A new efficient simulation method to approximate the probability of failure and most probable point

Rashki, Mohsen; Miri, Mahmoud; Moghaddam, Mehdi Azhdary

doi:10.1016/j.strusafe.2012.06.003

Cited by 134 publications

(51 citation statements)

References 39 publications

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“…In this example, the failure probability assessment of the LSF with two variables is carried out according to Equation 7, assuming a normal distribution function with mean 10 and standard deviation 5 for each variable x 1 and x 2 (Rashki et al, 2012;Wang and Grandhi, 1994).…”

Section: Examplementioning

confidence: 99%

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A fast and robust method for estimating the failure probability of structures

Arab¹,

Ghasemi²

2015

Proceedings of the Institution of Civil Engineers - Structures

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A new approach is presented to estimate quickly and accurately the probability of failure of structures. The approach works by employing first-order reliability methods to determine the closest point to the mean of random variables in a failure region. Then, by presenting sub-intervals in various layers and by grouping the generated samples in a Monte Carlo simulation (MCS), it was possible to reduce the number of structural calculations with controllable error where acceptable accuracy was introduced. Various numerical and engineering examples with complex limit state functions were solved by the proposed approach and the results were compared with those of common reliability methods. The outcome shows the high accuracy of the proposed approach. Furthermore, the number of required structural calculations was significantly reduced compared to normal MCS.

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Section: Examplementioning

confidence: 99%

“…If using some of the developed FORM algorithms, such as the algorithm provided by Der Kiureghian and Dakessian (1998), however, a failure probability equal to 0 . 00911 will be obtained (Rashki et al, 2012). Also, if the SORM is used, a failure probability of 0 .…”

mentioning

confidence: 99%

A fast and robust method for estimating the failure probability of structures

Arab¹,

Ghasemi²

2015

Proceedings of the Institution of Civil Engineers - Structures

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“…These uncertainties can be considered based on probabilistic models and the reliability analysis can evaluate safety levels for engineering problems by using the failure probability. The analytical methods including first-order reliability method [1,2], second-order reliability method [3], and moment methods [4] or simulation methods such as Monte Carlo simulation (MCS) [2], subset simulation [5], and weighted simulation [6] are generally used for estimating failure probabilities based on probabilistic model. The simulation methods are time-consuming approach for complicated real engineering structures [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of First-Order Reliability Method-Based Steepest Descent Search Directions for Reliability Analysis of Steel Structures

Makhduomi

Keshtegar

Shahraki

2017

Advances in Civil Engineering

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Three algorithms of first-order reliability method (FORM) using steepest descent search direction are compared to evaluate the reliability index of structural steel problems which are designed by the Iranian National Building code. The FORM formula is modified based on a dynamic step size which is computed based on the merit functions named modified Hasofer-Lind and Rackwitz-Fiessler (MHL-RF) method. The efficiency of the gradient, HL-RF, and MHL-RF method was compared for a bar structure under tensile capacity, a multispan beam under bending capacity, a connection under tension load, and a column under axial force. The results illustrated that the MHL-RF method is more efficient than the HL-RF and gradient method. The designed steel components by the Iranian National Building code showed good confidence levels with the reliability index in the range from 2.5 to 3.0.

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“…Cada g (v) constitui um modo de falha e representa um estado indesejável em um modelo de engenharia. A g (v) determina a fronteira entre os domínios de falha (Ω f ) e não falha (Ω s ), conforme a Equação 6.2 [248,249].…”

Section: Generalidadesunclassified

“…Com relação aos métodos de transformação, o mais empregado é o First Order Reliability Method. Para maiores detalhes desses métodos recomendase os trabalhos de [58,59,248,249].…”

Section: Generalidadesunclassified

Análise mecânica e probabilística de estruturas treliçadas sujeitas ao colapso progressivo

Felipe¹

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A new efficient simulation method to approximate the probability of failure and most probable point

Cited by 134 publications

References 39 publications

A fast and robust method for estimating the failure probability of structures

A fast and robust method for estimating the failure probability of structures

A Comparative Study of First-Order Reliability Method-Based Steepest Descent Search Directions for Reliability Analysis of Steel Structures

Análise mecânica e probabilística de estruturas treliçadas sujeitas ao colapso progressivo

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