Changes between Version 3 and Version 4 of Features
 Timestamp:
 06/14/08 07:24:22 (9 years ago)
Legend:
 Unmodified
 Added
 Removed
 Modified

Features
v3 v4 2 2 3 3 OpenTURNS is able to perform a complete probabilistic study: 4 * The first step consists in quantifying uncertainty sources : OpenTURNS provides tools that can analyze data samples in order to chose the best uncertainty source modeling ; 5 * The second step of a study allows to spread the uncertainty in a physical model ; 6 * The third step of a study gives the possibility to analyze the importance of each parameter (ranking uncertainty sources, sensitivity analysis). 4 * The first step consists in identifying the numerical model through which one wants to propagate uncertainties, and to define the decision criteria 5 * The second step consists in quantifying uncertainty sources : OpenTURNS provides tools that can analyze data samples in order to chose the best uncertainty source modeling ; 6 * The third step of a study allows to propagate the uncertainty in the numerical model ; 7 * The fourth step of a study gives the possibility to analyze the importance of each parameter (ranking uncertainty sources, sensitivity analysis). 7 8 8 All the OpenTURNS' features (of version 0. 9.1) for each step are listed below:9 All the OpenTURNS' features (of version 0.12.0) for each step are listed below: 9 10 10 11 = First step: Quantifying uncertainty sources = 11 12 13 * Definition of the numerical model : 14  Link with external numerical simulation process (wrapper) 15  Analytical formulas 16  Python functions 17  Metamodel by Taylor Extension 18  Metamodel by Least Square method 19 * Scalar failure criteria 20 21 = Second step: Quantifying uncertainty sources = 22 12 23 * Empirical cumulative distribution function 13 * Density by Kernel Smoothing (Gaussian Kernel) 24 * Density by Kernel Smoothing (General Kernel Product) 25 * Composed distribution (1D marginals and copula) 26 * Composed copula (copulas linked by the Independent Copula) 14 27 * Standard parametric models: 15 28  Normal … … 28 41  Poisson 29 42  Multinormal 43  Noncentral Student 44  Epanechnikov 30 45 * Independent Copula 31 46 * Normal Copula 47 * Clayton copula 48 * Franck copula 49 * Gumbel Copula 32 50 * Using QQplot to compare two samples 33 51 * Smirnov's test … … 47 65 48 66 49 = Second step: Uncertainty propagation =67 = Third step: Uncertainty propagation = 50 68 51 69 * MinMax Approach using Design of Experiments 70 * Deterministic MinMax using TNC (Truncated Newton Constrained) algorithm 52 71 * Quadratic Combination / Perturbation Method 53 72 * Estimating the mean and variance using the MC Method … … 58 77  Cobyla 59 78  AbdoRackwitz 79  SQP 60 80 * Calculation of Reliability index : 61 81  Hasofer reliability index … … 64 84  Generalized HohenBichler reliability index 65 85  Generalized Tvedt reliability index 66 * Sphere sampling method67 86 * Design point validation : Strong Maximum Test 68 * Estimating the probability of an event using Monte Carlo Sampling 69 * Estimating the probability of an event using Importance Sampling 70 * DEstimating the probability of an event using irectional Simulation 71 * Estimating the probability of an event using Latin Hypercube Sampling 87 * Estimating the probability of an event : 88  Monte Carlo Sampling 89  Importance Sampling 90  Directional Simulation 91  Latin Hypercube Sampling 92  Controlled Importance Sampling in standard space 72 93 * Estimating a quantile by Sampling / Wilk's Method 73 * Response Surface by Taylor Extension74 * Polynomial response Surface75 * Response surface obtained by Least Square method76 94 77 78 = Third step: Ranking uncertainty sources / sensitivity analysis = 95 = Fourth step: Ranking uncertainty sources / sensitivity analysis = 79 96 80 97 * Importance Factors derived from Quadratic Combination Method