The following is the list of application requirements across all the SimCenter tools. It is helpful to view an abstract hierarchy of the tools, showing R2D at the top and the components at the bottom. Each tool can pull in requirements from other applications lower on the hierarchy. For example, PBE builds upon EE-UQ. It has its own requirements, i.e. DL, but includes the loading, modeling, and analysis requirements from EE-UQ. It specializes the UQ requirement, in that it only incorporates the sampling option. One set of requirements not shown in the figure is CR, the list of common research functionalities required in all the applications.

1. R2D Requirements

Table 1.1 Requirements - R2D

#

Description

Source

Priority

Status

R2D

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 UM 3.1

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 UM 2.4.1

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 UM 2.6.1 , R2D UM 2.7.1

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 UM 2.7.1.3 , R2D Example 1

R2D.4.2

Ability to include high-resolution earthquake damage and loss assessment for buildings from FEMA P58

SP

M

Implemented

R2D UM 2.8.1

R2D.4.3

Ability to include building-level wind damage and loss assessment from HAZUS

SP

M

Implemented

PELICUN UM 2.4

R2D.4.4

Ability to include building-level water damage and loss assessment from HAZUS

SP

M

Implemented

PELICUN UM 2.4

R2D.4.5

Ability to include earthquake damage and loss assessment for transportation networks from HAZUS

SP

M

Implemented

R2D Example 14

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 UM 2.9

R2D.7.2

Ability to utilize HPC resources in regional simulations that enables repeated simulation for stochastic modeling

GC

M

Implemented

R2D UM Run at DesignSafe

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 DM 2.3

R2D.7.4

Provide open-source software for developers to test new data and algorithms

GC

M

Implemented

R2D DM 1

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 UM 2.3.3

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
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

2. PBE Requirements

Table 2.1 Requirements - PBE

#

Description

Source

Priority

Status

PBE

PBE

Integrate fully coupled multi-model computations from hazard source through structure response, to compute reliable estimates of financial loss, business interruption, and casualties

GC

M

InProgress

Application

PBE.1

Ability to determine damage and loss for multiple different hazards

PBE.1.1

Damage and Loss due to ground shaking from Earthquake

GC

M

Implemented

Example 1

PBE.1.2

Damage and Loss due to Wind Loading

GC

M

InProgress

1.1.3.5.1

PBE.1.3

Damage and Loss due to water damage from Tsunami or Coastal Inundation

GC

M

InProgress

1.1.3.5.2

PBE.2

Ability to Select from Different Hazard Options

PBE.2.1

Ability to select from all EE-UQ Event Options listed in EE-UQ

SP

M

Implemented

Example 2

PBE.2.2

Ability to select from all WE-UQ Event Options listed in WE-UQ

SP

M

InProgress

1.1.3.5.1

PBE.2.3

Ability to select from all HydroUQ Event Options listed in Hydro-UQ

SP

M

InProgress

1.1.3.5.2

PBE.3

Ability to use different Model Generation Tools

PBE.3.1

Ability to Select All Building Model Generators in EE-UQ

SP

M

Implemented

Example 2

PBE.3.2

Ability to Select All Building Model Generators in WE-UQ

SP

M

InProgress

1.1.3.5.1

PBE.3.3

Ability to Select All Building Model Generators in HydroUQ

SP

M

InProgress

1.1.3.5.2

PBE.4

Ability to use Various UQ Methods and Variable Options

PBE.4.1

Ability to use all forward propagation methods available in EE-UQ, WE-UQ and HydroUQ

SP

M

Implemented

Example 2

PBE.4.2

Ability to use all random variable distributions in EE-UQ, WE-UQ and HydroUQ

SP

M

Implemented

Example 2

PBE.4.3

Ability to use train surrogate models using the methods from quoFEM

SP

D

InProgress

1.1.2.2.1, 1.1.2.2.2, 1.1.2.2.4

PBE.5

Ability to determine damage and loss utilizing different methods

PBE.5.1

Interface with pelicun to make available its suite of methods for damage and loss assessment for buildings

SP

M

Implemented

Example 1

PBE.6

Miscelleneous User Requests

PBE.6.1

Ability to Process own Output Parameters

UF

D

PBE.6.2

Add to Standard Earthquake a variable indicating analysis failure

UF

D

PBE.6.3

Allow users to provide their own set of EDPs for the analysis.

UF

D

Implemented

Example 1

PBE.6.4

Simplify run local and run remote by removing workdir locations. Move to preferences

UF

D

Implemented

Preferences

PBE.6.5

Add to EDP a variable indicating analysis failure

UF

D

PBE.6.6

Enable saving and loading Performance Models in CSV files

UF

D

Implemented

Example 1

PBE.7

General Software Requirements

PBE.7.1

Application to Provide Common SimCenter Research Application Requirements listed in CR

GC

M

InProgress

RTM

PBE.7.2

Ability to use new vizualization tools for viewing large datasets generated by PBE

GC

M

Implemented

Results Documentation
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

3. WE-UQ Requirements

Table 3.1 Requirements - WE

#

Description

Source

Priority

Status

WE-UQ

WE

Application to determine response of Building Subject to Wind Loading including formal treatment of randomness and uncertainty uncertainty

InProgress

Application

WE.1

Adaptation of non-linear analysis methods used in seismic design

GC

M

Implemented

WE.1.1

Include ability to create models incorprating options listed in MOD under BM

SP

M

Implemented

SIM

WE.1.2

Include ability to perform nonlinear analysis on the building models listed in ANA

SP

M

Implemented

SIM

WE.2

Ability to select from Wind Loading Options listed in WL2

SP

M

Implemented

WE.3

Ability to use Various UQ Methods and Variable Options

WE.3.1

Ability to use Forward Propagtion methods listed in UQ under UF

SP

M

Implemented

Example

WE.3.2

Ability to use Reliability Methods listed in UQ under UR

SP

M

Implemented

Example

WE.3.3

Ability to use Global Sensitivity Methods listed in UQ under UG

SP

M

Implemented

Example

WE.3.4

Ability to both use and create surrogates listed in UQ under US

SP

M

InProgress

1.2.2.2

WE.3.5

Ability to use High Dimensional UQ listed in UQ under UH

SP

M

InProgress

WE.4

Ability to see pressure distribution on buildings

GC

M

InProgress

1.2.1.1

WE.5

Ability to obtain basic building responses

SP

M

Implemented

EDP

WE.6

Ability to Visualize the Results

SP

M

Implemented

WE.6.1

Ability to view individual sample results

SP

M

Implemented

RES

WE.6.2

Ability to graphically view the results to show distribution in respone

SP

M

Implemented

RES

WE.7

Miscelleneous User Requests

WE.7.1

Ability to Process own Output Parameters

UF

M

Implemented

WE.7.2

Ability to Remove from Results certain Samples,e.g. ones that failed in analysis

UF

M

Implemented

WE.7.3

Create a digital twin of the Wall of Wind facility to allow researchers to simulate experiments

