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.

distributionComposedDistribution

The joint distribution of the parameters.

independentDistributionComposedDistribution

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

Create a polynomial chaos metamodel by integration on the cantilever beam

Compute Sobol’ indices confidence intervals

Compute Sobol' indices confidence intervals

Kriging : cantilever beam model

Kriging : cantilever beam model

Configuring an arbitrary trend in Kriging

Configuring an arbitrary trend in Kriging

Kriging the cantilever beam model using HMAT

Kriging the cantilever beam model using HMAT

Choose the trend basis of a kriging metamodel

Choose the trend basis of a kriging metamodel

Analyse the central tendency of a cantilever beam

Analyse the central tendency of a cantilever beam

Use a randomized QMC algorithm

Use a randomized QMC algorithm

Use the Adaptive Directional Stratification Algorithm

Use the Adaptive Directional Stratification Algorithm

Use the Directional Sampling Algorithm

Use the Directional Sampling Algorithm

Use the Importance Sampling algorithm

Use the Importance Sampling algorithm

Use the FORM - SORM algorithms

Use the FORM - SORM algorithms