Publications

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In July 2012, protestors cut through security fences and gained access to the Y-12 National Security Complex. This was believed to be a highly reliable, multi-layered security system. This report documents the results of a Laboratory Directed Research and Development (LDRD) project that created a consistent, robust mathematical framework using complex systems analysis algorithms and techniques to better understand the emergent behavior, vulnerabilities and resiliency of multi-layered security systems subject to budget constraints and competing security priorities. Because there are several dimensions to security system performance and a range of attacks that might occur, the framework is multi-objective for a performance frontier to be estimated. This research explicitly uses probability of intruder interruption given detection (P_I) as the primary resilience metric. We demonstrate the utility of this framework with both notional as well as real-world examples of Physical Protection Systems (PPSs) and validate using a well-established force-on-force simulation tool, Umbra.

This report summarizes the work performed as part of a Laboratory Directed Research and Development project focused on evaluating and mitigating risk associated with biological dual use research of concern. The academic and scientific community has identified the funding stage as the appropriate place to intervene and mitigate risk, so the framework developed here uses a portfolio-level approach and balances biosafety and biosecurity risks, anticipated project benefits, and available mitigations to identify the best available investment strategies subject to cost constraints. The modeling toolkit was designed for decision analysis for dual use research of concern, but is flexible enough to support a wide variety of portfolio-level funding decisions where risk/benefit tradeoffs are involved. Two mathematical optimization models with two solution methods are included to accommodate stakeholders with varying levels of certainty about priorities between metrics. An example case study is presented.

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Sandia National Laboratories (Sandia) is in Phase 3 Sustainment of development of a prototype tool, currently referred to as the Contingency Contractor Optimization Tool - Prototype (CCOTP), under the direction of OSD Program Support. CCOT-P is intended to help provide senior Department of Defense (DoD) leaders with comprehensive insight into the global availability, readiness and capabilities of the Total Force Mix. The CCOT-P will allow senior decision makers to quickly and accurately assess the impacts, risks and mitigating strategies for proposed changes to force/capabilities assignments, apportionments and allocations options, focusing specifically on contingency contractor planning. During Phase 2 of the program, conducted during fiscal year 2012, Sandia developed an electronic storyboard prototype of the Contingency Contractor Optimization Tool that can be used for communication with senior decision makers and other Operational Contract Support (OCS) stakeholders. Phase 3 used feedback from demonstrations of the electronic storyboard prototype to develop an engineering prototype for planners to evaluate. Sandia worked with the DoD and Joint Chiefs of Staff strategic planning community to get feedback and input to ensure that the engineering prototype was developed to closely align with future planning needs. The intended deployment environment was also a key consideration as this prototype was developed. Initial release of the engineering prototype was done on servers at Sandia in the middle of Phase 3. In 2013, the tool was installed on a production pilot server managed by the OUSD(AT&L) eBusiness Center. The purpose of this document is to specify the CCOT-P engineering prototype platform requirements as of May 2016. Sandia developed the CCOT-P engineering prototype using common technologies to minimize the likelihood of deployment issues. CCOT-P engineering prototype was architected and designed to be as independent as possible of the major deployment components such as the server hardware, the server operating system, the database, and the web server. This document describes the platform requirements, the architecture, and the implementation details of the CCOT-P engineering prototype.

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The Contingency Contractor Optimization Tool – Prototype (CCOT-P) database is used to store input and output data for the linear program model described in [1]. The database allows queries to retrieve this data and updating and inserting new input data.

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.

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This requirements document serves as an addendum to the Contingency Contractor Optimization Phase 2, Requirements Document [1] and Phase 3 Requirements Document [2]. The Phase 2 Requirements document focused on the high-level requirements for the tool. The Phase 3 Requirements document provided more detailed requirements to which the engineering prototype was built in Phase 3. This document will provide detailed requirements for features and enhancements being added to the production pilot in the Phase 3 Sustainment.

The reports and test plans contained within this document serve as supporting materials to the activities listed within the “Contingency Contractor Optimization Tool – Prototype (CCOT-P) Verification & Validation Plan” [1]. The activities included test development, testing, peer reviews, and expert reviews. The engineering prototype reviews were done for both the software and the mathematical model used in CCOT-P. Section 2 includes the peer and expert review reports, which summarize the findings from each of the reviews and document the resolution of any issues. Section 3 details the test plans that were followed for functional testing of the application through the interface. Section 4 describes the unit tests that were run on the code.

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The performance of a multi-layered security system, such as those protecting high-value facilities or critical infrastructures, is characterized using several different attributes including detection and interruption probabilities, costs, and false/nuisance alarm rates. The multitude of technology options, alternative locations and configurations for those technologies, threats to the system, and resource considerations that must be weighed make exhaustive evaluation of all possible architectures extremely difficult. This paper presents an optimization model and a computationally efficient solution procedure to identify an estimated frontier of system configuration options which represent the best design choices for the user when there is uncertainty in the response time of the security force, once an intrusion has been detected. A representative example is described.

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This paper presents a probabilistic origin-destination table for waterborne containerized imports. The analysis makes use of 2012 Port Import/Export Reporting Service data, 2012 Surface Transportation Board waybill data, a gravity model, and information on the landside transportation mode split associated with specifc ports. This analysis suggests that about 70% of the origin-destination table entries have a coeffcient of variation of less than 20%. This 70% of entries is associated with about 78% of the total volume. This analysis also makes evident the importance of rail interchange points in Chicago, Illinois; Memphis, Tennessee; Dallas, Texas; and Kansas City, Missouri, in supporting the transportation of containerized goods from Asia through West Coast ports to the eastern United States.

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The Microgrid Design Toolkit (MDT) is a decision support software tool for microgrid designers to use during the microgrid design process. The models that support the two main capabilities in MDT are described. The first capability, the Microgrid Sizing Capability (MSC), is used to determine the size and composition of a new microgrid in the early stages of the design process. MSC is a mixed-integer linear program that is focused on developing a microgrid that is economically viable when connected to the grid. The second capability is focused on refining a microgrid design for operation in islanded mode. This second capability relies on two models: the Technology Management Optimization (TMO) model and Performance Reliability Model (PRM). TMO uses a genetic algorithm to create and refine a collection of candidate microgrid designs. It uses PRM, a simulation based reliability model, to assess the performance of these designs. TMO produces a collection of microgrid designs that perform well with respect to one or more performance metrics.

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This paper focuses on optimizing the selection and configuration of detection technologies to protect a target of interest. The ability of an intruder to simply reach the target is assumed to be sufficient to consider the security system a failure. To address this problem, we develop a game theoretic model of the strategic interactions between the system owner and a knowledgeable intruder. A decomposition-based exact method is used to solve the resultant model.

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