This Ph.D. work focuses on the investigation of numerical methods for estimating the aerodynamics and aerothermodynamics of space objects re-entering the Earth atmosphere. The well-known simplified panel methods applicable to hypersonic aerothermodynamics within continuum and rarefied ﬂow regimes have been implemented in a numerical framework in order to assess different methods and techniques aiming at increasing their accuracy on arbitrarily shaped objects and assemblies. The main tested methods and techniques comprise: the use of a combination of panels visibility detection algorithms, the application of a local radius computation and smoothing algorithm, the introduction of high fidelity-based correction factors, and the definition of general rarefied transitional regime bridging functions for both aerodynamic and aerothermodynamics. Various re-entry scenarios, experimental tests, and literature references have been simulated with the proposed methods in order to understand their accuracy. A preliminary validation of the aerodynamics and aerothermodynamics was performed on different test cases: Space Shuttle Orbiter, Orion Crew Exploration Vehicle, Mars Microprobe, Stardust Sample Return Capsule, VEGA payload fairing, and various other test cases such as spheres, and blunted cones. A particular effort was made to define and apply the methods for allowing the simulation of complete atmospheric re-entry scenarios, in order to simulate and study controlled and uncontrolled re-entres of simple and complex objects assemblies.In order to evaluate the applicability of the proposed methodologies, different re-entry scenarios have been simulated, such as: Stardust SRC (focusing on the thermal protection system ablation and temperature), and the Intermediate Experimental Vehicle (estimating the wall temperature over the re-entry). The last application which has been studied was the estimation of the re-entry human casualty risk as expressed by the space debris mitigation guidelines. For such application, a toy satellite was built and simulated using a statistical approach based on the use of surrogate models and Monte Carlo technique aiming at providing a statistical impact ground footprint along with the human casualty risk distribution for a set of uncertain parameters given as input.
|Date of Award||28 Feb 2020|
- University Of Strathclyde
|Sponsors||University of Strathclyde|
|Supervisor||Edmondo Minisci (Supervisor) & Massimiliano Vasile (Supervisor)|