Abstract:

This paper conducted an axial compression test on 32 group of FRP concrete composite structure with 3 kinds of section forms (FRP pipe-concrete-steel section, FRP pipe-concrete-steel pipe and hollow FRP pipe concrete). The artificial neural network was used to analysis the experimental dates. The increase of ultimate bearing capacity values was used as mechanical performance evaluation indicators. The effects of five parameters on the mechanical performance, such as the thickness of FRP pipes, the pipe diameter, the hollow ratio, the concrete strength and the steel ratio, were the emphasis of the investigation. The research results show that the most influential parameters of mechanical performance are the thickness of FRP pipes and the pipe diameter, followed by concrete strength, the difference between the three is insignificant, and the influence of hollow ratio and steel ratio are the lowest. Both the increase of the thickness and diameter of FRP pipe, The mechanical performance is significantly improved. The overall trend of ultimate bearing capacity values is decreasing with increasing the concrete strength. But under different conditions, the trend of ultimate bearing capacity values is also increasing or increased at first and then decreased, which effected by the concrete strength. With the increase of the hollow ratio and steel ratio, the overall mechanical performance decrease and the downward trend is relatively slow. The mechanical performance of small wall thickness member is decreased significant with the increase of hollow ratio. But the impact of large wall member components is not obvious. With the increase of steel ratio is significantly decreased the mechanical performance of small thickness and high concrete strength member, but the mechanical performance of big thickness and high concrete strength member is significantly increased.

Key words: FRP concrete composite structure, The thickness of FRP pipes, Pipe diameter, Concrete strength, Hollow ratio, Steel ratio, Artificial neural network

摘要： 对3种截面形式(FRP管-混凝土-型钢、FRP管-混凝土-钢管、中空FRP管混凝土)的32组FRP混凝土组合构件进行轴压试验,并利用人工神经网络技术对试验数据建模分析,以极限承载力提高值作为力学性能评判指标,研究壁厚、管径、混凝土强度、空心率和含钢当量5个参数对力学性能的影响规律。结果表明,对力学性能影响最大的参数是FRP管壁厚度和管径,其次是混凝土强度,三者相差不大,空心率和含钢当量影响最低;FRP管壁厚和管径的增加均会使力学性能有显著提升;混凝土强度对力学性能整体影响趋势是递减的,但在不同情况下,随混凝土强度的提高力学性能会出现降低、先升高后降低以及升高等情况;随空心率和含钢当量的提高,整体力学性能有所下降且下降趋势较为平缓。

关键词: FRP混凝土组合构件, FRP管壁厚, 管径, 混凝土强度, 空心率, 含钢当量, 人工神经网络