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A comparison of multiple behavior models in a simulation of the aftermath of an improvised nuclear detonation

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Abstract

We describe a large-scale simulation of the aftermath of a hypothetical 10kT improvised nuclear detonation at ground level, near the White House in Washington DC. We take a synthetic information approach, where multiple data sets are combined to construct a synthesized representation of the population of the region with accurate demographics, as well as four infrastructures: transportation, healthcare, communication, and power. In this article, we focus on the model of agents and their behavior, which is represented using the options framework. Six different behavioral options are modeled: household reconstitution, evacuation, healthcare-seeking, worry, shelter-seeking, and aiding & assisting others. Agent decision-making takes into account their health status, information about family members, information about the event, and their local environment. We combine these behavioral options into five different behavior models of increasing complexity and do a number of simulations to compare the models.

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Notes

  1. http://nuclearsecrecy.com/blog/2011/12/30/friday-image-bullseye-on-washington-1953/.

  2. The unit Gray (Gy) expresses absorbed radiation. Roentgen (R) is the unit for exposure in air. It is assumed that 1 R \(=\) 0.01 Gy [12].

  3. http://washington.org.

  4. http://www.citytowninfo.com/.

  5. http://data.dc.gov.

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Acknowledgments

We thank our external collaborators and members of the Network Dynamics and Simulation Science Laboratory (NDSSL) for their suggestions and comments. This work has been supported in part by DTRA CNIMS Contract HDTRA1-11-D-0016-0001, DTRA Grant HDTRA1-11-1-0016, NIH MIDAS Grant 5U01GM070694-11, NIH Grant 1R01GM109718, NSF NetSE Grant CNS-1011769, and NSF SDCI Grant OCI-1032677.

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Correspondence to Nidhi Parikh.

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Parikh, N., Hayatnagarkar, H.G., Beckman, R.J. et al. A comparison of multiple behavior models in a simulation of the aftermath of an improvised nuclear detonation. Auton Agent Multi-Agent Syst 30, 1148–1174 (2016). https://doi.org/10.1007/s10458-016-9331-y

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