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This document is the users guide to using the Screening and Evaluation Tool (SET). SET is a tool for comparing multiple fuel cycle options against a common set of criteria and metrics. It does this using standard multi-attribute utility decision analysis methods.
A method to identify the hydrostratigraphic location of well screens was developed using triangulation with known locations. This method was applied to all of the monitor wells being used to develop the new GSA groundwater model. Results from this method are closely aligned with those from an alternate method which uses a mesh surface.
Rhodium is the most extensively used metal in catalytic applications; it occurs in mixed ores with platinum group metals (PGMs) in the earth’s crust in low concentrations (0.4 - 10 ppb). It is resistant to aerial oxidation and insoluble in all acids, including aqua regia, making classical purification methods time-consuming and inefficient. To ensure adequate purity, several precipitation and dissolution steps are necessary during separation. Low abundance, high demand, and extensive processing make rhodium the most expensive of all PGMs. From alternative sources, rhodium is also produced in sufficient quantities (0.47 kg per ton initial heavy metal (tIHM)) during the fission of U-235 in nuclear reactors along with other PGMs (i.e., Ag, Pd, Ru). A typical power water reactor operating with UO 2 fuel after cooling can generate PGMs in quantities greater than found in the earth’s crust (0.5-2 kg/tIHM). This currently untapped supply of PGMs has the potential to yield $5,000-30,000/tIHM. It is estimated that by the year 2030, the amount of rhodium generated in reactors could exceed natural reserves. Typical SNF processing removes the heavier lanthanides and actinides and can leave PGMs at ambient temperatures in aqueous acidic (Cl⁻ or NO 3 ⁻; pH < 1) solutions at various activities. While the retrieval of these precious metals from SNF would minimize waste generation and improve resource utilization, it has been difficult to achieve thus far. Two general strategies have been utilized to extract Rh(III) from chloride media: ion pairing and coordination complexation. Ion pairing mechanisms have been studied primarily with the tertiary and quaternary amines. Additionally, mixed mechanism extractions have been observed in which ion pairing is the initial mechanism, and longer extraction equilibrium time generated coordination complexes. Very few coordination complexation extraction ligands have been studied. This project approached this problem through the design of a software program that uses state-of-the-art computational combinatorial chemistry, and is developed and validated with experimental data acquisition; the resulting tool allows for rapid design and screening of new ligands for the extraction of precious metals from SNF. This document describes the software that has been produced, ligands that have been designed, and fundamental new understandings of the extraction process of Rh(III) as a function of solution phase conditions (pH, nature of acid, etc.).
During the course of International Atomic Energy Agency (IAEA) inspections, many samples are taken for the purpose of verifying the declared facility activities and identifying any possible undeclared activities. One of these sampling techniques is the environmental swipe sample. Due to the large number of samples collected, and the amount of time that is required to analyze them, prioritizing these swipes in the field or upon receipt at the Network of Analytical Laboratories (NWAL) will allow sensitive or mission-critical analyses to be performed sooner. As a result of this study, technologies were placed into one of three categories: recommended, promising, or not recommended. Both neutron activation analysis (NAA) and X-ray fluorescence (XRF) are recommended for further study and possible field deployment. These techniques performed the best in initial trials for pre-screening and prioritizing IAEA swipes. We learned that for NAA more characterization of cold elements (such as calcium and magnesium) would need to be emphasized, and for XRF it may be appropriate to move towards a benchtop XRF versus a handheld XRF due to the increased range of elements available on benchtop equipment. Promising techniques that will require additional research and development include confocal Raman microscopy, fluorescence microscopy, and infrared (IR) microscopy. These techniques showed substantive responses to uranium compounds, but expensive instrumentation upgrades (confocal Raman) or university engagement (fluorescence microscopy) may be necessary to investigate the utility of the techniques completely. Point-and-shoot (handheld) Raman and attenuated total reflectance–infrared (ATR-IR) measurements are not recommended, as they have not shown enough promise to continue investigations.
Four imaging papers are described:1. Kodak Linagraph 1895 2. GEX Radiation Indicator 3. Gafchromic XR-QA2 4. PFG screen Although other products exist, these are the most commonly available and generally useful for “beam finding” at beamlines. Characteristics of each are described below.
Primary Hazard Screening (PHS) Documents (PHS Lists of Radiological Facilities_R01) for OIG audit in FY18.