UF

M

Implemented

Example

WE.8

Tool should incorporate data from www

GC

M

Implemented

WE.8.1

Tool could obtain loading from Vortex Winds over www

SP

M

Implemented

Event

WE.8.2

Tool should obtain loading info from TPU wind tunnel tests

SP

D

Implemented

Example

WE.8.3

Tool should obtain building modelling info from database through www

SP

D

WE.9

General Software Requirements

WE.9.1

Application to Provide Common SimCenter Research Application Requirements listed in CR

GC

M

InProgress
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

4. Hydro-UQ Requirements

Table 4.1 Requirements - H

#

Description

Source

Priority

Status

Hydro-UQ

H

Application to determine response of a Building Subject to Water Action due to Storm Surge or Tsunami Hazards including formal treatment of randomness and uncertainty

GC

M

InProgress

Application

H.1

Quantification of water-borne debris hazards

GC

M

InProgress

1.1.2.1.2

H.1.1

Multiple debris impacts in a solitary-like wave

GC

M

Implemented

Example

H.1.2

Multiple debris impacts in a tsunami-like wave

GC

M

Implemented

Example

H.1.3

Multiple debris impacts in a surge-like wave

GC

M

InProgress

1.1.2.1.2

H.2

Effects of over-land flow, including waves, debris, flood velocity, wind-driven influences, erosion effects at buildings and channeling effects of the built environment

H.2.1

Effects of over-land flow

GC

D

Implemented

Example

H.2.2

Effects of waves, e.g. solitary vs irregular type

GC

D

Implemented

Example & Example

H.2.3

Effects of debris

GC

D

Implemented

Example

H.2.4

Effects of flood velocity

GC

D

Implemented

Example

H.2.5

Effects of wind-driven influences

GC

D

H.2.6

Effects of erosion at buildings

GC

D

H.2.7

Effects of flow channeling in the built environment

GC

D

Implemented

Example

H.2.8

Effects of frictional resistance with respect to debris hazards

SP

D

Implemented

hdro-0004

H.3

Ability to select from all Loading Options listed in HL.2

H.3.1

Ability to define local-scale tsunami loading events

SP

M

InProgress

1.1.2.1.2

H.3.2

Ability to define local-scale surge loading events

SP

M

InProgress

1.1.2.1.2

H.4

Ability to select from Building Modeling Options listed in MOD under BM

SP

M

Implemented

SIM

H.5

Include ability to perform nonlinear analysis on the building models listed in ANA

SP

M

Implemented

FEM

H.5.1

Implement ability to perform a strongly two-way coupled analysis between the fluid and structural domains

SP

M

Implemented

hdro-0003

H.5.2

Implement ability to perform a unified analysis between the fluid and structural domains

SP

M

Implemented

hdro-0002

H.5.3

Implement ability to perform a strongly two-way or unified analysis between the debris-fluid-structure domains

SP

M

Implemented

hdro-0002

H.6

Ability to use Various UQ Methods and Variable Options

H.6.1

Ability to use Forward Propagtion methods listed in UQ under UF

SP

M

InProgress

UQ

H.6.2

Ability to use Random Variable Distributions defined in RV

SP

M

Implemented

RV

H.6.3

Ability to use Reliability Methods listed in UQ under UR

SP

M

InProgress

H.6.4

Ability to use Global Sensitivity Methods listed in UQ under UG

SP

M

InProgress

H.6.5

Ability to both use and create surrogates listed in UQ under US

SP

M

InProgress

1.1.2.2.2 & 1.1.2.2.3

H.6.6

Ability to use High Dimensional UQ listed in UQ under UH

SP

M

H.7

Ability to Visualize the Results

H.7.1

Ability to view individual sample results

SP

M

Implemented

Example

H.7.2

Ability to graphically view the results to show distributions in structural responses

SP

M

Implemented

RES

H.8

Miscelleneous User Requests

H.8.1

Ability to quickly model experimental tests performed in Oregon State University’s Large Wave Flume (OSU LWF) wave tank

UF

M

Implemented

Example

H.8.1

Ability to quickly model experimental tests performed in Waseda University’s Tsunami Wave Basin (WU TWB) wave tank

UF

D

Implemented

Example

H.9

General Software Requirements

H.9.1

Application to Provide Common SimCenter Research Application Requirements listed in CR

GC

M

InProgress

1.1.2.5.1

H.10

Tool should incorporate data from world-wide-web (www)

H.10.1

Tool should use satelite imagery in aid of determine channeling effect

SP

D

H.10.2

Tool should use satelite imagery in aid of determining amount of debris

SP

D

InProgress

1.1.3.5.2

H.10.3

Tool should obtain building modelling info from database through www

SP

D

H.10.4

Tool should obtain bathymetry elevation data through www

UF

D

InProgress

NOAA Digital Coast

H.10.5

Tool should obtain sea-level rise data through www

UF

D

InProgress

NOAA Digital Coast

H.10.6

Tool should incorporate hardware-accelerated web-applications through www

UF

D

InProgress

Celeris-WebGPU

H.11

Library for surge/tsunami debris materials, geometries, longitudinal andlateral spread, uncertainties and correlations between parameters

SP

D

Proposed

Mar 2025

H.11.1

Library for broad regions, e.g. PNW, SoCal, Hawaii, or the Great Lakes

SP

D

Proposed

Mar 2025

H.11.2

Library for land-use classifications, e.g. rural, residential, industrial

SP

D

Proposed

Mar 2025

H.11.3

Library for seminal events, e.g. Tohoku 2011

SP

D

Proposed

Mar 2025

H.11.4

Library for a likely future event, e.g. Cascadia M9.0 Event

SP

D

Proposed

Mar 2025

H.12

Probabilistic methods to enable site- and wave-specific specific characterization of likely debris types, weights, and speeds

GC

D

Proposed

Jan 2025

H.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

Proposed

Jan 2025

H.12.2

Develop a probabilistic framework to couple debris mobilization,generation,and transport, e.g. random-walk skewed by friction anisotropy, flood and wind vectors

SP

D

Proposed

Jan 2025

H.13

Develop a PBE-compatible characterization of debris-fields, e.g. material laws, porosity, angularity

SP

D

Proposed

Jan 2025
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

5. EE-UQ Requirements

Table 5.1 Requirements - EE

#

Description

Source

Priority

Status

EE-UQ

EE

Application to determine response of Building Subject to Earthquake hazard including formal treatment of randomness and uncertainty

