Concrete gravity dams model parameters updating using static measurements

• Published in: Engineering structures 2019-10, Vol.196, p.109231, Article 109231
• Main Authors: Sevieri, Giacomo, Andreini, Marco, De Falco, Anna, Matthies, Hermann G.
• Format: Article
• Language: English
• Subjects: Bayesian analysis; Bayesian updating; Computer applications; Concrete dams; Dams; Feasibility studies; Finite element method; Fourier analysis; General polynomial chaos expansion; Gravity dams; Mathematical models; Model parameters identification; Monitoring; Numerical models; Parameters; Prediction models; Probabilistic models
• ISSN: 0141-0296; 1873-7323
• DOI: 10.1016/j.engstruct.2019.05.072

The structural control of concrete gravity dams is of primary importance. In this context, numerical models play a fundamental role both to assess the vulnerability of gravity dams and to control their behaviour during normal operativity and after extreme events. In this regard, data monitoring represents an important source of information for numerical model calibrations. This study proposes a novel probabilistic procedure, defined in the Bayesian framework, to calibrate the parameters of finite elements models of dams. To this aim, monitoring data and the results of material tests are used as reference information. The computational burden is reduced by using a new hybrid-predictive model of the dam displacements. An application on an Italian dam shows the feasibility of the proposed procedure.