Reliability & Sensitivity

Central dispersion

Evaluate the mean of a random vector by simulations

Evaluate the mean of a random vector by simulations

Analyse the central tendency of a cantilever beam

Analyse the central tendency of a cantilever beam

Estimate moments from Taylor expansions

Estimate moments from Taylor expansions

Reliability

Simulate an Event

Simulate an Event

Estimate a probability with Monte Carlo

Estimate a probability with Monte Carlo

Use a randomized QMC algorithm

Use a randomized QMC algorithm

Use the Adaptive Directional Stratification Algorithm

Use the Adaptive Directional Stratification Algorithm

Use the post-analytical importance sampling algorithm

Use the post-analytical importance sampling algorithm

Use the Directional Sampling Algorithm

Use the Directional Sampling Algorithm

Specify a simulation algorithm

Specify a simulation algorithm

Create a threshold event

Create a threshold event

Estimate a flooding probability

Estimate a flooding probability

Use the Importance Sampling algorithm

Use the Importance Sampling algorithm

Estimate a probability with Monte-Carlo on axial stressed beam: a quick start guide to reliability

Estimate a probability with Monte-Carlo on axial stressed beam: a quick start guide to reliability

Estimate a buckling probability

Estimate a buckling probability

Exploitation of simulation algorithm results

Exploitation of simulation algorithm results

Use the FORM algorithm in case of several design points

Use the FORM algorithm in case of several design points

Subset Sampling

Subset Sampling

Use the FORM - SORM algorithms

Use the FORM - SORM algorithms

Non parametric Adaptive Importance Sampling (NAIS)

Non parametric Adaptive Importance Sampling (NAIS)

Create a domain event

Create a domain event

Test the design point with the Strong Maximum Test

Test the design point with the Strong Maximum Test

Time variant system reliability problem

Time variant system reliability problem

Estimate a probability using Line Sampling

Estimate a probability using Line Sampling

Create unions or intersections of events

Create unions or intersections of events

Axial stressed beam : comparing different methods to estimate a probability

Axial stressed beam : comparing different methods to estimate a probability

Cross Entropy Importance Sampling

Cross Entropy Importance Sampling

An illustrated example of a FORM probability estimate

An illustrated example of a FORM probability estimate

Using the FORM - SORM algorithms on a nonlinear function

Using the FORM - SORM algorithms on a nonlinear function

Reliability processes

Create an event based on a process

Create an event based on a process

Estimate a process-based event probability

Estimate a process-based event probability

Estimate Sobol indices on a field to point function

Estimate Sobol indices on a field to point function

Sensitivity analysis

Sobol’ sensitivity indices using rank-based algorithm

Sobol' sensitivity indices using rank-based algorithm

Estimate Sobol’ indices for the beam by simulation algorithm

Estimate Sobol' indices for the beam by simulation algorithm

FAST sensitivity indices

FAST sensitivity indices

Parallel coordinates graph as sensitivity tool

Parallel coordinates graph as sensitivity tool

Estimate Sobol’ indices for a function with multivariate output

Estimate Sobol' indices for a function with multivariate output

Sobol’ sensitivity indices from chaos

Sobol' sensitivity indices from chaos

Estimate Sobol’ indices for the Ishigami function by a sampling method: a quick start guide to sensitivity analysis

Estimate Sobol' indices for the Ishigami function by a sampling method: a quick start guide to sensitivity analysis

Use the ANCOVA indices

Use the ANCOVA indices

The HSIC sensitivity indices: the Ishigami model

The HSIC sensitivity indices: the Ishigami model

Example of sensitivity analyses on the wing weight model

Example of sensitivity analyses on the wing weight model

Design of experiments

Create a composite design of experiments

Create a composite design of experiments

Create a Monte Carlo design of experiments

Create a Monte Carlo design of experiments

Probabilistic design of experiments

Probabilistic design of experiments

Create a Gauss product design

Create a Gauss product design

Compute the L2 error between two functions

Compute the L2 error between two functions

Create a random design of experiments

Create a random design of experiments

Create mixed deterministic and probabilistic designs of experiments

Create mixed deterministic and probabilistic designs of experiments

Create a design of experiments with discrete and continuous variables

Create a design of experiments with discrete and continuous variables

The PlotDesign method

The PlotDesign method

Deterministic design of experiments

Deterministic design of experiments

Create a deterministic design of experiments

Create a deterministic design of experiments

Plot Smolyak multi-indices

Plot Smolyak multi-indices

Various design of experiments

Various design of experiments

Generate low discrepancy sequences

Generate low discrepancy sequences

Optimize an LHS design of experiments

Optimize an LHS design of experiments

Plot the Smolyak quadrature

Plot the Smolyak quadrature

LOLA-Voronoi sequential design of experiment

LOLA-Voronoi sequential design of experiment

Merge nodes in Smolyak quadrature

Merge nodes in Smolyak quadrature

Use the Smolyak quadrature

Use the Smolyak quadrature