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Approximation of the Monte Carlo Sampling Method for Reliability Analysis of Structures
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-05-15
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Structural load types, on the one hand, and structural capacity to withstand these loads, on the other hand, are of a probabilistic nature as they cannot be calculated and presented in a fully deterministic way.
As such, the past few decades have witnessed the development of numerous probabilistic approaches towards the analysis and design of structures.
Among the conventional methods used to assess structural reliability, the Monte Carlo sampling method has proved to be very convenient and efficient.
However, it does suffer from certain disadvantages, the biggest one being the requirement of a very large number of samples to handle small probabilities, leading to a high computational cost.
In this paper, a simple algorithm was proposed to estimate low failure probabilities using a small number of samples in conjunction with the Monte Carlo method.
This revised approach was then presented in a step-by-step flowchart, for the purpose of easy programming and implementation.
American Psychological Association (APA)
Shadab Far, Mahdi& Wang, Yuan. 2016. Approximation of the Monte Carlo Sampling Method for Reliability Analysis of Structures. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1112352
Modern Language Association (MLA)
Shadab Far, Mahdi& Wang, Yuan. Approximation of the Monte Carlo Sampling Method for Reliability Analysis of Structures. Mathematical Problems in Engineering No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1112352
American Medical Association (AMA)
Shadab Far, Mahdi& Wang, Yuan. Approximation of the Monte Carlo Sampling Method for Reliability Analysis of Structures. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1112352
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112352