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.
Matching the Implant to the Breast: A Systematic Review of Implant Size Selection Systems for Breast Augmentation
Background: For primary breast augmentation, several implant selection systems have been described to guide the surgeon with choosing from a variety of manufactured implant dimensions and properties. Controversy exists regarding the most efficacious method of selecting an appropriate implant size that best matches the patient’s breast. Methods: The goal of this systematic review was to provide a comprehensive list of documented implant size selection systems, and to critically evaluate them. Implant size selection systems were grouped into categories based on selection principles. Articles were evaluated based on reported outcome measures and methodologic quality. Results: Thirty-three implant size selection systems were included in the final analysis. Only 12 percent of articles (four of 33) reported clinical outcomes that could be compared to accepted literature values or industry standards. Articles that described tissue-based planning systems, which use clinical guidelines to determine the optimal patient-specific implant dimensions, were of highest methodologic quality using the Methodological Index for Non-Randomised Studies scale, when compared to systems that used breast “dimensional” analyses that stress tissues to the desire of the patient and/or surgeon, and compared to systems that did not use breast measurement (means ± SD, 6.0 ± 1.4, 1.4 ± 2.3, and 0.0 ± 0.0, respectively). Conclusions: There is some evidence to support tissue-based planning as a superior approach to implant size selection planning; studies that used tissue-based planning reported lower reoperation rates compared with industry standards and accepted literature values. The authors offer several suggestions on how to improve the methodologic quality of future studies describing new implant selection systems.