ANALYSIS OF DOMAIN-SPECIFIC NUCLEAR ONTOLOGY USING MONTEREY PHOENIX BEHAVIOR MODELING

Current nuclear energy ontologies are known to lack a common vocabulary to formally verify nuclear energy data relationships for modeling system behaviors. Idaho National Laboratory (INL) developed the Data Integration Aggregated Model and Ontology for Nuclear Deployment (DIAMOND) ontology to provide a standard vocabulary and taxonomy for identifying data relationships in nuclear energy system models. This thesis conducted an analysis of DIAMOND using a Spent Fuel Pool (SFP) Monterey Phoenix (MP) behavior model. The SFP MP behavior modeling application demonstrated components of and interactions among a spent fuel cooling pool and its environment. The MP behavior model demonstrated a viable approach for analyzing nuclear reactor system behavior consistent with DIAMOND and the ability to generate the exhaustive set of nuclear reactor cooling pool behavior scenarios. The results supported the ability of DIAMOND definitions to be used to organize and structure knowledge about SFP’s normal and off-normal behaviors. The SPF example showed the application of assets, actions, and triggers from DIAMOND to events and relationships in MP. Assets and actions were represented as MP events, and triggers were represented as precedence relations between MP events. This thesis research verified the DIAMOND ontology was implemented correctly in the model from data representative of operationally realistic behavior and the modeling results validated the MP behavior model was well constrained.Idaho National LabCivilian, Department of the Air ForceApproved for public release. Distribution is unlimited

Microperimetric changes in neovascular age-related macular degeneration treated with ranibizumab

PURPOSE: To assess the value of microperimetry in eyes with neovascular age-related macular degeneration previously treated with ranibizumab and now in the maintenance phase of therapy.METHODS: A total of 21 eyes (14 patients) were included. Microperimetry was performed using the Macular Integrity Assessment Device on at least three occasions for each eye. Intravitreal ranibizumab was administered if visual acuity (VA) or optical coherence tomography (OCT) showed signs of active disease.RESULTS: Five eyes showed no change in VA or OCT findings, and required no intravitreal injections. In these eyes, mean threshold sensitivity (TS) decreased by 13% (paired t-test, P=0.05) during the study period, but fixation stability (FS) was unchanged. In all, 16 eyes showed signs of disease activity, and therefore required ranibizumab injections during the study. In these eyes, VA, central retinal thickness (CRT), FS, and TS remained unchanged during follow-up. Peak TS was noted when CRT was 210 ?m; above or below 210 ?m, there was a gradual reduction in TS.CONCLUSION: This study has provided novel information on the relationship between macular sensitivity, CRT, and VA in the maintenance phase of ranibizumab therapy. Patients with stable VA and CRT may still have deteriorating retinal sensitivity. This is usually a late manifestation and may indicate subclinical CNV activity.<br/

Connectivity, permeability and channeling in randomly-distributed and kinematically-defined discrete fracture network models

International audienceA major use of DFN models for industrial applications is to evaluate permeability and flow structure in hardrock aquifers from geological observations of fracture networks. The relationship between the statistical fracture density distributions and permeability has been extensively studied, but there has been little interest in the spatial structure of DFN models, which is generally assumed to be spatially random (i.e. Poisson). In this paper, we compare the predictions of Poisson DFNs to new DFN models where fractures result from a growth process defined by simplified kinematic rules for nucleation, growth and fracture arrest (Davy et al, 2010, 2013). This so-called ‘kinematic fracture model' is characterized by a large proportion of T-intersections, and a smaller number of intersections per fracture. Several kinematic models were tested and compared with Poisson DFN models with the same density, length and orientation distributions. Connectivity, permeability and flow distribution were calculated for 3D networks with a self-similar power-law fracture length distribution. For the same statistical properties in orientation and density, the permeability is systematically and significantly smaller by a factor of 1.5 to 10 for kinematic than for Poisson models. In both cases, the permeability is well described by a linear relationship with the areal density p32, but the threshold of kinematic models is 50% larger than of Poisson models. Flow channeling is also enhanced in kinematic DFN models. This analysis demonstrates the importance of choosing an appropriate DFN organization for predicting flow properties from fracture network parameters