Enhancing Human Spaceflight Safety Through Spacecraft Survivability Engineering
Notice bibliographique
Résumé
These Lockheed Martin introduced an innovation entitled Spacecraft Survivability (SCS) Engineering to further the advancement of crew safety design techniques for implementation on the Orion CEV contract with NASA awarded in September of 2006. This innovation identified new potential for enhancing crew safety of the Orion vehicle through the adaptation of techniques pioneered for military aircraft survivability. The benefit of this approach became apparent in early applications as vehicle evolution trade studies were undertaken when new advantages of potential designs were identified through the study of design options through SCS and considered in the trade study decisions. Three years after the award, Spacecraft Vulnerability Reduction (SVR) has grown from a concept to an application. Where only System Reliability, Crew Survival and System Safety were applied, SVR brings further closure of gaps to prevent loss of life for potential mishap scenarios by complementing but not duplicating efforts in System Safety, Reliability, and Crew Survival and providing a more comprehensive design and assessment approach. This innovation has been embraced by the aircraft survivability world with recent developments for potential collaboration of efforts. These techniques must be developed and applied to space design, now, in order to support human missions to Mars. The example set by military aircraft programs teaches the road to developing and implementing a structured survivability program is long and could take decades to mature. Collaborative work has begun with the Naval Post Graduate College and NASA in efforts to gain expertise and expand what is traditionally done for spacecraft safety by applying new techniques to support design survivability decisions, drive designs through new survivability requirements, and measure the effectiveness of these techniques through a new system metric. This paper describes the program as envisioned and currently implemented, the achieved and projected benefits to the NASA project Orion, and insight into the future of Survivability and potential benefits beyond Orion to other human and uncrewed space applications where common concerns such as optimizing safety while minimizing weight are priority concerns. Work being performed now includes the Damage Modes and Effects Analysis (DMEA) and Methodology Document written for Spacecraft application, Emergency Return Mode application to affect design and operational scenario development, additional robustness to lowered fault tolerance systems, and program development. The DMEA follows the widely know Failure Modes and Effects Analysis (FMEA). Where the FMEA identifies the possible failures and hazards, the DMEA plays through the failures and analyzes the damage and its cascading events. To this day, safety requirements only look at the susceptibility: “how likely is it to happen?”, and design only to prevent occurrence to a certain level of reliability. SVR is the practice of assuming the hazard has occurred. What then? By identifying these vulnerabilities during the design phase, LM is able to create a safer spacecraft, while having positive impacts on budget and schedule. This paper will propose the potential future of survivability driven design to strengthen the synergy between aircraft and spacecraft as we prepare for the moon, Mars and beyond.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».