Reliability analysis of Pole Kheshti historical arch bridge under service loads using SFEM

  • Majid PouraminianEmail author
  • Somayyeh Pourbakhshian
  • Mehdi Moahammad Hosseini
Research Article


The main purpose of this paper is the probabilistic safety analysis of the historical masonry arch bridges (HMAB) and to calculate its reliability index (RI) using the “probabilistic design system” of the ANSYS software. In evaluating the reliability of bridge, the load-resistance model has been used to express the bridge failure functions. Calculating the RI requires the definition of loads effects on the structure and structure resistance. The load and resistance implicit functions are evaluated by stochastic finite element method and the Monte Carlo method has been used for laboratory simulation. The sampling method is the Latin hypercube sampling. The innovations in this paper is to use the functions dependent on parameters, modulus of elasticity, Poisson ratio, density of materials, and traffic load of bridge deck. The number of random parameters is 19. These random parameters are defined by the Log-normal distribution function. In this paper, the reliability status of bridge is investigated in the ultimate limit state under gravitational loading. The constitutive law of the bridge material is considered to be linear elastic. Three types of compressive, tensile, and allowable deflection are considered as limit states of the present research. The case study of the Pole Kheshti Langroud HMAB showed that the required safety is not provided for the ultimate limit state and the bridge is at risk of failure. The RI of bridge in the tensile limit state is lower than the target RI. The sensitivity analysis of random variables of the load and resistance implicit functions to the deflection and tensile responses is investigated, and random parameters with more impact are specified. In the stress limit state and deflection limit state, the modulus of elasticity and weight per unit volume of the sidewalls have the greatest impact on safety, respectively.


Stochastic finite element (SFE) Deterministic finite element (DFE) Monte Carlo Sensitivity analysis (SA) Epistemic uncertainty Random variable (RV) 



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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Civil Engineering, Ramsar BranchIslamic Azad UniversityRamsarIran

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