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X-10 reactor forensic analysis and evaluation using a suite of neutron transport codesRedd, Evan M. 21 September 2015 (has links)
X-10, the genesis production reactor for the U.S. paved the way for all weapons material production. This feat offers a unique fundamental opportunity of nuclear forensic analysis and popular neutron code package evaluation. Production reactor nuclear forensic signatures and characteristics are emphasized throughout this work. These underlying production characteristics are reported and analyzed for potential in-core zone provenance and axial slug location coupled with how the nuclear data uncertainties affect these conclusions. Material attribution with respect to commercial versus military reactor applications is also featured in this study. Three nuclear code packages are examined including Scale 6.1 (Scale 6.2 beta-3 for nuclear data uncertainty reporting and evaluation), Monte Carlo N-Particle (MCNP) and Parallel Environment Neutral-particle TRANsport (PENTRAN). Each of these code packages employs different neutron transport methods and cross-section evaluation. These code results are compared and contrasted for the researcher to gain perspective into if and how nuclear forensic analysis is affected by these relative outcomes from the neutronics packages. Notably, Scale 6.2 beta-3 offers perspective on the nuclear data uncertainty and how it affects final conclusions on isotopic reporting and material provenance.
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Analytical inverse model for post-event attribution of plutoniumMiller, James Christopher 15 May 2009 (has links)
An integral part of deterring nuclear terrorism is the swift attribution of any event
to a particular state or organization. By quickly being able to identify the responsible
party after a nuclear event, appropriate people may be held accountable for their actions.
Currently, there is a system in place to determine the origin of nuclear devices and
materials from post-event data; however, the system requires significant time to produce
an answer within acceptable error margins. Described here is a deterministic approach
derived from first principles to solve the inverse problem. The derivation starts with the
basic change rate equation and ends in relationships for important nuclear concentrations
and device yield. This results in a computationally efficient and timely method for
producing an estimate of the material attributes. This estimate can then be used as a
starting point for other more detailed methods and reduce the overall computation time
of the post-event forensics.
This work focused on a specific type of nuclear event: a plutonium improvised
nuclear device (IND) explosion. From post-event isotopic ratios, this method determines
the device’s pre-event isotopic concentrations of special nuclear material. From the original isotopic concentrations, the field of possible origins for the nuclear material is
narrowed. In this scenario, knowing where the nuclear material did not originate is as
important as knowing where it did.
The derived methodology was tested using several cases of interest including
simplified and realistic cases. For the simplistic cases, only two isotopes comprised the
material being fissioned. In the realistic cases, both Weapons Grade and Reactor Grade
plutonium were used to cover the spectrum of possible fissile material to be used by
terrorists. The methodology performed very well over the desired energy range. Errors
were under two percent from the expected values for all yields under 50 kT. In the
realistic cases, competing reactions caused an increase in error; however, these stayed
under five percent. As expected, with an increased yield, the error continued to rise, but
these errors increased linearly. A sensitivity analysis was performed on the
methodology to determine the impact of uncertainty in various physical constants. The
result was that the inverse methodology is not overly sensitive to perturbations in these
constants.
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The simultaneous quantification of fissile U and Pu nuclides using delayed neutron activation analysisKapsimalis, Roger James, 1985- 14 October 2013 (has links)
The ability to quickly and accurately quantify fissile constituents in bulk materials remains essential to many aspects of nuclear forensics and for safeguarding nuclear materials and operations. This often entails the analysis of trace quantities of nuclear debris or effluents, and typically requires bulk sample digestion followed by actinide separation and mass spectrometry. Because destructive methods are time and labor intensive, efforts have been made to develop alternative nondestructive methods for this type of analysis. This work, performed at Oak Ridge National Laboratory at the High Flux Isotope Reactor (HFIR), seeks to utilize delayed neutron activation analysis on samples of interest containing multiple fissile constituents. Based on the variances in the fission product yields of individual fissile nuclides, this work utilizes methods of linear regression to derive a technique that allows for such analysis, forgoing chemical separation and using only a single irradiation and counting step. / text
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Investigations of Nuclear Forensic Signatures in Uranium Bearing MaterialsMeyers, Lisa A. January 2013 (has links)
No description available.
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Evaluation of Environmental Concentratorsfor Trace Actinide MeasurementsLavelle, Kevin B. January 2016 (has links)
No description available.
