Considering Uncertainty and Risk in Public Protection Decisions During Nuclear and Radiological Emergencies.
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The Office of Legacy management asked the Aerial Measurement System to perform an aerial survey and analyze the results for a three uranium mines in Wyoming
presentation to accompany the AMS DRUM survey report
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A particle filter algorithm is presented to estimate the position, strength, and cardinality of an unknown number of radioactive point sources in an obstacle-rich environment using count measurements. The algorithm addresses gaps in the prior literature by incorporating two novel elements. The first is a precomputation step in which local terrain and obstacle data is processed to compute attenuation kernels throughout the search area. This enables rapid estimation performance in obstacle-rich environments as measurements are gathered. The second novel feature is a dynamic particle allocation technique in which the number of particles is adjusted in real time to meet convergence goals. This feature allows the algorithm to scale more efficiently to scenarios with a larger number of sources. A series of computational experiments using simulated data demonstrates the algorithm’s performance in a cluttered environment with up to eight sources.
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This is the final thesis and research paper for Frank Pulciano. He is graduating with his Masters in Mechanical Engineering and will be presenting his research and defending his thesis.
Aqueous dispersivity is a phenomenon by which a solute moving in groundwater mixes with water that does not contain the solute and becomes diluted. Solutes take paths of varying lengths through pore networks or experience slower velocities due to interactions with pore walls. Aqueous dispersivity leads to breakthrough curves with earlier arrival than expected in purely advective systems and persistent 'tails,' or late-arriving, dilute concentrations of the solute. Dispersivity can be longitudinal (in the direction of flow) or transverse (orthogonal to flow). LANL has disposed of radioactive material at Material Disposal Area (MDA) G since the late 1950's. Most of the disposed materials at MDA G are low-level waste (LLW), but other types of radioactive wastes are disposed or stored at the site. For example, there is a collection of remote-handled transuranic waste (RH-TRU) waste in 33 shafts, which were intended to be stored retrievably. Aqueous-phase radionuclides included in models of contaminant transport at MDA G are subject to dispersive processes in porous media of the vadose zone and saturated zone. To model dispersivity at MDA G probabilistically, we created site-specific distributions of aqueous dispersivity. First, we performed a comprehensive review of peer-reviewed publications, reports from other performance assessments of MDA G, and documentation from sites that were considered similar based on expert opinion, such as Yucca Mountain. Data were included from a wide range of sources, so that distributions developed based on the data reflect the current state of knowledge in properties of the subsurface environment. Data were grouped based on value type (e.g., determined via experiment or used in a different model), rock type, zone type (saturated or unsaturated), and site, and were weighted in the distributions according to their relevance to the site and zone type. We combined Monte Carlo simulation and bootstrapping techniques to produce approximate distributions of mean aqueous dispersivity. Distributions of dispersivity for saturated and unsaturated zone transport are differentiated by data weight and the length scales over which transport occurs. We find that underestimating or disregarding transverse dispersivity may lead to overstating simulated well capture in the saturated zone at MDA G. Neglecting transverse dispersivity is a common assumption due in part to use of one-dimensional transport models that do not consider solute spreading orthogonal to flow. Also, we find that variability in longitudinal dispersivity is associated with substantial travel time alterations in the MDA G unsaturated zone and in simulated contaminant breakthrough times at a downstream observation plane in the MDA G saturated zone. Finally, at large scales (>1000 m), a linear trend between the dispersivity coefficient and length over which transport occurs may overestimate the dispersivity coefficient. Future modeling work with application to solute spreading could include interacting advective and diffusive zones in the highly fractured basalt below MDA G. (authors)
Additive manufacturing of polymers is a widely used and growing technology throughout the DOE complex. Composite filaments for Fused Deposition Modeling (FDM) printers are commonly used to enhance material properties such as mechanical strength, operating temperature and chemical resistance. Radio luminescent properties were added to 3D filaments by impregnating clear poly(ethylene terephthalate)-glycol (PETG) with X-ray scintillator powder. X-ray scintillators have unique, narrow emission spectra which can be imaged with low light DSLR cameras, photomultiplier tubes, or spectrometers. Filament Production: 1. Pellets are loaded into the hopper. 2. Temperature and extrusion speed are set on extruder. 3. Extruder turned on and filament is pulled from nozzle along air path to cool. 4. Spooler drive speeds set. 5. Filament is inserted through Filameasure then guided along drive wheels and into traverse. 6. Parameters adjusted to obtain 1.75 mm diameter 7. Filament is inserted into spooler wheel. Traverse speed set and slip nut adjusted to make tight and even roll. From Raw Materials to Printed Part: Clear PETG pellets were dipped in ZnS:Cu scintillator powder to coat pellets. Coated and uncoated pellets were mixed together before inserting into hopper. Filament showed trace amounts of powder and luminesced under UV light. Powder distribution is random and not reproducible thus providing a unique identification marker potentially useful for national security applications. Multiple X-ray scintillators can be arranged in a panel to discriminate incident X-ray photon energies. Variable panel arrangement: pixelated, layered, solid from homogenous filament. Ratio of emission intensities. Response varies with incident photon energy. Spectrally separate scintillators. Scintillators: Yttrium Oxide Europium Doped - Red, Gadolinium Oxysulfide Terbium Doped - Green, Barium Magnesium Aluminate Europium Doped - Blue, Zinc Sulfide Copper Doped - Green. Powder concentrations will need to be increased in the filament for use in the energy discriminating panel. Homogeneity in the filament will be a challenge that can be solved by turning the pellets into a powder and mixing it with scintillator powder prior to extrusion. The panels will be tested using x-ray booths and button sources such as Am-241, Cs-137, and Co-60.