000013613 001__ 13613
000013613 005__ 20161114165848.0
000013613 04107 $$aeng
000013613 046__ $$k2011-05-25
000013613 100__ $$aNaess, A.
000013613 24500 $$aEnhanced Monte Carlo for Reliability-Based Design and Calibration

000013613 24630 $$n3.$$pComputational Methods in Structural Dynamics and Earhquake Engineering
000013613 260__ $$bNational Technical University of Athens, 2011
000013613 506__ $$arestricted
000013613 520__ $$2eng$$aThis paper extends the recently developed enhanced Monte Carlo approach to the problem of reliability-based design. The objective is to optimize a design parameter(s) so that the system, represented by a set of failure modes or limit states, achieves a target reliability. In a large majority of design and/or calibration contexts, the design parameter α itself can be used to parameterize the system safety margin M (α). The lower tail of this random variable behaves in a regular way and is therefore amenable to straightforward parametric analysis. In contrast to the original Naess et al. method [1], the intention is to estimate the value αT that corresponds to a (very) small target system failure probability pf T . Monte Carlo sampling occurs at a range of values for α that result in larger failure probabilities, and so the design problem essentially amounts to a statistical estimation of a high quantile. Bounds for αT can easily be constructed. Several examples of the approach are given in the paper.

000013613 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000013613 653__ $$aReliability; Calibration; Enhanced Monte Carlo; System failure probability.

000013613 7112_ $$aCOMPDYN 2011 - 3rd International Thematic Conference$$cIsland of Corfu (GR)$$d2011-05-25 / 2011-05-28$$gCOMPDYN2011
000013613 720__ $$aNaess, A.$$iMaes, M.$$iDann M., R.
000013613 8560_ $$ffischerc@itam.cas.cz
000013613 8564_ $$s3902001$$uhttps://invenio.itam.cas.cz/record/13613/files/376.pdf$$yOriginal version of the author's contribution as presented on CD, section: MS 21 Reliability of Structural and Mechanical Systems for Uncertain Operating Conditions.
000013613 962__ $$r13401
000013613 980__ $$aPAPER