GC

M

Implemented

EE.1

Ability to select from Earthquake Loading Options listed in EL2

SP

M

Implemented

RTM

EE.2

Ability to select from Building Modeling Options listed in MOD under BM

SP

M

Implemented

RTM

EE.3

Ability to select from nonlinear analysis options listed in ANA

SP

M

Implemented

RTM

EE.4

Ability to use Various UQ Methods and Variable Options**

EE.4.1

Ability to use Forward Propagtion methods listed in UQ under UF

SP

M

Implemented

RTM

EE.4.2

Ability to use Random Variable Distributions defined in RV

SP

M

Implemented

RTM

EE.4.3

Ability to use Reliability Methods listed in UQ under UR

SP

M

Implemented

RTM

EE.4.4

Ability to use Global Sensitivity Methods listed in UQ under UG

SP

M

Implemented

RTM

EE.4.5

Ability to both use and create surrogates listed in UQ under US

SP

M

Implemented

RTM

EE.4.6

Ability to use High Dimensional UQ listed in UQ under UH

SP

M

EE.5

Ability to Visualize the Results

SP

M

Implemented

EE.5.1

Ability to view individual sample results

SP

M

Implemented

eeuq-0001

EE.5.2

Ability to graphically view the results to show distribution in response

SP

M

Implemented

eeuq-0001

EE.6

Miscellaneous User Requests

EE.6.1

Add to Standard Earthquake a variable indicating analysis failure

UF

D

EE.6.3

Run application from command line, include option to run remotely

UF

D

EE.7

General Software Requirements

EE.7.1

Application to Provide Common SimCenter Research Application Requirements listed in CR

GC

M

InProgress

RTM

EE.8

Tool should incorporate data from www

GC

M

Implemented

EE.8.1

Tool should obtain motion input data from www

SP

M

Implemented

eeuq-0003

EE.8.2

Tool should obtain building modelling info from database through www

SP

D
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

6. quoFEM Requirements

Table 6.1 Requirements - QF

#

Description

Source

Priority

Status

quoFEM

QF

Application to promote and aid use of UQ methods in NHE research for response estimation, surrogate modeling, and calibration

GC

M

InProgress

QF.1

Ability to use Various UQ Methods and Variable Options

QF.1.1

Ability to use Forward Propagtion methods listed in UQ under UF

SP

M

Implemented

qfem-0001

QF.1.2

Ability to use Random Variable Distributions defined in RV

SP

M

Implemented

qfem-0001

QF.1.3

Ability to use Reliability Methods listed in UQ under UR

SP

M

Implemented

qfem-0001

QF.1.4

Ability to use Global Sensitivity Methods listed in UQ under UG

SP

M

Implemented

qfem-0009

QF.1.5

Ability to both use and create surrogates listed in UQ under US

SP

M

Implemented

qfem-0016

QF.1.6

Ability to use High Dimensional UQ listed in UQ under UH

SP

M

InProgress

qfem-0022

QF.1.7

Ability to use Bayesian Calibration methods listed in UQ under UB

SP

M

InProgress

qfem-0014

QF.1.8

Ability to use Nonlinear Least Squares methods listed in UQ under UN

SP

M

Implemented

qfem-0007

QF.2

Ability to use Different Simulation Applications

QF.2.1

Ability to use OpenSees

SP

M

Implemented

qfem-0001

QF.2.2

Ability to use OpenSeesPy

SP

M

Implemented

qfem-0002

QF.2.3

Ability to Incorporate User Own Applications

UF

M

Implemented

qfem-0005

QF.3

Ability to Visualize the Results

SP

M

Implemented

QF.3.1

Ability to view individual sample results

SP

M

Implemented

qfem-0001

QF.3.2

Ability to graphically view the results to show distribution in respone

SP

M

Implemented

qfem-0001

QF.3.2

Ability to view statistical measures of response

SP

M

Implemented

qfem-0001

QF.4

Miscellaneous User Requests

QF.4.1

Run application from command line, include option to run remotely

UF

D

QF.5

General Software Requirements

QF.5.1

Application to Provide Common SimCenter Research Application Requirements listed in CR

GC

M

InProgress
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

7. Earthquake Loading Requirements

Table 7.1 Requirements - EL

#

Description

Source

Priority

Status

EE-UQ

PBE

R2D

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

_

_

R2D UM 2.3.5

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

_

_

R2D UM 3.1.4.3

EL.1.3

Use GIS-Specified Matrix of Recorded Motions

SP

M

Implemented

_

_

R2D UM 2.3

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

UM

_

_

EL.2.1.2

Select using all options available at PEER site

UF

D

Implemented

UM

_

_

EL.2.1.3

Select using user-supplied spectrum

UF

D

Implemented

eeuq-0003

_

_

EL.2.2

Ability to select utilizing PEER NGA_West web service

SP

D

Implemented

eeuq-0003

_

R2D UM 3.1.6

EL.2.3

Ability to select from a list of user-supplied PEER motions

SP

M

Implemented

eeuq-0001

_

_

EL.2.4

Ability to select from a list of SimCenter motions

SP

M

Implemented

UM

_

_

EL.2.5

Ability to use OpenSHA and selection methods to generate motions

UF

D

Implemented

_

_

R2D UM 3.1.2

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

eeuq-0002

_

R2D UM 2.3.5

EL.2.7.2

Nonlinear site response with bidirectional loading

SP

M

Implemented

UM

_

_

EL.2.7.3

Nonlinear site response with full stochastic characterization of soil layers

SP

M

Implemented

eeuq-0002

_

_

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

eeuq-0005

_

_

EL.2.8.2

per Dabaghi Der Kiureghian (2017)

UF

D

Implemented

eeuq-0005

_

_

EL.2.9

Ability to select from synthetic ground motions

SP

M

Implemented

eeuq-0005

_

_

EL.2.10

Ability to select surrogate modeling events

SP

M

Implemented

eeuq-0007

_

_
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

8. Wind Loading Requirements

Table 8.1 Requirements - WL

#

Description

Source

Priority

Status

WE-UQ

PBE

R2D

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

N/A

_

_

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

1.1.3.3.2

_

_

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

_

_

_

weuq-0007

_

_

WL.2.1.1

Accommodate Range of Low Rise building shapes

_

_

_

_

_

_

WL.2.1.1.1

Flat Shaped Roof - TPU dataset

SP

M

Implemented

weuq-0007

_

_

WL.2.1.1.2

Gable Shaped Roof - TPU dataset

SP

M

Implemented

weuq-0007

_

_

WL.2.1.1.3

Hipped Shaped Roof - TPU dataset

SP

M

Implemented

weuq-0007

_

_

WL.2.1.2

Accommodate Range of High Rise building

SP

M

InProgress

UM

_

_

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

UM

_

_

WL.2.3

Accommodate Data from Wind Tunnel Experiment

SP

M

Implemented

UM

_

_

WL.2.4

Simple CFD model generation and turbulence modeling

GC

M

Implemented

weuq-0013

_

_

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

weuq-0013

_

_

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

weuq-0001

_

_

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

_

_

_

_
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

9. Surge/Tsunami Loading Requirements

Table 9.1 Requirements - HL

#

Description

Source

Priority

Status

Hydro-UQ

PBE

R2D

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

1.1.3.3.2

_

_

HL.2

Local Scale Storm Surge/Tsunami Hazard Options

GC

M

InProgress

1.1.2.1.2

_

_

HL.2.1

Using computational fluid dynamics to model the interface and loading between waves and buildings

GC

M

InProgress

1.1.2.1.2

_

_

HL.2.1.1

CFD to model fluid flow around a single rigid structure

SP

M

Implemented

UM

_

_

HL.2.1.2

Mesh refinement around structures

SP

M

Implemented

hdro-0003

_

_

HL.2.1.3

CFD to model fluid flow around a single deformable structure

SP

M

Implemented

hdro-0003

_

_

HL.2.1.4

CFD to model fluid flow considering inflow and accumulation of fluid inside a rigid structure