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Forward model calculations for determining isotopic compositions of materials used in a radiological dispersal deviceBurk, David Edward 29 August 2005 (has links)
In the event that a radiological dispersal device (RDD) is detonated in the U.S. or
near U.S. interests overseas, it will be crucial that the actors involved in the event can be
identified quickly. If irradiated nuclear fuel is used as the dispersion material for the
RDD, it will be beneficial for law enforcement officials to quickly identify where the
irradiated nuclear fuel originated. One signature which may lead to the identification of
the spent fuel origin is the isotopic composition of the RDD debris.
The objective of this research was to benchmark a forward model methodology
for predicting isotopic composition of spent nuclear fuel used in an RDD while at the
same time optimizing the fidelity of the model to reduce computational time. The code
used in this study was Monteburns-2.0. Monteburns is a Monte Carlo based neutronic
code utilizing both MCNP and ORIGEN. The size of the burnup step used in
Monteburns was tested and found to converge at a value of 3,000 MWd/MTU per step.
To ensure a conservative answer, 2,500 MWd/MTU per step was used for the
benchmarking process. The model fidelity ranged from the following: 2-dimensional pin
cell, multiple radial-region pin cell, modified pin cell, 2D assembly, and 3D assembly.
The results showed that while the multi-region pin cell gave the highest level of
accuracy, the difference in uncertainty between it and the 2D pin cell (0.07% for 235U)
did not warrant the additional computational time required. The computational time for
the multiple radial-region pin cell was 7 times that of the 2D pin cell. For this reason, the
2D pin cell was used to benchmark the isotopics with data from other reactors.
The reactors from which the methodology was benchmarked were Calvert Cliffs
Unit #1, Takahama Unit #3, and Trino Vercelles. Calvert Cliffs is a pressurized water
reactor (PWR) using Combustion Engineering 14??14 assemblies. Takahama is a PWR
using Mitsubishi Heavy Industries 17??17 assemblies. Trino Vercelles is a PWR using
non-standard lattice assemblies. The measured isotopic concentrations from all three of
the reactors showed good agreement with the calculated values.
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A comparison of nuclide production and depletion using MCNPX and ORIGEN-ARP reactor models and a sensitivity study of reactor design parameters using MCNPX for nuclear forensics purposesChambers, Angela Sue 22 February 2011 (has links)
The Oak Ridge Isotope Generation and Depletion – Automatic Rapid Proccessing (ORIGEN-ARP) deterministic code has been extensively utilized for determining nuclide concentrations at various specific burnup values for a variety of nuclear reactor designs. Given nuclide concentrations or ratios, such calculations can be used in nuclear forensics and nuclear non-proliferation applications to reverse-calculate the type of reactor and specific burnup of the fuel from which the nuclides originated.
Recently, Los Alamos National Laboratory has released a version of its probabilistic radiation transport code, MCNPX 2.6.0, which incorporates a fuel burnup feature which can also determine, via the probabilistic Monte Carlo method, nuclide concentrations as a function of fuel burnup.
This dissertation compares the concentrations of 46 nuclides significant to nuclear forensics analyses for different reactor types using results from the ORIGEN-ARP and the MCNPX 2.6.0 codes. Three reactor types were chosen: the Westinghouse 17x17
Pressurized Water Reactor (PWR), the GE 8x8-4 Boiling Water Reactor (BWR), and the Canadian Deuterium Uranium, CANDU-37, reactor.
Additionally, a sensitivity study of the different reactor parameters within the MCNPX Westinghouse 17x17 PWR model was performed. This study analyzed the different nuclide concentrations resulting from minor perturbations of the following parameters: assembly rod pitch, initial moderator boron concentration, fuel pin cladding thickness, moderator density, and fuel temperature. / text
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Flat Quartz-Crystal X-ray Spectrometer for Nuclear Forensics ApplicationsGoodsell, Alison 2012 August 1900 (has links)
The ability to quickly and accurately quantify the plutonium (Pu) content in pressurized water reactor (PWR) spent nuclear fuel (SNF) is critical for nuclear forensics purposes. One non-destructive assay (NDA) technique being investigated to detect bulk Pu in SNF is measuring the self-induced x-ray fluorescence (XRF). Previous XRF measurements of Three Mile Island (TMI) PWR SNF taken in July 2008 and January 2009 at Oak Ridge National Laboratory (ORNL) successfully illustrated the ability to detect the 103.7 keV x ray from Pu using a planar high-purity germanium (HPGe) detector. This allows for a direct measurement of Pu in SNF. Additional gamma ray and XRF measurements were performed on TMI SNF at ORNL in October 2011 to measure the signal-to-noise ratio for the 103.7 keV peak.
