LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

A hybrid relaxed first-order reliability method for efficient structural reliability analysis

Photo by dawson2406 from unsplash

Abstract The Hasofer-Lind and Rakwitz-Fiessler (HL-RF) algorithm is widely used for structural reliability analysis in first-order moment method (FORM). However, it meets non-convergence problem including generating periodic and chaotic solutions… Click to show full abstract

Abstract The Hasofer-Lind and Rakwitz-Fiessler (HL-RF) algorithm is widely used for structural reliability analysis in first-order moment method (FORM). However, it meets non-convergence problem including generating periodic and chaotic solutions for highly nonlinear limit state function. In this paper, relaxed HL-RF (RHL-RF) is developed based on a relaxed factor, which is dynamically computed by the second-order interpolation between zero and one. A hybrid relaxed HL-RF (HRHL-RF) method is proposed, in which the HL-RF and RHL-RF are adaptively implemented by using an angle criterion to improve the robustness and efficiency of FORM formula. The angle condition is simply calculated based on the results from the new and previous points. Finally, the performances in terms of robustness and efficiency of the HRHL-RF are compared with several existing FORM methods through five mathematical and structural examples. The results indicate that HRHL-RF method is more robust than the HL-RF and more efficient than other existing methods.

Keywords: first order; reliability analysis; method; structural reliability; reliability

Journal Title: Structural Safety
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.