Spatiotemporal Integration of an Agent-Based First Responder Performance Model With a Fire Hazard Propagation Model for Probabilistic Risk Assessment of Nuclear Power Plants
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 6, Issue 1
Abstract
To advance emergency response (ER) modeling in probabilistic risk assessment (PRA), this research offers a new methodology that explicitly incorporates the spatiotemporal evolution of underlying physical and social phenomena and their bidirectional interactions. While this methodology is applicable for various ER scenarios on different spatial and temporal scales, this paper focuses on advancing ER modeling for a nuclear power plant (NPP) internal fire. This paper provides a thorough review and categorization of existing studies on internal fire ER modeling for NPPs and highlights the contributions of this research. This paper then develops a new methodology for fire ER modeling by integrating an agent-based model of first responder performance (FRP) with a fire hazard propagation (FHP) model through a shared geographical information system (GIS)-based spatial simulation environment. This research is the first to explicitly incorporate space (in addition to time) into the FRP modeling within ER modeling of NPP fire probabilistic risk assessment (fire PRA). In addition, this research develops a GIS-based interface between FRP and FHP that has the capability of transferring both spatial and temporal information in a bidirectional way. Although this paper is focused on a fire ER scenario, the new methodology developed in this paper can contribute to modeling external control room (ExCR) human performance in other contexts, such as diverse and flexible coping strategy (FLEX), maintenance, and offsite first responders in level 3 PRA. This article is available in the ASME Digital Collection at https://doi.org/10.1115/1.4044793.
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Copyright © 2020 by ASME.
History
Received: Dec 3, 2018
Revision received: May 18, 2019
Published online: Nov 15, 2019
Published in print: Mar 1, 2020
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