In the era of global space industry’s rapid expansion,reusable launch technology has the advantage of cost reduction,but makes launch frequency and flight reliability remain critical.This study proposes that Artifici...In the era of global space industry’s rapid expansion,reusable launch technology has the advantage of cost reduction,but makes launch frequency and flight reliability remain critical.This study proposes that Artificial Intelligence(AI)would be the potential disruptive technology to solve these challenges.AI enables transformative capabilities for launch vehicles which are pointed out in four domains:Agile launch operations enabling automate testing,fault diagnosis,and decision-making for targeting hour-level launch cycles and minute-level fault resolution;high-reliability flight enabling real-time autonomous fault diagnosis,mission replanning,and fault-tolerant control within seconds during anomalies,potentially improving reliability by 1–2 orders of magnitude;rapid maintenance enabling real-time health monitoring and lifespan prediction for swift relaunch decisions;efficient space traffic management enabling predict/resolve orbital conflicts amid growing congestion from satellites and debris.The key challenges for AI applications are analyzed as well,including multi-system coupling,uncertain failure modes and narrow flight corridors,limited sensor data,and massive heterogeneous data processing.Finally,the study also proposes that AI promises substantial efficiency gains in launch vehicle design,manufacturing,and testing through multidisciplinary optimization and reduced reliance on physical testing.展开更多
基金supported by the National Natural Science Foundation of China(Nos.52495000 and 52332012).
文摘In the era of global space industry’s rapid expansion,reusable launch technology has the advantage of cost reduction,but makes launch frequency and flight reliability remain critical.This study proposes that Artificial Intelligence(AI)would be the potential disruptive technology to solve these challenges.AI enables transformative capabilities for launch vehicles which are pointed out in four domains:Agile launch operations enabling automate testing,fault diagnosis,and decision-making for targeting hour-level launch cycles and minute-level fault resolution;high-reliability flight enabling real-time autonomous fault diagnosis,mission replanning,and fault-tolerant control within seconds during anomalies,potentially improving reliability by 1–2 orders of magnitude;rapid maintenance enabling real-time health monitoring and lifespan prediction for swift relaunch decisions;efficient space traffic management enabling predict/resolve orbital conflicts amid growing congestion from satellites and debris.The key challenges for AI applications are analyzed as well,including multi-system coupling,uncertain failure modes and narrow flight corridors,limited sensor data,and massive heterogeneous data processing.Finally,the study also proposes that AI promises substantial efficiency gains in launch vehicle design,manufacturing,and testing through multidisciplinary optimization and reduced reliance on physical testing.
