SORMAnalysis

class persalys.SORMAnalysis(*args)

Run a reliability analysis using the SORM method.

Parameters:

namestr

Name

limitStateLimitState

Limit state

Examples

>>> import openturns as ot
>>> import persalys

Create the model:

>>> R = persalys.Input('R', 0., ot.LogNormalMuSigma(300., 30., 0.).getDistribution(), 'Yield strength')
>>> F = persalys.Input('F', 0., ot.Normal(75000., 5000.), 'Traction load')
>>> G = persalys.Output('G', 'deviation')
>>> myPhysicalModel = persalys.SymbolicPhysicalModel('myPhysicalModel', [R, F], [G], ['R-F/(pi_*100.0)'])

Create the limit state:

>>> limitState = persalys.LimitState('ls1', myPhysicalModel, 'G', ot.Less(), 0.)

Process a reliability analysis using the SORM method:

>>> analysis = persalys.SORMAnalysis('myAnalysis', limitState)
>>> analysis.run()

Get the result:

>>> result = analysis.getResult().getSORMResult()
>>> pf = result.getEventProbabilityBreitung()
>>> designPoint = result.getStandardSpaceDesignPoint()

Methods

getClassName()	Accessor to the object's name.
getErrorMessage()	Error message accessor.
getId()	Accessor to the object's id.
getInterestVariables()	Get the variables to analyse.
getLimitState()	Limit-state accessor.
getName()	Accessor to the object's name.
getOptimizationAlgorithm()	Accessor to the optimization algorithm used to find the design point.
getPhysicalModel()	Physical model accessor.
getPhysicalStartingPoint()	Physical starting point accessor.
getPythonScript()	Physical model accessor.
getResult()	Result accessor.
getShadowedId()	Accessor to the object's shadowed id.
getVisibility()	Accessor to the object's visibility state.
getWarningMessage()	Warning message accessor.
hasName()	Test if the object is named.
hasValidResult()	Whether the analysis has been run.
hasVisibleName()	Test if the object has a distinguishable name.
isReliabilityAnalysis()	Whether the analysis involves reliability.
isRunning()	Whether the analysis is running.
run()	Launch the analysis.
setInterestVariables(outputsNames)	Set the variables to analyse.
setName(name)	Accessor to the object's name.
setOptimizationAlgorithm(solver)	Accessor to the optimization algorithm used to find the design point.
setPhysicalStartingPoint(point)	Physical starting point accessor.
setShadowedId(id)	Accessor to the object's shadowed id.
setVisibility(visible)	Accessor to the object's visibility state.

canBeLaunched
getElapsedTime
getParentObserver

__init__(*args)

getClassName()

Accessor to the object’s name.

Returns:

class_namestr

The object class name (object.__class__.__name__).

getErrorMessage()

Error message accessor.

Returns:

messagestr

Error message if the analysis failed

getId()

Accessor to the object’s id.

Returns:

idint

Internal unique identifier.

getInterestVariables()

Get the variables to analyse.

Returns:

variablesNamessequence of str

Names of the variables to analyse

getLimitState()

Limit-state accessor.

Returns:

limitStateLimitState

The Limit-state.

getName()

Accessor to the object’s name.

Returns:

namestr

The name of the object.

getOptimizationAlgorithm()

Accessor to the optimization algorithm used to find the design point.

Returns:

algorithmopenturns.OptimizationAlgorithm

Optimization algorithm used to research the design point. Cobyla is the default used algorithm.

getPhysicalModel()

Physical model accessor.

Returns:

modelPhysicalModel

Physical model

getPhysicalStartingPoint()

Physical starting point accessor.

Returns:

pointopenturns.Point

Physical starting point. By default it set to the mean of the composed distribution of the physical model

getPythonScript()

Physical model accessor.

Returns:

scriptstr

Python script to replay the analysis

getResult()

Result accessor.

Returns:

resultSORMAnalysisResult

Result

getShadowedId()

Accessor to the object’s shadowed id.

Returns:

idint

Internal unique identifier.

getVisibility()

Accessor to the object’s visibility state.

Returns:

visiblebool

Visibility flag.

getWarningMessage()

Warning message accessor.

Returns:

messagestr

Warning message which can appear during the analysis computation

hasName()

Test if the object is named.

Returns:

hasNamebool

True if the name is not empty.

hasValidResult()

Whether the analysis has been run.

Returns:

hasValidResultbool

Whether the analysis has already been run

hasVisibleName()

Test if the object has a distinguishable name.

Returns:

hasVisibleNamebool

True if the name is not empty and not the default one.

isReliabilityAnalysis()

Whether the analysis involves reliability.

Returns:

isReliabilityAnalysisbool

Whether the analysis involves a reliability analysis

isRunning()

Whether the analysis is running.

Returns:

isRunningbool

Whether the analysis is running

run()

Launch the analysis.

setInterestVariables(outputsNames)

Set the variables to analyse.

Parameters:

variablesNamessequence of str

Names of the variables to analyse

setName(name)

Accessor to the object’s name.

Parameters:

namestr

The name of the object.

setOptimizationAlgorithm(solver)

Accessor to the optimization algorithm used to find the design point.

Parameters:

algorithmopenturns.OptimizationAlgorithm

Optimization algorithm used to research the design point. Cobyla is the default used algorithm.

setPhysicalStartingPoint(point)

Physical starting point accessor.

Parameters:

pointsequence of float

Physical starting point. By default it set to the mean of the composed distribution of the physical model

setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters:

idint

Internal unique identifier.

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters:

visiblebool

Visibility flag.