Brendan Mindiak
(Advisor: Prof. Ahuja and Prof. Whorton)

will propose a master’s thesis entitled,

Improving the Efficiency and Accuracy of Landing Site Error Calculations for Re-Entry Vehicles

On

Monday, April 29 at 3:30 p.m.
Montgomery Knight 325

Abstract
Upon entering Earth’s atmosphere, a re-entry body is subjected to a series of largely unpredictable conditions. These may include: entry trajectory, entry mass, vehicle drag, sensor error, atmospheric and weather conditions, unexpected perturbations, and any other unforeseen circumstance. These conditions make the modeling and tracking of the re-entry body’s trajectory a highly uncertain process. The cumulative effect of this uncertainty produces an area of possible landing locations, which often takes on the shape of an ellipse. It is often desirable to reduce the size of the landing ellipse or change the ellipse’s location so that the potential landing sites are restricted to a smaller or unpopulated area, increasing the mission safety and the recoverability of the spacecraft. To change the size or location of a landing ellipse, either the re-entry conditions can be altered or a flight control system, such as the system utilized by the space shuttle, can be implemented.

The current process of analyzing landing site error for re-entry missions is highly inefficient. Landing site error is most often determined by stochastically modeling the re-entry trajectory hundreds or thousands of times to observe the statistical distribution of landing sites, known as a Monte-Carlo simulation. In order to achieve an acceptable landing site and error, a Monte-Carlo simulation is performed, then a re-entry condition is changed based on engineering intuition and the process is repeated until the landing conditions satisfy the mission requirements. Attempts to improve the efficiency of this process focus on reducing the computational cost of the Monte-Carlo simulation, either by making edge-case assumptions for the dynamics or by using optimization techniques which struggle to achieve convergence on a solution.

The current study seeks to improve both the efficiency and accuracy of uncertainty modeling. By combining the accuracy of Monte-Carlo simulations with the efficiency of a reference table, a re-entry body’s landing ellipse location and size can be readily determined using only basic information about the atmospheric re-entry conditions and without the need to produce a full trajectory simulation. In this study, the re-entry conditions that define a landing ellipse are reduced to: the velocity magnitude, the flight path angle, the ballistic coefficient, the heading angle, and the latitude of re-entry. This table will be produced for both uncontrolled bodies and bodies with a propulsive flight control system.

The results produced from these five re-entry conditions represent the first method of determining landing site uncertainty that does not require any modeling of the system dynamics. Overall, the current study can be used to explore a wide range of trajectories to fully understand the envelope of hyper-sonic flight conditions and how they apply to different re-entry vehicles, even being able to scale down to extremely small sizes.

Committee

• Prof. Krish Ahuja – GTRI and School of Aerospace Engineering (advisor)
• Prof. Mark Whorton – GTRI and School of Aerospace Engineering (co-advisor)
• Prof. John Dec – School of Aerospace Engineering