6. R2D Requirements
R2D is the UI for a regional simulation. It uses rWhale to run the workflow. The requirements from R2D come from many components.
6.1. General Requirements
# |
Description |
Source |
Priority |
Status |
Implementation |
|---|---|---|---|---|---|
R2D |
Ability to perform regional simulation allowing communities to evaluate resilience and perform what-if types of analysis for natural hazard events |
GC |
M |
InProgress |
1.1.1.1.3-1.1.1.1.4, 1.1.3.4.6, 1.1.4.2.1-1.1.4.2.5, 1.1.4.3.1-1.1.4.3.2 |
R2D.1 |
Include Various Hazards |
GC |
M |
InProgress |
|
R2D.1.1 |
Ability to perform simulations for ground shaking due to earthquakes using methods defined in EL1 |
GC |
M |
Implemented |
|
R2D.1.2 |
Ability to perform simulations for wave action due to earthquake induced tsunami using methods defined in HL1 |
GC |
M |
InProgress |
1.1.3.3.2-1.1.3.3.3, 1.1.3.5.2 |
R2D.1.3 |
Ability to perform simulations for wind action due to hurricane using methods defined in WL1 |
GC |
M |
InProgress |
1.1.3.3.2-1.1.3.3.3, 1.1.3.5.1-1.1.3.5.2 |
R2D.1.4 |
Ability to perform simulations for wave action due to hurricane storm surge using methods defined in HL1 |
GC |
M |
InProgress |
1.1.3.3.2-1.1.3.3.3, 1.1.3.5.1-1.1.3.5.2 |
R2D.1.5 |
Ability to perform multi-hazard simulations: wind + storm surge + rain + wind and water borne debris |
GC |
M |
InProgress |
1.1.3.3.2-1.1.3.3.3, 1.1.3.5.1-1.1.3.5.2 |
R2D.1.6 |
Ability to utilize machine learning ensemble techniques in hazard simulation |
GC |
M |
||
R2D.1.7 |
Ability to incorporate surrogate models in hazard simulation |
SP |
M |
||
R2D.1.8 |
Ability to incorporate multi-scale models in hazard simulation |
SP |
M |
InProgress |
1.1.3.3.2, 1.1.3.3.5 |
R2D.1.9 |
Ability to incorporate ground deformation hazards for pipes, roadways, and other infrastructure |
SP |
M |
InProgress |
1.1.3.4.4, R2D UM 3.1.5 |
R2D.2 |
Include Different Asset Types |
GC |
M |
InProgress |
|
R2D.2.1 |
Ability to incorporate building assets |
GC |
M |
Implemented |
|
R2D.2.1.1 |
Ability to incorporate multi-fidelity building model asset descriptions |
GC |
M |
InProgress |
1.1.3.3.1 |
R2D.2.2 |
Ability to incorporate transportation networks |
GC |
M |
InProgress |
1.1.3.1.3, 1.1.3.4.1, 1.1.3.4.3, 1.1.3.5.3, R2D UM 2.4.3 |
R2D.2.3 |
Ability to incorporate utility networks |
GC |
M |
InProgress |
1.1.3.1.4, 1.1.3.3.5, 1.1.3.4.1-1.1.3.4.7 |
R2D.2.3.1 |
Methods to overcome national security issues with certain utility data |
GC |
M |
InProgress |
1.1.3.4.5 |
R2D.2.4 |
Ability to incorporate surrogate models in asset modeling |
SP |
M |
||
R2D.3 |
Include Different Analysis options |
GC |
M |
Implemented |
|
R2D.3.1 |
Ability to include multi-scale nonlinear models |
GC |
M |
Implemented |
|
R2D.3.2 |
Ability to perform capacity spectrum analysis for buildings |
UF |
M |
Implemented |
|
R2D.4 |
Include Different Damage & Loss options |
GC |
M |
InProgress |
|
R2D.4.1 |
Ability to include building-level earthquake damage and loss assessment from HAZUS |
SP |
M |
Implemented |
|
R2D.4.2 |
Ability to include high-resolution earthquake damage and loss assessment for buildings from FEMA P58 |
SP |
M |
Implemented |
|
R2D.4.3 |
Ability to include building-level wind damage and loss assessment from HAZUS |
SP |
M |
Implemented |
|
R2D.4.4 |
Ability to include building-level water damage and loss assessment from HAZUS |
SP |
M |
Implemented |
|
R2D.4.5 |
Ability to include earthquake damage and loss assessment for transportation networks from HAZUS |
SP |
M |
Implemented |
|
R2D.4.6 |
Ability to include earthquake damage and loss assessment for buried pipelines from HAZUS |
