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Thermochemical ablation modeling forward uncertainty analysis—Part I: Numerical methods and effect of model parameters
Next generation spacecraft will bring back heavier payloads from explored planets. Advance in the modeling of the thermo-chemical ablation of carbon-based thermal protection system materials is fundamental to improve the design capabilities of these vehicles. Computational fluid dynamic approaches a...
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Published in: | International journal of thermal sciences 2017-08, Vol.118, p.497-509 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Next generation spacecraft will bring back heavier payloads from explored planets. Advance in the modeling of the thermo-chemical ablation of carbon-based thermal protection system materials is fundamental to improve the design capabilities of these vehicles. Computational fluid dynamic approaches are extensively used to model the gas-surface interaction phenomena over ablative materials. The advantage of such kind of approaches is the accurate description of the aerothermal environment obtained through the full resolution of the mechanical, thermal, and chemical boundary layers that develop over an ablative surface when exposed to a high-enthalpy flow. This paper is devoted to the assessment of the uncertainties of such kind of thermo-chemical ablation model and to study their effect on the model final outcomes. A sphere of non-pyrolyzing carbon-based material, exposed to conditions similar to those of a typical plasma wind tunnel test, is the selected test case for the analysis. Two forward non-intrusive uncertainty quantification techniques are used to analyze the influence of the defined set of uncertain parameters on the estimate of steady-state mass blowing flux and surface temperature. Our results show that for the selected conditions, and uncertainty ranges, the surface nitridation reaction probability has the strongest impact on the model outcomes. |
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ISSN: | 1290-0729 1778-4166 |
DOI: | 10.1016/j.ijthermalsci.2017.04.004 |