An RF-PCE Hybrid Surrogate Model for Sensitivity Analysis of Dams

Mohammad Hariri-Ardebili,Ali Amini,Golsa Mahdavi,Azam Abdollahi

doi:10.3390/w13030302

Abstract

Quantification of structural vibration characteristics is an essential task prior to perform any dynamic health monitoring and system identification. Anatomy of vibration in concrete arch dams (especially tall dams with un-symmetry shape) is very complicated and requires special techniques to solve the eigenvalue problem. The situation becomes even more complicated if the material distribution is assumed to be heterogeneous within the dam body (as opposed to conventional isotropic homogeneous relationship). This paper proposes a hybrid Random Field (RF)–Polynomial Chaos Expansion (PCE) surrogate model for uncertainty quantification and sensitivity assessment of dams. For different vibration modes, the most sensitive spatial locations within dam body are identified using both Sobol’s indices and correlation rank methods. Results of the proposed hybrid model is further validated using the classical random forest regression method. The outcome of this study can improve the results of system identification and dynamic analysis by properly determining the vibration characteristics.

Highlights

Determination of the vibration characteristics in concrete dams is an essential task prior to perform any nonlinear seismic analysis [1], dynamic health monitoring [2,3], and system identification [4,5]
The performance of the Polynomial chaos expansion (PCE) for frequency response is very similar to the effective mass
Aside from random forest applications in classification and regression problems, it has a variable importance feature too. It is founded on the Out-of-Bag (OOB) data concept which refers to the samples that are not selected in bootstrapping in the random forest procedure

Summary

Introduction

Determination of the vibration characteristics in concrete dams (especially the unsymmetrical tall arch dams) is an essential task prior to perform any nonlinear seismic analysis [1], dynamic health monitoring [2,3], and system identification [4,5]. The hybrid RF-PCE surrogate model is used to identify the most sensitive regions of two (symmetry and un-symmetry) arch dams at different vibration modes. The findings of this study will help to identify the locations of dams (and any other infrastructure) which most contribute to various vibration frequencies This will be later used to perform a successful transient analysis for large-scale heterogeneous structures and can greatly improve the model validation and verification. Α∈A where Ψα ( X ) are the multi-variate polynomials orthonormal with respect to f X , yα are the expansion coefficients, α are multi-indices that identify the components of the multi-variate polynomials, and A is the truncation set of multi-indices of cardinality P This format of PCE is typically used for simulation-based uncertainty quantification problems.

Objectives

Methods

Results

Conclusion