where N is the sample size of the MCS. The accuracy of MCS can also be expressed in

terms of percentage error corresponding 95% confidence interval as

 (1 Pof ")
 E% = x 196% (5-3)
 Nx Pof "

where Pof is the true probability of failure. Table 5-9 shows the accuracy and error

bounds for MCS. Together with Table 5-8 the error calculation indicates that the

probability of failure of the rounded design is still below the target probability of failure

of 0.0001. The errors can be reduced by more accurate approximations and advanced

Monte Carlo simulations. Another reliability-based design cycle in a reduced size design

region can be performed to obtain more accurate result.

Table 5-9. Accuracy of MCS
 Coefficient of Variation Percentage errors (Absolute
 (COV) errors) for 95% CI
MCS of lx107 samples 4.2% 8.2% (f4.66x10-6)

MCS of lx106 Samples 12.05% 23.6%(fl.63x10- )



 Effects of Quality Control on Laminate Design

 Comparing deterministic designs to the reliability-based design, there is an increase

of 20% in the thickness. In addition, the design failure probability of 10-4 is quite high. In

order to improve the design the possibility of limiting the variability in material

properties through quality control (QC) is considered. Here, quality control means that

materials will be tested by the manufacturer and/or fabricator, and that extremely poor

batches will not be accepted. Normal distributions assume the possibility (though very

small) of unbounded variation. In practice, quality control truncates the low end of the

distribution. That is, specimens with extremely poor properties are rejected. It is also