COMPUTATIONAL ENVIRONMENT FOR MODELING AND ENHANCING COMMUNITY RESILIENCE: INTRODUCING THE CENTER FOR RISK-BASED COMMUNITY RESILIENCE PLANNING

Published

December 10, 2015

Author(s)

John W. van de Lindt, Bruce Ellingwood, Therese P. McAllister, Gardoni Paolo, Daniel Cox, Harvey Cutler, Walter G. Peacock

Abstract

The resilience of a community is defined as its ability to prepare for, withstand, recover from and adapt to the effects of natural or human-caused disasters, and depends on the performance of the built environment and on supporting social, economic and public institutions that are essential for immediate response and long-term recovery and adaptation. The performance of the built environment generally is governed by codes and standards, which are applicable to individual facilities and residences, are based on different performance criteria, and do not account for the interdependence of buildings, transportation, utilities and other infrastructure sectors. The National Institute of Standards and Technology recently awarded a new Center of Excellence (NIST-COE) for Risk-Based Community Resilience Planning, which is headquartered at Colorado State University and involves nine additional universities. Research in this Center is focusing on three major research thrusts: (1) developing the NIST-Community Resilience Modeling Environment known as NIST-CORE, thereby enabling alternative strategies to enhance community resilience to be measured quantitatively; (2) developing a standardized data ontology, robust data architecture and data management tools in support of NIST-CORE; and (3) performing a comprehensive set of hindcasts on disasters to validate the data architecture and NIST-CORE.

Proceedings Title

Second International Conference on Performance-based and Lifecycle Structural Engineering (PLSE 2015)

Conference Dates

December 9-11, 2015

Conference Location

Brisbane, AU

Pub Type

Conferences

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Keywords

Community resilience, hazards, investment optimization, post-disaster recovery, resilience performance metrics, risk-informed decision

Citation

van de Lindt, J. , Ellingwood, B. , McAllister, T. , Paolo, G. , Cox, D. , Cutler, H. and Peacock, W. (2015), COMPUTATIONAL ENVIRONMENT FOR MODELING AND ENHANCING COMMUNITY RESILIENCE: INTRODUCING THE CENTER FOR RISK-BASED COMMUNITY RESILIENCE PLANNING, Second International Conference on Performance-based and Lifecycle Structural Engineering (PLSE 2015), Brisbane, AU, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=918890 (Accessed December 14, 2024)