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• W2782995109 abstract "A numerical simulation model of plasma flows and electromagnetic waves around a vehicle was developed to predict a radio frequency blackout. Plasma flows in the shock layer and the wake region were calculated using a computational fluid dynamics technique with a three-dimensional model. A finite-catalytic wall condition known to affect plasma properties, such as the number density of electrons, was considered for accurate prediction. A parametric study was performed to investigate the effect of uncertainty in the chemical reaction rate model on evaluating a radio frequency blackout. The behavior of electromagnetic waves in plasma was investigated using a frequency-dependent finite-difference time-domain method. Numerical simulations of reentry blackout were performed for the Atmospheric Reentry Demonstrator mission at various altitudes. The plasma flows and the complex movement of electromagnetic waves around the Atmospheric Reentry Demonstrator vehicle were clarified. The predicted signal loss profile was then directly compared with the experimental flight data to validate the present models. The numerical results generally reproduced the trends over altitudes of the measured data. It is suggested that the present simulation model can be used to investigate the radio frequency blackout and signal loss of electromagnetic waves in the communication of a reentry vehicle. It was confirmed that high associative ionization reaction rates contribute to reducing the electron density in the wake region and radio frequency blackout. It is suggested that the accuracy of predicting the signal loss improved when considering the uncertainty in the chemical reaction model for associative ionizations." @default.
• W2782995109 created "2018-01-26" @default.
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• W2782995109 date "2018-01-01" @default.
• W2782995109 modified "2023-10-01" @default.
• W2782995109 title "Reentry blackout prediction for atmospheric reentry demonstrator mission considering uncertainty in chemical reaction rate model" @default.
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• W2782995109 doi "https://doi.org/10.1063/1.5010713" @default.
• W2782995109 hasPublicationYear "2018" @default.
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