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Automated Assessment of Tall Building Wind-Induced Response Data to Support Long-Term Monitoring Programs

机译：高层建筑风致响应数据的自动评估，以支持长期监控程序

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While there is incredible value in long-term monitoring programs for tall buildings under wind, these programs generate large volumes of data that can be difficult to mine effectively to generate knowledge that improves the design process and delivers information of value to the owner. As such the authors have begun to develop a suite of automated tools to manage and more effectively mine these large stores of data. This paper presents one such automated framework for parameterizing response data by waveform for the purposes of conducting an occupant comfort assessment. The framework can project, at multiple levels and for multiple modes of an instrumented building, the likely number of occupants who may experience nausea or task disruption based on the data collected in actual motion simulator experiments. A case study is provided to demonstrate the insights that can be obtained from such a tool.
机译：虽然在风中的高层建筑物的长期监控程序中存在令人难以置信的价值，但这些程序会产生大量数据，这可能很难有效地产生改善设计过程的知识，并将价值信息提供给所有者。因此，作者已经开始开发一套自动化工具来管理和更有效地挖掘这些大型的数据存储。本文介绍了一种如此自动化框架，用于通过波形参数化响应数据，以便进行乘员舒适评估。该框架可以在多个级别和多种仪表建筑模式下投射，这是根据在实际运动模拟器实验中收集的数据遇到恶心或任务中断的可能占用者的可能数。提供案例研究以证明可以从这种工具获得的见解。

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