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考虑多源土工试验数据的土体参数概率化估计研究

任金明 汪明元 潘孙珏徐 葛圣泰

人民长江2026,Vol.57Issue(2):205-212,231,9.
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人民长江2026,Vol.57Issue(2):205-212,231,9.DOI:10.16232/j.cnki.1001-4179.2026.02.025

考虑多源土工试验数据的土体参数概率化估计研究

Probabilistic prediction of soil parameters based on multi-source geotechnical test data

任金明 1汪明元 1潘孙珏徐 2葛圣泰2

作者信息

  • 1. 浙江华东工程建设管理有限公司,浙江 杭州 310030||中国电建集团华东勘测设计研究院有限公司,浙江 杭州 311122
  • 2. 浙江工业大学 土木工程学院,浙江 杭州 310023||浙江省工程结构与防灾减灾技术研究重点实验室,浙江 杭州 310023
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摘要

Abstract

To address the challenge of determining reliable soil parameters in cases with limited underwater geotechnical investi-gation data,a database involving ten soil parameters is established.Based on a hierarchical Bayesian model(HBM),quantitative information is learned and extracted from the abundant data in the database.By incorporating the constructed database with the limited test data from a target site,a quasi-site-specific multivariate probability distribution of soil parameters is constructed to improve the prediction accuracy of unknown soil properties for the target site.The effects of the quantity and types of data on soil parameter estimation were also investigated.The results indicate that HBM can provide the statistical characteristics and probabili-ty distribution of the target soil parameters,and accurately estimate them even with limited and incomplete geotechnical data from the target site.Only a small amount of data is required to effectively reduce estimation uncertainty.Moreover,using the compressi-bility coefficient,compression modulus,liquid limit,and plastic limit to predict cohesion and friction angle can effectively reduce prediction uncertainty.

关键词

土体参数/参数估计/数据库/多元概率分布/贝叶斯模型

Key words

soil parameter/parameter estimation/database/multivariate probability distribution/Bayesian model

分类

建筑与水利

引用本文复制引用

任金明,汪明元,潘孙珏徐,葛圣泰..考虑多源土工试验数据的土体参数概率化估计研究[J].人民长江,2026,57(2):205-212,231,9.

基金项目

浙江省水利厅重大科技计划项目(RA2211) (RA2211)

人民长江

1001-4179

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