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).
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).
Radiation transport calculations were performed to compute the angular tallies for scattered gamma-rays as a function of distance, height, and environment. Greens Functions were then used to encapsulate the results a reusable transformation function. The calculations represent the transport of photons throughout scattering surfaces that surround sources and detectors, such as the ground and walls. Utilization of these calculations in GADRAS (Gamma Detector Response and Analysis Software) enables accurate computation of environmental scattering for a variety of environments and source configurations. This capability, which agrees well with numerous experimental benchmark measurements, is now deployed with GADRAS Version 18.2 as the basis for the computation of scattered radiation.
The Gamma Detector Response and Analysis Software-Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray 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, and analyzing spectra to identify isotopes or to estimate flux profiles. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving researchers and other users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).
T to compute the radiography properties of various materials, the flux profiles of X-ray sources must be characterized. This report describes the characterization of X-ray beam profiles from a Kimtron industrial 450 kVp radiography system with a Comet MXC-45 HP/11 bipolar oil-cooled X-ray tube. The empirical method described here uses a detector response function to derive photon flux profiles based on data collected with a small cadmium telluride detector. The flux profiles are then reduced to a simple parametric form that enables computation of beam profiles for arbitrary accelerator energies.
Continued acts of terrorism using explosive materials throughout the world have led to great interest in explosives detection technology, especially technologies that have a potential for remote or standoff detection. This LDRD was undertaken to investigate the benefit of the possible use of quantum cascade lasers (QCLs) in standoff explosives detection equipment. Standoff detection of explosives is currently one of the most difficult problems facing the explosives detection community. Increased domestic and troop security could be achieved through the remote detection of explosives. An effective remote or standoff explosives detection capability would save lives and prevent losses of mission-critical resources by increasing the distance between the explosives and the intended targets and/or security forces. Many sectors of the US government are urgently attempting to obtain useful equipment to deploy to our troops currently serving in hostile environments. This LDRD was undertaken to investigate the potential benefits of utilizing quantum cascade lasers (QCLs) in standoff detection systems. This report documents the potential opportunities that Sandia National Laboratories can contribute to the field of QCL development. The following is a list of areas where SNL can contribute: (1) Determine optimal wavelengths for standoff explosives detection utilizing QCLs; (2) Optimize the photon collection and detection efficiency of a detection system for optical spectroscopy; (3) Develop QCLs with broader wavelength tunability (current technology is a 10% change in wavelength) while maintaining high efficiency; (4) Perform system engineering in the design of a complete detection system and not just the laser head; and (5) Perform real-world testing with explosive materials with commercial prototype detection systems.
Rapid detection and identification of bacteria and other pathogens is important for many civilian and military applications. The taxonomic significance, or the ability to differentiate one microorganism from another, using fatty acid content and distribution is well known. For analysis fatty acids are usually converted to fatty acid methyl esters (FAMEs). Bench-top methods are commercially available and recent publications have demonstrated that FAMEs can be obtained from whole bacterial cells in an in situ single-step pyrolysis/methylation analysis. This report documents the progress made during a three year Laboratory Directed Research and Development (LDRD) program funded to investigate the use of microfabricated components (developed for other sensing applications) for the rapid identification of bioorganisms based upon pyrolysis and FAME analysis. Components investigated include a micropyrolyzer, a microGC, and a surface acoustic wave (SAW) array detector. Results demonstrate that the micropyrolyzer can pyrolyze whole cell bacteria samples using only milliwatts of power to produce FAMEs from bacterial samples. The microGC is shown to separate FAMEs of biological interest, and the SAW array is shown to detect volatile FAMEs. Results for each component and their capabilities and limitations are presented and discussed. This project has produced the first published work showing successful pyrolysis/methylation of fatty acids and related analytes using a microfabricated pyrolysis device.