AxialStressedBeam¶
- class AxialStressedBeam¶
Data class for the axial stressed beam example.
Examples
>>> from openturns.usecases import stressed_beam >>> # Load the axial stressed beam >>> sm = stressed_beam.AxialStressedBeam()
- Attributes:
- dimThe dimension of the problem
dim=2.
- DConstant
Diameter D = 0.02 (m)
- modelSymbolicFunction
The limit state function.
- muRConstant
muR=3.0e6, yield strength mean
- sigmaRConstant
sigmaR = 3.0e5, yield strength variance
- distribution_RLogNormalMuSigma distribution of the yield strength
ot.LogNormalMuSigma(muR, sigmaR, 0.0).getDistribution()
- muFConstant
muF=750.0, traction load mean
- sigmaFConstant
sigmaR = 50.0, traction load variance
- distribution_FNormal distribution of the traction load
ot.Normal(muF, sigmaF)
- distributionComposedDistribution
The joint distribution of the inpput parameters.
- __init__()¶
Examples using the class¶
Estimate a probability with Latin Hypercube Sampling
Estimate a probability with Latin Hypercube Sampling
Estimate a probability with Monte Carlo
Estimate a probability with Monte Carlo
Estimate a probability with Monte-Carlo on axial stressed beam: a quick start guide to reliability
Estimate a probability with Monte-Carlo on axial stressed beam: a quick start guide to reliability
Axial stressed beam : comparing different methods to estimate a probability
Axial stressed beam : comparing different methods to estimate a probability
Cross Entropy Importance Sampling
Cross Entropy Importance Sampling