SP |
M |
InProgress |
1.1.3.4.3 |
R2D.4.7 |
Ability to include earthquake damage and loss assessment for power lines from HAZUS |
SP |
M |
InProgress |
1.1.3.4.3 |
R2D.4.8 |
Ability to include high-resolution wind damage and loss assessment for buildings |
SP |
M |
InProgress |
1.1.3.5.1 |
R2D.4.9 |
Ability to include high-resolution water damage and loss assessment for buildings |
SP |
M |
InProgress |
1.1.3.5.2 |
R2D.4.10 |
Ability to include high-resolution damage and loss assessment for transportation networks |
SP |
M |
InProgress |
1.1.3.5.3 |
R2D.4.11 |
Ability to include high-resolution damage and loss assessment for buried pipelines |
SP |
M |
InProgress |
1.1.3.5.4 |
R2D.5 |
Include Different Response/Recovery options |
GC |
M |
InProgress |
|
R2D.5.1 |
Response/Recovery options for households |
SP |
M |
InProgress |
1.1.4.2.3 |
R2D.5.2 |
Response/Recovery options for infrastructure |
SP |
M |
InProgress |
1.1.4.2.4 |
R2D.5.3 |
Response/Recovery options for business operations |
SP |
M |
InProgress |
1.1.4.2.5 |
R2D.5.4 |
Response/Recovery and Effect on Environment |
SP |
M |
InProgress |
1.1.4.3.1 |
R2D.5.4.1 |
CO2 emissions from demolition and repair |
SP |
M |
InProgress |
1.1.4.3.1 |
R2D.6 |
Present results using GIS so communities can visualize hazard impacts |
GC |
M |
Implemented |
|
R2D.6.1 |
Ability to use popular ArcGIS for visualization |
SP |
M |
Implemented |
|
R2D.6.2 |
Ability to include open-source ArcGIS alternatives |
SP |
P |
Implemented |
|
R2D.6.3 |
Ability to capture uncertainty of results in visualization |
SP |
P |
InProgress |
1.1.3.6.4 |
R2D.6.4 |
Features to visualize environmental impact |
SP |
P |
||
R2D.7 |
Software Features |
GC |
M |
InProgress |
|
R2D.7.1 |
Ability to include a formal treatment of uncertainty and randomness |
GC |
M |
Implemented |
|
R2D.7.2 |
Ability to utilize HPC resources in regional simulations that enables repeated simulation for stochastic modeling |
GC |
M |
Implemented |
|
R2D.7.3 |
Ability to use a tool created by linking heterogeneous array of simulation tools to provide a toolset for regional simulation |
GC |
M |
Implemented |
|
R2D.7.4 |
Provide open-source software for developers to test new data and algorithms |
GC |
M |
Implemented |
|
R2D.7.5 |
Ability of stakeholders to perform simulations of different scenarios that aid in planning and response after damaging events |
GC |
M |
Implemented |
|
R2D.7.7 |
Ability to explore different strategies in community development pre-event early response and post event through long term recovery |
GC |
P |
InProgress |
1.1.4.2.1-1.1.4.2.5 |
R2D.7.8 |
Ability to use system that creates and monitors real-time data updates models incorporates crowd sourcing technologies and informs decision makers |
GC |
P |
||
R2D.7.9 |
Ability to use sensor data to update models for simulation and incorporate sensor data into simulation |
GC |
P |
||
R2D.7.10 |
Ability to include latest information and algorithms (i.e. new attenuation models building fragility curves demographics lifeline performance models network interdependencies indirect economic loss) |
GC |
D |
InProgress |
1.1.3.4.6 |
R2D.7.11 |
Incorporate programs that can address lifeline network disruptions and network interdependencies |
GC |
M |
InProgress |
1.1.3.4.6 |
R2D.7.12 |
Application to provide common SimCenter research application requirements listed in CR (not already listed above) |
GC |
M |
InProgress |
6.2. Earthquake Loading Requirements
# |
Description |
Source |
Priority |
Status |
Implementation |
|---|---|---|---|---|---|
EL.1 |
