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Applicability of nonlinear static procedures for low-rise unreinforced masonry buildings with flexible diaphragms

机译:非线性静力程序在柔性膜片低层无筋砌体建筑中的适用性

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摘要

The applicability of the N2 method, the modal pushover analysis (MPA) and an adaptive pushover analysis method are investigated for estimating the peak seismic responses of unrein-forced masonry buildings with flexible diaphragms. The performance of nonlinear static procedures are compared against the nonlinear time-history analyses of three low-rise building models with various levels of stiffness eccentricity, type of failure mechanisms of piers (rocking or shear), and a range of diaphragm stiffness representing timber floor and roof systems. The results indicate that the MPA is unsuitable for unrein-forced masonry buildings with flexible diaphragms, if the building response is shear-dominated. The adaptive method provides the most accurate estimates when the diaphragms are relatively stiff. When the diaphragms are relatively flexible, none of these methods can provide accurate predictions of peak seismic demands. However, conservative results may be obtained with the N2 method, by taking the envelope of pushover analyses carried out using the force distributions proportional to the uniform and linear displacement shapes along the height Of the building. The present study has also identified the most suitable parameters/methods for the use of various nonlinear static procedures, such as the location of the control node used in the N2 method and the modal combination rule used in the MPA, for unrein-forced masonry buildings with flexible diaphragms. (C) 2017 Elsevier Ltd. All rights reserved.
机译:研究了N2方法,模态推覆分析(MPA)和自适应推覆分析方法的适用性,用于估计具有柔性膜片的无筋砌筑房屋的峰值地震响应。将非线性静态程序的性能与三种低层建筑模型的非线性时程分析进行了比较,这些模型具有不同水平的刚度偏心率,墩破坏机理的类型(摇摆或剪切)以及代表木地板的一系列膜片刚度和屋顶系统。结果表明,如果建筑响应以剪力为主,则MPA不适合具有柔性膜片的无筋砌体建筑。当膜片相对较硬时,自适应方法可提供最准确的估计。当膜片相对柔软时,这些方法都无法提供峰值地震需求的准确预测。但是,采用N2方法,通过采用与建筑物沿高度方向的均匀和线性位移形状成比例的力分布进行推覆分析,可以得出保守的结果。本研究还确定了用于各种非线性静态程序的最合适的参数/方法,例如用于非钢筋砌体建筑的N2方法中使用的控制节点的位置以及MPA中使用的模态组合规则。带有柔性隔膜。 (C)2017 Elsevier Ltd.保留所有权利。

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