Use a randomized QMC algorithmΒΆ

In this example we are going to estimate a failure probability on the cantilever beam.

from openturns.usecases import cantilever_beam
import openturns as ot


We load the data class containing the probabilistic modeling of the beam.

cb = cantilever_beam.CantileverBeam()

We load the joint probability distribution of the input parameters :

distribution = cb.distribution

We load the model as well,

model = cb.model

We create the event whose probability we want to estimate.

vect = ot.RandomVector(distribution)
G = ot.CompositeRandomVector(model, vect)
event = ot.ThresholdEvent(G, ot.Greater(), 0.3)

Define the low discrepancy sequence.

sequence = ot.SobolSequence()

Create a simulation algorithm.

experiment = ot.LowDiscrepancyExperiment(sequence, 1)
algo = ot.ProbabilitySimulationAlgorithm(event, experiment)

Retrieve results.

result = algo.getResult()
probability = result.getProbabilityEstimate()
print("Pf=", probability)
Pf= 0.0