Regional Scale Earthquake Hazard Simulation Options |
_ |
_ |
_ |
_ |
EL.1.1 |
Coupling of multi-scale nonlinear models from the point of rupture through rock and soil into structure |
_ |
_ |
_ |
_ |
EL.1.1.1 |
Replacement of empirical linear models with multi-scale nonlinear models |
GC |
D |
_ |
_ |
EL.1.1.2 |
Include both multi-scale and multi-phase (account for liquefaction) |
GC |
M |
InProgress |
1.1.3.3.3, 1.1.3.3.5 |
EL.1.1.3 |
Interface between asset and regional simulations using site response method |
SP |
M |
Implemented |
|
EL.1.1.4 |
Interface between asset and regional simulations using DRM method |
SP |
M |
InProgress |
_ |
EL.1.2 |
Method to include both the intra-event residual and inter-event residual in simulating spatial correlated ground motion intensity measures with multiple correlation model options. Select site-specific ground motions from PEER to match target intensity |
SP |
M |
Implemented |
|
EL.1.3 |
Use GIS-Specified Matrix of Recorded Motions |
SP |
M |
Implemented |
|
EL.2 |
Select from Multiple Local Scale Earthquake Hazard Options |
_ |
_ |
_ |
_ |
EL.2.1 |
Interact with PEER NGA |
SP |
M |
Implemented |
_ |
EL.2.1.1 |
Select using default selection options |
SP |
D |
Implemented |
_ |
EL.2.1.2 |
Select using all options available at PEER site |
UF |
D |
Implemented |
_ |
EL.2.1.3 |
Select using user-supplied spectrum |
UF |
D |
Implemented |
_ |
EL.2.2 |
Ability to select utilizing PEER NGA_West web service |
SP |
D |
Implemented |
|
EL.2.3 |
Ability to select from a list of user-supplied PEER motions |
SP |
M |
Implemented |
_ |
EL.2.4 |
Ability to select from a list of SimCenter motions |
SP |
M |
Implemented |
_ |
EL.2.5 |
Ability to use OpenSHA and selection methods to generate motions |
UF |
D |
Implemented |
|
EL.2.6 |
Ability to Utilize Own Application in Workflow |
SP |
M |
||
EL.2.7 |
Ability to include Soil-Structure Interaction Effects |
_ |
_ |
_ |
_ |
EL.2.7.1 |
1D nonlinear site response with effective stress analysis |
SP |
M |
Implemented |
|
EL.2.7.2 |
Nonlinear site response with bidirectional loading |
SP |
M |
Implemented |
_ |
EL.2.7.3 |
Nonlinear site response with full stochastic characterization of soil layers |
SP |
M |
Implemented |
_ |
EL.2.7.4 |
Nonlinear site response bidirectional different input motions |
SP |
M |
_ |
|
EL.2.8 |
Ability to generate synthetic ground motions |
_ |
_ |
_ |
_ |
EL.2.8.1 |
per Vlachos Papakonstantinou Deodatis (2017) |
SP |
D |
Implemented |
_ |
EL.2.8.2 |
per Dabaghi Der Kiureghian (2017) |
UF |
D |
Implemented |
_ |
EL.2.9 |
Ability to select from synthetic ground motions |
SP |
M |
Implemented |
_ |
EL.2.10 |
Ability to select surrogate modeling events |
SP |
M |
Implemented |
_ |
6.3. Wind Loading Requirements
# |
Description |
Source |
Priority |
Status |
Implementation |
|---|---|---|---|---|---|
WL.1 |
Regional Loading due to Wind Hazards |
_ |
_ |
_ |
|
WL.1.1 |
Regional Hurricane Wind Options |
_ |
_ |
_ |
_ |
WL.1.1.1 |
Utilize GIS and online to account for wind speed given local terrain, topography and nearby buildings |
GC |
D |
_ |
_ |
WL.1.1.2 |
Multi-scale models for wind and water flows, i.e. lower fidelity regional models with more refined models to capture local flow |
SP |
D |
InProgress |
_ |
WL.1.1.3 |
Multi-scale models for wind and water flows, i.e. lower fidelity regional models with more refined models to capture local flow |
SP |
D |
InProgress |
_ |
WL.1.2 |
Modeling and simulation for determination of wind loads due to non-synoptic winds, including tornadoes |
GC |
D |
_ |
_ |
WL.1.3 |
Interface with NOAA |
SP |
D |
Implemented |
_ |
WL.2 |
