ULTIMATE COMPRESSION STRENGTH AND PROBABILISTIC ANALYSIS OF STIFFENEDPLATES

Citation
Y. Pu et al., ULTIMATE COMPRESSION STRENGTH AND PROBABILISTIC ANALYSIS OF STIFFENEDPLATES, Journal of offshore mechanics and Arctic engineering, 119(4), 1997, pp. 270-275
Citations number
20
ISSN journal
08927219
Volume
119
Issue
4
Year of publication
1997
Pages
270 - 275
Database
ISI
SICI code
0892-7219(1997)119:4<270:UCSAPA>2.0.ZU;2-K
Abstract
In the paper, a formulation for predicting the ultimate strength of a stiffened plate is proposed by incorporating Guedes Soares's formula, which gives the best prediction for unstiffened plates according to th e calibration carried our recently by the authors, into Faulkner's met hod (Faulkner et al., 1973). The proposed algorithm is then calibrated by using a considerable amount of experimental and numerical data. It is observed that: (a) The proposed method shows better prediction tha n Faulkner's original method if only the experimental data (63 samples ) are included in the calibration, the bias and COV of the model uncer tainty of the proposed method are 0.992 and 0.099, respectively, while they are 1.039 and 0.143 for Faulkner's original method, and the skew ness of the proposed method is small (only -0.105 slope, which is defi ned as the slope of the regressed straight line on the plot of model u ncertainty against predicted value). (b) On the whole, including exper imental and numerical data, the results of the proposed method demonst rate more or less the same accuracy as that of the original Faulkner m ethod with better bias and skewness, but slightly larger scatters than the original Faulkner method. In addition, the reliability analyses o f stiffened plates are carried out by using advanced first-order secon d-moment method (AFOSM), the second-order reliability method (SORM), a nd Monte Carlo simulation to investigate the accuracy of the first and second-order methods. It is found that the difference between the two methods is so small that the values obtained from AFOSM are acceptabl e in practice, considering the nominal nature of the reliability index .