By accessing the Interdependent Networked Community Resilience Modeling Environment (IN-CORE) platform, users can run analyses that model the impact of natural hazards on a particular community. In doing so, IN-CORE can gauge a community’s resilience to major disasters.
IN-CORE Lab, which is a customized Jupyter Lab with pyIncore installed and hosted on a cloud system provided by the National Center for Supercomputing Applications (NCSA), gives users the ability to develop, run or test their model in their own workspace.
By actualizing a risk-based approach to decision making, IN-CORE enables comparisons between various resilience strategies. This platform allows researchers to seamlessly integrate their community data, thereby allowing users to optimize community disaster resilience planning.
What’s more, IN-CORE can also help with the formulation of post-disaster recovery strategies. Both of these goals are accomplished with the help of physics-based models of interdependent physical systems which are then combined with socio-economic systems.