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The reliability of the approximation is demonstrated via several engineering mechanics/dynamics related numerical examples pertaining to the stochastic beam bending problem, as well as to the response determination of stochastically excited nonlinear oscillators.
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For most patterns, this approach improves the reliability of the approximations, even if we still see noticeable differences.
Therefore, it inevitably rises the question about the reliability of the computed approximations.
This paper draws together some important recent results which are designed to improve: (a) the robustness of standard score tests; and (b) the reliability of the asymptotic approximations used for inferential purposes.
Intuitively, the average approximation assigns to all the symbols the average reliability of all the symbols, whereas the maximum approximation assigns to all the symbols the reliability of the worst symbol estimate.
These errors decrease the reliability of the optimum values and discard the realistic approximation of using surrogate models.
The reliability of the joint is assessed with several limit state approximation methods.
When the reliability of the system is relatively low, the Poisson and compound Poisson approximations begin to degrade.
The reliability of the regression coefficient estimates was assessed by testing the sensitivity of the quadrature approximation.
The influence of rheometrical aspects on the reliability of the measurements was consequently studied in order to attain a reduction of the necessary approximation.
Many questioned the reliability of the survey.
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