Inverse radiation transport focuses on identifying the configuration of an unknown radiation source given its observed radiation signatures. The inverse problem is solved by finding the set of transport model variables that minimizes a weighted sum of the squared differences by channel between the observed signature and the signature predicted by the hypothesized model parameters. The weights per channel are inversely proportional to the sum of the variances of the measurement and model errors at a given channel. In the current treatment, the implicit assumption is that the errors (differences between the modeled and observed radiation signatures) are independent across channels. In this paper, an alternative method that accounts for correlated errors between channels is described and illustrated for inverse problems based on gamma spectroscopy.
The heightened focus on nuclear safeguards and accountability has increased the need to develop and verify simulation tools for modeling these applications. The ability to accurately simulate safeguards techniques, such as neutron multiplicity counting, aids in the design and development of future systems. This work focuses on validating the ability of the Monte Carlo code MCNPX-PoliMi to reproduce measured neutron multiplicity results for a highly multiplicative sample. The benchmark experiment for this validation consists of a 4.5-kg sphere of plutonium metal that was moderated by various thicknesses of polyethylene. The detector system was the nPod, which contains a bank of 15 3He detectors. Simulations of the experiments were compared to the actual measurements and several sources of potential bias in the simulation were evaluated. The analysis included the effects of detector dead time, source-detector distance, density, and adjustments made to the value of {nu}-bar in the data libraries. Based on this analysis it was observed that a 1.14% decrease in the evaluated value of {nu}-bar for 239Pu in the ENDF-VII library substantially improved the accuracy of the simulation.
Sandia National Laboratories has developed an inverse radiation transport solver that applies nonlinear regression to coupled neutron-photon deterministic transport models. The inverse solver uses nonlinear regression to fit a radiation transport model to gamma spectrometry and neutron multiplicity counting measurements. The subject of this paper is the experimental validation of that solver. This paper describes a series of experiments conducted with a 4.5 kg sphere of {alpha}-phase, weapons-grade plutonium. The source was measured bare and reflected by high-density polyethylene (HDPE) spherical shells with total thicknesses between 1.27 and 15.24 cm. Neutron and photon emissions from the source were measured using three instruments: a gross neutron counter, a portable neutron multiplicity counter, and a high-resolution gamma spectrometer. These measurements were used as input to the inverse radiation transport solver to evaluate the solver's ability to correctly infer the configuration of the source from its measured radiation signatures.
With increasing concern over the ability to detect and characterize special nuclear materials, the need for computer codes that can successfully predict the response of detector systems to various measurement scenarios is extremely important. These computer algorithms need to be benchmarked against a variety of experimental configurations to ensure their accuracy and understand their limitations. The Monte Carlo code MCNP-PoliMi is a modified version of the MCNP-4c code. Recently these modifications have been ported into the new MCNPX 2.6.0 code, which gives the new MCNPX-PoliMi a wider variety of options and abilities, taking advantage of the improvements made to MCNPX. To verify the ability of the MCNPX-PoliMi code to simulate the response of a neutron multiplicity detector simulated results were compared to experimental data. The experiment consisted of a 4.5-kg sphere of alpha-phase plutonium that was moderated with various thicknesses of polyethylene. The results showed that our code system can simulate the multiplicity distributions with relatively good agreement with measured data. The enhancements made to MCNP since the release of MCNP-4c have had little to no effect on the ability of the MCNP-PoliMi to resolve the discrepancies observed in the simulated neutron multiplicity distributions when compared experimental data.
Forward radiation transport is the problem of calculating the radiation field given a description of the radiation source and transport medium. In contrast, inverse transport is the problem of inferring the configuration of the radiation source and transport medium from measurements of the radiation field. As such, the identification and characterization of special nuclear materials (SNM) is a problem of inverse radiation transport, and numerous techniques to solve this problem have been previously developed. The authors have developed a solver based on nonlinear regression applied to deterministic coupled neutron-photon transport calculations. The subject of this paper is the experimental validation of that solver. This paper describes a series of experiments conducted with a 4.5-kg sphere of alpha-phase, weapons-grade plutonium. The source was measured in six different configurations: bare, and reflected by high-density polyethylene (HDPE) spherical shells with total thicknesses of 1.27, 2.54, 3.81, 7.62, and 15.24 cm. Neutron and photon emissions from the source were measured using three instruments: a gross neutron counter, a portable neutron multiplicity counter, and a high-resolution gamma spectrometer. These measurements were used as input to the inverse radiation transport solver to characterize the solver's ability to correctly infer the configuration of the source from its measured signatures.
