quoFEM Requirements¶
# |
Description |
Source |
Priority |
Status |
|---|---|---|---|---|
Q.1 |
A tool that facilitates civil engineers performing UQ methods and provides a platform for those in UQ to promote their research to a broader audience |
SP |
M |
1.0 |
Q.2 |
Ability to utilize existing open-source software for faster deployment |
SP |
M |
1.0 |
Q.1.2 |
Ability to extend to multiple UQ engines |
SP |
M |
2.2 |
Q.1.3 |
Ability to utilize resources beyond the desktop, e.g. HPC, for computations |
SP |
M |
1.0 |
UQ Requirements¶
# |
Description |
Source |
Priority |
Status |
quoFEM |
|---|---|---|---|---|---|
UF.1 |
Ability to use basic Monte Carlo and LHS methods |
SP |
M |
Implemented |
|
UF.2 |
Ability to use Gaussian Process Regression |
SP |
M |
Implemented |
|
UF.3 |
Ability to use Multi-Scale Monte Carlo |
SP |
M |
_ |
_ |
UF.4 |
Ability to use Multi-Fidelity Models |
SP |
M |
Implemented |
|
UF.5 |
Ability to use Multi-model Forward Propagation |
UF |
D |
Implemented |
|
UR.1 |
Ability to use First Order Reliability method |
SP |
M |
Implemented |
|
UR.2 |
Ability to use Second Order Reliability method |
SP |
M |
Implemented |
|
UR.3 |
Ability to use Surrogate Based Reliability |
SP |
M |
Implemented |
|
UR.4 |
Ability to use Importance Sampling |
SP |
M |
Implemented |
|
UG.1 |
Ability to obtain Global Sensitivity Sobol indices |
UF |
M |
Implemented |
|
UG.2 |
Ability to use probability model-based global sensitivity analysis (PM-GSA) |
SP |
M |
Implemented |
|
UG.3 |
Ability to use probability model-based global sensitivity analysis (PM-GSA) for high-dimensional outputs |
UF |
D |
Implemented |
|
US.1 |
Ability to Construct Gaussian Process (GP) Regression Model from a Simulation Model |
SP |
M |
Implemented |
|
US.2 |
Ability to Construct GP Regression Model from Input-output Dataset |
SP |
M |
Implemented |
|
US.3 |
Ability to use Surrogate Model for UQ Analysis |
SP |
M |
Implemented |
|
US.4 |
Ability to Save the Surrogate Model |
SP |
M |
Implemented |
|
US.5 |
Ability to Use Adaptive Design of Experiments |
SP |
M |
Implemented |
|
US.6 |
Ability to Assess Reliability of Surrogate Model |
SP |
M |
Implemented |
|
US.7 |
Ability to Build Surrogate Under Stochastic Excitation |
SP |
M |
Implemented |
|
US.8 |
Ability to Use Physics-Informed Machine Learning |
SP |
M |
_ |
_ |
UN.1 |
Ability to use Gauss-Newton solvers for parameter estimation |
SP |
M |
Implemented |
|
UN.2 |
Ability to read calibration data from a file |
UF |
M |
Implemented |
|
UN.3 |
Ability to handle non-scalar response quantities |
UF |
M |
Implemented |
|
UN.4 |
Ability to run gradient-free parameter estimation |
UF |
D |
Implemented |
|
UB.1 |
Ability to use DREAM algorithm for Bayesian inference |
SP |
M |
Implemented |
|
UB.2 |
Ability to use TMCMC algorithm for Bayesian inference |
SP |
M |
Implemented |
|
UB.3 |
Ability to read calibration data from a file |
UF |
M |
Implemented |
|
UB.4 |
Ability to handle non-scalar response quantities |
UF |
M |
Implemented |
|
UB.5 |
Ability to calibrate multipliers on error covariance |
UF |
M |
Implemented |
|
UB.6 |
Ability to use a default log-likelihood function |
UF |
M |
Implemented |
|
UB.7 |
Ability to use Kalman Filtering |
UF |
M |
_ |
_ |
UB.8 |
Ability to use Particle Filtering |
UF |
M |
_ |
_ |
UB.9 |
Ability to perform model-class selection/averaging |
UF |
D |
Implemented |
|
UB.10 |
Ability to perform hierarchical Bayesian calibration |
UF |
D |
Implemented |
|
UB.11 |
Ability to perform surrogate-aided Bayesian calibration |
UF |
D |
In Progress |
1.1.2.3.4 |
UH.1 |
Ability to sample from manifold |
SP |
M |
Implemented |
|
UH.2 |
Ability to build Reduced Order Model |
SP |
M |
In Progress |
1.2.4.4 |
UO.1 |
Ability to use User-Specified External UQ Engine |
SP |
M |
Implemented |
|
UO.2 |
Ability to use Own External FEM Application |
UF |
M |
Implemented |
|
UO.3 |
Ability to use UQ Engines other than SimCenterUQ, Dakota, or UCSD-UQ |
UF |
P |
_ |
_ |
# |
Description |
Source |
Priority |
Status |
quoFEM |
|---|---|---|---|---|---|
RV.1 |
Various Random Variable Probability Distributions |
||||
RV.1.1 |
Normal |
SP |
M |
Implemented |
|
RV.1.2 |
Lognormal |
SP |
M |
Implemented |
|
RV.1.3 |
Uniform |
SP |
M |
Implemented |
|
RV.1.4 |
Beta |
SP |
M |
Implemented |
|
RV.1.5 |
Weibull |
SP |
M |
Implemented |
|
RV.1.6 |
Gumbel |
SP |
M |
Implemented |
|
RV.1.7 |
Exponential |
SP |
M |
Implemented |
|
RV.1.8 |
Discrete |
SP |
M |
Implemented |
|
RV.1.9 |
Gamma |
SP |
M |
Implemented |
|
RV.1.10 |
Chi-squared |
SP |
M |
Implemented |
|
RV.1.11 |
Truncated Exponential |
SP |
M |
Implemented |
|
RV.2 |
User-defined Distribution |
SP |
M |
_ |
_ |
RV.3 |
Define Correlation Matrix |
SP |
M |
Implemented |
|
RV.4 |
Random Fields |
SP |
M |
_ |
_ |
RV.5 |
Ability to View Graphically the density function when defining the RV |
UF |
D |
Implemented |