4.6 Article

Reliability Assessment of RC Bridges Subjected to Seismic Loadings

Journal

APPLIED SCIENCES-BASEL
Volume 12, Issue 1, Pages -

Publisher

MDPI
DOI: 10.3390/app12010206

Keywords

reliability; demand hazard curves; failure probability; bridges

Funding

  1. CONACyT
  2. Universidad Autonoma Metropolitana (UAM)
  3. Consejo Nacional de Ciencia y Tecnologia [CB 2017-2018 A1-S-8700]
  4. Universidad Autonoma Metropolitana

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This study proposes an approach to estimate both the reliability index and the probability of failure through closed-form expressions, taking into account the uncertainties of concrete compressive strength, steel yield, section geometry, and seismic loadings. The results show that there is a difference between the closed-form expression and numerical integration, demonstrating the significance of considering epistemic uncertainties in the estimation of reliability indicators.
An approach to estimate both the reliability index beta and its complement, the probability of failure, through closed-form expressions that consider aleatory and epistemic uncertainties, is proposed. Alternatively, exceedance demand rates are obtained based on simplified expressions and numerical integration. Reliability indicators are calculated, considering the uncertainties in the compressive strength of concrete, steel yield, and section geometry, together with the aleatory uncertainties related to seismic loadings. Such indicators are estimated in a continuous RC bridge located in Acapulco, Guerrero, Mexico. The bridge was designed to comply with a drift of 0.004. Exceedance demand rates for drift thresholds from 0.001 to 0.012 are estimated, and maximum differences of 5.5% are found between the closed-form expression and numerical integration. The exceedance demand rate expressed by means of its inverse, the return period, indicates that the serviceability limit state is exceeded after 58 years of the bridge construction. The reliability index decreases by about 1.66%, and the probability of failure increases by about 16.1% when the epistemic uncertainties are considered. The approach shows the importance of epistemic uncertainties in the estimation of reliability indicators.

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