Local Scale Wind Hazard Options |
SP |
M |
Implemented |
_ |
WL.2.1 |
Utilize Extensive wind tunnel datasets in industry and academia for wide range of building shapes |
_ |
_ |
_ |
_ |
WL.2.1.1 |
Accommodate Range of Low Rise building shapes |
_ |
_ |
_ |
_ |
WL.2.1.1.1 |
Flat Shaped Roof - TPU dataset |
SP |
M |
Implemented |
_ |
WL.2.1.1.2 |
Gable Shaped Roof - TPU dataset |
SP |
M |
Implemented |
_ |
WL.2.1.1.3 |
Hipped Shaped Roof - TPU dataset |
SP |
M |
Implemented |
_ |
WL.2.1.2 |
Accommodate Range of High Rise building |
SP |
M |
InProgress |
_ |
WL.2.1.3 |
Non Isolated Low Rise Buildings - TPU dataset |
SP |
M |
InProgress |
_ |
WL.2.2 |
Interface with data-driven Interface with Vortex Winds DEDM-HRP Web service |
SP |
M |
Implemented |
_ |
WL.2.3 |
Accommodate Data from Wind Tunnel Experiment |
SP |
M |
Implemented |
_ |
WL.2.4 |
Simple CFD model generation and turbulence modeling |
GC |
M |
Implemented |
_ |
WL.2.5 |
Computational Fluid Dynamics tool for utilizing open source CFD software for practitioners |
_ |
_ |
_ |
_ |
WL.2.5.1 |
Uncoupled OpenFOAM CFD model with nonlinear FEM code for building response |
SP |
M |
Implemented |
_ |
WL.2.5.2 |
Coupled OpenFOAM CFD model with linear FEM code for building response |
SP |
M |
InProgress |
_ |
WL.2.5.3 |
Inflow Conditions for non-synoptic winds |
GC |
M |
_ |
_ |
WL.2.6 |
Quantification of Effects of Wind Borne Debris |
GC |
D |
_ |
_ |
WL.2.7 |
Ability to utilize synthetic wind loading algorithms per Wittig and Sinha |
SP |
D |
Implemented |
_ |
WL.2.8 |
Hazard modification by terrain, topography, and nearby buildings |
GC |
D |
_ |
_ |
WL.2.9 |
Probabilistic methods are needed to enable site-specific and storm-type specific characterization of likely debris types, weights,and speeds |
GC |
D |
_ |
_ |
WL.2.10 |
Joint description for hurricane wind, storm surge, and wave hazards |
GC |
D |
_ |
_ |
WL.2.11 |
Libraries of high-resolution hurricane wind/surge/wave simulations |
GC |
M |
InProgress |
_ |
WL.2.12 |
Multi-scale models for wind and water flows, i.e. lower fidelity regional models with more refined models to capture local flow |
SP |
M |
InProgress |
_ |
WL.2.13 |
Ability to select surrogate modeling events |
SP |
M |
_ |
_ |
6.4. Surge/Tsunami Loading Requirements
# |
Description |
Source |
Priority |
Status |
Implementation |
|---|---|---|---|---|---|
HL.1 |
Regional Loading due to Storm Surge/Tsunami Hazards |
GC |
D |
InProgress |
_ |
HL.1.1 |
Multi-scale models for wind and water flows, i.e. lower fidelity regional models with more refined models to capture local flow |
SP |
D |
InProgress |
_ |
HL.2 |
Local Scale Storm Surge/Tsunami Hazard Options |
GC |
M |
InProgress |
_ |
HL.2.1 |
Using computational fluid dynamics to model the interface and loading between waves and buildings |
GC |
M |
InProgress |
_ |
HL.2.1.1 |
CFD to model fluid flow around a single rigid structure |
SP |
M |
Implemented |
_ |
HL.2.1.2 |
Mesh refinement around structures |
SP |
M |
Implemented |
_ |
HL.2.1.3 |
CFD to model fluid flow around a single deformable structure |
SP |
M |
Implemented |
_ |
HL.2.1.4 |
CFD to model fluid flow considering inflow and accumulation of fluid inside a rigid structure |
SP |
M |
InProgress |
_ |
HL.2.1.5 |
CFD to model fluid flow considering inflow, accumulation, and possible outflow of fluid across a deformable structure |
SP |
M |
Implemented |
_ |
HL.2.1.6 |
CFD to model fluid flow considering a collapsing structure |
SP |
M |
InProgress |
_ |
HL.2.2 |
Quantification of flood-borne debris hazards |
GC |
M |
InProgress |
_ |
HL.2.2.1 |
Ability to quantify the effect of unconstrained and non-colliding floating bodies |
