Seismic damage assessment and prediction using artificial neural network of RC building considering irregularities

IF 3 Q2 ENGINEERING, CIVIL
Pritam Hait, Arjun Sil, S. Choudhury
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引用次数: 19

Abstract

ABSTRACT This paper investigated multi-objective seismic damage assessment procedure. Primarily, it estimates damage index (DI) of reinforcement concrete (RC) framed low-rise residential buildings under the seismic ground motions. Three-dimensional DI has been estimated for a four-storey building by Park–Ang method considering irregularities. With increasing storey level, calculation of Park–Ang DI becomes tedious and more time consuming; therefore, this method is difficult to implement in large-scale damage evaluation. In this study, a simplified method has been proposed to estimate global DI (GDI) for regular and irregular buildings. It has been observed that ground floor experiences maximum damage where roof is experiencing least damage. Alternatively, an artificial neural network based prediction model has also been adopted in this paper to minimize the error. Factors affecting GDI of RC framed building has been narrated. To visualize the weightage of the relation between input parameters and GDI, a neural interpretation diagram has also been presented. The present study could be useful for designers to estimate GDI as performance criteria within short time frame. Abbreviation: LDI: local damage index of a member; CPWD: Central public work department; SDI: storey damage index of a particular storey; MVR: multivariable regression; GDI: global damage index of the entire building; MAD: mean absolute deviation; EDPs: engineering demand parameters; MSE: mean square error; NLTHA: nonlinear time history analysis; MAPE: mean absolute percentage error; ANN: artificial neural network; PGA: peak ground acceleration; ANND: artificial neural network of damage model; Sa: spectral acceleration; SDOF: single-degree of freedom system; PGV: peak ground velocity; MDOF: multi-degree of freedom system; PGD: peak ground displacement; DBDI: ductility-based damage indices; IDR: inter-storey drift; RC: reinforcement concrete; SCGM: spectrum compatible ground motion; PAR: plan aspect ratio; EQ: earthquake; PWD: public work department
考虑不规则性的钢筋混凝土建筑震害评估与预测
研究了多目标地震震害评估方法。首先对钢筋混凝土框架低层住宅在地震作用下的损伤指数进行了估算。考虑到不规则性,利用Park-Ang方法估算了四层建筑的三维DI。随着楼层的增加,Park-Ang DI的计算变得繁琐且耗时;因此,该方法在大规模损伤评估中难以实现。本文提出了一种估算规则和不规则建筑总体DI (GDI)的简化方法。据观察,地面层受到的破坏最大,而屋顶受到的破坏最小。另外,本文还采用了一种基于人工神经网络的预测模型来最小化误差。叙述了影响钢筋混凝土框架建筑GDI的因素。为了可视化输入参数与GDI之间关系的权重,还提出了一种神经解释图。本研究可为设计者在短时间内评估GDI作为性能标准提供参考。简写:LDI:构件的局部损伤指数;CPWD:中央公共工作部;SDI:特定楼层的楼层损伤指数;MVR:多变量回归;GDI:整个建筑的整体损伤指数;MAD:平均绝对偏差;EDPs:工程需求参数;MSE:均方误差;NLTHA:非线性时程分析;MAPE:平均绝对百分比误差;ANN:人工神经网络;PGA:峰值地加速度;ANND:损伤模型人工神经网络;Sa:谱加速度;SDOF:单自由度系统;PGV:峰值地面速度;多自由度:多自由度系统;PGD:峰值地面位移;DBDI:基于延性的损伤指标;IDR:层间漂移;RC:钢筋混凝土;SCGM:频谱兼容地面运动;PAR:平面纵横比;情商:地震;PWD:公共工作部
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来源期刊
CiteScore
3.90
自引率
9.50%
发文量
24
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