Parameter inversion of nonlinear constitutive model of rockfill materials using observed deformations after dam construction

LI Shou-ju; ZHANG Jun; LIANG Jin-quan; SUN Zhen-xiang

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Parameter inversion of nonlinear constitutive model of rockfill materials using observed deformations after dam construction

更新时间：2026-06-25

- Parameter inversion of nonlinear constitutive model of rockfill materials using observed deformations after dam construction
- Vol. 35, Issue S2, (2014)
- 作者机构：
  
  1. 大连理工大学工业装备结构分析国家重点实验室,辽宁,大连,116023
  2. 辽宁蒲石河抽水蓄能有限公司,辽宁,丹东,118216
- 作者简介：
- 基金信息：
- DOI：
  CLC： TV33
- Online First：12 November 2014，
  
  Published：2014
- 稿件说明：
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LI Shou-ju, ZHANG Jun, LIANG Jin-quan, et al. Parameter inversion of nonlinear constitutive model of rockfill materials using observed deformations after dam construction[J]. 2014, 35(S2).
DOI：

LI Shou-ju, ZHANG Jun, LIANG Jin-quan, et al. Parameter inversion of nonlinear constitutive model of rockfill materials using observed deformations after dam construction[J]. 2014, 35(S2). DOI：

摘要

为了高效和准确地确定堆石料的非线性本构模型参数，提出了基于响应面方法的参数反演方法。采用有限元方法数值模拟了堆石坝的分层填筑过程。建立了堆石坝变形观测点沉降的响应面函数，确定了多项式响应面函数的系数。根据堆石坝竣工期变形观测数据和确定的响应面函数，采用优化方法反演确定了堆石料本构模型参数。工程实际应用结果表明，该方法具有较高的计算效率，预测的堆石坝沉降变形与现场观测值吻合较好。

Abstract

In order to determine nonlinear constitutive model parameters of rockfill materials

the inversion procedure based on response surface method is proposed. The sequential impoundment processes of concrete-faced rockfill dam are simulated by using nonlinear finite element method. The response surface functions of forecasting dam settlement for every observing point are presented. The coefficients of response surface function are calculated. Model parameters of nonlinear constitutive relationship of rockfill materials are determined using observed deformations after dam construction and response surface functions of forecasting dam settlement. The practical applications show that the proposed inversion procedure is of higher computing efficiency; and the forecasted dam settlements agree well with observed values.

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