SP |
M |
Implemented |
_ |
HL.2.2.2 |
Ability to quantify the effect of colliding flood-borne debris |
SP |
M |
Implemented |
_ |
HL.2.2.3 |
Explore multiple methods like Material Point Method (MPM), Immersed Boundary Method (IBM), DEM-CFD, Smoothed Particle Hydrodyanmics (SPH), particle tracking |
SP |
M |
InProgress |
_ |
HL.2.2.4 |
Integrate one of the methods for integrating particles with Hydro workflow |
GC |
M |
Implemented |
_ |
HL.2.3 |
Load combinations need to be developed to account for the simultaneous impacts of various flood forces, such as those generated by breaking waves, moving water and flood-borne debris |
GC |
M |
InProgress |
_ |
HL.2.5 |
Multi-scale models for wind and water flows, i.e., lower fidelity regional models with more refined models to capture local flow |
SP |
D |
InProgress |
|
HL.2.5.1 |
Interface GeoClaw and OpenFOAM |
SP |
M |
Implemented |
_ |
HL.2.5.2 |
Interface AdCirc and OpenFOAM |
SP |
M |
InProgress |
_ |
HL.2.6 |
Libraries of high-resolution hurricane wind/surge/wave simulations |
SP |
M |
InProgress |
_ |
HL.2.6.1 |
Develop a simulation library of GeoClaw simulations |
SP |
M |
_ |
_ |
HL.2.6.2 |
Develop a simulation library of AdCirc simulations |
SP |
M |
_ |
_ |
HL.2.6.3 |
Develop a simulation library of OpenFOAM simulations |
SP |
M |
InProgress |
_ |
HL.2.6.4 |
Develop a simulation library of MPM or SPH simulations |
SP |
D |
InProgress |
_ |
HL.2.6.5 |
Develop a simulation library of Celeris simulations |
SP |
D |
InProgress |
_ |
HL.2.7 |
Ability to simulate with surrogate models as an alternative to full 3D simulations |
SP |
M |
InProgress |
_ |
HL.2.7.1 |
Ability to simulate with surrogate models as an alternative to full 3D debris |
SP |
M |
InProgress |
_ |
HL.2.7.2 |
Ability to simulate with surrogate models as an alternative to full 3D fluids |
SP |
M |
InProgress |
_ |
HL.2.8 |
Develop digital twin(s) for wave tank facility(ies) |
SP |
M |
Implemented |
_ |
HL.2.8.1 |
Develop digital twin of the Oregon State University’s Large Wave Flume (OSU LWF) wave tank facility |
SP |
M |
Implemented |
_ |
HL.2.8.2 |
Develop digital twin of the Oregon State University’s Directional Wave Basing (OSU DWB) wave tank facility |
SP |
D |
InProgress |
_ |
HL.2.8.3 |
Develop digital twin of the Waseda University’s Tsunami Wave Basin (WU TWB) wave tank facility |
SP |
D |
Implemented |
_ |
HL.2.8.4 |
Develop digital twin of the University of Washington’s Wind-Air-Sea Interaction Facility (UW WASIRF) wave tank facility |
SP |
D |
InProgress |
_ |
HL.2.8.5 |
Develop digital twin of the Hannover Large Wave Flume (HLWF) wave tank facility |
SP |
D |
InProgress |
_ |
HL.2.9 |
Ability to utilize synthetic wave loading algorithms |
SP |
D |
_ |
_ |
HL.2.9.1 |
Implement a FEMA or ASCE wave loading algorithm |
SP |
D |
_ |
_ |
HL.2.9.2 |
Implement one or more cutting-edge research-based wave loading algorithms |
SP |
D |
_ |
_ |
HL.2.9.3 |
Add functionality for users to create and implement their own wave loading algorithms, e.g. in Python |
SP |
D |
_ |
_ |
HL.2.10 |
Ability to utilize synthetic debris loading algorithms |
SP |
D |
_ |
_ |
HL.2.10.1 |
Implement a FEMA or ASCE debris loading algorithm |
SP |
D |
_ |
_ |
HL.2.10.2 |
Implement one or more cutting-edge research-based debris loading algorithms |
SP |
D |
_ |
_ |
HL.2.10.3 |
Add functionality for users to create and implement their own debris loading algorithms, e.g. in Python |
SP |
D |
_ |
_ |
HL.2.11 |
