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Table 3 Random characteristics of material parameters

From: Stochastic analysis for bending capacity of precast prestressed concrete bridge piers using Monte-Carlo simulation and gradient boosted regression trees algorithm

Distribution

Symbols

Probability density function (PDF)

Normal distribution

Normal

\({f\left(x\right)=\frac{1}{\sigma \sqrt{2\pi }}e}^{-\frac{{\left(x-\mu \right)}^{2}}{{2\sigma }^{2}}}\)

Lognormal distribution

Lognormal

\({f\left(x\right)=\frac{1}{x\sigma \sqrt{2\pi }}e}^{-\frac{{\left(\mathrm{ln}x-\mu \right)}^{2}}{{2\sigma }^{2}}}\)

Generalized extreme value distribution

GEV

\(\begin{array}{cc}{f\left(x\right)=\frac{1}{\sigma }\left[1+\xi \left(\frac{x-\mu }{\sigma }\right)\right]}^{-\frac{1}{\xi }-1}& {e}^{{-\left[1+\xi \left(\frac{x-\mu }{\sigma }\right)\right]}^{-\frac{1}{\xi }}}\end{array}\)

Gamma distribution

Gamma

\(f\left(x\right)=\frac{{\beta }^{\alpha }}{\Gamma \left(\alpha \right)}{x}^{\alpha -1}{e}^{-\beta x}\)

Weibull distribution

Weibull

\(f\left(x\right)=\left\{\begin{array}{c}{\frac{k}{\lambda }\left(\frac{x}{\lambda }\right)}^{k-1}{e}^{{-\left(x/\lambda \right)}^{k}},x\ge 0\\ 0,x<0\end{array}\right. \)

  1. In the formulas above, μ represents the mean, σ represents the standard deviation, ξ represents the shape parameter, α and β are parameters of the Gamma distribution, and k and λ are parameters of the Weibull distribution