与反应谱相容的多点完全非平稳地震动随机过程的快速模拟
SIMULATION OF STOCHASTIC PROCESSES OF FULLY NON-STATIONARY AND RESPONSE-SPECTRUM-COMPATIBLE MULTIVARIATE GROUND MOTIONS
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摘要: 为了精确评估结构地震响应的概率特性,地震动随机过程的模拟需要考虑时间变异性(频率和强度非平稳)、空间变异性以及与反应谱的相容性。在经典的多点完全非平稳随机过程的模拟方法中,由于频率与时间变量不可分离,演化功率谱矩阵分解效率较低。为了加快谱矩阵的分解,提出了新Cholesky分解方法。该方法的核心是将演化谱矩阵分离为相位和模矩阵,而模矩阵进一步被转化为与时间不相关的延迟相干矩阵。通过与时间相关的演化谱矩阵相比,延迟相干矩阵仅与频率相关,这样就显著提高了矩阵分解的效率;此外,延迟相干矩阵更适合采用插值技术。最后,将新Cholesky分解方法和插值技术应用到生成与反应谱相容的随机方法中。结果表明:新Cholesky分解与插值能够高效地模拟多点完全非平稳并且与反应谱相容的地震动样本;线性插值与三次样条插值均可达到良好的分辨率,少量的插值点即可满足精度的要求。Abstract: To accurately evaluate the probabilistic characteristics of seismic responses of structures, the temporal and spatial variability and the spectral compatibility need to be considered when simulating stochastic processes of ground motions. In classical simulations of multivariate fully non-stationary processes, the decomposition efficiency of the evolutionary power spectral density (EPSD) matrix is low due to the inseparability of frequency and temporal variables. To speed up the decomposition of the EPSD matrix, a novel Cholesky decomposition approach is proposed to simulate the non-stationary processes. The key of this approach is to separate the EPSD matrix into aphase and a modulus matrix. The modulus matrix will be further transformed to a lagged coherency matrix. The lagged coherence matrix is only related to the frequency, as opposed to the time-dependent EPSD matrix, which remarkably enhances the Cholesky decomposition efficiency. Furthermore, the lagged coherency matrix is more compatible with interpolation techniques. Finally, the novel Cholesky decomposition method and interpolation techniques are used in a stochastic method which is capable of generating spectrum-compatible ground motion samples. Results show that the novel Cholesky decomposition and interpolation techniques are valid for generating fully non-stationary and spectrum-compatible multivariate ground motion samples. Both the linear and cubic spline interpolations achieve a satisfactory level of resolution and accuracy, even with a small number of interpolation points.