Coupled Flow, Radiation, and Ablation Simulations of Atmospheric Entry Vehicles using the Hybrid Statistical Narrow Band Model

Abstract

A model for coupled flow, radiation, and ablation calculations along the stagnation lines of atmospheric entry vehicles is developed to study the effects these coupled phenomena have on each other as well as the predicted quantities of interest to vehicle designers. The flow model is based on the two-temperature, multicomponent, reacting Navier-Stokes equations coupled to radiative heat and photochemistry source terms and reduced to onedimension using the dimensionally reduced Navier-Stokes approximation. The radiative source terms are computed using the hybrid statistical narrow band model developed at the EM2C laboratory at Ecole Centrale Paris. This model has previously been shown to accurately produce radiative properties at significantly reduced computational cost when compared to line-by-line calculations for uncoupled flows without ablation. In this work, the hybrid statistical narrow band model is coupled to the one-dimensional stagnation line flow solver with ablation. Ablation is treated through a simple steady-state ablation boundary condition with finite-rate heterogenous reactions capable of simulating ablation products blowing into the boundary layer. The model is first used to simulate the effect of carbonaceous species in a typical boundary layer environment. In particular, it is shown that a boundary layer contaminated with a relatively small amount of ablation and pyrolysis products can have significantly lower transmissivities than a boundary layer with pure air. Finally, the peak heating point for the Apollo 4 command module is analyzed using each of the four possible coupling strategies: flow, flow and ablation, flow and radiation, and fully coupled. It is shown that for this case, radiation coupling is the dominant phenomena due to a relatively small carbon yield in the boundary layer. In addition, comparison of cumulative intensities with the radiometer measurement made during the flight shows excellent agreement and confirms the assumption that the radiometer cavity has little effect on the measured intensity due to the low amount of carbon present in the cavity.

Linear Theory of Hypersonic Shocks Interacting with Turbulence in Air

“…Hence, estimating the intense aerothermodynamic loads at which the vehicle will be is vital for the mission's success. In this context, besides 90% of the energy is dissipated into the atmosphere by convection and radiation, the remainder requires additional technologies [98].…”

On binary scaling and ground-to-flight extrapolation in high-enthalpy facilities

“…4.1 Calculated radiative cooling at stagnation point for Earth and gas giants (a) [188] and for Venus (b) [42] Notice that the deviation from the adiabatic case does indeed become non-negligible for Γ > 0.01. 4.2 Effect of the non-adiabaticity of the convective heat flux using numerical results from [70] (stars), [6] (circles), [67] (squares), [210] (diamonds), [95] (triangles pointing to the right), [165] (triangle pointing downwards), [174] (triangles pointing upwards). 8.3 Sensitivity of type-E thermocouples according to the calibration of Lourel et al [112] compared to the polynomial fit of the NIST database [1].…”

“…That renewed interest was also motivated by the availability of flight data from the atmospheric entry of probes such as Stardust (2006) 2005). The number of publications on the topic that can be found in the literature since the last decade illustrates the renewed interest of the scientific community for these issues (see for example [67,80,52,95,118,165,174,186,210]). …”

“…Nevertheless, an equivalent to figure 4.1 was developed for the convective heat flux, based on the results of numerical studies for air [6,67,95,165,174] and for Titan [210]. A least-square optimization was then performed on those datapoints to obtain an expression similar to that of Tauber [70] (stars), [6] (circles), [67] (squares), [210] (diamonds), [95] (triangles pointing to the right), [165] (triangle pointing downwards), [174] …”

“…A least-square optimization was then performed on those datapoints to obtain an expression similar to that of Tauber [70] (stars), [6] (circles), [67] (squares), [210] (diamonds), [95] (triangles pointing to the right), [165] (triangle pointing downwards), [174] …”