ChabocheModel¶

class ChabocheModel(strainMin=0.0, strainMax=0.07, trueR=750000000.0, trueC=2750000000.0, trueGamma=10.0)¶

Data class for the Chaboche mechanical model.

Parameters:

strainMinfloat, optional: The minimum value of the strain. The default is 0.0.
strainMaxfloat, optional: The maximum value of the strain. The default is 0.07
trueRfloat, optional: The true value of the R parameter. The default is 750.0e6.
trueCfloat, optional: The true value of the C parameter. The default is 2750.0e6.
trueGammafloat, optional: The true value of the Gamma parameter. The default is 10.0.

Attributes:

dimint: Dimension of the problem, dim=4.
StrainUniform distribution: Uniform(strainMin, strainMax)
RLogNormal distribution: LogNormal().setParameter(ot.LogNormalMuSigma()([750.0e6, 11.0e6, 0.0]))
CNormal distribution: Normal(2750.0e6, 250.0e6)
GammaNormal distribution: Normal(10.0, 2.0)
inputDistributionJointDistribution: The joint distribution of the input parameters.
modelFunction: The Chaboche mechanical law. The model has input dimension 4 and output dimension 1. More precisely, we have $\vect{X} = (\epsilon, R, C, \gamma)$ and $Y = \sigma$ .
dataSample: A data set of size 10 and dimension 2 which contains noisy observations of the strain (column 0) and the stress (column 1).

Examples

>>> from openturns.usecases import chaboche_model
>>> # Load the Chaboche model
>>> cm = chaboche_model.ChabocheModel()
>>> print(cm.data[:5])
        [ Strain      Stress (Pa) ]
0 : [ 0           7.56e+08    ]
1 : [ 0.0077      7.57e+08    ]
2 : [ 0.0155      7.85e+08    ]
3 : [ 0.0233      8.19e+08    ]
4 : [ 0.0311      8.01e+08    ]
>>> print("Inputs:", cm.model.getInputDescription())
Inputs: [Strain,R,C,Gamma]
>>> print("Outputs:", cm.model.getOutputDescription())
Outputs: [Sigma]