Abstract:The parameter distribution of the material damping ratio of shallow soil can be identified by inversion through the surface wave attenuation curve extracted by the multi-channel surface wave analysis method (MASW). However, the attenuation curves of surface waves are insensitive to the property changes of soil with larger depths and small spatial scales, and the damping ratio distribution of subsoil material is non-unique and uncertain. Therefore, in this paper, the variation of the damping ratio with depth is expressed by a non-Gaussian prior probability distribution model, and then is decomposed into the sum of standard Gaussian variables and also eigenvalues and eigenvectors by using the Nataf transformation and the Karhunen-Loeve decomposition. Moreover, on the basis of the Bayesian theory, the TLM-PML theory was combined with a half-power bandwidth method in the frequency-wavenumber domain to simulate the attenuation curves, which is compared with the experimental data to construct the likelihood function. The Monte Carlo Markov chain (MCMC)-Metropolis (MH) algorithm was used to obtain the posterior probability distribution model of soil damping ratio from the posterior sample data, and the convergence and independence of the Markov chain were validated so that multiple sets of independent posterior sample data were obtained. Finally, the independent posterior samples were used to calculate the vibration responses of the free field. The confidence interval with a certain degree of confidence was obtained using the kernel density estimation and thus was compared with the experimental data, which validates the rationality and reliability of the non-deterministic probability model of soil damping ratio proposed in this paper.
曹艳梅,李东伟,张玉玉,杨林. 基于贝叶斯理论及MCMC-MH算法推演地基土材料阻尼比的概率分布模型[J]. 振动与冲击, 2021, 40(8): 216-222.
CAO Yanmei, LI Dongwei, ZHANG Yuyu, YANG Lin. Inversion of a probability distribution model of soil damping ratio based on the Bayesian theory and the MCMC-MH algorithm. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(8): 216-222.
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