Daniel E. Archer

Multiagency Urban Search Experiment Detector and Algorithm Test Bed

In order to provide benchmark data sets for radiation detector and algorithm development, a particle transport test bed has been created using experimental data as model input and validation. A detailed radiation measurement campaign at the Combined Arms Collective Training Facility in Fort Indiantown Gap, PA (FTIG), USA, provides sample background radiation levels for a variety of materials present at the site (including cinder block, gravel, asphalt, and soil) using long dwell high-purity germanium (HPGe) measurements. In addition, detailed light detection and ranging data and ground-truth measurements inform model geometry. This paper describes the collected data and the application of these data to create background and injected source synthetic data for an arbitrary gamma-ray detection system using particle transport model detector response calculations and statistical sampling. In the methodology presented here, HPGe measurements inform model source terms while detector response calculations are validated via long dwell measurements using 2”

A Methodology for Determining the Concentration of Naturally Occurring Radioactive Materials in an Urban Environment

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Systematic Assessment of Neutron and Gamma Backgrounds Relevant to Operational Modeling and Detection Technology Implementation

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Characterization of gamma-ray background outside of the High Flux Isotope Reactor

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Concepts for the Measurements Subsystems of the Third Generation Attributes Measurement System

” NaI(Tl) detectors at a variety of measurement points. A collection of responses, along with sampling methods and interpolation, can be used to create data sets to gauge radiation detector and algorithm (including detection, identification, and localization) performance under a variety of scenarios. Data collected at the FTIG site are available for query, filtering, visualization, and download at muse.lbl.gov.

Fieldable Nuclear Material Identification System

Abstract The detection of radioactive sources in an urban setting is greatly complicated by natural background radiation, which emanates from various materials including roadways, sidewalks, soil, and building exteriors. The method presented and demonstrated here represents an effort to characterize the concentration of naturally occurring radioactive material (NORM) in these types of materials. The location surveyed in this work was the Fort Indiantown Gap Combined Arms Collective Training Facility in Lebanon County, Pennsylvania. Over 70 measurements with a high-purity germanium detector were performed to ascertain the NORM concentrations present in the soil, asphalt, gravel, concrete, and walls found throughout the site. Monte Carlo radiation transport calculations were used to obtain detector responses for these various geometries and materials to convert these measurements into NORM concentration estimates. Finally, synthetic spectra were simulated using the predicted source terms and compared to actual measurements, showing acceptable agreement.

Subcriticality Measurements with HEU (93.2) Metal Annular Storage Castings

This report summarizes the findings of a two year effort to systematically assess neutron and gamma backgrounds relevant to operational modeling and detection technology implementation. The first year effort focused on reviewing the origins of background sources and their impact on measured rates in operational scenarios of interest. The second year has focused on the assessment of detector and algorithm performance as they pertain to operational requirements against the various background sources and background levels.

Modeling Urban Scenarios & Experiments: Fort Indiantown Gap Data Collections Summary and Analysis

Static gamma-ray measurements collected between September 2017 and March 2018 in the vicinity of the High Flux Isotope Reactor (HFIR) and the Radiochemical Engineering Development Center (REDC) at Oak Ridge National Laboratory are presented. Temporal events are identified and tracked, including radioactive material transfers, rain events, and 41Ar emissions. The remaining data is used to determine the average background and its variation. These results will be used to benchmark Monte Carlo transport models of the HFIR/REDC vicinity and provide training data for material transfer tracking algorithms and data fusion algorithms to determine HFIR operational status under the Multi-Informatics for Nuclear Operations Scenarios program.