Library for surge/tsunami debris materials, geometries, mass, mobilized speeds, likelihood of mobilization, longitudinal displacements, lateral spreading angles, uncertainties (e.g. in material properties), and correlations between parameters |
SP |
D |
_ |
_ |
HL.2.11.1 |
Library for broad regions (e.g. PNW, SoCal, Hawaii, U.S. Territories, Great Lakes, Gulf-Coast, Florida, Mid-Atlantic) |
SP |
D |
_ |
_ |
HL.2.11.2 |
Library for (e.g. rural, residential, industrial) |
SP |
D |
_ |
_ |
HL.2.11.3 |
Library for seminal events (e.g. Tohoku 2011) |
SP |
D |
_ |
_ |
HL.2.11.4 |
Library for likely future events (e.g. Cascadia M9.0 Event, Alaskan Landslide Induced Tsunami) |
SP |
D |
_ |
_ |
HL.2.12 |
Probabilistic methods to enable site-specific and wave-property specific characterization of likely relevant debris types, weights, and speeds |
GC |
D |
_ |
_ |
HL.2.12.1 |
Develop a probabilistic framework to quantify the likelihood of debris generation and mobilization in a given event at a given site (e.g. refine the 0.9 m flow-depth threshold) |
SP |
D |
_ |
_ |
HL.2.12.2 |
Develop a probabilistic framework to couple debris mobilization, generation, and transport (e.g. random-walk / normal distribution skewed by friction anisotropy / flood vector / wind vector) with tsunami / storm-surge / wind models |
SP |
D |
_ |
_ |
HL.2.13 |
Develop a PBE-compatible characterization of debris-fields (e.g. material laws, porosity, angularity) |
SP |
D |
_ |
_ |
6.5. UQ Requirements
# |
Description |
Source |
Priority |
Status |
Implementation |
|---|---|---|---|---|---|
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 |
NA |
UF.3 |
Ability to use Multi-Scale Monte Carlo |
SP |
M |
_ |
_ |
UF.4 |
Ability to use Multi-Fidelity Models |
SP |
M |
Implemented |
NA |
UF.5 |
Ability to use Multi-model Forward Propagation |
UF |
D |
Implemented |
NA |
UR.1 |
Ability to use First Order Reliability method |
SP |
M |
Implemented |
NA |
UR.2 |
Ability to use Second Order Reliability method |
SP |
M |
Implemented |
NA |
UR.3 |
Ability to use Surrogate Based Reliability |
SP |
M |
Implemented |
NA |
UR.4 |
Ability to use Importance Sampling |
SP |
M |
Implemented |
NA |
UG.1 |
Ability to obtain Global Sensitivity Sobol indices |
UF |
M |
Implemented |
NA |
UG.2 |
Ability to use probability model-based global sensitivity analysis (PM-GSA) |
SP |
M |
Implemented |
NA |
UG.3 |
Ability to use probability model-based global sensitivity analysis (PM-GSA) for high-dimensional outputs |
UF |
D |
Implemented |
NA |
US.1 |
Ability to Construct Gaussian Process (GP) Regression Model from a Simulation Model |
SP |
M |
Implemented |
NA |
US.2 |
Ability to Construct GP Regression Model from Input-output Dataset |
SP |
M |
Implemented |
NA |
US.3 |
Ability to use Surrogate Model for UQ Analysis |
SP |
M |
Implemented |
NA |
US.4 |
Ability to Save the Surrogate Model |
SP |
M |
Implemented |
NA |
US.5 |
Ability to Use Adaptive Design of Experiments |
SP |
M |
Implemented |
NA |
US.6 |
Ability to Assess Reliability of Surrogate Model |
SP |
M |
Implemented |
NA |
US.7 |
Ability to Build Surrogate Under Stochastic Excitation |
SP |
M |
Implemented |
NA |
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 |
NA |
UN.2 |
Ability to read calibration data from a file |
UF |
M |
Implemented |
NA |
UN.3 |
Ability to handle non-scalar response quantities |
UF |
M |
Implemented |
NA |
UN.4 |
Ability to run gradient-free parameter estimation |
UF |
D |
Implemented |
NA |
UB.1 |
Ability to use DREAM algorithm for Bayesian inference |
SP |
M |
Implemented |
NA |
UB.2 |
Ability to use TMCMC algorithm for Bayesian inference |
SP |
M |
Implemented |
NA |
UB.3 |
Ability to read calibration data from a file |
UF |
M |
Implemented |
