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基于80根混凝土设计强度等级为C60—C80的型钢高强混凝土(SRHSC)框架柱的低周反复加载试验结果,对其位移延性系数进行研究。基于MATLAB利用人工神经网络原理建立4-6-1型BP神经网络模型,分析了混凝土强度、轴压比、体积配箍率和剪跨比等试验设计参数对SRHSC框架柱位移延性的影响规律和机理。结合各因素对SRHSC框架柱位移延性的影响规律,建立位移延性系数计算模型。通过对试验数据和网络预测数据进行多元非线性回归分析,得到考虑多影响因素的SRHSC框架柱位移延性系数经验公式。研究成果可为SRHSC框架柱的抗震与优化设计提供参考。
Displacement ductility coefficient was studied based on 80 low-cycle cyclic loading tests of 80 steel reinforced concrete columns (SRHSC) with C60-C80 strength design. Based on the theory of artificial neural network, the 4-6-1 BP neural network model is established based on MATLAB. The influence law of experimental parameters such as concrete strength, axial compression ratio, volumetric stirrup ratio and shear span ratio on the displacement ductility of SRHSC frame columns is analyzed. mechanism. Combined with the influence of various factors on the displacement ductility of SRHSC frame, a model of displacement ductility coefficient was established. By multivariate nonlinear regression analysis of test data and network prediction data, empirical formulas of displacement ductility coefficient of SRHSC columns considering multiple influential factors were obtained. The research results can provide a reference for the seismic and optimization design of SRHSC frame columns.