复合加固方形木柱的抗震性能分析

SEISMIC PERFORMANCE ANALYSIS OF COMPOSITE STRENGTHENED SQUARE TIMBER COLUMNS

为了提高方形木柱的承载能力和抗震性能,提升古建木结构的抗震安全性,提出采用内嵌钢筋、外包碳纤维(carbon fiber reinforced polymer,CFRP)布复合加固木柱。通过方形木柱的低周往复荷载试验,研究了不同加固模式、钢筋用量、CFRP布加固量等因素对木柱抗震加固效果的影响;利用有限元软件OpenSees对复合加固方形木柱的抗震性能开展了数值模拟,通过数值模拟结果和试验数据的对比验证了有限元模型的可靠性;分析了轴向荷载、钢筋直径、CFRP布层数等参数对复合加固方形木柱滞回性能、侧向承载能力、延性性能、刚度退化以及耗能能力的影响。分析结果表明,内嵌钢筋可以显著提升方形木柱的侧向承载能力和耗能能力;外包CFRP布能够限制木材横向变形和内嵌钢筋的外凸,提高方形木柱的延性性能,延缓其刚度退化;复合加固能够大幅度提高方形木柱侧向承载力、延性及耗能能力,改善其刚度和强度退化,抗震加固效果显著。

In order to improve the bearing capacity and seismic performance of square timber columns and improve the seismic safety of ancient wooden structures,a composite method with near surface mounted steel bars and wrapped CFRP(Carbon Fiber Reinforced Polymer)strips is proposed to strengthen the timber columns.Low cyclic loading tests were carried out on square timber columns to study the influence of different strengthening modes,amount of steel bars and CFRP strips on the seismic performance.The finite element software OpenSees was also used,and the reliability of the finite element model was verified by comparing the analytical and experimental results.The effects of axial load,steel bar diameter and the number of CFRP layers on the hysteretic behavior,lateral bearing capacity,ductility,stiffness degradation and energy dissipation capacity of composite strengthened square timber columns were analyzed.The results show that the near-surface mounted steel bar can significantly improve the lateral bearing capacity and energy dissipation capacity of square timber columns;the external CFRP strips can limit the lateral deformation of timber and protrusion of mounted steel bars,and can improve the ductility and reduce the stiffness degradation of square timber columns;the composite strengthening method can significantly improve the lateral bearing capacity,ductility,energy dissipation capacity,as well as the stiffness and strength degradation of square timber columns.In conclusion,the effectiveness of composite strengthening method is remarkable.