NCSA Helps Launch IN-CORE Platform to Model Community Resilience and Natural Hazards

The National Institute of Standards and Technology (NIST)-funded Center of Excellence for Risk-Based Community Resilience Planning (CoE), a collaboration including the National Center for Supercomputing Applications (NCSA) at the University of Illinois, has launched version 1.0.0 of the Interdependent Networked Community Resilience Modeling Environment (IN-CORE) software platform, which will allow researchers to model the impacts of natural hazards in a given community and the community’s resilience to those hazards.

The platform has been used for four testbeds of the CoE. Seaside (Oregon) with earthquake and tsunami, Memphis Metropolitan Statistical Area (Tennessee) with earthquake and flood, Joplin (Missouri) with tornado, and Galveston (Texas) with surges and hurricane winds. The results of Seaside and Joplin were released with IN-CORE v1.0.0. Other testbeds will be released with future releases of IN-CORE.

The Resilience CoE, which is hosted at Colorado State University, is a collaboration of researchers spanning the entire country, including NCSA’s Software Directorate, which is developing and maintaining IN-CORE platform and services, including the web application and related services, database management, GIS expertise, project management, and more.

The IN-CORE team at NCSA actively collaborated with CoE researchers on scientific implementation and requirements of the platform. Moreover, the team provided expertise of programming, designing the implementation of the platform, geospatial data analysis, and more.

Jong Lee, NCSA Lead for IN-CORE

The IN-CORE platform consists of several open source components developed by NCSA and is available via NCSA’s IN-CORE site. Free accounts are provided by NCSA’s Identity Management. More information on the CoE for Risk-Based Community Resilience Planning can be found on their website.

Read the full description of the platform below:

The National Institute of Standards and Technology (NIST) funds the Center of Excellence for Risk-Based Community Resilience Planning (CoE) (Cooperative Agreement 70NANB15H044) to develop the measurement science to support community resilience assessment. This measurement science is implemented on a platform called Interdependent Networked Community Resilience Modeling Environment (IN-CORE). It incorporates a risk-based approach to decision-making that enables quantitative comparisons of alternative resilience strategies. On the IN-CORE platform, data from the community can be seamlessly integrated which allows users to optimize community disaster resilience planning and post-disaster recovery strategies intelligently using physics-based models of inter-dependent physical systems combined with socio-economic systems.

IN-CORE consists of the components as shown below:

pyIncore is a Python package consisting of three primary components: 1) a set of service classes to interact with the IN-CORE web services described below, 2) IN-CORE analyses and 3) visualization. pyIncore allows users to apply various hazards to infrastructure in selected areas, propagating the effect of physical infrastructure damage and loss of functionality to social and economic impacts. Refer to the pyIncore section of the IN-CORE manual for detailed information.

IN-CORE Web Services are written in Java with the JAX-RS specification and are comprised of a Hazard Service, DFR3 (Damage, Functionality, Repair, Recovery, Restoration) Service, Data Service, Geospatial Visualization Service, Semantic Service, and Space Service. These services allow users to create and access hazards, fragilities, and data. Users can access and utilize these services via pyIncore and IN-CORE Web Tools. For detailed information, please refer to the technical reference document.

IN-CORE Web Tools is a set of web viewers for interacting with the different IN-CORE web services. The viewers enable users to browse, search Datasets, Hazards, Fragility curves, Repair curves, etc., view the metadata and visualizations, and download items. For detailed information, please refer to the IN-CORE Web Tools section.

IN-CORE Lab is a customized JupyterLab instance with pyIncore installed and hosted on an NCSA cloud system. It allows users to develop/run/test their scientific model with pyIncore in their own workspace. Example Jupyter notebooks are provided with each pyIncore analysis to help users get started and to help them understand how to use pyIncore. For detailed information, please refer to the IN-CORE Lab section.

ABOUT NCSA

The National Center for Supercomputing Applications at the University of Illinois Urbana-Champaign provides supercomputing and advanced digital resources for the nation’s science enterprise. At NCSA, University of Illinois faculty, staff, students and collaborators from around the globe use these resources to address research challenges for the benefit of science and society. NCSA has been advancing many of the world’s industry giants for over 35 years by bringing industry, researchers and students together to solve grand challenges at rapid speed and scale.