Inverse reliability measures and reliability-based design optimisation

International Journal of Reliability and Safety

Volumn 1, Issue 1-2, 2006, Pages 187-205

  Ramu, Palaniappan ^a   Qu, Xueyong ^b   Youn, Byeng Dong ^c   Haftka, Raphael T ^d   Choi, Kyung K ^e  

^a UNIVERSITY OF FLORIDA   (United States)

^b ALTAIR ENGINEERING   (United States)

^c Michigan Technological University   (United States)

^d University of Florida   (United States)

^e IA United States   (United States)

Author keywords

First Order Reliability Method (FORM); inverse reliability measures; Monte Carlo Simulation (MCS); Probabilistic Performance Measure (PPM); Probabilistic Sufficiency Factor (PSF); Reliability Based Design Optimisation (RBDO)

Indexed keywords

EID: 73549098131     PISSN: 1479389X     EISSN: 14793903     Source Type: Journal    
DOI: 10.1504/ijrs.2006.010697     Document Type: Article

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23. A more accurate estimate of PPM or PSF will be obtained from the averae of the nthe and (n+1)th smallest values. So in the case of Fig. 3, PPM is more accurately estimated as 0.35.
24. For this example, the random variables are shown in bold face.