PNNL-13501 - Pacific Northwest National Laboratory

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A next-generation technology is needed to address the problem of plutonium mass measurement in arms control applications. Despite the tremendous inertia behind the established technique of coincidence counting, there is a growing acknowledgment of the general failure of neutron-based methods to properly support the United States arms control objectives. Further, it is likely that a simple but effective technology such as this could actually accelerate progress in negotiations such as START III, START III+, and Mayak. The amount of necessary measurement hardware would be greatly reduced, with a single measurement involving a single detector and single information barrier potentially being sufficient. The timeline for development and testing of measurement systems would be greatly accelerated. Approach The approach to this problem necessarily involves the development of a model for the plutonium configuration, with subsequent evaluation of the errors resulting from the use of the model. Two major simplifications are necessary for such a model to proceed. First, the set of shielding materials can be reduced to three basic types with quantifiable properties. High-Z shielding accounts for substances such as lead and uranium, medium-Z shielding accounts for substances such as iron, low-Z shielding accounts for all hydrogenous substances and materials with atomic numbers below roughly aluminum. A plot of mass attenuation coefficients (as a function of energy) for the simplified model is shown in Figure 1. Figure 1. Mass attenuation coefficients for selected materials as a function of photon energy The second major simplification involves object geometry. Calculations are most easily completed for slab (planar) geometries, while real components incorporate more complex geometries. Our initial algorithm assumes slab geometry. Future work will assess improvements, if any, from incorporating a nonslab geometry. Perfectly accurate geometries are not possible because nuclear weapons are constructed in a variety of shapes, sizes, and designs. We anticipate that the uncertainties associated with using this simplification will be small. Estimates accurate to within 25 to 50% may be more than satisfactory for arms control applications. This work complements and extends the Sandia National Laboratory algorithm work, called “Minimum Mass Estimate (MME)” (Mitchell and Marlow 2000), by the use of a larger part of the gamma-ray spectrum, an elaborate shielding and geometric model, and sophisticated statistical methods. Results and Accomplishments Our approach to development and testing of the initial mass estimate algorithms was based on the use of increasingly complicated gamma-ray spectra. Initially, simplified spectra were generated using the SYNTH gamma-ray generating software, followed by spectra collected in the laboratory from a small (~100 gram) weapons grade plutonium source. A wide variety of absorbers (that spanned a broad range of atomic number and density) were then used to attenuate the gamma-rays from the plutonium both individually and in combinations with other absorber materials. Measurements were made using both short and long acquisition times so that we could determine the sensitivity of the algorithms to the statistics of the input spectra. The key to the probabilistic approach to this problem is that the expected (average) gamma-ray signals, as a function of energy, are completely determined by known physics. Under the absorber and geometric assumptions discussed above, the expected gamma-ray signal at a spectrometer has been described mathematically using first-order effects. The current algorithm assumes known thickness of the low, medium, and high barriers. This assumption will be relaxed in future development and the mathematics of mass estimation in the presence of absorber-thicknessuncertainty is developed. Summary and Conclusions The first round of algorithm development has yielded very promising results. We were able to successfully calculate an accurate plutonium mass from experimental data given the composition of a combination of Sensors and Electronics 407
attenuation materials (but unknown thickness), as well as calculate the attenuation material thickness given plutonium mass and attenuation material. Thus, we have been able to show that the individual pieces of the underlying algorithm appear to be well behaved in the regions of the parameter space examined. We have also seen some early indications that the method may be somewhat insensitive to the poor statistics associated with short data acquisition times. 408 FY 2000 Laboratory Directed Research and Development Annual Report The success of this year’s research indicates improvement can be made through additional testing and refinements to the algorithm. Reference Mitchell DJ and KW Marlow. 2000. Minimum Mass Estimates for Plutonium Based on the Peak Intensities and Scattered Radiation in HPGe Spectra SAND2000- 0383, Sandia National Laboratories, Albuquerque, New Mexico.
