PARTICLE INDUCED TRANSITION IN HIGH-SPEED BOUNDARY-LAYER FLOWS

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Date

2024

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Abstract

Boundary-layer transition to turbulence presents a critical challenge in aerospace engineering due to its impact on thermal load, especially for hypersonic vehicles. This transition, influenced by various disturbances such as acoustic waves, entropy waves, and particle impingement, follows complex and non-unique pathways to turbulence. It significantly affects the surface heat flux and thus will impact the design of thermal protection systems. This dissertation focuses on the transition process initiated by particle impingement, which introduces small-scale disturbances through a complex receptivity process that typically initiates a natural transition path.

Using direct numerical simulations, this study explores the particle-induced transition process. The disturbance spectrum, consisting of both stable and unstable modes along with continuous acoustic contributions, is meticulously reconstructed near the particle impingement site using biorthogonal decomposition to assess the contributions of different eigenmodes to the initial disturbance spectrum. A large number of discrete and continuous eigenmodes are seeded, but the dominant eigenmodes capture only a small fraction of the disturbance energy, with the majority reflected into the freestream through the continuous modes associated with the continuous acoustic branches.

The modeling fidelity is also investigated, particularly the particle-source-in-cell (PSIC) approach, commonly used due to its efficiency in capturing particle-flow interactions. Comparisons with the Immersed-Boundary-Method (IBM), however, reveal that PSIC inadequately captures particle-wall interactions and needs correction for accurate disturbance modeling.

Finally, a reduced-order model is developed for the prediction of particle-induced transition. This model integrates data from high-fidelity simulations, linear stability theory, and a saturation amplitude model while also considering particle characteristics like size, density and concentration. The model’s capability is demonstrated for a wide range of transition scenarios, including data from the HIFiRE-1 flight test, offering a robust tool for rapid transition prediction in hypersonicvehicle design.

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