响应面法是解决桥梁抗震可靠度中非线性和复杂性等问题的有效方法，但其存 在代理模型类型和训练样本的选取问题． 鉴于此，提出了基于样本填充准则( ISC) 最优化 和 Kriging 模型的改进序贯抽样响应面法． 其以 Kriging 模型作为代理模型，结合蒙特卡洛 抽样技术，利用 Kriging 模型优秀的预测值估计性能及独有的预测均方差估计能力，建立 包含未知样本预测值和预测均方差的 ISC 函数，在迭代阶段通过求解 ISC 最优化问题，进 行局部和全局的平衡搜索，逐一序贯产生后续训练样本． 最后采用所提的基于 ISC-Kriging 改进响应面法对随机地震激励下某悬索桥的动力可靠度问题进行了计算分析． 结果表明， 所提方法具有较高的准确性、高效性．

The response surface method is regarded as an effective way to solve the nonlinearity and complexity problems of the seismic reliability of bridges，but it has problems in selecting both agent model types and training samples． In order to solve these problems，an improved sequential sampling response surface method is proposed based on the infill sampling criterion ( ISC) optimization method and the Kriging model． In the proposed method， by taking the Kriging model as the agency and by drawing on the Monte Carlo sampling technique，an ISC function，which includes the predictive values of unknown samples and the corresponding MSE，is established by making use of the excellent prediction performance of the Kriging model and its unique ability to estimate the mean square error ( MSE) ． In the iterative phase，by solving the ISC optimization problem，the local and global searches are conducted and then the subsequent training samples are generated sequentially． Finally，the proposed method is utilized to analyze the dynamic reliability of a suspension bridge under random seismic excitation． The results show that the proposed method is of high accuracy and high efficiency．