Abstract
This work presents a dedicated plasma wind tunnel experimental methodology that significantly improves the stochastic characterization of TPS catalytic efficiencies when dealing with uncertain measurements and model parameters. We first use synthetic data to test whether the proposed experimental methodology brings any advantages in terms of uncertainty reduction. The evaluation is done using a Bayesian framework developed in a previous work with the advantage of being able to fully and objectively characterize the uncertainty on the calibrated parameters. We then propose a comprehensive set of real wind tunnel cases for which stochastic analyses are carried out. All model parameters are calibrated jointly with the boundary conditions of the experiments. The testing methodology confirms to be a reliable experimental approach able to reduce the uncertainty on the TPS catalytic efficiencies by more than 50%. An account of the posteriors statistics is provided to enrich the current state-of-the-art experimental databases.
| Original language | English (US) |
|---|---|
| Article number | 111528 |
| Journal | Chemical Physics |
| Volume | 559 |
| DOIs | |
| State | Published - Jul 1 2022 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2022 Elsevier B.V.
Keywords
- Bayesian Inference
- Catalysis
- Thermal Protection System
- Uncertainty Quantification