Robert J. Estep

A method for correcting NaI spectra for attenuation losses in hand-held instrument applications

In this paper we present the gross-count material basis set (GC-MBS) method for estimating transmission losses in measurements of radionuclides using low-resolution gamma-ray detectors such as NaI or CdZnTe. The application to continuum-subtracted peaks measured with high-purity Ge detectors is also discussed. To illustrate the method, we apply it to the correction of spectra from enriched uranium that have been distorted by various intervening absorbers. We also examine the application to simultaneous determination of the uranium enrichment through an unknown absorber using an NaI detector.

A maximum-likelihood reconstruction algorithm for tomographic gamma-ray nondestructive assay☆

Abstract A new tomographic reconstruction algorithm for nondestructive assay with high-resolution gamma-ray spectroscopy (HRGS) is presented. The reconstruction problem is formulated using a maximum-likelihood approach in which the statistical structure of both the gross and continuum measurements used to determine the full-energy response in HRGS is modeled. An accelerated expectation-maximization algorithm is used to determine the optimal solution. The algorithm is applied to safeguards and environmental assays of large samples (for example, 55 gal drums) in which high continuum levels caused by Compton scattering are routinely encountered. Details of the implementation of the algorithm and a comparative study of the algorithms performance are presented.

An innovative method for extracting isotopic information from low-resolution gamma spectra

Abstract A method is described for the extraction of isotopic information from attenuated gamma-ray spectra using the gross-count material basis set (GC-MBS) model. This method solves for the isotopic composition of an unknown mixture of isotopes attenuated through an absorber of unknown material. For binary isotopic combinations the problem is nonlinear in only one variable and is easily solved using standard line optimization techniques. Results are presented for NaI spectrum analyses of various binary combinations of enriched uranium, depleted uranium, low burnup Pu, 137 Cs, and 133 Ba attenuated through a suite of absorbers ranging in Z from polyethylene through lead. The GC-MBS method results are compared to those computed using ordinary response function fitting and with a simple net peak area method. The GC-MBS method was found to be significantly more accurate than the other methods over the range of absorbers and isotopic blends studied.

Estimation of obliquely scattered gamma-ray response functions in the gross-count tomographic gamma scanner (GC-TGS) method

It was recently shown that a logarithmic response-function technique based on the material basis set (MBS) formalism used in the tomographic gamma scanner (TGS) method allows gross spectra from NaI detectors to be used in both measuring MBS transmission corrections using external transmission sources and in applying the corrections to emission spectra to arrive at radionuclide mass estimates. In this work we have attempted to show that addition of the oblique scatter component can increase the accuracy of the GC-TGS measurements with both NaI and high-purity germanium detectors. This paper describes the formalism behind the GC-TGS method and the improvement achieved in the analysis by including the scatter component.

Improved Isotopic Identification for NaI Spectroscopic Portal Monitors Using the Material Basis Set (MBS) Method

This report describes our application of the multiple isotope material basis set (MIMBS) method for isotope identification to the analysis of simulated spectra of Nal logs used in spectral portal monitors. The MIMBS method couples attenuation corrections for shielding materials with an ordinary isotopic response function fit. Spectrum simulations of twenty-four isotopes were generated using the Speculator software (with MCNP for attenuation calculations) for a 3 x 5 x 16-inch Nal log detector, through a series of attenuating absorbers representing a Z range from Al through Pb. Two-isotope combinations of these were analyzed using the MIMBS algorithm, with and without added 4 K background and Poisson noise. We found the MIMBS method to be highly accurate in identifying both the component isotopes and their relative amounts, even at high noise and background levels.

Energy Calibration Algorithms for the Multiple Isotope Material Basis Set (MIMBS) Isotope Identification Method

As we show in this report, the multiple isotope material basis set (MIMBS) method for isotope identification with medium- and low-resolution gamma-ray detectors requires an accurate energy calibration to be optimally effective. Determination of the detectors energy calibration using one or more known radioisotopes is generally required for all applications. We are developing an algorithm that automatically finds the best energy calibration using one or more identified (standard) gamma spectra as input, with no effort on the part of the user other than qualitatively identifying the isotopes present in the spectrum. Instruments that suffer significant energy calibration drift, such as Nal handheld identifiers, also require some type of real time gain stabilization to keep their calibration steady. We have developed two approaches for stabilizing the energy calibration for MIMBS analyses, (1) a standard peak-based gain stabilization algorithm for use when seeded or background gamma peaks are known to be present and (2) a peak-free stabilization algorithm based on a non-linear gain optimization. In this report, we describe the calibration algorithms and evaluate their effectiveness on real and simulated gamma-ray spectra under varying measurement conditions.