SP

M

InProgress

1.1.2.1.2

_

_

HL.2.1.5

CFD to model fluid flow considering inflow, accumulation, and possible outflow of fluid across a deformable structure

SP

M

Implemented

hdro-0003

_

_

HL.2.1.6

CFD to model fluid flow considering a collapsing structure

SP

M

InProgress

1.1.3.5.2

_

_

HL.2.2

Quantification of flood-borne debris hazards

GC

M

InProgress

hdro-0002, hdro-0004

_

_

HL.2.2.1

Ability to quantify the effect of unconstrained and non-colliding floating bodies

SP

M

Implemented

hdro-0002

_

_

HL.2.2.2

Ability to quantify the effect of colliding flood-borne debris

SP

M

Implemented

hdro-0004

_

_

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

hdro-0004

_

_

HL.2.2.4

Integrate one of the methods for integrating particles with Hydro workflow

GC

M

Implemented

hdro-0004

_

_

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

hdro-0002

_

_

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

1.1.3.3.2

HL.2.5.1

Interface GeoClaw and OpenFOAM

SP

M

Implemented

UM

_

_

HL.2.5.2

Interface AdCirc and OpenFOAM

SP

M

InProgress

1.1.2.1.2, 1.1.3.3.2

_

_

HL.2.6

Libraries of high-resolution hurricane wind/surge/wave simulations

SP

M

InProgress

1.1.1.1.4

_

_

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

1.1.1.1.4

_

_

HL.2.6.4

Develop a simulation library of MPM or SPH simulations

SP

D

InProgress

1.1.1.1.4

_

_

HL.2.6.5

Develop a simulation library of Celeris simulations

SP

D

InProgress

1.1.1.1.4

_

_

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

1.1.2.2.2

_

_

HL.2.7.2

Ability to simulate with surrogate models as an alternative to full 3D fluids

SP

M

InProgress

1.1.2.2.3

_

_

HL.2.8

Develop digital twin(s) for wave tank facility(ies)

SP

M

Implemented

hdro-0002

_

_

HL.2.8.1

Develop digital twin of the Oregon State University’s Large Wave Flume (OSU LWF) wave tank facility

SP

M

Implemented

hdro-0002

_

_

HL.2.8.2

Develop digital twin of the Oregon State University’s Directional Wave Basing (OSU DWB) wave tank facility

SP

D

InProgress

1.1.2.5.1

_

_

HL.2.8.3

Develop digital twin of the Waseda University’s Tsunami Wave Basin (WU TWB) wave tank facility

SP

D

Implemented

hdro-0004

_

_

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

1.1.2.5.1

_

_

HL.2.8.5

Develop digital twin of the Hannover Large Wave Flume (HLWF) wave tank facility

SP

D

InProgress

1.1.2.5.1

_

_

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

_

_

_

_
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

10. UQ Requirements

Table 10.1 Requirements - Uncertainty Quantification Methods and Variables

#

Description

Source

Priority

Status

quoFEM

EE-UQ

WE-UQ

Hydro-UQ

PBE

R2D

UF.1

Ability to use basic Monte Carlo and LHS methods

SP

M

Implemented

qfem-0001

eeuq-0001

weuq-0001

hdro-0001

pbdl-0001

r2d

UF.2

Ability to use Gaussian Process Regression

SP

M

Implemented

UM

UM

NA

NA

NA

NA

UF.3

Ability to use Multi-Scale Monte Carlo

SP

M

_

_

_

_

_

_

_

UF.4

Ability to use Multi-Fidelity Models

SP

M

Implemented

UM

eeuq-0011

UM

UM

NA

NA

UF.5

Ability to use Multi-model Forward Propagation

UF

D

Implemented

qfem-0027

eeuq-0008

weuq-0001

UM

NA

NA

UR.1

Ability to use First Order Reliability method

SP

M

Implemented

qfem-0001

UM

UM

UM

NA

NA

UR.2

Ability to use Second Order Reliability method

SP

M

Implemented

UM

UM

UM

UM

NA

NA

UR.3

Ability to use Surrogate Based Reliability

SP

M

Implemented

UM

eeuq-0001

UM

UM

NA

NA

UR.4

Ability to use Importance Sampling

SP

M

Implemented

UM

UM

UM

UM

NA

NA

UG.1

Ability to obtain Global Sensitivity Sobol indices

UF

M

Implemented

qfem-0001

UM

UM

UM

NA

NA

UG.2

Ability to use probability model-based global sensitivity analysis (PM-GSA)

SP

M

Implemented

qfem-0009

UM

UM

UM

NA

NA

UG.3

Ability to use probability model-based global sensitivity analysis (PM-GSA) for high-dimensional outputs

UF

D

Implemented

qfem-0023

UM

UM

UM

NA

NA

US.1

Ability to Construct Gaussian Process (GP) Regression Model from a Simulation Model

