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Effect of Thermal Protection System on Aerodynamics and Pressure of Reusable Launch Vehicle
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作者 Haipeng P.Chen Yang Yang Zhang Mang 《Space(Science & Technology)》 2025年第1期198-210,共13页
Insulation felt is an essential thermal protection component of reusable launch vehicles.The non-smooth microstructure and local structure,such as gaps or grooves,formed during the laying process of insulation felt ha... Insulation felt is an essential thermal protection component of reusable launch vehicles.The non-smooth microstructure and local structure,such as gaps or grooves,formed during the laying process of insulation felt have a considerable influence on the aerodynamic performance of space shuttles in broad space and velocity areas.In particular,they cause a substantial deviation in the pressure at the flush air data sensing system measurement points in the transonic velocity area,relative to the theoretical shape.This study builds a geometric model of the thermal protection structure according to the optical scanning data of an actual thermal protection structure.A geometric error was added to the thermal protection structure at the aircraft head and wing.The influence of the geometric error on the surface pressure and aerodynamic performance of the aircraft was studied using numerical simulation and experiments with Ma=0.4 to 2.0,angles of attack varying from 3°to 14°,and slide angles of 0°and 5°.The results indicate that the surface pressure deviation of the thermal protection structure on the aircraft head was less than 5%.The surface pressure deviation substantially increased because of the slide angle;it was approximately 7%for Ma=0.95 and a 5°slide angle.Under subsonic and transonic speed conditions,the geometric error caused by the placement of thermal protection may lead to an axial force varying by 12.3%and a pitch moment varying by 5%. 展开更多
关键词 insulation felt aerodynamics thermal protection component aerodynamic performance reusable launch vehiclesthe pressure space shuttles flush air data sensing system
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Machine learning and high-throughput computational guided development of high temperature oxidation-resisting Ni-Co-Cr-Al-Fe based high-entropy alloys
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作者 Xingru Tan William Trehern +10 位作者 Aditya Sundar Yi Wang Saro San Tianwei Lu Fan Zhou Ting Sun Youyuan Zhang Yuying Wen Zhichao Liu Michael Gao Shanshan Hu 《npj Computational Materials》 2025年第1期975-990,共16页
Ni-Co-Cr-Al-Fe-based high-entropy alloys(HEAs)have been demonstrated to possess exceptional oxidation resistance,rendering them promising candidates as bond coats to protect critical components in turbine power system... Ni-Co-Cr-Al-Fe-based high-entropy alloys(HEAs)have been demonstrated to possess exceptional oxidation resistance,rendering them promising candidates as bond coats to protect critical components in turbine power systems.However,with the conventional time-consuming alloy design approach,only a small fraction of Ni-Co-Cr-Al-Fe-based HEAs,focusing on equiatomic compositions,has been explored to date.In this study,we developed an effective design framework with the aid of machine learning(ML)and high throughput computations,enabling the rapid exploration of high-temperature oxidation-resistant non-equiatomic HEAs.This innovative approach leverages ML techniques to swiftly select candidates with superior oxidation resistance within the expansive high-entropy composition landscape.Complemented by a thermodynamic-informed ranking-based selection process,several novel non-equiatomic Ni-Co-Cr-Al-Fe HEA candidates surpassing the oxidation resistance of the state-of-the-art bond coat material MCrAlY have been identified and further experimentally demonstrated.Our findings offer a pathway for the development of advanced bond coats in the realm of next-generation turbine engine technology. 展开更多
关键词 turbine power systemshoweverwith high entropy alloys high throughput co machine learning ml bond coats machine learning oxidation resistance protect critical components
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