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On-line Access: 2019-08-05

Received: 2018-08-09

Revision Accepted: 2018-12-17

Crosschecked: 2019-07-08

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jian Zhang

https://orcid.org/0000-0003-2457-9558

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Journal of Zhejiang University SCIENCE A 2019 Vol.20 No.8 P.634-638

http://doi.org/10.1631/jzus.A1800467


Regenerative Bayesian detection of foundation constant with variable scale gradient theory


Author(s):  Jian Zhang, Wei Sun, Chao Jia, Feng Wang

Affiliation(s):  Department of Mechanics and Structural Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; more

Corresponding email(s):   zjmech@163.com

Key Words:  Regenerative Bayesian detection, Variable scale gradient theory, Bayesian objective function


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Jian Zhang, Wei Sun, Chao Jia, Feng Wang. Regenerative Bayesian detection of foundation constant with variable scale gradient theory[J]. Journal of Zhejiang University Science A, 2019, 20(8): 634-638.

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Abstract: 
Before the geotechnical structures are designed, it is often required to determine the mathematical physical model of the corresponding geotechnical medium to properly describe and predict the behavior of the rock and soil during construction and operation in deformation and stability. With the deepening of our understanding of physical phenomena, the geotechnical mechanics, which is evolved from the limit equilibrium theory on basis of rigid body mechanics to the elastic, elastoplastic or viscoelastic theory based on continuum mechanics, is now progressed to various non-continuous media mechanics methods. In this process, various mathematical models have been established for the purpose of describing the system response of the geotechnical medium system even when external environmental conditions are involved. In the process of numerical simulation analysis of actual geotechnical engineering, the value of geotechnical parameter is often an important factor affecting the accuracy, objectivity and practicability of geotechnical engineering simulation analysis results.

基于变尺度梯度理论地基参数的修正Bayes探索

目的:建立弹性地基参数的修正Bayes分析模型,并获得地基参数的变尺度优化结果.
创新点:推求地基参数的变尺度梯度优化方法,建立地基参数的修正Bayes探索分析模型.
方法:建立修正Bayes目标函数及弹性地基参数的修正Bayes探索分析模型,并利用变尺度梯度搜索方法进行参数的优化迭代计算.
结论:地基参数的变尺度梯度搜索分析模型在优化过程中能够稳定地收敛于地基参数的真值(图2). 变尺度梯度优化理论能够适时地修正空间矩阵尺度以产生新的搜索方向,并有效地优化修正Bayes目标函数.

关键词:变尺度法; Bayes目标函数; 地基参数; 优化

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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