CantileverBeam¶
- class CantileverBeam¶
Data class for the cantilever beam example.
Examples
>>> from openturns.usecases import cantilever_beam >>> # Load the cantilever beam model >>> cb = cantilever_beam.CantileverBeam()
- Attributes:
- dimThe dimension of the problem
dim=4.
- EBeta distribution
ot.Beta(0.9, 3.5, 65.0e9, 75.0e9)
- FLogNormal distribution
ot.LogNormalMuSigma()([300.0, 30.0, 0.0])
- LUniform distribution
ot.Uniform(2.5, 2.6)
- IBeta distribution
ot.Beta(2.5, 4.0, 1.3e-7, 1.7e-7)
- modelSymbolicFunction, the physical model of the cantilever beam.
- RCorrelationMatrix
Correlation matrix used to define the copula.
- copulaNormalCopula
Copula of the model.
- distributionJointDistribution
The joint distribution of the parameters.
- independentDistributionJointDistribution
The joint distribution of the parameters with independent copula.
- __init__()¶
Examples using the class¶
Create a polynomial chaos metamodel by integration on the cantilever beam
Compute Sobol’ indices confidence intervals
Kriging : cantilever beam model
Kriging: choose an arbitrary trend
Kriging the cantilever beam model using HMAT
Kriging: choose a polynomial trend on the beam model
Analyse the central tendency of a cantilever beam
Use a randomized QMC algorithm
Use the Adaptive Directional Stratification Algorithm
Use the Directional Sampling Algorithm
Use the Importance Sampling algorithm
Use the FORM - SORM algorithms