基于RNN模型的智能中层隔离系统控制性能评价

Hyun-Su Kim
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摘要

本文采用随机神经网络模型研究了智能中层隔震系统的减震能力。为此,建立了RNN模型,对建筑结构在地震荷载作用下的动力响应进行预测。本研究选取了一座具有中层隔离系统的既有高层建筑作为实例结构进行现实研究。智能中层隔离系统由MR阻尼器代替现有的铅阻尼器组成。与有限元模型相比,RNN模型能更准确地预测地震反应。与有限元模型相比,RNN模型的仿真时间大大缩短。数值模拟结果表明,与传统隔震系统相比,智能中层隔震系统能有效降低既有建筑的地震反应。
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Control Performance Evaluation of Smart Mid-story Isolation System with RNN Model
The seismic response reduction capacity of a smart mid-story isolation system was investigated using the RNN model in this study. For this purpose, an RNN model was developed to make a dynamic response prediction of building structures subjected to seismic loads. An existing tall building with a mid-story isolation system was selected as an example structure for realistic research. A smart mid-story isolation system was comprised of an MR damper instead of existing lead dampers. The RNN model predicted the seismic responses accurately compared to those of the FEM model. The simulation time of the RNN model can be reduced significantly compared to the FEM model. After the numerical simulations, the smart mid-story isolation system could effectively reduce the seismic responses of the existing building compared to the conventional mid-story isolation system.
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