Welcome to otpod’s documentation!

otpod is a module for OpenTURNS.

This package enables to build Probability of Detection (POD) curves from Non Destructive Test. The curves are built using parametric models : univariate linear regression, quantile regression, kriging and polynomial chaos. Analysis can be run in order to test the linear regression hypothesis.

PoD can be built from a set of data or directly from a given physical model that simulate the Non Destructive Test. In this case, the design of experiments is defined iteratively.

Sensitivity analysis can be also be performed. The aggregated Sobol indices are available as well as the perturbation law indices.

Contents:

• Documentation of the API
  • Data analysis
    • UnivariateLinearModelAnalysis
  • POD computation methods
    • UnivariateLinearModelPOD
    • QuantileRegressionPOD
    • PolynomialChaosPOD
    • KrigingPOD
  • Adaptive algorithms
    • AdaptiveSignalPOD
    • AdaptiveHitMissPOD
  • Sensitivity analysis
    • SobolIndices
    • PLI
    • PLIMean
    • PLIVariance
  • Tools
    • PODSummary
    • DataHandling

• Examples of the API
  • Linear model analysis
  • Linear model analysis with censored data
  • Linear model POD
  • Linear model POD with censored data
  • Quantile Regression POD
  • Polynomial chaos POD
  • Kriging POD
  • POD Summary
  • Adaptive Signal POD using Kriging
  • Adaptive Hit Miss POD
  • Sobol Indices
  • Perturbation Law Indices

Indices and tables

• Index

• Search Page