Uncertainty Propagation in Integrated Airframe Propulsion System Analysis for Hypersonic Vehicles
Air{breathing hypersonic vehicles are based on airframe{integrated SCRAMjet engine. The elongated forebody which serves as the inlet of the engine is subject to harsh aerothermodynamic loading which causes it to deform. Unpredicted deformations may produce unstart, combustor chocking or structural failure due to increased loads. This study presents a framework allowing one to assess the impact of aerothermoelastic deformations on the engine performance prediction. Aerothermoelastic deformations are calculated for trajectories and angle of attack and transferred to a SCRAMjet engine analysis. Uncertainty associated with deformation prediction is propagated to the engine performance analysis. The importance of modeling the aerodynamic heating and aerothermoelastic deformations at the cowl of the inlet is noted. The cowl deformation is the main contributor to uncertainty and sensitivity of the propulsion system analysis.
Error Quantification and Confidence Assessment of Aerothermal Model Predictions for Hypersonic Aircraft (Preprint)
Abstract : Assessing prediction confidence and enabling its use as a decision-making metric for autonomous model fidelity selection is essential to the USAF's vision of a Digital Twin as a viable approach for condition-based fleet management by tail number. Significant strides have been made in modeling complex interactions of the multi-physics, fluid-thermal-structural coupling applicable to hypersonic flow conditions. However, validation of these models remains a challenge due to limited experimental data for hypersonic conditions. This research addresses quantifying errors and assessing the confidence in aerodynamic pressure and heating predictions for a spherical dome protruding from a flat ramp. Well-characterized aerothermal test data from hypersonic wind tunnel experiments are used to calibrate uncertain model parameters and quantify errors through Bayesian techniques. A Bayesian hypothesis testing-based confidence metric is employed to compare the accuracy in various model predictions. A model selection study is performed for 1st-, 2nd-, and 3rd-order piston theories. The results showed that the greatest confidence in model predictions does not necessarily correspond to the highest-order model.
Mass loss of a TEOS-coated, reinforced carbon-carbon composite subjected to a simulted shuttle entry environment
Coated, reinforced carbon-carbon (RCC) is used for the leading edges of the space shuttle. The mass loss characteristics of RCC specimens coated with tetraethyl orthosilicate (TEOS) were determine for conditions which simulated the environment expected at the lug attachment area of the leading edge. Mission simulation included simultaneous application of load, temperature, and oxygen partial pressure. Maximum specimen temperature was 900 K (1160 F). Specimens were exposed for up to 80 simulated missions. Stress levels up to 6.8 MPa (980 psi) did not significantly affect the mass loss characteristics of the TEOS-coated RCC material. Mass loss was correlated with the bulk density of the specimens.