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基于自适应采样的高超声速飞行器气动热全局快速预示 被引量:3
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作者 杨国涛 岳振江 刘莉 《航空学报》 EI CAS CSCD 北大核心 2023年第6期133-150,共18页
高超声速飞行器热防护系统设计中高精度气动热分析模型使得设计计算成本不断增加,基于数据驱动的气动热环境预示方法受到广泛关注。针对有限高精度模型计算成本下提升全局预示精度的问题,提出一种基于模糊聚类的批量自适应采样方法。根... 高超声速飞行器热防护系统设计中高精度气动热分析模型使得设计计算成本不断增加,基于数据驱动的气动热环境预示方法受到广泛关注。针对有限高精度模型计算成本下提升全局预示精度的问题,提出一种基于模糊聚类的批量自适应采样方法。根据预示误差分布特征通过聚类采用超球分割构建采样影响域,兼顾误差较大的重点采样域与全局探索;通过当地误差评分系数加权构建采样拒绝域,减小新增样本冗余;结合maxmin准则在综合确定的重点采样空间中新增样本,提升采样质量,进而实现预示模型全局精度快速提升。数值测试算例表明,所提方法与One-Shot、APSFC、CV-Voronoi方法相比能有效降低所需采样规模,加速提升预示精度。通过类HTV-2飞行器气动热快速预示实例,验证了方法的有效性与工程实用性。 展开更多
关键词 自适应采样 模糊聚类 快速预示 高超声速 气动热
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Virtual sensing method for monitoring vibration of continuously variable configuration structures using long short-term memory networks 被引量:3
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作者 zhenjiang yue Li LIU +1 位作者 Teng LONG Yuanchen MA 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2020年第1期244-254,共11页
Vibration monitoring by virtual sensing methods has been well developed for linear timeinvariant structures with limited sensors.However,few methods are proposed for Time-Varying(TV)structures which are inevitable in ... Vibration monitoring by virtual sensing methods has been well developed for linear timeinvariant structures with limited sensors.However,few methods are proposed for Time-Varying(TV)structures which are inevitable in aerospace engineering.The core of vibration monitoring for TV structures is to describe the TV structural dynamic characteristics with accuracy and efficiency.This paper propose a new method using the Long Short-Term Memory(LSTM)networks for Continuously Variable Configuration Structures(CVCSs),which is an important subclass of TV structures.The configuration parameters are used to represent the time-varying dynamic characteristics by the‘‘freezing"method.The relationship between TV dynamic characteristics and vibration responses is established by LSTM,and can be generalized to estimate the responses with unknown TV processes benefiting from the time translation invariance of LSTM.A numerical example and a liquid-filled pipe experiment are used to test the performance of the proposed method.The results demonstrate that the proposed method can accurately estimate the unmeasured responses for CVCSs to reveal the actual characteristics in time-domain and modal-domain.Besides,the average one-step estimation time of responses is less than the sampling interval.Thus,the proposed method is promising to on-line estimate the important responses of TV structures. 展开更多
关键词 Data-based METHOD RECURRENT neural NETWORKS Time-varying structure VIBRATION MONITORING Virtual sensing
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