Publications

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We present a neutron detector system based on time-encoded imaging, and demonstrate its applicability toward the spatial mapping of special nuclear material. We demonstrate that two-dimensional fast-neutron imaging with 2° resolution at 2 m stand-off is feasible with only two instrumented detectors.

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The intent of the proposed work, in collaboration with University of Michigan, is to develop the algorithms that will bring the analysis from qualitative images to quantitative attributes of objects containing SNM. The first step to achieving this is to develop an indepth understanding of the intrinsic errors associated with the deconvolution and MLEM algorithms. A significant new effort will be undertaken to relate the image data to a posited three-dimensional model of geometric primitives that can be adjusted to get the best fit. In this way, parameters of the model such as sizes, shapes, and masses can be extracted for both radioactive and non-radioactive materials. This model-based algorithm will need the integrated response of a hypothesized configuration of material to be calculated many times. As such, both the MLEM and the model-based algorithm require significant increases in calculation speed in order to converge to solutions in practical amounts of time.

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A Bayesian approach is proposed for pulse shape discrimination of photons and neutrons in liquid organic scinitillators. Instead of drawing a decision boundary, each pulse is assigned a photon or neutron confidence probability. In addition, this allows for photon and neutron classification on an event-by-event basis. The sum of those confidence probabilities is used to estimate the number of photon and neutron instances in the data. An iterative scheme, similar to an expectation-maximization algorithm for Gaussian mixtures, is used to infer the ratio of photons-to-neutrons in each measurement. Therefore, the probability space adapts to data with varying photon-to-neutron ratios. A time-correlated measurement of Am–Be and separate measurements of ¹³⁷Cs, ⁶⁰Co and ²³²Th photon sources were used to construct libraries of neutrons and photons. These libraries were then used to produce synthetic data sets with varying ratios of photons-to-neutrons. Probability weighted method that we implemented was found to maintain neutron acceptance rate of up to 90% up to photon-to-neutron ratio of 2000, and performed 9% better than the decision boundary approach. Furthermore, the iterative approach appropriately changed the probability space with an increasing number of photons which kept the neutron population estimate from unrealistically increasing.

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This report summarizes the discussion and conclusions reached during a table top exercise held at Sandia National Laboratories, Albuquerque on September 3, 2014 regarding a recently described approach for nuclear warhead verification based on the cryptographic concept of a zero-knowledge protocol (ZKP) presented in a recent paper authored by Glaser, Barak, and Goldston. A panel of Sandia National Laboratories researchers, whose expertise includes radiation instrumentation design and development, cryptography, and arms control verification implementation, jointly reviewed the paper and identified specific challenges to implementing the approach as well as some opportunities. It was noted that ZKP as used in cryptography is a useful model for the arms control verification problem, but the direct analogy to arms control breaks down quickly. The ZKP methodology for warhead verification fits within the general class of template-based verification techniques, where a reference measurement is used to confirm that a given object is like another object that has already been accepted as a warhead by some other means. This can be a powerful verification approach, but requires independent means to trust the authenticity of the reference warhead - a standard that may be difficult to achieve, which the ZKP authors do not directly address. Despite some technical challenges, the concept of last-minute selection of the pre-loads and equipment could be a valuable component of a verification regime.

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In coded aperture imaging, one of the most important factors determining the quality of reconstructed images is the choice of mask/aperture pattern. In many applications, uniformly redundant arrays (URAs) are widely accepted as the optimal mask pattern. Under ideal conditions, thin and highly opaque masks, URA patterns are mathematically constructed to provide artifact-free reconstruction however, the number of URAs for a chosen number of mask elements is limited and when highly penetrating particles such as fast neutrons and high-energy gamma-rays are being imaged, the optimum is seldom achieved. In this case more robust mask patterns that provide better reconstructed image quality may exist. Through the use of heuristic optimization methods and maximum likelihood expectation maximization (MLEM) image reconstruction, we show that for both point and extended neutron sources a random mask pattern can be optimized to provide better image quality than that of a URA.

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This note summarizes an effort to characterize the effects of adding water-based liquid scintillator to the WATCHMAN detector. A detector model was built in the Geant4 Monte Carlo toolkit, and the position reconstruction of positrons within the detector was compared with and without scintillator. This study highlights the need for further modeling studies and small-scale experimental studies before inclusion into a large-scale detector, as the benefits compared to the associated costs are unclear.

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This report provides a short overview of the DNN R&D funded project, Time-Encoded Imagers. The project began in FY11 and concluded in FY14. The Project Description below provides the overall motivation and objectives for the project as well as a summary of programmatic direction. It is followed by a short description of each task and the resulting deliverables.