Utility of Social Modeling for Proliferation Assessment - Enhancing a Facility-Level Model for Proliferation Resistance Assessment of a Nuclear Enegry System

Abstract

SummaryThis report presents the results of efforts towards development of a Facility-Level Model (i.e., singlelocation assessment) that demonstrates the use of social modeling to enhance an assessment process that is technical in nature. This effort builds on a literature search and preliminary assessment performed as the first stage of the Utility of Social Modeling or Proliferation Assessment project. This second report represents the culmination of the first year of research for project PL09-UtilSocial.This report provides: 1) background information on relevant social factors literature and on existing facility assessment modeling approaches germane to this demonstration, 2) a discussion of social modeling done to support determination of social factors relevant to nuclear facility modeling, 3) an enhancement concept for a specific existing nuclear facility assessment model using social factors, 4) a discussion of engagement with the facility assessment model owners about using social factors, 5) discussion of implementation of the new assessment approach based on the proposed modeling enhancement, including discussion of functionality and potential users, and 6) conclusions. This report represents technical deliverables for the NA-22 Simulations, Algorithms, and Modeling program. Specifically this report is the Task 2 and 3 deliverables for project PL09-UtilSocial.Based on the literature search preliminary assessment (i.e., PNNL-18438, Utility of Social Modeling for Proliferation Assessment) performed as the first stage of this research, we have concluded that there are opportunities to use social models to improve understanding and assessment of proliferation-related problems. For decades analysts have theorized about the factors that dictate whether a State pursues the development of nuclear weapons-these factors are primarily social factors or are factors that are intimately related to social factors (e.g., national identity, leadership, politics, domestic security, and economic capability). Social modeling offers a way to formalize or leverage this body of analysis and theory. PNNL-18438 also identifies opportunities for social modeling to support both overarching kinds of assessments like a State safeguards evaluation; facility-level assessments like a Proliferation Resistance (PR) assessment of a nuclear energy system (NES); and other kinds of specific proliferation assessmentrelated modeling efforts such as the use of satellite imagery to identify proliferation activity. One kind of facility-level assessment is a PR assessment. Various approaches and methodologies have been proposed to assess the PR of NES facilities. An international approach being developed and supported by the Generation IV International Forum (GIF) PR and Physical Protection (PR&PP) working group uses defined proliferation measures and incorporates structured expert elicitation. This methodology uses pathway analysis to evaluate different scenarios in NES facilities that could result in nuclear proliferation by considering five po...

Utility of Social Modeling in Assessment of a State’s Propensity for Nuclear Proliferation

“…The diagnosticity of the predictors identified in the Singh and Way study were calculated in an early BN model and presented in an earlier report (Coles 2009b), and is omitted here. The greater the diagnosticity of a predictor the larger the impact it will have in deciding whether a State is acquiring nuclear weapons.…”

“…Our second report (Coles 2009b) describes a way to enhance evaluation of the proliferation resistance of the facility by considering social information. The proliferation factors we considered are the proliferation resistance metrics defined as part of the Generation IV International Forum (GIF) proliferation resistance assessment approach: 1) proliferation technical difficulty, 2) proliferation cost, 3) proliferation time, 4) proliferation material, 5) detection probability, and 6) detection resource efficiency.…”