KHNP/CRI Integrated Security and Consequence Analysis Project Status
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Sandia National Laboratories (SNL) is providing training and consultation activities on security planning and design for the Korea Hydro and Nuclear Power Central Research Institute (KHNPCRI). As part of this effort, SNL performed a literature review on computer security requirements, guidance and best practices that are applicable to an advanced nuclear power plant. This report documents the review of reports generated by SNL and other organizations [U.S. Nuclear Regulatory Commission, Nuclear Energy Institute, and International Atomic Energy Agency] related to protection of information technology resources, primarily digital controls and computer resources and their data networks. Copies of the key documents have also been provided to KHNP-CRI.
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The current wave of small modular reactor (SMR) designs all have the goal of reducing the cost of management and operations. By optimizing the system, the goal is to make these power plants safer, cheaper to operate and maintain, and more secure. In particular, the reduction in plant staffing can result in significant cost savings. The introduction of advanced reactor designs and increased use of advanced automation technologies in existing nuclear power plants will likely change the roles, responsibilities, composition, and size of the crews required to control plant operations. Similarly, certain security staffing requirements for traditional operational nuclear power plants may not be appropriate or necessary for SMRs due to the simpler, safer and more automated design characteristics of SMRs. As a first step in a process to identify where regulatory requirements may be met with reduced staffing and therefore lower cost, this report identifies the regulatory requirements and associated guidance utilized in the licensing of existing reactors. The potential applicability of these regulations to advanced SMR designs is identified taking into account the unique features of these types of reactors.
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Nuclear fuel reprocessing plants contain a wealth of plant monitoring data including material measurements, process monitoring, administrative procedures, and physical protection elements. Future facilities are moving in the direction of highly-integrated plant monitoring systems that make efficient use of the plant data to improve monitoring and reduce costs. The Separations and Safeguards Performance Model (SSPM) is an analysis tool that is used for modeling advanced monitoring systems and to determine system response under diversion scenarios. This report both describes the architecture for such a future monitoring system and present results under various diversion scenarios. Improvements made in the past year include the development of statistical tests for detecting material loss, the integration of material balance alarms to improve physical protection, and the integration of administrative procedures. The SSPM has been used to demonstrate how advanced instrumentation (as developed in the Material Protection, Accounting, and Control Technologies campaign) can benefit the overall safeguards system as well as how all instrumentation is tied into the physical protection system. This concept has the potential to greatly improve the probability of detection for both abrupt and protracted diversion of nuclear material.
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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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SIMULATION
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. © 2004, SAGE Publications. All rights reserved.
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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