Publications

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Material control and accounting (MC&A) safeguards operations that track and account for critical assets at nuclear facilities provide a key protection approach for defeating insider adversaries. These activities, however, have been difficult to characterize in ways that are compatible with the probabilistic path analysis methods that are used to systematically evaluate the effectiveness of a site's physical protection (security) system (PPS). MC&A activities have many similar characteristics to operator procedures performed in a nuclear power plant (NPP) to check for anomalous conditions. This work applies human reliability analysis (HRA) methods and models for human performance of NPP operations to develop detection probabilities for MC&A activities. This has enabled the development of an extended probabilistic path analysis methodology in which MC&A protections can be combined with traditional sensor data in the calculation of PPS effectiveness. The extended path analysis methodology provides an integrated evaluation of a safeguards and security system that addresses its effectiveness for attacks by both outside and inside adversaries.

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Traditional safeguards and security design for fuel cycle facilities is done separately and after the facility design is near completion. This can result in higher costs due to retrofits and redundant use of data. Future facilities will incorporate safeguards and security early in the design process and integrate the systems to make better use of plant data and strengthen both systems. The purpose of this project was to evaluate the integration of materials control and accounting (MC&A) measurements with physical security design for a nuclear reprocessing plant. Locations throughout the plant where data overlap occurs or where MC&A data could be a benefit were identified. This mapping is presented along with the methodology for including the additional data in existing probabilistic assessments to evaluate safeguards and security systems designs.

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Next generation nuclear fuel cycle facilities will face strict requirements on security and safeguards of nuclear material. These requirements can result in expensive facilities. The purpose of this project was to investigate how to incorporate safeguards and security into one plant monitoring system early in the design process to take better advantage of all plant process data, to improve confidence in the operation of the plant, and to optimize costs. An existing reprocessing plant materials accountancy model was examined for use in evaluating integration of safeguards (both domestic and international) and security. International safeguards require independent, secure, and authenticated measurements for materials accountability--it may be best to design stand-alone systems in addition to domestic safeguards instrumentation to minimize impact on operations. In some cases, joint-use equipment may be appropriate. Existing domestic materials accountancy instrumentation can be used in conjunction with other monitoring equipment for plant security as well as through the use of material assurance indicators, a new metric for material control that is under development. Future efforts will take the results of this work to demonstrate integration on the reprocessing plant model.

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This article describes how features of event tree analysis and Monte Carlo-based discrete event simulation can be combined with concepts from object-oriented analysis to develop a new risk assessment methodology, with some of the best features of each. The resultant object-based event scenario tree (OBEST) methodology enables an analyst to rapidly construct realistic models for scenarios for which an a priori discovery of event ordering is either cumbersome or impossible. Each scenario produced by OBEST is automatically associated with a likelihood estimate because probabilistic branching is integral to the object model definition. The OBEST methodology is then applied to an aviation safety problem that considers mechanisms by which an aircraft might become involved in a runway incursion incident. The resulting OBEST model demonstrates how a close link between human reliability analysis and probabilistic risk assessment methods can provide important insights into aviation safety phenomenology.

Event tree analysis and Monte Carlo-based discrete event simulation have been used in risk assessment studies for many years. This report details how features of these two methods can be combined with concepts from object-oriented analysis to develop a new risk assessment methodology with some of the best features of each. The resultant Object-Based Event Scenarios Tree (OBEST) methodology enables an analyst to rapidly construct realistic models for scenarios for which an a priori discovery of event ordering is either cumbersome or impossible (especially those that exhibit inconsistent or variable event ordering, which are difficult to represent in an event tree analysis). Each scenario produced by OBEST is automatically associated with a likelihood estimate because probabilistic branching is integral to the object model definition. The OBEST method uses a recursive algorithm to solve the object model and identify all possible scenarios and their associated probabilities. Since scenario likelihoods are developed directly by the solution algorithm, they need not be computed by statistical inference based on Monte Carlo observations (as required by some discrete event simulation methods). Thus, OBEST is not only much more computationally efficient than these simulation methods, but it also discovers scenarios that have extremely low probabilities as a natural analytical result--scenarios that would likely be missed by a Monte Carlo-based method. This report documents the OBEST methodology, the demonstration software that implements it, and provides example OBEST models for several different application domains, including interactions among failing interdependent infrastructure systems, circuit analysis for fire risk evaluation in nuclear power plants, and aviation safety studies.

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The objectives for the ASP large early release frequency (LERF) model development work is to build a Level 2 containment response model that would capture all of the events necessary to define LERF as outlined in Regulatory Guide 1.174, can be directly interfaced with the existing Level 1 models, is technically correct, can be readily modified to incorporate new information or to represent another plant, and can be executed in SAPHIRE. The ASP LERF models being developed will meet these objectives while providing the NRC with the capability to independently assess the risk impact of plant-specific changes proposed by the utilities that change the nuclear power plants' licensing basis. Together with the ASP Level 1 models, the ASP LERF models provide the NRC with the capability of performing equipment and event assessments to determine their impact on a plant's LERF for internal events during power operation. In addition, the ASP LERF models are capable of being updated to reflect changes in information regarding the system operations and phenomenological events, and of being updated to assess the potential for early fatalities for each LERF sequence. As the ASP Level 1 models evolve to include more analysis capabilities, the LERF models will also be refined to reflect the appropriate level of detail needed to demonstrate the new capabilities. An approach was formulated for the development of detailed LERF models using the NUREG-1150 APET models as a guide. The modifications to the SAPHIRE computer code have allowed the development of these detailed models and the ability to analyze these models in a reasonable time. Ten reference LERF plant models, including six PWR models and four BWR models, which cover a wide variety of containment and nuclear steam supply systems designs, will be complete in 1999. These reference models will be used as the starting point for developing the LERF models for the remaining nuclear power plants.