Seong Hyeon Hong, Claire Drnek, Austin Downey, Yi Wang, J. Dodson
{"title":"结构高速率动态事件的实时模型更新算法","authors":"Seong Hyeon Hong, Claire Drnek, Austin Downey, Yi Wang, J. Dodson","doi":"10.1115/smasis2020-2439","DOIUrl":null,"url":null,"abstract":"\n Real-time model updating of active structures subject to unmodeled high-rate dynamic events require structural model updates on the timescale of 2 ms or less. Examples of active structures subjected to unmodeled high-rate dynamic events include hypersonic vehicles, active blast mitigation, and orbital infrastructure. Due to the unmodeled nature of the events of interest, the real-time model updating algorithm should circumvent any model pre-calculations. In this work, we present a methodology that updates the finite element analysis (FEA) model of a structure experiencing varying dynamics through online measurements. The algorithm is demonstrated for a testbed, comprised of a cantilever beam and a roller that serves as movable support. The structure’s state is updated (i.e. the position of the moving roller) by continuously updating the associated FEA model through an online adaptive meshing and search algorithm. The structure’s state is continuously estimated by comparing the measured signals with FEA models. New FEA models are built based on the enhanced estimate of the structure’s state through adaptive meshing for modal analysis and adaptive search space for the FEA model selection. The proposed methodology is verified experimentally in real-time using the testbed. It is demonstrated that the adaptive features can achieve accurate state estimations within the required 2 ms timescale.","PeriodicalId":118010,"journal":{"name":"ASME 2020 Conference on Smart Materials, Adaptive Structures and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Real-Time Model Updating Algorithm for Structures Experiencing High-Rate Dynamic Events\",\"authors\":\"Seong Hyeon Hong, Claire Drnek, Austin Downey, Yi Wang, J. Dodson\",\"doi\":\"10.1115/smasis2020-2439\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Real-time model updating of active structures subject to unmodeled high-rate dynamic events require structural model updates on the timescale of 2 ms or less. Examples of active structures subjected to unmodeled high-rate dynamic events include hypersonic vehicles, active blast mitigation, and orbital infrastructure. Due to the unmodeled nature of the events of interest, the real-time model updating algorithm should circumvent any model pre-calculations. In this work, we present a methodology that updates the finite element analysis (FEA) model of a structure experiencing varying dynamics through online measurements. The algorithm is demonstrated for a testbed, comprised of a cantilever beam and a roller that serves as movable support. The structure’s state is updated (i.e. the position of the moving roller) by continuously updating the associated FEA model through an online adaptive meshing and search algorithm. The structure’s state is continuously estimated by comparing the measured signals with FEA models. New FEA models are built based on the enhanced estimate of the structure’s state through adaptive meshing for modal analysis and adaptive search space for the FEA model selection. The proposed methodology is verified experimentally in real-time using the testbed. It is demonstrated that the adaptive features can achieve accurate state estimations within the required 2 ms timescale.\",\"PeriodicalId\":118010,\"journal\":{\"name\":\"ASME 2020 Conference on Smart Materials, Adaptive Structures and Intelligent Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ASME 2020 Conference on Smart Materials, Adaptive Structures and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/smasis2020-2439\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASME 2020 Conference on Smart Materials, Adaptive Structures and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/smasis2020-2439","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-Time Model Updating Algorithm for Structures Experiencing High-Rate Dynamic Events
Real-time model updating of active structures subject to unmodeled high-rate dynamic events require structural model updates on the timescale of 2 ms or less. Examples of active structures subjected to unmodeled high-rate dynamic events include hypersonic vehicles, active blast mitigation, and orbital infrastructure. Due to the unmodeled nature of the events of interest, the real-time model updating algorithm should circumvent any model pre-calculations. In this work, we present a methodology that updates the finite element analysis (FEA) model of a structure experiencing varying dynamics through online measurements. The algorithm is demonstrated for a testbed, comprised of a cantilever beam and a roller that serves as movable support. The structure’s state is updated (i.e. the position of the moving roller) by continuously updating the associated FEA model through an online adaptive meshing and search algorithm. The structure’s state is continuously estimated by comparing the measured signals with FEA models. New FEA models are built based on the enhanced estimate of the structure’s state through adaptive meshing for modal analysis and adaptive search space for the FEA model selection. The proposed methodology is verified experimentally in real-time using the testbed. It is demonstrated that the adaptive features can achieve accurate state estimations within the required 2 ms timescale.