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Interconnected Infrastructure Modeling Investigation
Citation:
Joshi, T., B. Richter, R. James, T. Boe, W. Calfee, S. Lee, Joe Wood, P. Lemieux, S. Ryan, AND L. Mickelsen. Interconnected Infrastructure Modeling Investigation. U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-21/096, 2021.
Impact/Purpose:
Large-scale chemical, biological, radiological, and nuclear (CBRN) incidents, whether a product of terrorism, war, or accidents, have the potential to damage core infrastructure assets. In this situation, not only are directly affected areas not able to operate, but operations in other infrastructure sectors may not be able to operate without the services of the affected assets. For example, in a CBRN incident that impacts an electric power plant, the operations of connected transportation systems, communications facilities, and/or hospitals will likely be impacted regardless of whether these sectors were directly affected by the event. In order to more effectively respond to and remediate following such events, information about interconnected infrastructure systems is necessary to bring services back online as quickly as possible. This report describes preliminary efforts of simulating interconnected infrastructure systems in order to obtain information regarding infrastructure system remediation following a wide area CBRN incident. These efforts include a literature review that describes methods and software tools for the purpose of infrastructure modeling, an assessment of pre-existing critical infrastructure modeling software (such as PATH/AWARE), a description of preliminary development of the Stochastic Infrastructure Remediation Model (SIRM), selection of a final model for use in future analysis, and preliminary efforts made to translating a specific set of geographically defined CBRN events as input to the SIRM.
Description:
The goal of the literature review was to observe the methods by which other researchers have attempted to model interconnected infrastructure systems. A series of books and journal articles on the subject of modeling complex systems of systems (SoS) and interconnected critical infrastructure were documented. Many of these models are used to provide estimates of immediate losses after a CBRN event, but the dynamic process of restoring infrastructure is not determined effectively, and many models provided in literature are not able to accommodate all 16 infrastructure sectors on the Department of Homeland Security’s Critical Infrastructure Sector (DHSCIS) list.1 The literature review included an overview of existing infrastructure applications, many of which were agent-based models (ABMs). While these models proved to be powerful in their ability to dynamically model CBRN events, these programs were not able to model all 16 DHSCIS sectors, and the methodology used by many of these programs is unclear. On top of literature specific to infrastructure systems, a number of more general modeling strategies were considered. More specifically, stochastic modeling processes were studied due to their powerful ability to incorporate statistics that provide the user with a range of potential outcomes. Although these modeling strategies were not used for infrastructure modeling in previous literature, they provided the ability to be generalized to all DHSCIS sectors and allowed for statistics around the effects of CBRN events to be collected. An ABM program titled PATH/AWARE (which contains two acronyms that stand for Prioritization Analysis Tool for All-Hazards (PATH) and Analyzer for Wide Area Effectiveness (AWARE)) was reviewed in detail. This program allows the user to model a CBRN event by placement of contaminated zones on a map and will determine the infrastructure assets that are directly affected by the event. The program will also determine other assets that are affected by the losses in other facilities. Once the affected assets are determined, the user can run either the PATH or AWARE tool on the scenario. The PATH tool is used to generate a prioritized list of assets to repair, and lists all the asset dependencies, while the AWARE tool is used to calculate restoration costs and timelines based on a set of user-defined inputs (e.g., number of decontamination teams, labor rates, number of people on a team, etc.). Although PATH/AWARE provides helpful information for direct response to CBRN events, this package does not dynamically model the systems of interest (as it is merely doing a static calculation of restoration timelines) and some interconnected response elements (e.g., waste and decontamination) are not coupled in the model. A model based on the Gillespie algorithm was developed – a stochastic modeling process originally intended for modeling a system of coupled chemical reactions.1 This model allows for all infrastructure sectors to be modeled and considers the realistic variability of the impact of a CBRN event. The SIRM considered each of the infrastructure sectors as an operating efficiency percentage and models the restoration of services in each sector as a set of reactions that use resources from other infrastructure sectors in order to restore services in another sector. This process dynamically models the time required to repair an infrastructure sector, while also allowing the user to consider changes in resource allocation based on user-defined repair factors (RFs). The SIRM is able to dynamically model all of the desired sectors and allows the user to draw statistical conclusions specific to a CBRN event. Because of these desirable model characteristics, the SIRM was selected for use in future infrastructure analysis and a model improvement plan was generated in order to guide the future development of the model.