Previous work had shown that the Pu/U peak ratio was directly proportional to the Pu/U content and increased linearly with burnup. However, the underlying Compton background significantly reduced the signal-to-noise ratio for the x-ray peaks of interest thereby requiring a prolonged count time. Comprehensive SNF simulations by Stafford et al showed the contributions to the Compton continuum were due to high-energy gamma rays scattering in the fuel, shipping tube, cladding, collimator and detector1. The background radiation was primarily due to the incoherent scattering of the 137Cs 661.7 keV gamma. In this work methods to reduce the Compton background and thereby increase the signal-to-noise ratio were investigated.
To reduce the debilitating effects of the Compton background, a crystal x-ray spectrometer system was designed. This wavelength-dispersive spectroscopy technique isolated the Pu and U x rays according to Bragg's law by x-ray diffraction through a crystal structure. The higher energy background radiation was blocked from reaching the detector using a customized collimator and shielding system.
A flat quartz-crystal x-ray spectrometer system was designed specifically to fit the constraints and requirements of detecting XRF from SNF. Simulations were performed to design and optimize the collimator design and to quantify the improved signal-to-noise ratio of the Pu and U x-ray peaks. The proposed crystal spectrometer system successfully diffracted the photon energies of interest while blocking the high-energy radiation from reaching the detector and contributing to background counts. The spectrometer system provided a higher signal-to-noise ratio and lower percent error for the XRF peaks of interest from Pu and U. Using the flat quartz-crystal x-ray spectrometer and customized collimation system, the Monte Carlo N-Particle (MCNP) simulations showed the 103.7 keV Pu x-ray peak signal-to-noise ratio improved by a factor of 13 and decreased the percent error by a factor of 3.3.
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Nuclear Fission Weapon Yield, Type, and Neutron Spectrum Determination Using Thin Li-ion BatteriesJanuary 2017 (has links)
abstract: With the status of nuclear proliferation around the world becoming more and more complex, nuclear forensics methods are needed to restrain the unlawful usage of nuclear devices. Lithium-ion batteries are present ubiquitously in consumer electronic devices nowadays. More importantly, the materials inside the batteries have the potential to be used as neutron detectors, just like the activation foils used in reactor experiments. Therefore, in a nuclear weapon detonation incident, these lithium-ion batteries can serve as sensors that are spatially distributed.
In order to validate the feasibility of such an approach, Monte Carlo N-Particle (MCNP) models are built for various lithium-ion batteries, as well as neutron transport from different fission nuclear weapons. To obtain the precise battery compositions for the MCNP models, a destructive inductively coupled plasma mass spectrometry (ICP-MS) analysis is utilized. The same battery types are irradiated in a series of reactor experiments to validate the MCNP models and the methodology. The MCNP nuclear weapon radiation transport simulations are used to mimic the nuclear detonation incident to study the correlation between the nuclear reactions inside the batteries and the neutron spectra. Subsequently, the irradiated battery activities are used in the SNL-SAND-IV code to reconstruct the neutron spectrum for both the reactor experiments and the weapon detonation simulations.
Based on this study, empirical data show that the lithium-ion batteries have the potential to serve as widely distributed neutron detectors in this simulated environment to (1) calculate the nuclear device yield, (2) differentiate between gun and implosion fission weapons, and (3) reconstruct the neutron spectrum of the device. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017
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N-SLOPE: A One-Class Classification Ensemble for Nuclear ForensicsKehl, Justin 01 June 2018 (has links) (PDF)
One-class classification is a specialized form of classification from the field of machine learning. Traditional classification attempts to assign unknowns to known classes, but cannot handle novel unknowns that do not belong to any of the known classes. One-class classification seeks to identify these outliers, while still correctly assigning unknowns to classes appropriately. One-class classification is applied here to the field of nuclear forensics, which is the study and analysis of nuclear material for the purpose of nuclear incident investigations. Nuclear forensics data poses an interesting challenge because false positive identification can prove costly and data is often small, high-dimensional, and sparse, which is problematic for most machine learning approaches. A web application is built using the R programming language and the shiny framework that incorporates N-SLOPE: a machine learning ensemble. N-SLOPE combines five existing one-class classifiers with a novel one-class classifier introduced here and uses ensemble learning techniques to combine output. N-SLOPE is validated on three distinct data sets: Iris, Obsidian, and Galaxy Serpent 3, which is an enhanced version of a recent international nuclear forensics exercise. N-SLOPE achieves high classification accuracy on each data set of 100%, 83.33%, and 83.33%, respectively, while minimizing false positive detection rate to 0% across the board and correctly detecting every single novel unknown from each data set. N-SLOPE is shown to be a useful and powerful tool to aid in nuclear forensic investigations.
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