SP

M

Implemented

qfem-0016

eeuq-0009

NA

NA

NA

NA

US.2

Ability to Construct GP Regression Model from Input-output Dataset

SP

M

Implemented

UM

UM

NA

NA

NA

NA

US.3

Ability to use Surrogate Model for UQ Analysis

SP

M

Implemented

qfem-0016

eeuq-0010

NA

NA

NA

NA

US.4

Ability to Save the Surrogate Model

SP

M

Implemented

qfem-0016

eeuq-0009

NA

NA

NA

NA

US.5

Ability to Use Adaptive Design of Experiments

SP

M

Implemented

UM

NA

NA

NA

NA

NA

US.6

Ability to Assess Reliability of Surrogate Model

SP

M

Implemented

qfem-0016

eeuq-0009

NA

NA

NA

NA

US.7

Ability to Build Surrogate Under Stochastic Excitation

SP

M

Implemented

qfem-0025

eeuq-0009

NA

NA

NA

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

qfem-0007

NA

NA

NA

NA

NA

UN.2

Ability to read calibration data from a file

UF

M

Implemented

qfem-0007

NA

NA

NA

NA

NA

UN.3

Ability to handle non-scalar response quantities

UF

M

Implemented

qfem-0007

NA

NA

NA

NA

NA

UN.4

Ability to run gradient-free parameter estimation

UF

D

Implemented

UM

NA

NA

NA

NA

NA

UB.1

Ability to use DREAM algorithm for Bayesian inference

SP

M

Implemented

UM

NA

NA

NA

NA

NA

UB.2

Ability to use TMCMC algorithm for Bayesian inference

SP

M

Implemented

qfem-0014

NA

NA

NA

NA

NA

UB.3

Ability to read calibration data from a file

UF

M

Implemented

qfem-0014

NA

NA

NA

NA

NA

UB.4

Ability to handle non-scalar response quantities

UF

M

Implemented

qfem-0014

NA

NA

NA

NA

NA

UB.5

Ability to calibrate multipliers on error covariance

UF

M

Implemented

qfem-0014

NA

NA

NA

NA

NA

UB.6

Ability to use a default log-likelihood function

UF

M

Implemented

qfem-0014

NA

NA

NA

NA

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

qfem-0029

NA

NA

NA

NA

NA

UB.10

Ability to perform hierarchical Bayesian calibration

UF

D

Implemented

qfem-0028

NA

NA

NA

NA

NA

UB.11

Ability to perform surrogate-aided Bayesian calibration

UF

D

In Progress

1.1.2.3.4

NA

NA

NA

NA

NA

UH.1

Ability to sample from manifold

SP

M

Implemented

qfem-0022

eeuq-0006

NA

NA

NA

NA

UH.2

Ability to build Reduced Order Model

SP

M

In Progress

1.2.4.4

NA

NA

NA

NA

UO.1

Ability to use User-Specified External UQ Engine

SP

M

Implemented

qfem-0017

NA

NA

NA

NA

NA

UO.2

Ability to use Own External FEM Application

UF

M

Implemented

UM

NA

NA

NA

NA

NA

UO.3

Ability to use UQ Engines other than SimCenterUQ, Dakota, or UCSD-UQ

UF

P

_

_

_

_

_

_

_
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

11. RV Requirements

Table 11.1 Requirements - Random Variables

#

Description

Source

Priority

Status

quoFEM

EE-UQ

WE-UQ

Hydro-UQ

PBE

R2D

RV.1

Various Random Variable Probability Distributions

RV.1.1

Normal

SP

M

Implemented

qfem-0001

eeuq-0001

weuq-0001

hdro-0001

pbdl-0002

UM

RV.1.2

Lognormal

SP

M

Implemented

qfem-0001

eeuq-0000

weuq-0000

UM

pbdl-0000

UM

RV.1.3

Uniform

SP

M

Implemented

qfem-0014

eeuq-0000

weuq-0000

UM

pbdl-0000

UM

RV.1.4

Beta

SP

M

Implemented

qfem-0002

eeuq-0000

weuq-0000

UM

pbdl-0000

UM

RV.1.5

Weibull

SP

M

Implemented

qfem-0002

eeuq-0000

weuq-0000

UM

pbdl-0000

UM

RV.1.6

Gumbel

SP

M

Implemented

qfem-0000

eeuq-0000

weuq-0000

UM

pbdl-0000

UM

RV.1.7

Exponential

SP

M

Implemented

qfem-0000

eeuq-0000

weuq-0000

_

pbdl-0000

_

RV.1.8

Discrete

SP

M

Implemented

qfem-0000

eeuq-0000

weuq-0000

_

pbdl-0000

_

RV.1.9

Gamma

SP

M

Implemented

qfem-0000

eeuq-0000

weuq-0000

_

pbdl-0000

_

RV.1.10

Chi-squared

SP

M

Implemented

qfem-0000

eeuq-0000

_

_

_

_

RV.1.11

Truncated Exponential

SP

M

Implemented

qfem-0000

eeuq-0011

_

_

_

_

RV.2

User-defined Distribution

SP

M

_

_

_

_

_

_

_

RV.3

Define Correlation Matrix

SP

M

Implemented

qfem-0009

eeuq-0000

weuq-0000

UM

pbdl-0000

UM

RV.4

Random Fields

SP

M

_

_

_

_

_

_

_

RV.5

Ability to View Graphically the density function when defining the RV

UF

D

Implemented

qfem-0009

eeuq-0008

weuq-0013

UM

UM

UM
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

12. Modeling Requirements

Table 12.1 Requirements - MOD

#

Description

Source

Priority

Status

EE-UQ

WE-UQ

Hydro-UQ

PBE

R2D

MOD

Asset Model Generators for Analysis

BM

Asset Model Generators for Buildings

BM.1

Ability to quickly create a simple nonlinear building model

GC

D

Implemented

eeuq-0002

weuq-0012

UM

pbdl-0002

E2

BM.2

Ability to use existing OpenSees model scripts

SP

M

Implemented

eeuq-0001

weuq-0001

hdro-0001

pbdl-0000

E4

BM.3

Ability to define a building and use Expert System to generate FE mesh

SP

D

Implemented

eeuq-0004

_

_

UM

_

BM.4

Ability to define a building and use Machine Learning applications to generate FE

GC

D

_

_

_

_

_

_

BM.5

Ability to specify connection details for member ends

UF

D

_

_

_

_

_

_

BM.6

Ability to define a user-defined moment-rotation response representing the connection details

UF

D

_

_

_

_

_

_

BM.7

Ability to incorporate AutoSDA Steel Design Application in Local Applications

UF

M

Implemented

eeuq-0004

_

_

UM

BM.8

Ability to use user-supplied Python script to generate mesh

UF

M

InProgress

SC

SC

SC

SC

E4

BM.9

Ability to use multiple models of similar fidelity

SP

M

Implemented

eeuq-0008

BM.10

Ability to use multiple models of different fidelity

SP

M

Implemented

eeuq-0011
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

13. Analysis Requirements

Table 13.1 Requirements - ANA

#

Description

Source

Priority

Status

EE-UQ

WE-UQ

Hydro-UQ

PBE

R2D

ANA.1

Ability to select from different Nonlinear Analysis options

_

_

_

_

_

_

_

_

ANA.1.1

Ability to specify OpenSees as FEM engine and to specify different analysis options

SP

M

Implemented

eeuq-0001

_

_

pbdl-0000

_

ANA.1.2

Ability to provide own OpenSees Analysis script to OpenSees engine

SP

D

Implemented

eeuq-0001

_

_

pbdl-0000

_

ANA.1.3

Ability to provide own Python script and use OpenSeesPy engine

SP

D

_

_

_

_

_

_

ANA.1.4

Ability to use alternative FEM engines

SP

M

_

_

_

_

_

_

ANA.2

Ability to know if an analysis run fails

UF

M

_

_

_

_

_

_

ANA.3

Ability to specify Modal Damping

_

_

_

_

_

_

_

_

ANA.3.1

Ability to specify damping ratio as a random variable

UF

M

Implemented

UM

_

_

pbdl-0000

_

ANA.3.2

When using Rayleigh Damping, ability to specify the two modes used to calculate damping parameters

UF

M

Implemented

eeuq-0001

weuq-0001

UM

pbdl-0000

E2

ANA.4

Ability to run for more than 60 hours at DesignSafe

UF

D

_

_

_

_

_

_

ANA.5

Ability to specify the number of iterations in convergence test

UF

M

Implemented

eeuq-0001

weuq-0001

UM

pbdl-0000

E2

ANA.6

Ability to use multiple analysis options

SP

M

Implemented

eeuq-0008

pbdl-0000
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

14. Damage & Loss Requirements

Table 14.1 Requirements - DL

#

Description

Source

Priority

Status

PBE

R2D

DL.1

Damage and Loss Methods

_

_

_

_

_

DL.1.1

Make the component fragility and consequence functions from FEMA P58 available

_

_

_

_

_

DL.1.1.1

FEMA P58 First Edition

SP

M

Implemented

Superseded by Second Edition

Superseded by Second Edition

DL.1.1.2

FEMA P58 Second Edition

UF

M

Implemented

Example 1

Portfolio assessment example in development

DL.1.1.3

Extend FEMA P58 Second Edition consequence functions with environmental impact parameters

