| 自适应顺序采样Kriging方法及其在增量动力分析中的应用 |
| |
| 引用本文： | 焦圣虎,侯和涛,冉德胜,陈城,曾晓真,高梦起,熊方明.自适应顺序采样Kriging方法及其在增量动力分析中的应用[J].世界地震工程,2022,38(4):218-228. |
| |
| 作者姓名： | 焦圣虎 侯和涛 冉德胜 陈城 曾晓真 高梦起 熊方明 |
| |
| 作者单位： | 1. 山东大学 土建与水利学院, 山东 济南 250000;2. 旧金山州立大学 工程学院, 美国 旧金山 94132;3. 临沂市建设工程施工图审查有限公司, 山东 临沂 276000;4. 郑州城建集团投资有限公司, 河南 郑州 450001;5. 青岛鑫光正钢结构股份有限公司, 山东 青岛 266700 |
| |
| 摘 要： | 复杂结构的增量动力分析（IDA）对于结构的抗震设计和分析有着重要意义，但需对结构进行大量的非线性时程分析，计算量成本高。本文结合Kriging元模型和自适应顺序采样并用于结构增量动力分析以提高其计算效率和精度，其中:Kriging元模型用于预测结构的地震响应，顺序采样根据候选点的熵值补充非线性时程分析逐步增加Kriging模型的预测精度。借助本文方法，IDA曲线可通过少量的时程分析实现较高的精度。为了校验本文方法的可行性与有效性，对二层和九层钢框架结构模型应用直接IDA、hunt&fill方法和本文方法分析并比较了上述三种方法的计算误差、计算效率和IDA曲线差别。在此基础上本文将自适应顺序采样Kriging方法用于考虑结构不确定性参数的IDA分析，并和传统的蒙特卡洛方法进行比较。结果表明:该方法具有较高的计算效率，可以保证IDA曲线的精度。
|
| 关 键 词： | 增量动力分析 代理模型 Kriging 顺序采样 |
Adaptive sequential sampling Kriging method and its application in incremental dynamic analysis |
| |
| JIAO Shenghu,HOU Hetao,RAN Desheng,CHEN Cheng,ZENG Xiaozhen,GAO Mengqi,XIONG Fangming.Adaptive sequential sampling Kriging method and its application in incremental dynamic analysis[J].World Information On Earthquake Engineering,2022,38(4):218-228. |
| |
| Authors: | JIAO Shenghu HOU Hetao RAN Desheng CHEN Cheng ZENG Xiaozhen GAO Mengqi XIONG Fangming |
| |
| Institution: | 1. School of Civil Engineering, Shandong University, Jinan 25000, China;2. School of Engineering, San Francisco State University, San Francisco, CA 94132, U. S. A;3. Linyi Construction Engineering Construction Drawing Review Co., Ltd, Linyi 276000, China;4. Zhengzhou City Construction Group Investment Co., Ltd, Zhengzhou 450001, China;5. Qingdao Xinguangzheng Steel Structure Co., Ltd, Qingdao 266700, China |
| |
| Abstract: | Incremental dynamic analysis(IDA)of complex structures is of great significance for seismic analysis and design but often constrained by computational cost. This study proposes an integration of Kriging model and sequential sampling to improve the computational efficiency for IDA. Dynamic analysis of structure is first conducted for initial randomly selected intensity samples and their results are used to establish a Kriging model for response prediction for IDA. An entropy based sequential sampling is then applied to select new intensity samples for dynamic analysis in an adaptive manner to update the Kriging model and improve its accuracy of prediction. The IDA curves can thus be obtained with a small number of time history analysis. The proposed method is then applied for a two story and nine-story steel moment resisting frame and compared with direct IDA as well as the hunt & fill for two selected ground motions. Uncertainty in structural parameters are further introduced and the IDA results are compared with those from traditional Monte Carlo simulation. The results show that the proposed method provide high computational efficiency and decent accuracy of IDA in earthquake engineering. |
| |
| Keywords: | incremental dynamic analysis surrogate model Kriging sequential sampling model |
|
| 点击此处可从《世界地震工程》浏览原始摘要信息 |
| 点击此处可从《世界地震工程》下载免费的PDF全文 |
|
