Uncertainty and sensitivity study on blunt body's drag and heat reduction with combination of spike and opposing jet. (February 2020)

• Record Type: Journal Article
• Authors: Wang, Sheng; Zhang, Wei; Cai, Fangjie; Wang, Qiang; Yan, Chao
• Is Part Of: Acta astronautica. Volume 167(2020)
• Page Start: 52
• Page End: 62
• Publication Date: 2020-02
• Subjects: Uncertainty quantification -- Sensitivity analysis -- Drag and heat reduction -- Spike -- Opposing jet; Astronautics -- Periodicals; Outer space -- Exploration -- Periodicals; Astronautics; Periodicals; 629.405
• DOI: 10.1016/j.actaastro.2019.10.045
• Languages: English
• ISSNs: 0094-5765

Abstract

Abstract: Uncertainty and sensitivity study of three main parameters including length-to-diameter ratio, nozzle radius and total pressure ratio on the drag and heat reduction for the blunt body with spike and opposing jet is conducted. According to the simulation results obtained from the computational fluid dynamics, the relationship between input parameters and aerodynamic force/heat is established via the point-collocation non-intrusive polynomial chaos method. Uncertainties of pressure and heat flux caused by changes of input parameters are quantified. Sensitivity analysis is carried out to determine key parameters affecting pressure and heat flux changes. The results indicate that changes of peak pressure and peak heat flux are resulted from significant change in reattachment shock strength which varies with input parameters. Sensitivity analysis reveals that the length-to-diameter ratio has huge influence on the uncertainty in the recirculation zone, while the nozzle radius dominates the uncertainty in the reattachment zone. Moreover, it is found that the nozzle radius has an enormous effect on peak pressure and peak heat flux, and a significant negative correlation between them is identified. Highlights: Uncertainty quantification and sensitivity analysis of three main parameters on the drag and heat reduction are conducted. Relative contribution of each parameter to uncertainty is ranked. The key parameters contributing most to the uncertainty are identified.