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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.10083 |
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| _version_ | 1866916835973136384 |
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| author | Sanderson, Dawn L. Braverman, Amy Cataldo, Giuseppe Smith, Ralph C. Smith, Richard L. |
| author_facet | Sanderson, Dawn L. Braverman, Amy Cataldo, Giuseppe Smith, Ralph C. Smith, Richard L. |
| contents | In this paper, we employ a Bayesian approach to uncertainty quantification of computer simulations used to assess the probability of rare events. As a case study, we assess the reliability of an Earth reentry capsule for sample return missions that must be able to withstand the reentry loads in order to land intact. Our study uses Gaussian Process modeling under a Bayesian regime to analyze the reentry vehicle's resilience against operational stress. This Bayesian framework allows for a detailed probabilistic evaluation of the system's reliability, indicating our ability to verify stringent safety goals of rare events with a 0.999999 of probability of success. The findings underscore the effectiveness of Bayesian methods for complex uncertainty quantification analyses of computer simulations, providing valuable insights for computational reliability analysis in a risk-averse setting. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_10083 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Case Study on Quantifying Reliability under Extreme Risk Constraints in Space Missions Sanderson, Dawn L. Braverman, Amy Cataldo, Giuseppe Smith, Ralph C. Smith, Richard L. Applications In this paper, we employ a Bayesian approach to uncertainty quantification of computer simulations used to assess the probability of rare events. As a case study, we assess the reliability of an Earth reentry capsule for sample return missions that must be able to withstand the reentry loads in order to land intact. Our study uses Gaussian Process modeling under a Bayesian regime to analyze the reentry vehicle's resilience against operational stress. This Bayesian framework allows for a detailed probabilistic evaluation of the system's reliability, indicating our ability to verify stringent safety goals of rare events with a 0.999999 of probability of success. The findings underscore the effectiveness of Bayesian methods for complex uncertainty quantification analyses of computer simulations, providing valuable insights for computational reliability analysis in a risk-averse setting. |
| title | A Case Study on Quantifying Reliability under Extreme Risk Constraints in Space Missions |
| topic | Applications |
| url | https://arxiv.org/abs/2408.10083 |