Title:
Probabilistic algorithms for transition altitude optimization in ballistic airdrop
Probabilistic algorithms for transition altitude optimization in ballistic airdrop
Author(s)
Jumonville, Christopher J.
Advisor(s)
Ferri, Aldo A.
Ueda, Jun
Rogers, Jonathan
Ueda, Jun
Rogers, Jonathan
Editor(s)
Collections
Supplementary to
Permanent Link
Abstract
The development of a transition altitude optimization algorithm for ballistic airdrops is detailed. Ballistic airdrops are unguided, high-altitude, low-opening cargo drops for military or humanitarian purposes. Compared to their guided airdrop counterparts, unguided airdrops are cheaper but have less accurate impact locations since the flight path of unguided airdrops is not controlled. Because of their ability to be deployed in large quantities, efforts have been taken to improve the impact dispersion of unguided airdrops. The algorithm described here aims to increase accuracy and shape the impact dispersion while accounting for relevant sources of uncertainty by optimizing the parachute-package system’s transition altitude, e.g. the altitude of main parachute deployment. A simulation framework that consists of the airdrop dynamic model, atmospheric air density and wind model, and a parachute inflation model is generated. This framework serves as a test bed for algorithm development and testing. Additionally, the creation of complex impact distributions based on real-world map data is detailed. Nonlinear uncertainty propagation is employed to back-propagate the impact distribution through space and time from ground to airdrop altitude. This time-history of the impact distribution is leveraged for the purposed of optimal transition altitude selection. Finally, example results are presented and discussed.
Sponsor
Date Issued
2016-07-27
Extent
Resource Type
Text
Resource Subtype
Thesis