Defect Diagnosis in Solid Rocket Motors Using Sensors and Deep Learning Networks
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Veröffentlicht in: | AIAA journal 2021-01, Vol.59 (1), p.276-281 |
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creator | Liu, Dongxu Sun, Lizhi Miller, Timothy C |
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doi_str_mv | 10.2514/1.J059600 |
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All rights reserved. All requests for copying and permission to reprint should be submitted to CCC at ; employ the eISSN to initiate your request. See also AIAA Rights and Permissions .</rights><rights>Copyright © 2020 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the eISSN 1533-385X to initiate your request. 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source | Alma/SFX Local Collection |
subjects | Deep learning Defects Environmental engineering Finite element analysis Machine learning Rocket engines Rockets Sensors Simulation Solid propellant rocket engines Stress concentration Thermal cycling |
title | Defect Diagnosis in Solid Rocket Motors Using Sensors and Deep Learning Networks |
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