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タイトルReliability Analyses and Risk Assessments for Restricted Planetary Sample Return Missions
DOI10.1016/j.ress.2025.112085
本文(外部サイト)https://ntrs.nasa.gov/citations/20250011576
著者(英)Giuseppe Cataldo; Kyle F Grello; Amy Braverman; Peter J Gage
著者所属(英)Goddard Space Flight Center; Goddard Space Flight Center; Jet Propulsion Laboratory; Neerim Corporation
発行日2026-05-01
発行機関などElsevier Science
刊行物名Reliability Engineering and System Safety
巻269
抄録Restricted planetary sample return missions aim to bring back to Earth material from solar system bodies which, according to scientific consensus, might have hosted indigenous life forms. These missions must comply with backward planetary protection requirements to protect the Earth-Moon system from potentially harmful contamination from these bodies. This work describes multidisciplinary reliability analyses used to support the elaboration of an assurance case for a Mars sample return, although the methodology is relevant for any mission in the restricted return category. The assurance case requires both quantitative and qualitative evidence to justify the approach for a safe potential return of the sealed Martian sample tubes that the Perseverance rover has been collecting on Mars. Specifically, standard reliability techniques were employed to assess contributions to quantitative targets that correspond to a 0.999999 probability of maintaining containment of the Martian material through delivery to Earth, while qualitative assessments were made to support a low-credibility impact determination to backward planetary protection. These quantitative targets represent engineering goals that would be assessed to prove that all precautions being taken for the safety of the missions are, or will remain, operational and implemented in a robust manner. A mathematical framework was also created that enables probabilistic success tree analyses with any kind of probability distributions and dependencies among the tree events, while interrogating the relationships between different parts of the tree. This approach extends the state of the art from more traditional probabilistic risk assessments and overcomes the limitations of current reliability analysis software.
NASA分類Space Sciences (General)
ISSN0951-8320
1879-0836
URIhttps://repository.exst.jaxa.jp/dspace/handle/a-is/1428558


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