[1]王长虹,黄梦露.岩土参数转换模型的贝叶斯校准方法[J].自然灾害学报,2018,(04):096-102.[doi:10.13577/j.jnd.2018.0413]
 WANG Changhong,HUANG Menglu.Transformation model for geotechnical parameters calibration based on Bayesian approach[J].,2018,(04):096-102.[doi:10.13577/j.jnd.2018.0413]
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岩土参数转换模型的贝叶斯校准方法
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《自然灾害学报》[ISSN:/CN:23-1324/X]

卷:
期数:
2018年04期
页码:
096-102
栏目:
出版日期:
2018-09-28

文章信息/Info

Title:
Transformation model for geotechnical parameters calibration based on Bayesian approach
作者:
王长虹 黄梦露
上海大学 土木工程系, 上海 200444
Author(s):
WANG Changhong HUANG Menglu
Department of Civil Engineering, Shanghai University, Shanghai 200444, China
关键词:
静力触探空间随机场不确定性传递转换模型贝叶斯方法
Keywords:
cone penetration testspatial random fielduncertainty propagationtransformation modelBayesian inverse modeling
分类号:
TU454;P315.93;X43
DOI:
10.13577/j.jnd.2018.0413
摘要:
本文基于随机场理论建立了一种空间贝叶斯方法来校准转换模型。该方法主要包含3个要素:(1)三维各向异性随机场理论;(2)观测数据与误差分类体系,以及岩土工程勘察数据的不确定性传播规律;(3)转换模型未知系数和误差的贝叶斯校准方法。考虑土的变异性,把大量的CPT锥尖阻力数据表示为空间随机场变量,这类数据被归为直接数据。而诸如压缩模量在内的一些实验室试验数据被定义为间接数据。基于上述两类数据,同时考虑岩土材料的内在不确定性,测量误差等认知不确定性,转换模型本身的先验知识不确定性,统计参数的计算不确定性,利用贝叶斯反演方法对转换模型中的未知系数和误差进行校准。通过示例研究表明,本方法采用随机场理论,校准了CPT数据与常规岩土参数之间的转换模型。并将经过校准后的转换模型与经典线性回归模型进行对比分析,然后将其应用于背景工程的三维场地特征描述。
Abstract:
A Bayesian approach is proposed calibrating the transformation model based on spatial random field theory. The approach consists of three key elements:(1) three-dimensional anisotropic spatial random field theory; (2) classifications of measurement and error, and the uncertainty propagation diagram of geotechnical investigation; and (3) the unknown coefficients and error calibration of the transformation model given Bayesian inverse modeling method. The massive penetration resistance data from CPT, which is denoted as a spatial random field variable to account for the spatial variability of soil, are classified as type A data. Meanwhile, a few laboratory test data such as the compression modulus are defined as type B data. Based on the above two types of data, the unknown coefficients and error of the transformation model are inversely calibrated with consideration of intrinsic uncertainty of geomaterial, epistemic uncertainties such as measurement errors, prior knowledge uncertainty of transformation model itself, and computing uncertainties of statistical parameters as well as Bayesian method. Baseline studying indicates the proposed approach is applicable to calibrate the transformation model between CPT data and regular geotechnical parameter within spatial random field theory. Next, the calibrated transformation model was compared with classical linear regression in cross-validation, and then it was implemented at three-dimensional site characterization of the background project.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2018-04-30;改回日期:2018-05-30。
基金项目:国家自然科学基金项目(51208303)
作者简介:王长虹(1978-),男,副教授,博士,主要从事随机力学研究.E-mail:changhong_wang@163.com
更新日期/Last Update: 1900-01-01