当前位置: 首页> 国外交通期刊数据库 >详情
原文传递 Mechanics Based Numerical Modeling of Floor-Anchored Nonstructural Components
题名: Mechanics Based Numerical Modeling of Floor-Anchored Nonstructural Components
正文语种: eng
作者: Tal Feinstein;Jack P. Moehle
作者单位: Univ. of California;Univ. of California
摘要: Abstract Earthquake damage to nonstructural components presents a life-safety risk for occupants and can introduce extensive financial losses and lead to extended downtime of a structure. Current code provisions specify lateral force demands and anchoring requirements aimed at limiting life-safety hazards. Code demands are based on a simplified equation that accounts for some key parameters and does not fully consider the contribution of component attachment. Similarly, most nonstructural numerical and experimental simulations include a fixed-based single-degree-of-freedom model, with nonlinear behavior incorporated within the component. Previous research suggests that attachment design changes the boundary conditions and is an important parameter in determining component dynamic properties. Flexible attachments pose similar challenges with foundation uplift and rocking systems modeling. In this study, a mechanics-based numerical modeling approach for floor-anchored nonstructural components attached via steel channel connections is provided. The model considers the interaction between flexible component response and constrained rocking at the base. In this study, a generalized analytical approach to estimate the force-displacement relationships of the attachment is defined. An experimental test program of attachments connected to concrete with postinstalled expansion anchors supported the analytical approach. The mechanics-based model was compared with previous shake-table tests to evaluate its performance. The proposed model offers a simple approach for engineers to estimate the contribution of attachment design to the dynamic amplification of the component.
出版年: 2023
期刊名称: Journal of structural engineering
卷: 149
期: 1
页码: 1-14
检索历史
应用推荐