Autonomous Enrichment with GADRAS-DRF for any Gamma Detector
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A new scatter calculation algorithm has been implemented in the Gamma Detector Response and Analysis Software (GADRAS) package that accounts for spectral effects of scattering materials not in the line of sight of the detector and the source. Previously, GADRAS would only apply scattering effects due to materials that fall between the source and detector. This new routine will allow better modeling of various scenarios including gamma imagers, collimated detectors, or traditional gamma detectors where scattering materials are present.
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Gamma Detector Response and Analysis Software (GADRAS) is used by the radiation detection and emergency response community to perform modeling and spectral analysis for gamma detector systems. Built into GADRAS is the ability to define a detector, geometry, background characteristics and source composition to generate synthetic spectra for drills and exercises (injects). Consequence Management is currently in development of a sample result data simulator tool in which a deposition model is probed for source conditions at moments in time and locations in space. These values are used to generate realistic sample results for use in drills and exercises. In addition to sample results, there is a need to simulate the actual spectra that would be observed in the field by downlooking HPGe instruments given a deposition activity. This way, the FRMAC Gamma Spectroscopist can practice their process of generating quantified results from spectra on realistic data as well. Recognizing the decades of work done in GADRAS to accurately generate synthetic spectra, this team decided to build a link between the new simulator and GADRAS to generate these spectra quickly and easily. The simulator tool will generate a file that specifies the name of the spectra, its location, date/time of measurement, duration of measurement, height off the ground, and the deposition activity and age for every radionuclide in the simulation. Then, a new tool within the Inject Tab of GADRAS was developed to read in this file given a detector selection and generate In-Situ spectra for each row in the file in any file format the user chooses. This way, simulation cell staff can take these files and then upload them to the appropriate data system (RAMS or RadResponder) for use during drills and exercises. An advanced feature of this tool allows for generating any spectra given an appropriate model and mapping of source to model layer in the batch inject tool. This way, spectra from field sample counts, mobile laboratories, or even fixed laboratories can be generated in bulk given an estimate of the radioactivity concentration or total radioactivity in an import file. This expands the capabilities of this tool a great deal and will make it a more useful tool for CM and others to help estimate detector response for nearly any situation. This user guide will explain the steps needed to perform a batch inject file generation.
The Gamma Detector Response and Analysis Software Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation and provides analysis on measured spectra. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, estimating source energy distributions from measured spectra, and creating inject data. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).
This report describes how random pileup calculations are performed by the Gamma Detector Response and Analysis Software (GADRAS) Version 19.1. The computational approach and examples are presented for gamma-ray detectors with and without pileup rejectors. This pileup algorithm executes more quickly and the results are more accurate than previous versions of GADRAS. The detector response function can be refined to characterize distortions in peak shapes that occur at high-count rates. The empirical refinement can also be applied to describe the response of partially-effective pileup rejectors. Implications are discussed for the analysis of both static measurements and dynamic collections of the type acquired with radiation portals. ACKNOWLEDGEMENTS This work was funded by the Defense Threat Reduction Agency (DTRA) and the Department of Homeland Security (DHS) Counter Weapons of Mass Destruction (CWMD) office.
PCF files are binary files designed to contain gamma spectra and neutron count rates from radiation sensors. It is the native format for the GAmma Detector Response and Analysis Software (GADRAS) package. It can contain multiple spectra and information about each spectrum such as energy calibration. This document outlines the format of the file that would allow one to write a computer program to parse and write such files.
The effect of shielding on ionizing photon radiation can be estimated using radiation transport simulations. This report covers the methodology and implementation of using Green's Functions to pre-compute this effect, which allows the radiation field exiting a variety of shielding configurations to be quickly computed. It also covers a weighting function that makes a relatively small pre-computed library applicable to a large variety of heterogeneous shields. The method enables rapid computation of the intensity versus energy for scattered radiation exiting a variety of shield materials and thicknesses without running a full transport simulation.
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This report evaluates the relative performance of two directional gamma-ray spectrometers and processing algorithms that are used to construct images and spatially resolved spectra. Polaris, which was developed by H3D Inc., uses 18 pixelated CZT crystals to construct gamma-ray images in either Compton camera(CC) or coded aperture (CA) mode. The other sensor that is referenced in this report incorporates a commercial high-purity germanium based imager, called GeGI, with a coded aperture mask and processing software developed by Oak Ridge National Laboratory (ORNL). H3D and the University of Michigan provided several algorithms that can be used to process data collected by Polaris in CC mode. This evaluation compares the performance of these algorithms with a Directional Unfolded Source Term (DUST) approach developed by Sandia National Laboratories (SNL). DUST differs from the other algorithms because its primary objective is synthesis of spatially-resolved gamma ray spectra as opposed to image reconstruction.
A Directional Unfolded Source Term (DUST) algorithm was developed to enable improved spectral analysis capabilities using data collected by Compton cameras. Achieving this objective required modification of the detector response function in the Gamma Detector Response and Analysis Software (GADRAS). Experimental data that were collected in support of this work include measurements of calibration sources at a range of separation distances and cylindrical depleted uranium castings.
PCF files are binary files designed to contain gamma spectra and neutron count rates from radiation sensors. It is the native format for the GAmma Detector Response and Analysis Software (GADRAS) package [1]. It can contain multiple spectra and information about each spectrum such as energy calibration. This document outlines the format of the file that would allow one to write a computer program to parse and write such files.
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A Directional Unfolded Source Term (DUST) method was developed to compute directionally resolved gamma-ray source terms based on back-projection spectra synthesized by Compton Cameras. Spectral features in the unprocessed spectra are indistinct primarily because the rotational angles for the conical projections cannot be determined, so probability distributions are constructed from overlapping cones. The DUST method uses an angular response function to compute a covariance matrix, which is used to process count rates in back-projection spectra by linear regression to partition the gamma-rays among several spatial regions. This method was applied to analyze data collected by the Polaris detector during an evaluation that was conducted at Oak Ridge National Laboratory (ORNL). The evaluation includes measurements of calibration sources with angular separations ranging from 1° to more than 50°. Measurements were also performed for cylindrical depleted uranium castings and a 137Cs source inside a large polyethylene sphere. The DUST algorithm was able to differentiate gamma-rays emitted by 137Cs and 60Co when the sources were separated by less than 2°, but separation greater than 10° was required to isolate the 133Ba emission from gamma-rays emitted by the other sources. The computed source terms were consistent with emission profiles from the calibration sources and from models of the spatially-extended sources. Methods for viewing radiation profiles were also evaluated because user input is required to select spatial regions of interest.
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The Gamma Detector Response and Analysis Software–Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, and estimating source energy distributions from measured spectra. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).
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The Gamma Detector Response and Analysis Software--Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, and estimating source energy distributions from measured spectra. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).
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