extensive Monte Carlo simulations are performed to assess the accuracy of the developed polynomial surrogate model. These simulations show that the CUT method, in conjunction with the polynomial model, is able to capture input-output relationships with less than 1\% error. The model is then used to carry out a substantial Monte Carlo analysis. This analysis finds that, overall, the quantities of interest are best predicted by the entry vehicle's lift-drag ratio. Also, the entry vehicle's maximum deceleration is the most predictable quantity of interest. It is worth noting also that each quantity of interest is highly predictable based upon at least one of the input parameters.