Abstract
Modern Thermal Protection Systems (TPS) used for planetary exploration missions often utilize lightweight porous materials as their outer isolating layer. Due to its stochastic nature, such material exhibits a high level of material variability in various properties. Therefore, it is of paramount importance to accurately estimate the uncertainty margin and to understand how material response is affected. In this study, a well-established data-driven algorithm is used to estimate the FiberForm conductivity by using real-time experimental data. By combining the real-time experimental data and a high-fidelity simulation model, the inherent material property is obtained via the proposed method-the retrospective adaptation algorithm. The results also indicate that this methodology is of great potential and can be applied to a wide range of engineering problems, including parameter evaluation, and experimental data processing.
Original language | English |
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Title of host publication | AIAA AVIATION 2022 Forum |
DOIs | |
State | Published - 2022 |
Event | AIAA AVIATION 2022 Forum - Chicago, United States Duration: Jun 27 2022 → Jul 1 2022 |
Publication series
Name | AIAA AVIATION 2022 Forum |
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Conference
Conference | AIAA AVIATION 2022 Forum |
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Country/Territory | United States |
City | Chicago |
Period | 6/27/22 → 7/1/22 |
Bibliographical note
Publisher Copyright:© 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
Funding
Financial support for this work was provided by theNational Science Foundation (CNS-1932105). Additional funding was provided by NASA Kentucky through NASA award No: 80NSSC20M0047, as well as through the NASA ACCESS STRI award No: 80NSSC21K1117. The authors would also like to thank the University of Kentucky Center for Computational Sciences and Information Technology Services Research Computing for their support and use of the Lipscomb Compute Cluster and associated research computing resources. Financial support for this work was provided by the National Science Foundation (CNS-1932105). Additional funding was provided by NASA Kentucky through NASA award No: 80NSSC20M0047, as well as through the NASA ACCESS STRI award No: 80NSSC21K1117. The authors would also like to thank the University of Kentucky Center for Computational Sciences and Information Technology Services Research Computing for their support and use of the Lipscomb Compute Cluster and associated research computing resources.
Funders | Funder number |
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University of Kentucky Medical Center | |
National Science Foundation (NSF) | CNS-1932105 |
National Aeronautics and Space Administration | 80NSSC21K1117, 80NSSC20M0047 |
Kentucky Space Grant Consortium | |
Russian Science Foundation |
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Nuclear Energy and Engineering
- Aerospace Engineering