5. Capabilities¶
Version 3.3 of the quoFEM app was released in March 30. The following lists the functionality available in this current version. (Note: New features and fixes in this release are marked blue in the following list of features.)
5.1. UQ (Uncertainty Quantification and Optimization Options)¶
Forward Uncertainty Propagation
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Monte Carlo Sampling (MCS)
Latin Hypercube Sampling (LHS)
Gaussian Process Regression
Polynomial Chaos Expansion
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Monte Carlo Sampling (MCS)
Resample from existing correlated dataset of samples
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Global Sensitivity Analysis
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MCS
LHS
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Probability Model-based Global Sensitivity Analysis (PM-GSA)
First-order Sobol indices
Total-effect Sobol indices
Group-wise Sobol indices
Principal component analysis and probabilistic model-based GSA (PCA-PSA) for high-dimensional QoIs
Aggregated Sobol indices for field QoIs
Import input/output samples from data files
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Reliability Analysis
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Local Reliability [← minor bug fix]
Global Reliability
Importance Sampling
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Bayesian Calibration [← minor bug fix]
Deterministic Calibration
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NL2SOL
OPT++GaussNewton
Gradient-free optimization
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Surrogate Modeling
SimCenterUQ
Train Gaussian Process (GP) Surrogate Model
Multifidelity surrogate modeling
Adaptive design of experiments options for surrogate modeling
Nugget optimization options for surrogate modeling
Stochastic Kriging [← new option for ‘no replications’]
Surrogate modeling using Probabilistic Learning on Manifolds (PLoM) *
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Configure UQ analysis using JSON file
Note
Support for the running computation to be preformed on TACC’s high performance computer, Frontera, is provided through DesignSafe for all but the methods indicated with a star (*).
5.2. FEM (Computational Model Specification)¶
OpenSees
FEAPpv
Python
Custom
SurrogateGP [← simplified user interface]
None
Multi model
5.3. RV (Random Variable Options)¶
Inspect PDF of RV
Distributions available: 1
Normal
Lognormal
Beta
Uniform
Weibull
Gumbel
Continuous 2
Exponential 3
Discrete 3
Gamma 3
Chi-squared 3
Truncated exponential 3
Note
1: For SimCentreUQ and UCSD algorithms only, the RVs can be defined by any of parameters, moments, or a dataset. 2: Available for Optimization routines in Dakota only. 3: Available in SimCenterUQ and UCSD only.
5.4. EDP (Outputs from Computational Models)¶
Scalar quantities of interest
Vector quantities of interest
5.5. RES (Summary and Visualization of UQ Analysis Results)¶
Summary statistics of outputs displayed
Mean
Standard deviation
All output values presented in spreadsheet
Update chart by clicking on spreadsheet columns
Output values visualized in interactive chart
Scatter plot [← display of correlation coefficient]
Histogram
Cumulative distribution
Inspect points on chart
Spreadsheet save options
Save Table
Save Columns Separately (Useful after Bayesian updating, the posterior samples can later be directly loaded in quoFEM)
Save RVs (Useful for surrogate model training)
Save QoIs (Useful for surrogate model training)
Save Surrogate Predictions (Only for the surrogate model results)
Visualization of surrogate modeling (GP) results
Goodness-of-fit measures
90% confidence interval and prediction interval
Save GP model [← simplified surrogate model file]
Visualization of PLoM training results
PCA representation error plot
Diffusion maps eigenvalue plot