Modeling Community Resilience: Update on the Center for Risk-Based Community Resilience Planning and the Computational Environment IN-CORE
John W. van de Lindt, Bruce Ellingwood, Therese P. McAllister, Paolo Gardoni, Daniel Cox, Walter G. Peacock, Harvey Cutler, Maria K. Dillard, Jong Lee, Lori Peek, Judith Mitrani-Reiser
Community resilience is often defined as the ability of a community to prepare for, absorb, and recover rapidly from a hazard event. In 2015, the U.S. National Institute of Standards and Technology (NIST) funded the Center for Risk-Based Community Resilience Planning headquartered at Colorado State University, with the overarching objective of advancing measurement science related to community resilience by: (1) developing a computational environment that will allow researchers to identify attributes that resilient communities possess and make risk-informed decisions to enhance community resilience; (2) developing a standardized data ontology for managing diverse datasets and databases; and (3) conducting field studies and hindcasts to validate the computational environment. The Interconnected Networked Community Resilience Modeling Environment (IN-CORE), scheduled to be released at the end of 2019 as an open-source computational environment is the Centers main research product. IN-CORE utilizes the Jupyter Notebook where users can write Python scripts to call libraries, develop their own algorithms, and study community resilience. This paper introduces some of the special features of IN-CORE, highlights several testbeds related to earthquake and tsunami hazards that will serve as user examples in IN-CORE, reviews a joint Center-NIST longitudinal field study in progress, and outlines the development of a multidisciplinary glossary. The paper concludes with a summary of future tasks within the Center of Excellence and advancements in IN-CORE.
17th U.S.-Japan-New Zealand Workshop
on the Improvement of Structural Engineering
and Resilience (ATC-15-16)