Wide-area oblique detonation jet detonation regulation and control method based on deep learning
The invention discloses a wide-area oblique detonation jet detonation regulation and control method based on deep learning, and relates to the field of deep learning. On the premise that a transition detonation database is constructed, classification and discrimination of detonation conditions under...
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creator | HAN XIN BAO YUE LOU JINHUA YOU YANCHENG QIU RUOFAN |
description | The invention discloses a wide-area oblique detonation jet detonation regulation and control method based on deep learning, and relates to the field of deep learning. On the premise that a transition detonation database is constructed, classification and discrimination of detonation conditions under different working conditions and different jet flow conditions are achieved through deep learning, and the detonation conditions serve as a first sub-network. After the jet flow momentum ratio corresponding to the Mach number with the minimum probability in the predicted detonation area is checked to determine the reliability of the first sub-network, a database is built by utilizing the sub-network, a second sub-network is built, and the input of the second sub-network is different working conditions; and outputting a transition point from non-detonation to detonation of the flow field under different working conditions, which is retrieved by relying on the knowledge of the first sub-network, as a reasonable jet |
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After the jet flow momentum ratio corresponding to the Mach number with the minimum probability in the predicted detonation area is checked to determine the reliability of the first sub-network, a database is built by utilizing the sub-network, a second sub-network is built, and the input of the second sub-network is different working conditions; and outputting a transition point from non-detonation to detonation of the flow field under different working conditions, which is retrieved by relying on the knowledge of the first sub-network, as a reasonable jet</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNirEKwjAURbM4iPoPzw8oWCrSVYri5CQ41tfmWiPxvZik_6-gg6PTPYdzp-ZydhYFRzBp591zBFlkFc5Ohe7IvxoxjP6DLJZ6lRzV0wP5ppY6TrD0bhYI5MFRnAxzM7myT1h8d2aW-92pORQI2iIF7iHIbXMsy3pVVvV6s63--bwA2XI9bQ</recordid><startdate>20240510</startdate><enddate>20240510</enddate><creator>HAN XIN</creator><creator>BAO YUE</creator><creator>LOU JINHUA</creator><creator>YOU YANCHENG</creator><creator>QIU RUOFAN</creator><scope>EVB</scope></search><sort><creationdate>20240510</creationdate><title>Wide-area oblique detonation jet detonation regulation and control method based on deep learning</title><author>HAN XIN ; BAO YUE ; LOU JINHUA ; YOU YANCHENG ; QIU RUOFAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN118013846A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>HAN XIN</creatorcontrib><creatorcontrib>BAO YUE</creatorcontrib><creatorcontrib>LOU JINHUA</creatorcontrib><creatorcontrib>YOU YANCHENG</creatorcontrib><creatorcontrib>QIU RUOFAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>HAN XIN</au><au>BAO YUE</au><au>LOU JINHUA</au><au>YOU YANCHENG</au><au>QIU RUOFAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Wide-area oblique detonation jet detonation regulation and control method based on deep learning</title><date>2024-05-10</date><risdate>2024</risdate><abstract>The invention discloses a wide-area oblique detonation jet detonation regulation and control method based on deep learning, and relates to the field of deep learning. On the premise that a transition detonation database is constructed, classification and discrimination of detonation conditions under different working conditions and different jet flow conditions are achieved through deep learning, and the detonation conditions serve as a first sub-network. After the jet flow momentum ratio corresponding to the Mach number with the minimum probability in the predicted detonation area is checked to determine the reliability of the first sub-network, a database is built by utilizing the sub-network, a second sub-network is built, and the input of the second sub-network is different working conditions; and outputting a transition point from non-detonation to detonation of the flow field under different working conditions, which is retrieved by relying on the knowledge of the first sub-network, as a reasonable jet</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Wide-area oblique detonation jet detonation regulation and control method based on deep learning |
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