The purpose of this work is to improve detection methods that can reliably identify special nuclear material (SNM). One method that can be used to identify special nuclear material is neutron multiplicity analysis. This method detects multiple time-correlated neutrons released from a fission event in the SNM. This work investigates the ability of the software code MCNP-PoliMi to simulate neutron multiplicity measurements from a highly moderated SNM source. A measurement of a 4.5-kg alpha-phase metal plutonium sphere surrounded by up to 6 inches of polyethylene shells has recently been performed by Sandia National Laboratories personnel at the Nevada Test Site. A post-processing code was developed to account for dead-time effects within the detector and to determine the neutron multiplicity distributions for various time intervals. With the distributions calculated, the Feynman-Y can be determined. The Feynman-Y is a metric that measures the level of correlation present in a sample. At this time MCNP-PoliMi is able predict the Feynman-Y within 10% of the measured value.
A multi-group cross section collapsing code, YGROUP, has been developed to speed up deterministic particle transport simulations by reducing the number of discrete energy groups while maintaining computational transport accuracy. The YGROUP code leverages previous studies based on the "contributon" approach to automate group selection. First, forward and adjoint deterministic transport calculations are performed on a smaller problem model, or on one section of a large problem model representative of problem physics using a fine group structure. Then, the calculated forward flux and adjoint function moments are used by YGROUP to collapse the fine group cross section library and generate a problem-dependent broad group cross section library. Finally, the broad group library is used for new transport calculations on the full scale/refined problem model. YGROUP provides several weighting options to collapse the cross section library, including flat, flux, and contributon (the product of forward flux and scalar adjoint moments). Users can also specify fine groups in specific energy ranges of interest to be reserved after collapsing. YGROUP also can be used to evaluate the Feynman-Y asymptote characterizing neutron multiplicity.
The performance of the Gamma Detector Response and Analysis Software (GADRAS) was validated by comparing GADRAS model results to experimental measurements for a series of benchmark sources. Sources for the benchmark include a plutonium metal sphere, bare and shielded in polyethylene, plutonium oxide in cans, a highly enriched uranium sphere, bare and shielded in polyethylene, a depleted uranium shell and spheres, and a natural uranium sphere. The benchmark experimental data were previously acquired and consist of careful collection of background and calibration source spectra along with the source spectra. The calibration data were fit with GADRAS to determine response functions for the detector in each experiment. A one-dimensional model (pie chart) was constructed for each source based on the dimensions of the benchmark source. The GADRAS code made a forward calculation from each model to predict the radiation spectrum for the detector used in the benchmark experiment. The comparisons between the GADRAS calculation and the experimental measurements are excellent, validating that GADRAS can correctly predict the radiation spectra for these well-defined benchmark sources.
The primary function of the Gamma Detector Response and Analysis Software (GADRAS) is the solution of inverse radiation transport problems, by which the con-figuration of an unknown radiation source is inferred from one or more measured radia-tion signatures. GADRAS was originally developed for the analysis of gamma spec-trometry measurements. During fiscal years 2007 and 2008, GADRAS was augmented to implement the simultaneous analysis of neutron multiplicity measurements. This report describes the radiation transport methods developed to implement this new capability. This work was performed at the direction of the National Nuclear Security Administration's Office of Nonproliferation Research and Development. It was executed as an element of the Proliferation Detection Program's Simulation, Algorithm, and Modeling element. Acronyms BNL Brookhaven National Laboratory CSD Continuous Slowing-Down DU depleted uranium ENSDF Evaluated Nuclear Structure Data Files GADRAS Gamma Detector Response and Analysis Software HEU highly enriched uranium LANL Los Alamos National Laboratory LLNL Lawrence Livermore National Laboratory NA-22 Office of Nonproliferation Research and Development NNDC National Nuclear Data Center NNSA National Nuclear Security Administration ODE ordinary differential equation ONEDANT One-dimensional diffusion accelerated neutral particle transport ORNL Oak Ridge National Laboratory PARTISN Parallel time-dependent SN PDP Proliferation Detection Program RADSAT Radiation Scenario Analysis Toolkit RSICC Radiation Safety Information Computational Center SAM Simulation, Algorithms, and Modeling SNL Sandia National Laboratories SNM special nuclear material ToRI Table of Radioactive Isotopes URI uniform resource identifier XML Extensible Markup Language