Oscillator

class Oscillator

Data class for the oscillator example.

Examples

>>> from openturns.usecases import oscillator
>>> # Load the oscillator
>>> osc = oscillator.Oscillator()

Attributes:

dimint

dim = 8, dimension of the problem

modelSymbolicFunction

The limit state function

muMpfloat

muMp = 1.5, mean of the mass of the primary system

sigmaOverMuMpfloat

sigmaOverMuMp = 0.1, coefficient of variation of the mass of the primary system

distributionMpLogNormal distribution of the mass of the primary system

distributionMp = ot.LogNormalMuSigmaOverMu(muMp, sigmaOverMuMp).getDistribution()

muMsfloat

muMs = 0.01, mean of the mass of the primary system

sigmaOverMuMsfloat

sigmaOverMuMs = 0.1, coefficient of variation of the mass of the primary system

distributionMsLogNormal distribution of the mass of the secondary system

distributionMs = ot.LogNormalMuSigmaOverMu(muMs, sigmaOverMuMs).getDistribution()

muKpfloat

muKp = 1, mean of the spring stiffness of the primary system

sigmaOverMuKpfloat

sigmaOverMuKp = 0.2, coefficient of variation of the spring stiffness of the primary system

distributionKpLogNormal distribution of the spring stiffness of the primary system

distributionKp = ot.LogNormalMuSigmaOverMu(muKp, sigmaOverMuKp).getDistribution()

muKsfloat

muKs = 0.01, mean of the spring stiffness of the secondary system

sigmaOverMuKsfloat

sigmaOverMuKs = 0.2, coefficient of variation of the spring stiffness of the secondary system

distributionKsLogNormal distribution of the spring stiffness of the secondary system

distributionKs = ot.LogNormalMuSigmaOverMu(muKs, sigmaOverMuKs).getDistribution()

muZetapfloat

muZetap = 0.05, mean of the damping ratio of the primary system

sigmaOverMuZetapfloat

sigmaOverMuZetap = 0.4, coefficient of variation of the damping ratio of the primary system

distributionZetapLogNormal distribution of the damping ratio of the primary system

distributionZetap = ot.LogNormalMuSigmaOverMu(muZetap, sigmaOverMuZetap).getDistribution()

muZetasfloat

muZetas = 0.02, mean of the damping ratio of the secondary system

sigmaOverMuZetasfloat

sigmaOverMuZetas = 0.5, coefficient of variation of the damping ratio of the secondary system

distributionZetasLogNormal distribution of the damping ratio of the secondary system

distributionZetas = ot.LogNormalMuSigmaOverMu(muZetas, sigmaOverMuZetas).getDistribution()

muFsfloat

muFs = 27.5, mean of the loading capacity of the secondary spring

sigmaOverFsfloat

sigmaOverFs = 0.1, coefficient of variation of the loading capacity of the secondary spring

distributionFsLogNormal distribution of the loading capacity of the secondary spring

distributionFs = ot.LogNormalMuSigmaOverMu(muFs, sigmaOverFs).getDistribution()

muS0float

muS0 = 100, mean of the intensity of the white noise

sigmaOverS0float

sigmaOverS0 = 0.1, coefficient of variation of the intensity of the white noise

distributionS0LogNormal distribution of the intensity of the white noise

distributionS0 = ot.LogNormalMuSigmaOverMu(muS0, sigmaOverS0).getDistribution()

distributionJointDistribution

The joint distribution of the input parameters

__init__()

Examples using the class

Using the FORM - SORM algorithms on a nonlinear function

Using the FORM - SORM algorithms on a nonlinear function