Vanderbilt University
Engineering Capability Brief

Facility Protection Optimization Under Uncertainty

P. Hester and S. Mahadevan
Civil and Environmental Engineering, Vanderbilt University
VU Station B 351831, Nashville, TN 37235; 615-343-4658; fax 615-322-3365
E-mail: patrick.hester@Vanderbilt.edu

Introduction: Theft and sabotage are constant threats to facility owners. In order to protect against these threats, facility owners have a combination of detection, delay, and response elements, collectively known as a physical protection system. The goal of this research is ultimately to develop a computationally efficient decision-making methodology which will give facility operators input into how multiple adversary teams will attack a facility and therefore, how to design a physical protection system to defend against them. This will result in the ability for the facility operator to assess relative facility and/or infrastructure safety, and make decisions regarding how to invest money in physical protection elements to combat multiple team adversary threats.

This research begins by developing a conceptual methodology for computing system effectiveness, in order to answer the question of whether or not a system is doing an adequate job to protect itself. This framework is then developed mathematically and demonstrated by analyzing a single adversary attack on a facility. The proposed research extends the single adversary facility protection methodology to one that protects against a multiple team attack. Finally, the methodology is demonstrated on a hypothetical facility for a new facility protection system design, an existing design analysis, and an upgrades analysis.

Sample Applications: This research will allow facility owners, designers, and operators to assess existing facility security shortcomings, as well as to evaluate upgrades to the security system and develop security system designs for new facilities. Facilities from nuclear power plants to banks to stadiums could use this capability.

hester_p_01.jpg

ACKNOWLEDGEMENTS
This study is supported by funds from the National Science Foundation through the Vanderbilt University IGERT program on Risk and Reliability Engineering and, in part, by the Sandia National Laboratories through a National Physical Sciences Consortium Fellowship.

 

©