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

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.

Automated summary

A hybrid Random Field-Polynomial Chaos Expansion surrogate model for uncertainty quantification and sensitivity assessment of dams is proposed in this study. The most sensitive spatial locations within dam body for different vibration modes are identified using Sobol's indices and correlation rank methods. The results of the hybrid model are validated using the classical random forest regression method, improving system identification and dynamic analysis outcomes.