A deformation separation method for gravity dam body and foundation based on the observed displacements

Abstract

Summary The displacement at arbitrary point in the dam is composed of two parts: One is the elastic deformation of dam body and the other that is due to the constrained deformation of foundation. The two parts should be separated to obtain reliable information reflecting the different characteristics of dam body and foundation. A simplified simulation method for gravity dam foundations is proposed that reflects the constrained deformation of foundation in a rational manner while taking into account the complex and diverse mechanical properties. Only the effects of the foundation on dam is investigated in the proposed model, and they are considered either centralized constraints or distributed constraints. The solution of the global foundation deformation is based on the monitoring displacements at measuring points in the gravity dam section using the hybrid partition finite element–interface boundary element approach. The reaction of the foundation on dam can be reflected by the global foundation deformation and the constrained force at dam bottom. On the basis, the whole dam response under a given load combination can be estimated using finite element theory. Three analyses have been performed on a typical gravity dam section to verify the feasibility of simplified simulations for different foundations as well as to allow for discussions regarding the differences among the simulations. An example analysis based on the proposed method is performed on a prototype gravity dam, and the results, which compared with actual measurements for discussions, show that the proposed method is reasonable and practical.

Concrete gravity dams model parameters updating using static measurements

“…Lin et al [25] proposed a method to split dam displacements into two parts: the one related to the dam behaviour and the second one related to the foundation. The idea of partitioned FEM was used to define hybrid equations which allowed one to separate these two contributions.…”

Dynamic structural health monitoring for concrete gravity dams based on the Bayesian inference

“…The static SHM systems recently proposed for gravity dams are inspired by the progress made in machine learning. Different architectures have been used to define predictive models of dam static displacements [3,[13][14][15][16][17][18][19][20] in order to improve the accuracy of the prediction and to reduce the computational burden of the classical approaches based on functional approximation [21]. Artificial neural network, support vector machine learning, extreme machine learning, multiple linear regression and general polynomial chaos expansion have been successfully used for the approximation of static dam behaviour.…”

“…Lin et al [20] propose a procedure for the separation of dam displacements into two parts: one relating to the dam behaviour and another relating to the foundation deformation. The idea of partitioned finite element model (FEM) is used to define hybrid equations that enable these two contributions to be separated.…”

Risk evaluation of dam-break environmental impacts based on the set pair analysis and cloud model

“…In order to describe the environmental factors more efficiently, a comprehensive and complex index system is its inherent requirement (Chen et al 2020). However, due to numerous influencing factors, the accuracy of the weight calculation is challenged (Lin et al 2019b). For example, it is difficult to satisfy the consistency test in the AHP method.…”