Output-Based Adaptive Meshing Applied to Space Launch System Booster Separation Analysis
Author(s) -
Derek J. Dalle,
Stuart E. Rogers
Publication year - 2015
Publication title -
33rd aiaa applied aerodynamics conference
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2015-3152
Subject(s) - space shuttle , booster (rocketry) , solid fuel rocket , aerospace engineering , space launch , thrust , aerodynamics , separation (statistics) , computational fluid dynamics , rocket (weapon) , wind tunnel , international space station , drag , computer science , engineering , simulation , propellant , launch vehicle , machine learning
This paper presents details of Computational Fluid Dynamic (CFD) simulations of the Space Launch System during solid-rocket booster separation using the Cart3D inviscid code with comparisons to Overflow viscous CFD results and a wind tunnel test performed at NASA Langley Research Center’s Unitary Plan Wind Tunnel. The Space Launch System (SLS) launch vehicle includes two solid-rocket boosters that burn out before the primary core stage and thus must be discarded during the ascent trajectory. The main challenges for creating an aerodynamic database for this separation event are the large number of basis variables (including orientation of the core, relative position and orientation of the boosters, and rocket thrust levels) and the complex flow caused by the booster separation motors. The solid-rocket boosters are modified from their form when used with the Space Shuttle Launch Vehicle, which has a rich flight history. However, the differences between the SLS core and the Space Shuttle External Tank result in the boosters separating with much narrower clearances, and so reducing aerodynamic uncertainty is necessary to clear the integrated system for flight. This paper discusses an approach that has been developed to analyze about 6000 wind tunnel simulations and 5000 flight vehicle simulations using Cart3D in adaptive-meshing mode. In addition, a discussion is presented of Overflow viscous CFD runs used for uncertainty quantification. Finally, the article presents lessons learned and improvements that will be implemented in future separation databases.
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