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《地震研究》[ISSN:1000-0666/CN:53-1062/P]

卷:

47

期数:

2024年01期

页码:

123-134

栏目:

出版日期:

2024-01-01

文章信息/Info

Title:

Response Prediction Method of the RC Frame Structure Based on the Artificial Neural Network

作者:

赵煜东¹; 许卫晓¹; 于德湖²; 邱玲玲²; 陈阵隆³; 邱玉胜⁴

(1.青岛理工大学 土木工程学院,山东 青岛 266520; 2.山东建筑大学 土木工程学院,山东 济南 250101; 3.青岛中建联合集团有限公司,山东 青岛 266100; 4.青岛市博物馆,山东 青岛 266061)

Author(s):

ZHAO Yudong¹; XU Weixiao¹; YU Dehu²; QIU Lingling²; CHEN Zhenlong³; QIU Yusheng⁴

(1.College of Civil Engineering,Qingdao University of Technology,Qingdao 266520,Shandong,China)(2.College of Civil Engineering,Shandong Jianzhu University,Jinan 250101,Shandong,China)(3.Qingdao Zhongjian Combination Group Co.,Ltd.,Qingdao 266100,Shandong,China)(4.Qingdao Museum,Qingdao 266061,Shandong,China)

关键词:

RC框架结构;  人工神经网络;  地震响应;  参数敏感性分析

Keywords:

RC frame structure;  the artificial neural network;  seismic response;  analysis of the parameter sensitivity

分类号:

TU375.4; TU973⁺.212

DOI:

10.20015/j.cnki.ISSN1000-0666.2024.0004

摘要:

为了实现钢筋混凝土(Reinforced Concrete,RC)框架结构地震响应的快速预测,提出了一种基于人工神经网络的RC框架结构地震响应预测方法,设计低层、多层和小高层共3个典型RC框架结构作为研究对象,以四川雅安地区为目标场地,基于条件均值谱选取地震动记录作为输入并进行弹塑性时程分析,所得样本数据用于训练人工神经网络。以地震动强度信息和结构信息为输入预测结构响应,同时对模型进行参数敏感性分析。结果表明:建立的人工神经网络模型具有较好的泛化性能,平均谱加速度具有最高的平均影响值,提出的方法为快速预测RC框架结构地震响应提供了方法借鉴。

Abstract:

To realize the rapid prediction of seismic response of reinforced concrete(RC)frame structure,a seismic response prediction method of RC frame structure based on the artificial neural network(ANN)is proposed.Three typical RC frame structures of low-rise,multi-storey and small high-rise were designed as research examples.Ya’an area in Sichuan was taken as the target site.Based on the conditional mean spectrum(CMS),the ground motion records were selected as input and the elastic-plastic time history analysis was carried out.The obtained sample data were used to train the artificial neural network.The information of the ground motion intensity and the structures were used as input to predict the structural response,and the parameters’ sensitivity of the model was analyzed.The results show that the established artificial neural network model has good generalization performance,and the average spectral acceleration(AvgS_a)has the highest average impact value(MIV).The proposed method provides a reference for the rapid prediction of the seismic response of the RC frame structures,and has a good application prospect.

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备注/Memo

备注/Memo:

收稿日期:2023-02-22
基金项目:山东省自然科学基金项目(ZR2020ME246; ZR2022ME029).

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更新日期/Last Update: 2023-12-20