SP

M

Implemented

Example 1

Portfolio assessment example in development

DL.1.2

Make the building fragility and consequence functions from HAZUS available

_

_

_

_

_

DL.1.2.1

HAZUS earthquake damage and reconstruction cost and time

SP

M

Implemented

Example 2

Example 1

DL.1.2.2

HAZUS hurricane wind damage and reconstruction cost and time

SP

M

Implemented

1.1.3.5.1

Example 8

DL.1.2.3

HAZUS storm surge damage and reconstruction cost and time

SP

M

Implemented

1.1.3.5.2

Example 7

DL.1.3

Make the lifeline fragility and consequence functions from HAZUS available

_

_

_

_

_

DL.1.3.1

HAZUS bridge damage and reconstruction cost and time

SP

M

Implemented

1.1.3.5.3

Example 14

DL.1.3.2

HAZUS buried pipeline damage and reconstruction cost and time

SP

M

Implemented

1.1.3.5.4

Example 16

DL.1.3.3

HAZUS power network damage and reconstruction cost and time

SP

M

InProgress

1.1.3.4.3

1.1.3.4.3

DL.1.4

Extend available high-resolution building damage and loss model parameters

_

_

_

_

_

DL.1.4.1

Building damage and loss model parameters under wind hazards

SP

M

InProgress

1.1.3.5.1

1.1.3.5.1

DL.1.4.2

Building damage and loss model parameters under water hazards

SP

M

InProgress

1.1.3.5.2

1.1.3.5.2

DL.1.5

Make high-resolution damage and loss model parameters available for lifelines

_

_

_

_

_

DL.1.5.1

Transportation network damage and loss model parameters

SP

M

InProgress

1.1.3.5.3

1.1.3.5.3

DL.1.5.2

Buried pipeline network damage and loss model parameters

SP

M

InProgress

1.1.3.5.4

1.1.3.5.4

DL.2

Damage and Loss Database

_

_

_

_

_

DL.2.1

Interface with the Damage and Loss Model Database and make all model parameters available

SP

M

Implemented

Example 2

Example 1
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

15. Recovery Requirements

Table 15.1 Requirements - REC

#

Description

Source

Priority

Status

R2D

REC.1

Building Recovery

_

_

_

_

REC.1.1

Incorporate advanced methods for building recovery time estimation

SP

M

Implemented

Portfolio assessment example in development

REC.2

Housing and Community Recovery

_

_

_

_

REC.2.1

Incorporate modeling of the recovery of households and communities

SP

M

InProgress

1.1.4.2.3

REC.3

Infrastructure Recovery

_

_

_

_

REC.3.1

Incorporate modeling of the recovery of transportation networks

SP

M

InProgress

1.1.4.2.4

REC.3.2

Incorporate modeling of the recovery of buried pipeline networks

SP

M

InProgress

1.1.4.2.4

REC.3.3

Incorporate modeling of the recovery of power networks

SP

M

_

1.1.4.2.4

REC.4

Business Recovery

_

_

_

_

REC.4.1

Incorporate modeling of the recovery of businesses

SP

M

InProgress

1.1.4.2.5

REC.4.2

Ability to incorporate improved indirect economic loss estimation models

GC

M

_

1.1.4.2.5

REC.4.3

Ability to include demand surge in the determination of losses

GC

M

_

1.1.4.2.5

REC.5

Interdependencies

_

_

_

_

REC.5.1

Implement a framework to model interdependencies between the recovery of various systems

SP

M

InProgress

1.1.3.4.6

REC.5.2

Ability to include lifeline disruptions

GC

M

InProgress

1.1.3.4.6

REC.6

Metrics of recovery

_

_

_

_

REC.6.1

Implement metrics to inform recovery and community resilience based on the outputs of the available recovery models

SP

M

InProgress

1.1.4.3.2
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

16. Common Research Application Requirements

Table 16.1 Requirements - CR

#

Description

Source

Priority

Status

quoFEM

EE-UQ

WE-UQ

Hydro-UQ

PBE

R2D

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

quoFEM

EE-UQ

WE-UQ

HydroUQ

PBE

R2D

CR.1.2

Assign an open-source license that allows free use

SP

M

Implemented

quoFEM

EE-UQ

WE-UQ

HydroUQ

PBE

R2D

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

quoFEM

EE-UQ

WE-UQ

HydroUQ

PBE

R2D

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

quoFEM

EE-UQ

WE-UQ

HydroUQ

PBE

R2D

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

_

eeuq-0003

UM

_

pbdl-0001

UM

CR.4.3

Identify and include external viz tools

SP

M

InProgress

_

_

SC

_

SC

SC

CR.4.4

Identify and include external computing env

SP

M

Inprogress

1.1.2.5.5

1.1.2.5.5

1.1.2.5.5

1.1.2.5.5

1.1.2.5.5

1.1.2.5.5

CR.5

Tool available for download from web

CR.5.1

Tool downloadable from DesignSafe website

GC

M

Implemented

quoFEM

EE-UQ

WE-UQ

HydroUQ

PBE

R2D

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

quoFEM

EE-UQ

WE-UQ

_

PBE

R2D

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

core

core

core

core

core

CR.10

Installer which installs the application and all needed software

UF

D

Implemented

quoFEM

EE-UQ

WE-UQ

HydroUQ

PBE

R2D
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

17. BRAILS Requirements

Table 17.1 Requirements - BR

#

Description

Source

Priority

Status

BRAILS

BR.1

Need for scalable tools that autonomously create an accurate database of all infrastructure components, including points of inter- dependency with other infrastructure components

GC

M

InProgress

1.1.3.1.2, 1.1.3.1.3, 1.1.4.2.4

BR.2

Developing and sharing standardized definitions, measurement protocols and strategies for data collection

GC

M

InProgress

1.1.3.4.1, 1.1.3.6.2, 1.1.3.4.1

BR.3

Developing tools that utilize GIS information and online images, e.g., Google Maps, for data collection for gathering building information

GC

M

Implemented

BR.3.1

Develop framework for creating asset inventories

SP

M

Implemented

UM Workflow

BR.3.2

Create workflow application for building inventory from framework modules

SP

M

Implemented

UM Workflow

BR.3.2

Create workflow application for transportation network from framework modules

SP

M

Implemented

Transportation Inventory Generator

BR.3.2

Create workflow application for developing building inventories from NHERI RAPID imagery