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Laboratory Directed Research and De
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Laboratory Directed Research and De
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Computational Science and Engineeri
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Policy and Management Sciences Asse
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Introduction Department of Energy O
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5. After reviews by the Technical a
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• The Technical Council peer revi
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methods applicable to combustion, s
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Summary Each national laboratory mu
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Study Control Number: PN0004/1411 A
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Table 1. Positive and negative ions
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m/z Arbitrary Units Figure 1. Mass
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introduce low-volatility compounds
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arrangement, but the charge is reta
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two liquid chromatographic gradient
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Integrated Microfabricated Devices
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Matrix Assisted Laser Desorption/Io
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Molecular Beam Synthesis and Charac
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temperature distribution of the des
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expected to result in significant a
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Study Control Number: PN99069/1397
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Seuss DT and KA Prather. 1999. “M
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Analysis of Receptor-Modulated Ion
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laboratory (Lu and Xie 1997; Lu et
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Automated DNA Fingerprinting Microa
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Comparison of 4 Xanthomonas Isolate
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Approach Hematopoietic (bone marrow
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Anti-Human lgG Human lgG Protein G
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Characterization of Global Gene Reg
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PCR products for immobilization on
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identify novel proteins of importan
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Immunoprecipitaton of tyrosinephosp
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Coupled NMR and Confocal Microscopy
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In the optical microscopy image, th
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Development and Applications of a M
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Figure 3. Hepa-1 cells undergoing a
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cellular processing (such as post-t
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8. Initial demonstration of an off-
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expression systems for several year
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accumulation of protein products, i
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Fungal Conversion of Agricultural W
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Fungal Conversion of Waste Glucose/
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Summary and Conclusions We demonstr
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are shown in Figure 1(a) and 1(b),
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Anchorage-Independent Growth (% con
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selection of seedlings demonstratin
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NMR-Based Structural Genomics Micha
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Solution-State Structure and Fold-C
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Plant Root Exudates and Microbial G
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Summary and Conclusions • The gre
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Jones-Oliveira JB, JS Oliveira, HE
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• securely moves files to a targe
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Plenary invited lecture, “The Ele
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Figure 1. X3DGEN tetrahedral mesh o
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Figure 5a. OSO volume rendering of
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Development of Models of Cell-Signa
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SOS p 23 EGFR Professor Rodland at
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Oliveira JS, JB Jones-Oliveira, and
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Figure 2. Associating a dataset mar
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to 1) incorporate three-dimensional
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shown in Figure 1. Simulated result
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HostBuilder: A Tool for the Combina
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Invariant Discretization Methods fo
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Graphics, Inc., workstation. The co
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Mixed Hamiltonian Methods for Geoch
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guyanaite, and grimaldiite (see Fig
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in the Environmental Molecular Scie
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Simulation and Modeling of Electroc
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Summary and Conclusions We implemen
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Since the implementation of the gen
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asis of previous performance, perce
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Bioinformatics for High-Throughput
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Summary and Conclusions In previous
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User Cat - Supervisor (client) Anal
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The second goal was to research way
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Figure 1. A visualization technique
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and interactions. The flexibility o
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Figure 4. A filtered version of Fig
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Development of Modeling Tools for J
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Figure 2. Schematic of experimental
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Integrated Modeling and Simulation
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(a) (b) (c) (d) Figure 1. Results o
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Thurman DA. August 2000. Collaborat
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MARC Input initial m esh and result
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(Johnson 1999; Colligan 1999; Gould
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Modeling of High-Velocity Forming f
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Global divergence error 1 10 -14 0
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that users were unlikely to appreci
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Earth System Science
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the lateral extent of the plume so
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Biogeochemical Processes and Microb
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Analyses of populations of viable a
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The first task was to establish fiv
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purged for 2 minutes. The gas sampl
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developing code architecture to min
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Berkowitz, CM. June 2000. “Atmosp
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environmental monitoring, 2) portab
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corresponded to a current density o
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Enhancing Emissions Pre-Processing
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Environmental Fate and Effects of D
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nitrogen and unpredictable eutrophi
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Figure 1. Ordinary kriging of 2 m d
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precipitation of calcite occurred i
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Interrelationships Between Processe
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phenanthrene resistant fraction con
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injection of an immiscible gas phas
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still some key kinetic issues that
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Application of a Crop Model The res
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The Nature, Occurrence, and Origin
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Particle number concentration, 1/cm
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geometry optimized AlOOH and FeOOH
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allowable parameters using thermody
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TCE + 3H + + 3Fe 2+ Fe)=> acetylene
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Use of Shear-Thinning Fluids for In
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concentration of 0.5% AMX was the m
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Roberts AL, LA Totten, WA Arnold, D
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tetra-scale computing, envisioned a
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Energy Technology and Management
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Figure 2. Setup for the second expe
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phase. The algorithms will be teste
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[Pb-212]/[Pb-212] final 100 10 1 0.
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Plasma Particle Dielectric Fiber El
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(species, sub-species, and sex), sp
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Figure 3. Relative risk of bone and
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Development of a Preliminary Physio
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Development of a Virtual Respirator
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Figure 3. Use of the chest cavity a
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Examination of the Use of Diazolumi
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Indoor Air Pathways to Nuclear, Che
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Source Building Release Observed re
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To illustrate the potential impact
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Non-Invasive Biological Monitoring
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Materials Science and Technology
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Figure 1. (a) - (c) Successive magn
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Component Fabrication and Assembly
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Development of a Low-Cost Photoelec
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elaxations, indicating the adequacy
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Promising chemical durability, as m
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Study Control Number : PN98028/1274
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High Power Density Solid Oxide Fuel
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Hybrid Plasma Process for Vacuum De
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Matson DW, PM Martin, WD Bennett, J
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We showed the proof-of-principle ap
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Bandgap Energy (eV) 2.9 2.85 2.8 2.
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Ultrathin Electrolyte Test Results
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Detailed Investigations on Hydrogen
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identified low energy step structur
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Development of Novel Photo-Catalyst
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-2 -1 Energy (eV) 0 1 2 Cu2O SrTiO3
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Here, we perform adsorption and des
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exceed those in the all-metal devic
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Intensity (a.u.) 0 100 200 300 400
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PNNL-13501 - Pacific Northwest National Laboratory

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