Parameter predictions of hardening soil model based 
on multivariate probability distribution

TAO Yuan-qin; PAN Sun-jue-xu; SUN Hong-lei; NIE Yan-xia

doi:10.16285/j.rsm.2024.1006

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Parameter predictions of hardening soil model based on multivariate probability distribution

更新时间：2026-06-25

- Parameter predictions of hardening soil model based on multivariate probability distribution
- Vol. 46, Issue 5, Pages: 1392-1408(2025)
- 作者机构：
  
  1. 浙江工业大学土木工程学院,浙江,杭州,310023
  2. 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
  3. 中建一局集团发展有限公司,北京,100102
- 作者简介：
- 基金信息：
- DOI：10.16285/j.rsm.2024.1006
  CLC： TU431
- Online First：06 May 2025，
  
  Published：2025
- 稿件说明：
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TAO Yuan-qin, PAN Sun-jue-xu, SUN Hong-lei, et al. Parameter predictions of hardening soil model based on multivariate probability distribution[J]. 2025, 46(5): 1392-1408.
DOI：

TAO Yuan-qin, PAN Sun-jue-xu, SUN Hong-lei, et al. Parameter predictions of hardening soil model based on multivariate probability distribution[J]. 2025, 46(5): 1392-1408. DOI： 10.16285/j.rsm.2024.1006.

摘要

针对工程实际中土体硬化（hardening soil，简称HS）模型参数取值难的问题，建立了HS模型参数数据库HS-CLAY/9/196，并基于该数据库构建了HS参数的多元概率分布模型；通过易获得的常见土性参数测试数据更新难获得的HS参数的概率分布，并研究了已知测试数据类型及类型量对HS参数更新的影响，提出了给定测试数据下HS参数（参考切线模量E 、参考剪切模量和参考加卸载模量）的概率转换模型。结果表明：所建立的HS参数多元概率分布模型有效表征了HS参数的统计特征和互相关性；基于该多元概率分布模型，可通过贝叶斯更新综合利用多种土性参数测试数据，提高HS参数预测的准确性，预测不确定性随着已知测量数据类型量的增加而降低；在估计HS参数、和时，应优先考虑收集压缩模量、含水率和孔隙比等与目标参数具有强相关性的测试数据。

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