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Statistically Consistent Dispersion of Line Loads to Uncertain Integrated Forces and Moments

AMS Seminar Series

Speaker: Aaron Burkhead, Computational Aerosciences Branch, NASA Ames Research Center

Presentation

Seminar Slide Deck (PDF-7.3MB)

Abstract

The goal of this work is to describe a method to characterize uncertainty on launch vehicle "line loads" that is consistent with uncertainty in the integrated loads, even if the line loads come from CFD and the integrated loads come from wind tunnel tests. This is motivated by challenges from the engineering of the Space Launch System, where loads analysis is often performed assuming zero aerodynamic uncertainty (but safety factors or similar margin factors try to account for imperfect aerodynamics). A "line load" is a form of distributed aerodynamic loads where a launch vehicle or other shape is split into many slices, and the forces and moments on each slice becomes the database. Estimating the uncertainty in the loads on each slice is insufficient, because neighboring slices may be highly correlated, for example.

This work presents a method to generate line loads that are consistent with integrated force and moment constraints, while also following the statistical distribution underlying the known line load data. This work depends on efforts to tame very-high-dimensional probability density functions (PDFs). The promising results from this novel method are compared against results from applying an existing line load adjustment procedure to the same data set. Potential extension of this research to apply directly to surface pressure data is also discussed.

This work is supported by NASA's SLS Program.

Biography

Aaron Burkhead is a NASA Pathways student in the Computational Aerosciences Branch at NASA Ames Research Center. He is a member of the NASA Ames SLS aerodynamics team and currently pursuing a PhD in Mechanical and Aerospace Engineering from the University of California, Davis. His doctoral work is focused on uncertainty quantification methods, in particular their applications to CFD-based aerodynamic databases. He received his B.S. and M.S. in Mechanical and Aerospace Engineering from the University of California, Davis.