NA |
UB.4 |
Ability to handle non-scalar response quantities |
UF |
M |
Implemented |
NA |
UB.5 |
Ability to calibrate multipliers on error covariance |
UF |
M |
Implemented |
NA |
UB.6 |
Ability to use a default log-likelihood function |
UF |
M |
Implemented |
NA |
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 |
NA |
UB.10 |
Ability to perform hierarchical Bayesian calibration |
UF |
D |
Implemented |
NA |
UB.11 |
Ability to perform surrogate-aided Bayesian calibration |
UF |
D |
In Progress |
NA |
UH.1 |
Ability to sample from manifold |
SP |
M |
Implemented |
NA |
UH.2 |
Ability to build Reduced Order Model |
SP |
M |
In Progress |
NA |
UO.1 |
Ability to use User-Specified External UQ Engine |
SP |
M |
Implemented |
NA |
UO.2 |
Ability to use Own External FEM Application |
UF |
M |
Implemented |
NA |
UO.3 |
Ability to use UQ Engines other than SimCenterUQ, Dakota, or UCSD-UQ |
UF |
P |
_ |
_ |
6.6. RV Requirements
# |
Description |
Source |
Priority |
Status |
Implementation |
|---|---|---|---|---|---|
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 |
6.7. Common Research Application Requirements
# |
Description |
Source |
Priority |
Status |
Implementation |
|---|---|---|---|---|---|
CR.1 |
Open-source software where developers can test new data and develop algorithms |
||||
CR.1.1 |
Provide open-source applications utilizing code hosting platforms, e.g. GitHub |
SP |
M |
Implemented |
|
CR.1.2 |
Assign an open-source license that allows free use |
SP |
M |
Implemented |
|
CR.2 |
Ability to use multiple coupled resources (applications, databases, viz tools) by Practicing Engineers |
||||
CR.2.1 |
Allow users to launch scientific workflows |
SP |
M |
Implemented |
|
CR.3 |
Ability to utilize resources beyond the desktop including HPC |
||||
CR.3.1 |
Allow users to utilize HPC resources at TACC through DesignSafe |
SP |
M |
Implemented |
|
CR.4 |
Efficient use of multiple coupled and linked models requiring sharing and inter-operability of databases, computing environments, networks, visualization tools, and analysis systems |
||||
CR.4.1 |
Identify and include external analysis systems |
SP |
M |
InProgress |
_ |
CR.4.2 |
Identify and include external databases |
SP |
M |
InProgress |
|
CR.4.3 |
Identify and include external viz tools |
SP |
M |
InProgress |
|
CR.4.4 |
Identify and include external computing env |
SP |
M |
Inprogress |
1.1.2.5.5 |
CR.5 |
Tool available for download from web |
||||
CR.5.1 |
Tool downloadable from DesignSafe website |
GC |
M |
Implemented |
|
CR.6 |
Ability to benefit from programs that move research results into practice and obtain training |
||||
CR.6.1 |
Ability to use educational provisions to gain interdisciplinary education for expertise in earth sciences and physics, engineering mechanics, geotechnical engineering, and structural engineering to be qualified to perform these simulations |
GC |
D |
_ |
_ |
CR.6.2 |
Documentation exists demonstrating application usage |
SP |
M |
Implemented |
_ |
CR.6.3 |
Video exists demonstrating application usage |
SP |
M |
Implemented |
_ |
CR.6.4 |
Tool training through online and in-person training events |
SP |
M |
Implemented |
_ |
CR.7 |
Verification examples exist |
SP |
M |
Implemented |
|
CR.8 |
Validation of proposed analytical models against existing empirical datasets |
||||
CR.8.1 |
Validation examples exist, validated against tests or other software |
GC |
M |
_ |
|
CR.9 |
Tool to allow users to load and save user inputs |
SP |
M |
Implemented |
core |
CR.10 |
Installer which installs the application and all needed software |
UF |
D |
Implemented |