Stochastic finite elements analysis of large concrete structures’ serviceability under thermo-hydro-mechanical loads – Case of nuclear containment buildings

Bouhjiti, D.E.-M.; Baroth, Julien; Dufour, Frédéric; Michel-Ponnelle, Sylvie; Masson, Benoît

doi:10.1016/j.nucengdes.2020.110800

Cited by 19 publications

(1 citation statement)

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“…It has been shown that PCEassisted UQ demonstrates a better performance in terms of accuracy and efficiency. As an application of using meta-models in the context of nuclear engineering, Bouhjiti et al [19] applied PCE method to develop a global stochastic FE method to predict the uncertainty propagation in a thermo-hydro-mechanical leakage (THM-L) model. It is a framework to simulate the behavior of large reinforced and pre-stressed structures under uncertainties due to material and loading.…”

Section: Literature Reviewmentioning

confidence: 99%

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

Hariri-Ardebili

Mahdavi

Abdollahi

et al. 2021

Water

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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.

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Section: Literature Reviewmentioning

confidence: 99%