Towards Multiphase Simulations of Launch Environments for Acoustic Predictions

Speaker: Jordan Angel, Computational Aerosciences Branch, NASA Ames Research Center
March 24, 2022

Presentation

Abstract

Future missions of NASA's Artemis program will utilize new launch vehicle configurations like the Space Launch System (SLS) to deliver assets to lunar orbit. Ignition and liftoff of powerful launch vehicles like SLS can create violent acoustic waves that are potentially dangerous for the vehicle or surrounding support structures. These acoustic waves show both high-frequency broadband noise and lower frequency, high-amplitude ignition and duct overpressure (IOP/DOP) waves. Since the launch of STS-2 (Space Shuttle), water-based sound suppression systems have been used to attenuate and dampen these waves. Time-accurate computational fluid dynamics (CFD) simulations for IOP/DOP wave prediction with water can be numerically challenging especially for high-order methods which may predict a negative speed of sound squared, leading to a numerical instability. Here we demonstrate a new multiphase CFD capability using a high-performance Cartesian framework with a robust high-order numerical method that is provably positivity and boundedness preserving under some mild assumptions. A detailed description of the mathematical model and the numerical scheme can be found in the paper by Wong¹, et al. To date, we have applied this simulation capability to three major studies that include the SLS Scale Model Acoustic Test (SMAT), full scale simulations of the SLS, and simulations of another commercial super heavy lift vehicle. The flow dynamics is complex and extreme however we present results with relatively good agreement to measured data. Next stages of development and future applications will be outlined.

Funded by the NASA’s EGS, LSP, and NESC.

[1] "A Positivity-Preserving High-Order Weighted Compact Nonlinear Scheme for Compressible Gas-Liquid Flows," Wong, et al., Journal of Computational Physics, vol. 444, 2021.

Biography

Jordan Angel is a research scientist in the Computational Aerodynamics Branch of the NASA Advanced Supercomputing Division at NASA Ames Research Center. Jordan joined the Launch, Ascent, and Vehicle Aerodynamics (LAVA) group July 2018. Jordan's research is primarily in high-order numerical methods. He received his Ph.D. in mathematics from Rensselaer Polytechnic Institute in 2018.

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