Improved hilbert spectral representation method and its application to seismic analysis of shield tunnel subjected to spatially correlated ground motions

2018 ◽  
Vol 111 ◽  
pp. 119-130 ◽  
Author(s):  
Yu Miao ◽  
Erlei Yao ◽  
Bin Ruan ◽  
Haiyang Zhuang ◽  
Guoxing Chen ◽  
...  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ying He ◽  
Xueling Chen ◽  
Zhongxian Liu ◽  
Dejian Yang ◽  
Hai Zhang

Based on Biot’s theory, the boundary element method, and spectral representation method, an effective simulation method for multiple-station spatially correlated ground motions on both bedrock and surface is developed, incorporating the spectral density function, coherence function, and site transfer function that consider both the wave scattering effect and the medium saturation. The accuracy and feasibility of the present method are validated by a typical numerical example. Our results indicate that the local site conditions and the saturation property of the medium significantly affect the multipoint spatially correlated earthquake ground motions, especially in the long-period range. It is necessary to use spatially varying ground motions with the rational consideration of local site effects and medium saturation as input during the seismic analysis of large-span structures.


2013 ◽  
Vol 18 (3) ◽  
pp. 458-475 ◽  
Author(s):  
Yongxin Wu ◽  
Yufeng Gao ◽  
Dayong Li ◽  
Tugen Feng ◽  
Ali H. Mahfouz

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Luhua Zhu ◽  
Erlei Yao

This paper is an extension of the random amplitude-based improved Hilbert spectral representation method (IHSRM) that the authors developed previously for the simulation of spatially correlated earthquake ground motions (SCEGMs) possessing the nonstationary characteristics of the natural earthquake record. In fact, depending on the fundamental types (random phase method and random amplitude method) and matrix decomposition methods (Cholesky decomposition, root decomposition, and eigendecomposition), the IHSRM possesses various types. To evaluate the influence of different types of this method on the statistic errors, i.e., bias errors and stochastic errors, an error assessment for this method was conducted. First, the random phase-based IHSRM was derived, and its reliability was proven by theoretical deduction. Unified formulas were given for random phase- and random amplitude-based IHSRMs, respectively. Then, the closed-form solutions of statistic errors of simulated seismic motions were derived. The validness of the proposed closed-form solutions was proven by comparing the closed-form solutions with estimated values. At last, the stochastic errors of covariance (i.e., variance and cross-covariance) for different types of IHSRMs were compared, and the results showed that (1) the proposed IHSRM is not ergodic; (2) the random amplitude-based IHSRMs possessed higher stochastic errors of covariance than the random phase-based IHSRMs; and (3) the value of the stochastic error of covariance for the random phase-based IHSRM is dependent on the matrix decomposition method, while that for the random amplitude-based one is not.


2018 ◽  
Vol 22 (6) ◽  
pp. 1255-1265 ◽  
Author(s):  
Yongle Li ◽  
Chuanjin Yu ◽  
Xingyu Chen ◽  
Xinyu Xu ◽  
Koffi Togbenou ◽  
...  

A growing number of long-span bridges are under construction across straits or through valleys, where the wind characteristics are complex and inhomogeneous. The simulation of inhomogeneous random wind velocity fields on such long-span bridges with the spectral representation method will require significant computation resources due to the time-consuming issues associated with the Cholesky decomposition of the power spectrum density matrixes. In order to improve the efficiency of the decomposition, a novel and efficient formulation of the Cholesky decomposition, called “Band-Limited Cholesky decomposition,” is proposed and corresponding simulation schemes are suggested. The key idea is to convert the coherence matrixes into band matrixes whose decomposition requires less computational cost and storage. Subsequently, each decomposed coherence matrix is also a band matrix with high sparsity. As the zero-valued elements have no contribution to the simulation calculation, the proposed method is further expedited by limiting the calculation to the non-zero elements only. The proposed methods are data-driven ones, which can be applicable broadly for simulating many complicated large-scale random wind velocity fields, especially for the inhomogeneous ones. Through the data-driven strategies presented in the study, a numerical example involving inhomogeneous random wind velocity field simulation on a long-span bridge is performed. Compared to the traditional spectral representation method, the simulation results are with high accuracy and the entire simulation procedure is about 2.5 times faster by the proposed method for the simulation of one hundred wind velocity processes.


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