5. Capabilities¶
Version 5.1 of R2D app was released in Sep 30, 2024, introducing significant updates and enhancements. This document outlines the functionalities available in the current version, highlighting new features and improvements in blue.
Major updates from Version 4.0 are adding liquefaction-induced ground deformation estimation in the regional earthquake event generation tool, refactored regional inventory generation tool BRAILS, and upgraded damage and loss engine Pelicun.
Release date: April, 2024
Hazard Types:
ShakeMap Scenarios for earthquake events, allowing the import of ShakeMap XML grid file, PGA Contours (.json) file, and Fault Rupture (.json) file.
Raster Defined Hazard for Earthquake, Hurricane, Inundation.
GIS Defined Hazard for Earthquake, Hurricane, Inundation.
Asset Types:
- Buildings:
Load building database in a
.csv
format.Load building database in a
.gis
format.
- Transportation infrastructure:
Load transportation infrastructure database in SimCenter’s
.geojson
format.Load transportation infrastructure database in common
.gis
format.
- Water Distribution Network:
Load water distribution network database in EPANet’s format (used for REWET).
Load water distribution network from .csv files representing nodes and pipelines.
Load water distribution network from GIS files representing nodes and pipelines.
Load water distribution network database in EPANet’s format.
- Asset Modeling:
- Buildings:
MDOF-LU (MDOF shear building model).
OpenSeesPy building generator.
None (Used for the IMasEDP and Capacity Spectrum Method options in Asset Analysis).
CustomPy.
- Transportation infrastructure:
None (Used for the IMasEDP option in Asset Analysis).
- Asset Analysis:
- Buildings:
OpenSees.
OpenSeesPy.
IMasEDP (simplified analysis using Intensity Measures (IMs) as Engineering Demand Parameters (EDPs)).
Capacity Spectrum Method.
CustomPy for CustomPy Asset Modeling.
Pre-trained surrogate models.
- Transportation infrastructure:
IMasEDP (simplified analysis using Intensity Measures (IMs) as Engineering Demand Parameters (EDPs)).
- Damage and Loss:
- Buildings:
- Pelicun Damage and Loss Methods:
HAZUS MH EQ Story
HAZUS MH EQ IM
HAZUS MH HU
User-provided Models
- Transportation infrastructure:
- Pelicun Damage and Loss Methods:
HAZUS MH EQ IM
User-provided Models
- Water Network infrastructure:
- Pelicun Damage and Loss Methods:
HAZUS MH EQ IM
User-provided Models
- System Performance:
REWET System performance with or without Recovery
- Uncertainty Quantification:
- Dakota:
Latin hypercube sampling (LHS)
Monte Carlo Sampling (MCS)
- Additional Tools To Perform Tasks Generating or Using Data in Workflow:
- Earthquake Scenario Simulation (ground motion selection)
- Site definition:
Grid
Point
Scattered sites (user-defined sites in .csv format)
- Rupture forecast models:
OpenSHA UCERF rupture forecast models
OpenSHA Point source user-defined
OpenQuake rupture forecast
Hazard Occurrence Model
- Inter-event correlation:
Baker and Jayaram (2008)
- Intra-event correlation:
Jayaram and Baker (2009)
Markhvida et al. (2017)
Loth and Baker (2013)
- Record selection:
PEER NGA West 2 ground motion database
None, i.e., stop at the IM stage and no record selection
- Ground motion models:
Abrahamson, Silva & Kamai (2014)
Boore, Stewart, Seyhan & Atkinson (2014)
Campbell & Bozorgnia (2014)
Chiou & Youngs (2014)
- Intensity measures:
Spectral acceleration (SA)
Peak ground acceleraation (PGA)
Peak ground velocity (PGV)
- Ground failure models:
- Liquefaction triggering
Zhu et al. (2017)
Hazus (2020)
- Liquefaction lateral spreading permanent ground deformation (PGD_h)
Hazus (2020)
- Liquefaction settlement permanent ground deformation (PGD_v)
Hazus (2020)
- Vs30 model:
CGS/Wills Vs30 (Wills et al., 2015)
Thompson California Vs30 (Thompson et al., 2018)
Global Vs30 (Heath et al., 2020)
User Defined
- Hurricane Scenario Simulation (hurricane wind field generation)
- Site definition:
Grid
- Hurricane track definition:
User-defined sites in .csv format
Select from a database of historical hurricanes
Truncate hurricane track functionality
- Landfall location and parameters:
User selects on GIS map
Manual user entry in the input box
- Wind field generation model:
Snaiki and Wu (2017)
- Building and Infrastructure Recognition using AI at Large-Scale (BRAILS)
Building inventory generation
Transportation inventory generation