Reliability Analysis of Arch Dam Subjected to Seismic Loads

Chen, Hongjie; Xu, Weiya; Wu, Qing; Liu, Zaobao; Wang, Shengnian

doi:10.1007/s13369-014-1338-6

Cited by 12 publications

(4 citation statements)

References 12 publications

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“…In some studies, the evaluation of the failure functions (FF) has been obtained by analytical formulation [3,6,16,18,32,33] and in others; the finite element (FE) analysis method has been used [5,7,10,[13][14][15]17,25,26,29,30]. Different FF have been assigned to the safety assessment of concrete gravity dams as a system in various investigations [3,9,10,11,[15][16][17]25,32]. ANSYS is a powerful Multiphysics simulation software that has a PDS (Probabilistic Design System) toolbox which provides probability-based analysis and SA for the users [22,29].…”

Section: Introductionmentioning

confidence: 99%

Reliability Assessment and Sensitivity Analysis of Concrete Gravity Dams by Considering Uncertainty in Reservoir Water Levels and Dam Body Materials

Pouraminian

Pourbakhshian

Farsangi

2020

Civil and Environmental Engineering Reports

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An elaborate safety assessment of the Pine Flat (PF) concrete gravity dam (CGD) has been conducted in this paper. Structural analysis was performed by taking into account the uncertainties in the physical and mechanical properties of the dam body materials and the reservoir water level. The coefficient of variation of 5 and 10 percent and the Gaussian distribution (GAUS) are assigned to random variables (RVs). Sensitivity analysis (SA) of the RVs is done, and important parameters introduced. SA is done to identify the most influential RVs on the structural response. Also, the modulus of elasticity of concrete is the most effective parameter in response to horizontal deformation of the dam crest. The concrete density and US hydrostatic pressure height are the most effective parameters, and the Poisson's ratio is the insignificant parameter on the dam response. To be confident in the safety of the dam body under usual loading, including the dam weight and the upstream (US) hydrostatic pressure, the reliability index (RI) has been obtained by Monte Carlo simulation. The RI for the coefficients of variation of 5 and 10 percent were obtained at 4.38 and 2.47, respectively. If the dispersion of RVs is high, then the dam will be at risk of failure.

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Section: Introductionmentioning

confidence: 99%

Reliability Assessment and Sensitivity Analysis of Concrete Gravity Dams by Considering Uncertainty in Reservoir Water Levels and Dam Body Materials

Pouraminian

Pourbakhshian

Farsangi

2020

Civil and Environmental Engineering Reports

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“…Routine risk and safety assessments of dams are carried out by using the determination approach (safety factor) [27], particularly in the static analysis of dams, in which the physical and mechanical properties of the dam body materials and the hydrostatic pressure are assumed to be constant values. The probabilistic analysis approach seeks to more accurately assess the behavior of dams and has been used in many studies [1][2][3][4][5]7,[9][10][11][12][13][14][15][16][17]26]. In such studies, the Probabilistic Design System (PDS) tool from ANSYS software is used to evaluate the probabilistic and reliability analysis of structures [4,6,20,24].…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Safety Evaluation of a Concrete arch dam Based on Finite Element Modeling and A Reliability <i>L-R</i> Approach

Pouraminian

Pourbakhshian

Farsangi

et al. 2019

Civil and Environmental Engineering Reports

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The safety assessment of the Pacoima arch dam is investigated in this paper. A Load – Resistance (L-R) method was used to ensure that the dam is safe or if it is at risk of failure. The “probabilistic design system” ANSYS finite element software was used to calculate the probability of failure. The Monte Carlo (MC) method with 50,000 iterations utilized for simulation and the Latin Hypercube method were used for Sampling. Input random variables with normal distribution and coefficient of variation of 15% due to uncertainties were considered and the six random variables used are the concrete modulus of elasticity, Poisson’s ratio of concrete, concrete mass, up-stream normal water level of the reservoir, and the allowable tensile and compressive strength of the concrete. Linear elastic behavior was assumed for the constitutive law of concrete material and if the stress exceeds the allowable stress of the concrete this is considered as a failure limit state. The maximum and minimum principal stresses were considered as the output parameter. Dam body safety was investigated only under self-weight and upstream hydrostatic pressure at the normal water level. The probability of failure of the dam body system was determined as βsystem=3.98, the safety index as pfsystem =3.42×10−15 and the dam is at risk of failure. The first and third principal stresses in the dam body were also S1max=2.03MPa and S3min=4.6MPa, respectively for the worst case of MC simulation.

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“…The authors also presented some suggestions for improvement of some structural codes in that study. Chen et al (2014) performed a study to compute the dynamic effects of the Dayang arch dam under seismic loads. They applied the quadratic response surface method to build the limit state function of the structure.…”

Section: Introductionmentioning

confidence: 99%

ANN based investigations of reliabilities of the models for concrete under triaxial compression

Öztekin

2016

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Purpose A lot of triaxial compressive models for different concrete types and different concrete strength classes were proposed to be used in structural analyses. The existence of so many models creates conflicts and confusions during the selection of the models. In this study, reliability analyses were carried out to prevent such conflicts and confusions and to determine the most reliable model for normal- and high-strength concrete (NSC and HSC) under combined triaxial compressions. The paper aims to discuss these issues. Design/methodology/approach An analytical model was proposed to estimate the strength of NSC and HSC under different triaxial loadings. After verifying the validity of the model by making comparisons with the models in the literature, reliabilities of all models were investigated. The Monte Carlo simulation method was used in the reliability studies. Artificial experimental data required for the Monte Carlo simulation method were generated by using artificial neural networks. Findings The validity of the proposed model was verified. Reliability indexes of triaxial compressive models were obtained for the limit states, different concrete strengths and different lateral compressions. Finally, the reliability indexes were tabulated to be able to choose the best model for NSC and HSC under different triaxial compressions. Research limitations/implications Concrete compressive strength and lateral compression were taken as variables in the model. Practical implications The reliability indexes were tabulated to be able to choose the best model for NSC and HSC under different triaxial compressions. Originality/value A new analytical model was proposed to estimate the strength of NSC and HSC under different triaxial loadings. Reliability indexes of triaxial compressive models were obtained for the limit states, different concrete strengths and different lateral compressions. Artificial experimental data were obtained by using artificial neural networks. Four different artificial neural networks were developed to generate artificial experimental data. They can also be used in the estimations of the strength of NSC and HSC under different triaxial loadings.

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Reliability Analysis of Arch Dam Subjected to Seismic Loads

Cited by 12 publications

References 12 publications

Reliability Assessment and Sensitivity Analysis of Concrete Gravity Dams by Considering Uncertainty in Reservoir Water Levels and Dam Body Materials

Reliability Assessment and Sensitivity Analysis of Concrete Gravity Dams by Considering Uncertainty in Reservoir Water Levels and Dam Body Materials

Probabilistic Safety Evaluation of a Concrete arch dam Based on Finite Element Modeling and A Reliability <i>L-R</i> Approach

ANN based investigations of reliabilities of the models for concrete under triaxial compression

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