UF

M

Implemented

RAPID Tools

BR.4

Developing modules for asset inventory workflows identified in BR4

InProgress

BR.4.1

Predicting if building is a soft-story building for earthquake simulations

UF

M

Implemented

UM Soft Story Classifier

BR.4.2

Predicting first floor height

SP

M

Implemented

Facade Parser

BR.4.3

Predicting roof height

SP

M

Implemented

Facade Parser

BR.4.4

Predicting eave height

SP

M

Implemented

Facade Parser

BR.4.5

Predicting eave length

SP

D

Implemented

Facade Parser

BR.4.6

Predicting roof shape

SP

M

Implemented

UM Roof Classifier

BR.4.7

Predicting roof pitch

SP

M

Implemented

Facade Parser

BR.4.8

Predicting roof cover material

UF

M

Implemented

Roof Cover Classifier

BR.4.9

Predicting window area

SP

M

Implemented

Facade Parser

BR.4.10

Predicting number of floors

SP

M

Implemented

UM Number of Floor Detector

BR.4.11

Classifying elevated building

SP

M

Implemented

UM Foundation Elevation Classifier

BR.4.12

Predicting occupancy type

SP

M

Implemented

UM Occupancy Classifier

BR.4.13

Predicting Year Built

SP

M

Implemented

UM Year Built Classifier

BR.4.14

Predicting attached garage

SP

M

Implemented

UM Garage Detector

BR.4.15

Predicting presence of masonry chimney

UF

D

Implemented

UM Chimney Detector

BR.4.16

Predicting building material

SP

M

InProgress

1.1.3.1.2

BR.4.17

Predicting Structural Type

SP

M

Implemented

Inventory Generator

BR.5

DesignSafe integration to provide access to GPU

Implemented

BR.5.1

Create JupyterHub notebook at DesignSafe for building asset inventory workflow usage

SP

M

Implemented

Example Notebooks

BR.5.2

For classification done at DesignSafe, store images and meta data for BE Database

SP

M

Implemented

Example Notebooks

BR.5.3

Create JupyterHub notebook at DesignSafe for individual modules to demonstrate immediate results

SP

M

Implemented

Example Notebooks

BR.6

Work to gather data for Module Validation/Verification/Training

SP

M

InProgress

1.1.3.1.2, 1.1.3.1.5
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

18. PELICUN Requirements

Table 18.1 Requirements - P

#

Description

Source

Priority

Status

PELICUN

P.1

Existing Assessment Methods

P.1.1

Implement the high-resolution loss assessment methodologies

GC

P.1.1.1

Implement the scenario-based assessment from FEMA-P58

SP

M

Implemented

pbdl-0001

P.1.1.2

Implement the time-based assessment from FEMA-P58

SP

D

InProgress

P.1.1.3

Implement high-resolution assessment of buildings under wind hazards

SP

M

InProgress

1.1.3.5.1

P.1.1.4

Implement high-resolution assessment of buildings under water hazards

SP

M

InProgress

1.1.3.5.2

P.1.1.5

Implement high-resolution assessment of transportation networks

SP

M

InProgress

1.1.3.5.3

P.1.1.6

Implement high-resolution assessment of buried pipelines

SP

M

InProgress

1.1.3.5.4

P.1.2

Implement the efficient loss assessment methodologies from HAZUS

GC

P.1.2.1

Implement the assessment of buildings under earthquake hazard from HAZUS

SP

M

Implemented

E1

P.1.2.2

Implement the assessment of buildings under hurricane wind hazard from HAZUS

SP

M

Implemented

E8

P.1.2.3

Implement the assessment of buildings under storm surge hazard from HAZUS

SP

M

Implemented

E7

P.1.2.4

Implement the assessment of buried pipelines under earthquake hazard from HAZUS

SP

M

Implemented

E16

P.1.2.5

Implement the assessment of transportation networks under earthquake hazard from HAZUS

SP

M

Implemented

E14

P.1.2.6

Implement the assessment of power networks under earthquake hazard from HAZUS

SP

M

InProgress

1.1.3.4.3

P.2

Control

P.2.1

Analysis & Data

P.2.1.1

Allow users to set the number of realizations

SP

M

Implemented

pbdl-0001

P.2.1.2

Allow users to customize fragility and consequence function parameters

SP

D

Implemented

E9

P.2.1.3

Allow users to specify dependencies between logically similar parts of the stochastic models

SP

D

Implemented

pbdl-0001

P.2.2

Response Model

P.2.2.1

Allow users to specify the added uncertainty to EDPs (increase in log-standard dev.)

SP

M

Implemented

pbdl-0001

P.2.2.2

Allow users to specify the EDP ranges that correspond to reliable simulation results

SP

D

Implemented

pbdl-0001

P.2.2.3

Allow users to specify the type of distribution they want to fit to the empirical EDP data

UF

D

Implemented

pbdl-0001

P.2.2.4

Allow users to choose if they want to fit a distribution only to the non-collapsed EDPs

UF

M

Implemented

pbdl-0001

P.2.3

Performance Model

P.2.3.1

Allow users to prescribe a different number of inhabitants on each floor

SP

D

InProgress

Revision of model implemented in v2.0 in progress

P.2.3.2

Allow users to customize the temporal distribution of inhabitants

SP

D

InProgress

Revision of model implemented in v2.0 in progress

P.2.3.3

Allow users to prescribe different component quantities for each floor in each direction

SP

D

Implemented

pbdl-0001

P.2.3.4

Allow users to specify the number of component groups and their quantities in each performance group

UF

D

Implemented

pbdl-0001

P.2.4

Damage Model

P.2.4.1

Allow users to specify the residual drift limits that determine irrepairability

SP

D

Implemented

pbdl-0001

P.2.4.2

Allow users to specify the yield drift value that is used to estimate residual drifts from peak drifts

SP

D

Implemented

pbdl-0001

P.2.4.3

Allow users to specify the EDP limits that are used to determine collapse probability

SP

D

Implemented

pbdl-0001

P.2.4.4

Allow users to specify arbitrary collapse modes and their likelihood

SP

D

Implemented

UM

P.2.4.5

Allow users to prescribe the collapse probability of the structure

UF

M

Implemented

UM

P.2.5

Loss Model

P.2.5.1

Allow users to decide which DVs to calculate

SP

D

Implemented

UM

P.2.5.2

Allow users to specify the likelihood of various injuries in each collapse mode

SP

D

InProgress

Revision of model implemented in v2.0 in progress

P.3

Hazard Model

P.3.1

Hazard Occurrence Rate

P.3.1.1

Enable estimation of the likelihood of earthquake events

SP

D

P.3.1.2

Enable estimation of the likelihood of wind events

SP

D

P.3.1.3

Enable estimation of the likelihood of storm surge events

SP

D

P.3.1.4

Enable estimation of the likelihood of tsunami events

SP

D

P.4

Response Model

P.4.1

EDP (re-)sampling

P.4.1.1

Enable coupled assessment by using raw EDP values as-is

UF

M

Implemented

E1

P.4.1.2

Enable non-Gaussian EDP distributions

UF

D

Implemented

UM

P.4.2

EDP Identification

P.4.2.1

Implement automatic identification of required EDP types based on the performance model

SP

D

P.5

Performance Model

P.5.1

Auto-population of performance models

P.5.1.1

Implement framework to enable user-defined auto-population scripts

UF

D

Implemented

E1

P.5.1.2

Prepare script to perform auto-population based on normative quantities in FEMA P58

UF

D

P.6

Damage Model

P.6.1

Collapse estimation

P.6.1.1

Estimate collapse probability of the structure using EDP limits and the joint distribution of EDPs