Application of the gross-count material basis set (GC-MBS) method to the analysis of CdZnTe spectra

The gross-count material basis set model (GC-MBS) for response-function fitting is applied to CdZnTe spectra. This method has been developed to solve for the isotopic composition of an unknown mixture of radionuclides attenuated through absorbers of unknown material. Results are presented for source strength and isotopic composition measurements of binary combinations of highly-enriched uranium (HEU), depleted uranium (DU), Np-237, Ba-133, Cs137 and variable Pu burnups attenuated through a suite of absorbers ranging in Zeffective from polyethylene through lead. Comparisons are made between GC-MBS, net area method and simpler ordinary response-function methods.

An urban environment simulation framework for evaluating novel distributed radiation detection architectures

Protection of large and complex urban areas from radiological threats may be improved by employing a network of distributed radiation detectors. Among the many considerations involved in designing such a system are detector type, concept of operations, methods to collect and extract meaningful information from multiple data sources, and cost. We have developed a realistic simulation environment as an efficient method for accurately evaluating a variety of sensor queuing/routing schemes, distributed system architectures, and data fusion algorithms. This tool enables us to assesses and demonstrate overall system performance as a function of key operational and cost parameters. Early results show that a network of 8 fixed path and 5 random path NaI sensors achieves a Pd ∼ 90% within 10 minutes against a 1 mCi Cs137 source released to 1500 possible random locations within the ∼1.3 km × 1 km area centered around Philadelphia City Hall.

Performance of the Moving Voxel Image Reconstruction (MVIR) Method in the Fixed Site Detection System (FSDS) Prototype

We have developed a dynamic gamma-ray emission image reconstruction method called MVIR (Moving Voxel Image Reconstruction) for lane detection in multilane portal monitor systems. MVIR was evaluated for use in the Fixed Site Detection System (FSDS), a prototype three-lane gamma-ray portal monitor system for EZ-pass toll plazas. As a baseline, we compared MVIR with a static emission image reconstruction method in analyzing the same real and simulated data sets. Performance was judged by the distributions of image intensities for source and no-source vehicles over many trials as a function of source strength. We found that MVIR produced significantly better results in all cases. The performance difference was greatest at low count rates, where source/no-source distributions were well separated with the MVIR method, allowing reliable source vehicle identification with a low probability of false positive identifications. Static emission image reconstruction of the same data produced overlapping distributions that made source vehicle identification unreliable. The performance of the static method was acceptable at high count rates. Both algorithms reliably identified two strong sources passing through at nearly the same time.

The Handling of K-Edge Effects in the Multiple Isotope Material Basis Set (MIMBS) Method of Isotope Identification

The multiple isotope material basis set (MIMBS) method for isotope identification combines the material basis set (MBS) model of gamma spectrum attenuation with ordinary response function fitting to identify shielded gamma-emitting isotopes, using low and medium resolution gamma detectors such as NaI(Tl) and LaBr3. We recently improved the MIMBS algorithm to handle low energy gamma emitters such as 133Xe or 241Am. A concern with fitting the low energy region (below approximately 90 keV) is that the underlying MBS model assumptions fail because of the inherent K-edge discontinuities in the attenuation versus energy curve for the different atomic species. For example, with basis attenuators of Al (Z=13) and Pb (Z=82) , the MBS model for the attenuation curve of Sn (Z=50) would have Al and Pb K-edge discontinuities at 1.55 and 88 keV, rather than at the Sn K-edge energy of 29.2 keV. Complex mixtures such as cargo would have a complex and unpredictable K-edge distribution. In this presentation we show that the effect of K-edge discontinuities on the improved multiple-thickness MIMBS algorithm for low energy isotope identification and spectrum simulation is small for common attenuator distributions.