Shedding Light on the Effect of Uncertainties in the Seismic Fragility Analysis of Existing Concrete Dams

The seismic risk assessment of existing concrete gravity dams is of primary importance for our society because of the fundamental role of these infrastructures in the sustainability of a country. The seismic risk assessment of dams is a challenging task due to the lack of case histories, such as gravity dams’ seismic collapses, which hinders the definition of limit states, thus making the application of any conventional safety assessment approach difficult. Numerical models are then fundamental to predict the seismic behaviour of the complex dam-soil-reservoir interacting system, even though uncertainties strongly affect the results. These uncertainties, mainly related to mechanical parameters and variability of the seismic motion, are among the reasons that, so far, prevented the performance-based earthquake engineering approach from being applied to concrete dams. This paper discusses the main issues behind the application of the performance-based earthquake engineering to existing concrete dams, with particular emphasis on the fragility analysis. After a critical review of the most relevant studies on this topic, the analysis of an Italian concrete gravity dam is presented to show the effect of epistemic uncertainties on the calculation of seismic fragility curves. Finally, practical conclusions are derived to guide professionals to the reduction of epistemic uncertainties, and to the definition of reliable numerical models.

[1]  Dimitrios Vamvatsikos,et al.  Incremental dynamic analysis , 2002 .

[2]  Michael Havbro Faber,et al.  On the Treatment of Uncertainties and Probabilities in Engineering Decision Analysis , 2005 .

[3]  Pietro Croce,et al.  Seismic Reliability Assessment of a Concrete Water Tank Based on the Bayesian Updating of the Finite Element Model , 2017 .

[4]  Mohammad Amin Hariri-Ardebili,et al.  Risk, Reliability, Resilience (R3) and beyond in dam engineering: A state-of-the-art review , 2018, International Journal of Disaster Risk Reduction.

[5]  M. K. Ravindra,et al.  Seismic fragilities for nuclear power plant risk studies , 1984 .

[6]  Jeeho Lee,et al.  Plastic-Damage Model for Cyclic Loading of Concrete Structures , 1998 .

[7]  Anna De Falco,et al.  Dynamic structural health monitoring for concrete gravity dams based on the Bayesian inference , 2020 .

[8]  Victor E. Saouma,et al.  Sensitivity and uncertainty quantification of the cohesive crack model , 2016 .

[9]  Victor E. Saouma,et al.  Collapse Fragility Curves for Concrete Dams: Comprehensive Study , 2016 .

[10]  H. Westergaard Water Pressures on Dams During Earthquakes , 1933 .

[11]  Bensaibi Mahmoud,et al.  Seismic Fragility and uncertainty Analysis of Concrete Gravity Dams under Near-Fault Ground Motions , 2013 .

[12]  Hermann G. Matthies,et al.  Concrete gravity dams model parameters updating using static measurements , 2019, Engineering Structures.

[13]  A. Kiureghian,et al.  Aleatory or epistemic? Does it matter? , 2009 .

[14]  Terje Haukaas,et al.  Probabilistic capacity models and seismic fragility estimates for RC columns subject to corrosion , 2008, Reliab. Eng. Syst. Saf..

[15]  Qing Huo Liu,et al.  The perfectly matched layer for acoustic waves in absorptive media , 1997 .

[16]  Bruce R. Ellingwood,et al.  Seismic fragility assessment of concrete gravity dams , 2003 .

[17]  Victor E. Saouma,et al.  Quantification of seismic potential failure modes in concrete dams , 2016 .

[18]  Armando Miguel Awruch,et al.  Probabilistic finite element analysis of concrete gravity dams , 1998 .

[19]  Victor E. Saouma,et al.  Random finite element method for the seismic analysis of gravity dams , 2018, Engineering Structures.

[20]  Victor E. Saouma,et al.  Probabilistic seismic demand model and optimal intensity measure for concrete dams , 2016 .

[21]  Halil Sezen,et al.  Analytical fragility assessment using unscaled ground motion records , 2017 .

[22]  Maria Girardi,et al.  Model parameter estimation using Bayesian and deterministic approaches: the case study of the Maddalena Bridge , 2018 .

[23]  Alessio Lupoi,et al.  A probabilistic method for the seismic assessment of existing concrete gravity dams , 2011 .

[24]  Bruno Sudret,et al.  Global sensitivity analysis using polynomial chaos expansions , 2008, Reliab. Eng. Syst. Saf..

[25]  Mircea Grigoriu,et al.  The role of intensity measures on the accuracy of seismic fragilities , 2020 .

[26]  Omid Omidi,et al.  Seismic cracking of concrete gravity dams by plastic-damage model using different damping mechanisms , 2013 .

[27]  Ivan M. Viest,et al.  Load and Resistance Factor Design , 1981 .

[28]  Jack W. Baker,et al.  Incorporating modeling uncertainties in the assessment of seismic collapse risk of buildings , 2009 .

[29]  Ashutosh Bagchi,et al.  A New Iterative Procedure for Deconvolution of Seismic Ground Motion in Dam-Reservoir-Foundation Systems , 2014, J. Appl. Math..

[30]  A. Hillerborg,et al.  Analysis of crack formation and crack growth in concrete by means of fracture mechanics and finite elements , 1976 .

[31]  J. F. Hall The dynamic and earthquake behaviour of concrete dams: review of experimental behaviour and observational evidence , 1988 .

[32]  Iunio Iervolino,et al.  REXEL: computer aided record selection for code-based seismic structural analysis , 2010 .

[33]  Hasan Mirzabozorg,et al.  Seismic Assessment of Arch Dams Using Fragility Curves , 2015 .

[34]  Patrick Paultre,et al.  Seismic Fragility of Concrete Gravity Dams with Spatial Variation of Angle of Friction: Case Study , 2016 .

[35]  Jian Zhang,et al.  Effects of Pounding and Skewness on Seismic Responses of Typical Multispan Highway Bridges Using the Fragility Function Method , 2013 .

[36]  Yong Huang,et al.  State-of-the-art review on Bayesian inference in structural system identification and damage assessment , 2018, Advances in Structural Engineering.