Abstract
The failure of a large gravity dam might have catastrophic effects putting at risk human lives, not counting the considerable economic consequences. Most of dams are located in natural hazard prone areas so the structural control and the evaluation of the dam fragility (in particular against to flood and earthquake) assume great importance both to apply early warning procedures and to define resilience-enhancing strategies. Numerical models assume great importance to predict the seismic behaviour of the complex dam-soil-reservoir interacting system, nevertheless they are affected by different uncertainties. The effects of uncertainties can be reduced by calibrating finite element models with all available data about the structure. Measurements recorded by monitoring systems and in situ test results take on a major role as important sources of information. This paper investigates the effect of the uncertainties in the static and dynamic analysis of existing concrete gravity dams by means of two case studies. The general Polynomial Chaos Expansion technique is used to propagate the uncertainties through the numerical models of the case studies even without High Performance Computing. The effects of the uncertainties are thus quantified in terms of model output variation. General Polynomial Chaos Expansion-based predictive models are then used for the solution of the inverse problem thus reducing the computational burden.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Andreini M, De Falco A, Marmo G, Mori M, Sevieri G (2017) Modelling issues in the structural analysis of existing concrete gravity dams. In: Proceedings of the 85th ICOLD annual meeting, Prague, Czech Republic, pp 363–383
De Falco A, Mori M, Sevieri G (2018) Bayesian updating of existing concrete gravity dams model parameters using static measurements. In: Owen R, de Borst R, Reese J, Pearce C (eds) 6th European conference on computational mechanics & 7th European conference on computational fluid dynamics, ECCM-ECFD 2018, vol 1. International Center for Numerical Methods in Engineering (CIMNE), pp 2245–2256
De Falco A, Mori M, Sevieri G (2019) Soil-structure Interaction modeling for the dynamic analysis of concrete gravity dams. In: Papadrakakis M, Fragiadakis M (eds) 7th International conference on computational methods in structural dynamics and earthquake engineering, COMPDYN, vol 3. Institute of Structural Analysis and Antiseismic Research, School of Civil Engineering, National Technical University of Athens (NTUA), Greece, pp 5662–5673
De Falco A, Mori M, Sevieri G (2018) FE models for the evaluation of hydrodynamic pressure on concrete gravity dams during earthquakes. In: Owen R, de Borst R, Reese J, Pearce C (eds) 6th European conference on computational mechanics & 7th European conference on computational fluid dynamics, ECCM-ECFD, vol 1. International Center for Numerical Methods in Engineering (CIMNE), pp 1731–1742
De Falco A, Mori M, Sevieri G, Zani N (2017) Simulation of concrete crack development in seismic assessment of existing gravity dams. In: Braga F, Salvatore W, Vignoli A (eds) 17th Convegno ANIDIS—L’ingegneria Sismica in Italia, vol 1. Pisa University Press, pp 1–2
Sevieri G, Andreini M, De Falco A, Matthies HG (2019) Concrete gravity dams model parameters updating using static measurements. Eng Struct 196, article 109231
International Commission on Large Dams (2000) Bullettin 118—automated dam monitoring systems guidelines and case histories. ICOLD, Paris
De Falco A, Girardi M, Pellegrini D, Robol L, Sevieri G (2018) Model parameter estimation using Bayesian and deterministic approaches: the case study of the Maddalena Bridge. Procedia Struct Integr 11:210–217
Hadamard J (1923) Lectures on Cauchy’s problem in linear partial differential equations. New Haven Yale University Press
Xiu D (2010) Numerical methods for stochastic computations, 1st edn. Princeton University Press
Sevieri G, De Falco A (2010) Concrete gravity dams FE model parameters updating using ambient vibrations. In: Papadrakakis M, Papadopoulos V, Stefanou G (eds) 3rd international conference on uncertainty quantification in computational sciences and engineering, vol 1. UNCECOMP, Institute of Structural Analysis and Antiseismic Research, School of Civil Engineering, National Technical University of Athens (NTUA), Greece, pp 286–297
Kottegoda NT, Rosso R (2008) Applied statistics for civil and environmental engineers, 2nd edn. Blackwell Publishing
Ghanem RG, Spanos PD (1991) Stochastic finite elements: a spectral approach, 1st edn. Springer, New York
Bukenya P, Moyo P, Beushausen H, Oosthuizen C (2014) Health monitoring of concrete dams: a literature review. J Civil Struct Health Monitor 4:235–244
Sevieri G, De Falco A (2020) Dynamic structural health monitoring for concrete gravity dams based on the Bayesian inference. Journal of Civil Structural Health Monitoring 10:235–250
Huang Y, Shao C, Wu B, Beck JL, Li H (2018) State-of-the-art review on Bayesian inference in structural system identification and damage assessment. Adv Struct Eng 22(6):1329–1351
Acknowledgements
This research work has been supported by the Directorate of Dams of the Italian Ministry of Infrastructures and Transport and by the research programme “Multi-scale modelling in structural engineering” within the “Progetti di Ricerca di Ateneo 2018” of the University of Pisa.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Sevieri, G., De Falco, A., Marmo, G. (2021). Uncertainty Quantification and Reduction in the Structural Analysis of Existing Concrete Gravity Dams. In: Bolzon, G., Sterpi, D., Mazzà, G., Frigerio, A. (eds) Numerical Analysis of Dams . ICOLD-BW 2019. Lecture Notes in Civil Engineering, vol 91. Springer, Cham. https://doi.org/10.1007/978-3-030-51085-5_50
Download citation
DOI: https://doi.org/10.1007/978-3-030-51085-5_50
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51084-8
Online ISBN: 978-3-030-51085-5
eBook Packages: EngineeringEngineering (R0)