SP

D

Implemented

pbdl-0001

P.6.1.2

Estimate the collapse probability of the structure using empirical (raw) EDP data

UF

M

Implemented

UM

P.6.1.3

Enable user-defined collapse probability

UF

M

Implemented

UM

P.6.2

Building Damage

P.6.2.1

Implement earthquake fragility functions for building components from FEMA P58

SP

M

Implemented

pbdl-0001

P.6.2.2

Implement earthquake fragility functions for buildings from HAZUS

SP

M

Implemented

pbdl-0002

P.6.2.3

Implement wind fragility functions for buildings from HAZUS

SP

M

Implemented

E8

P.6.2.4

Implement inundation fragility functions for buildings from HAZUS

SP

M

Implemented

E7

P.6.2.5

Implement high-resolution wind fragility functions for building components

SP

M

InProgress

1.1.3.5.1

P.6.2.6

Implement high-resolution inundation fragility functions for building components

SP

M

InProgress

1.1.3.5.2

P.6.3

Lifeline Damage

P.6.3.1

Implement earthquake fragility functions for buried pipelines from HAZUS

SP

M

Implemented

E16

P.6.3.2

Implement earthquake fragility functions for bridges from HAZUS

SP

M

Implemented

E14

P.6.3.3

Implement earthquake fragility functions for power networks from HAZUS

SP

M

P.6.3.4

Implement high-resolution fragility functions for buried pipelines

SP

M

InProgress

1.1.3.5.4

P.6.3.5

Implement high-resolution fragility functions for transportation networks

SP

M

InProgress

1.1.3.5.3

P.6.4

Cascading Damages

P.6.4.1

Implement fault tree-based cascading damage model

SP

M

Implemented

UM

P.7

Loss Model

P.7.1

Consequence functions for buildings

P.7.1.1

Implement functions for repair cost and time as per FEMA P58

SP

M

Implemented

pbdl-0001

P.7.1.2

Implement functions for red tag triggering as per FEMA P58

SP

M

InProgress

Revision of model implemented in v2.0 in progress

P.7.1.3

Implement functions for injuries and fatalities as per FEMA P58

SP

M

InProgress

Revision of model implemented in v2.0 in progress

P.7.1.4

Implement functions for repair cost and time as per HAZUS earthquake

SP

M

Implemented

pbdl-0002

P.7.1.5

Implement functions for debris as per HAZUS earthquake

SP

D

P.7.1.6

Implement functions for business interruption as per HAZUS earthquake

SP

D

P.7.1.7

Implement functions for repair cost and time as per HAZUS wind

SP

M

Implemented

E8

P.7.1.8

Implement functions for repair cost and time as per HAZUS inundation

SP

M

Implemented

E7

P.7.1.9

Implement functions for environmental impact estimation as per FEMA P58 2nd edition

SP

M

Implemented

pbdl-0001

P.7.1.10

Implement functions for high-resolution repair cost and time assessment for wind hazards

SP

M

InProgress

1.1.3.5.1

P.7.1.11

Implement functions for high-resolution repair cost and time assessment for water hazards

SP

M

InProgress

1.1.3.5.2

P.7.2

Consequence functions for other assets

P.7.2.1

Implement functions for repair cost and time for buried pipelines as per HAZUS earthquake

SP

M

InProgress

1.1.3.4.3

P.7.2.2

Implement functions for repair cost and time for bridges as per HAZUS earthquake

SP

M

Implemented

E14

P.7.2.3

Implement functions for repair cost and time for power networks as per HAZUS earthquake

SP

M

1.1.3.4.3

P.7.2.4

Implement high-resolution functions for repair cost and time for transportation networks

SP

M

InProgress

1.1.3.5.3

P.7.2.5

Implement high-resolution functions for repair cost and time for buried pipelines

SP

M

InProgress

1.1.3.5.4
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

19. BE Database Requirements

Table 19.1 Requirements - BE

#

Description

Source

Priority

Status

DB-BE

BE

Establish a National Infrastructure Data Base for characterizing the physical and natural infrastructure

BE.1

Ability to use cumulative knowledge bases rather than the piecemeal individual approaches

BE.1.1

Utilize Federated Databases to maintain individual databases & data sources yet provide central database resource

SP

M

InProgress

1.1.3.2.1

BE.2

Include national building model inventories

BE.2.1

Incorporate Building data from existing datasets published by federal government, states, counties, and cities

SP

M

InProgress

1.1.3.1.2 UM

BE.2.2

Ingest building data from web-scraping techniques, e.g. from Zillow, county websites

SP

M

InProgress

1.1.3.1.2 UM

BE.2.3

Ingest building data using AI/ML techniques and satellite and street-level images

SP

M

InProgress

1.1.3.1.2 UM

BE.3

Incorporate transportation newtwork data from existing datasets made available through www

BE.3.1

Ingest additionally needed transportation network data utilizing AI/ML and satellite and street-level images

SP

M

InProgress

1.1.3.1.3

BE.4

Include National Models of Utility Networks

GC

M

BE.4.1

Incorporate utility network data from existing datasets made available through www

SP

M

InProgress

1.1.3.1.4
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code

20. DL Database Requirements

Table 20.1 Requirements - DLD

#

Description

Source

Priority

Status

DB-DL

DLD.1

Data Schema

_

_

_

_

DLD.1.1

Generic JSON format

_

_

_

_

DLD.1.1.1

Develop a generic JSON data format for component fragility and consequence functions

SP

D

Implemented

Superseded by DLD.1.1.3

DLD.1.1.2

Store FEMA P58 and HAZUS component data in the new JSON format and make them available

SP

D

Implemented

Superseded by DLD.1.1.3

DLD.1.1.3

Develop a second-generation data schema that combines CSV and JSON files for fragility and consequence functions

SP

D

Implemented

Example 1

DLD.1.2

HDF5 Data Storage

_

_

_

_

DLD.1.2.1

Store the JSON files in an HDF5 data structure for each data source

SP

M

Implemented

Superseded by DLD.2.1.3

DLD.2.1

Online Database

_

_

_

_

DLD.2.1.1

Create an online database for storing parameters of damage and loss models for buildings

SP

M

Implemented

DL Model Library

DLD.2.1.2

Extend online database to store parameters of damage and loss models for transportation networks

SP

M

Implemented

DL Models for Transportation

DLD.2.1.3

Extend online database to store parameters of damage and loss models for buried pipeline networks

SP

M

InProgress

1.1.3.5.3

DLD.2.1.4

Populate building database with high-resolution model parameters from researchers

SP

M

InProgress

1.1.3.5.1

DLD.2.1.5

Populate lifeline database with high-resolution model parameters from researchers

SP

M

InProgress

1.1.3.5.3
Key:
Source: GC=Needed for Grand Challenges, SP=Senior Personnel, UF=User Feedback
Priority: M=Mandatory, D=Desirable, P=Possible Future
Status: Implemented, InProgress, and Blank (i.e. not started)
Implementation: UM=User Manual, DM=Developer Manual, SC=Source Code