This Final Technical Report gives a brief overview of the apparatus upgrades, experimental results, and theory development which was funded by DOE grant DE-SC0008693 from 1-Aug-2012 to 31-Jul-2018. Experiments were performed on the "IV" apparatus, which contains un-neutralized Mg+ ion plasmas in a 3.Tesla magnetic field, with sophisticated laser diagnostics and control. The apparatus upgrade utilized a 4-channel absolute WaveMeter, with feedback control to stabilize the laser frequencies, enabling ultra-cold, highly-correlated plasma states. The Saltpeter enhancement of collisionality due to plasma correlations was verified experimentally, ruling out competing "dynamical screening" theories. This represents the only quantitative experimental tests of the Saltpeter enhancement, which is incorporated into all models of stellar nucleosynthesis. In closely related work, quantitative measurements of cyclotron modes for majority and minority ion species were obtained, verifying the theoretically-predicted dependence on the plasma electric field. Substantial experimental and theoretical work was devoted to understanding the (parametric) decay of large-amplitude plasma waves into longer-wavelength plasma waves. Here, there are simple "fluid theory" predictions, but the experimentally observed (dominant) process depends on subtle "kinetic" effects due to particles trapped in the wave-fields. The theory of this novel instability was augmented by several types of simulations, which are in broad agreement with the experiments. This research formed the basis for two Ph.D. theses, and also included undergraduate trainees. A list of journal publications is provided, in which the detailed scientific results are described.
Sandia National Laboratories and The Regents of the University of California, on Behalf of its Los Angeles Campus will collaboratively engage in the development of arrayed formatted genomic screening libraries based on CRISPR genome-editing technology. The effort will create libraries intended for use by the scientific community in research that includes therapeutic target discovery and comprehensive pathogen-host interaction analysis of agents of national security interest.
This document describes the underlying theory and use of a computer code written to simulate scintillation effects on propagating electromagnetic (EM) signals. The Multiple Phase Screen (MPS) technique [1, 2, 3, 4] is employed to model the effects of scintillation on EM signals as they travel through the earth’s ionosphere.
Current radiological surveys (exposure rate measurements and smear surveys) conducted outside the University of Washington (UW) Harborview Research and Training building found no evidence of Cs-137 contamination in public walk ways, or open areas, and preliminary soil concentrations from samples upwind and downwind of the building were within global fallout levels found in the region. Additional soil and outdoor surface sampling is being considered to more fully assess the possibility of an environmental release during the incident and the radiological impact, if any. This analysis is designed to assist in the evaluation of soil sample results and provide radiation dose-based Soil Screening Levels (SSLs) to help develop sampling and analysis plans and for evaluating these measurements in the context of radiation dose limits. Soil samples could be used to answer two general questions. The first asks if any detected Cs-137 in the soil is above global fallout levels measured in the area. Calculations based on fallout levels from Beck and Bennett (2002) and NCRP 154 suggest that current global fallout levels in Seattle area soil would range up to about 3 pCi/g in undisturbed soils, but there would be large variations based on a variety of transport factors related to the urban environment surrounding the area. Based on the sample result, any measurement significantly above background could prompt additional analysis including looking at the ratio of the Cs-137 to Pu-239/240 to help identify the source of the Cs-137, that is, from global fallout or from the incident. The second question is if there is detectable Cs-137 in the soil, what is the radiological impact of the Cs-137? For this, a dose pathway analysis using the RESRAD model was done to protectively estimate soil-based dose conversion factors and SSLs for Cs-137 in soil.
Methods for processing recorded data and efficiently screening experimental results from ducted fuel injection (DFI) experiments for soot mitigation in diesel engines are described. Specifically, a method for locating the spray tip in natural luminosity movies is detailed. DFI implementations are analyzed and are seen to significantly lower soot levels.
In this annex to a previously reported study, a series of laboratory screening tests was conducted to identify low-temperature glasses that have significant potential for use in disposition of technetium from a Hanford Tank Waste Treatment & Immobilization Plant (WTP) secondary liquid waste stream. Specifically, a glass waste form is sought that would be suitable for on-site disposition of technetium, salts, and other species in a Tc-rich stream recovered by ion exchange from the future Effluent Management Facility (EMF) evaporator concentrate. In the current study, several additional candidate glasses were identified, and testing of previous candidates was extended to include the Toxicity Characteristic Leaching Procedure (TCLP). In non-radioactive testing with rhenium surrogate, new formulations incorporated a simulated ion exchange eluate at temperatures below 750 °C to produce an amorphous, or mixed crystalline-amorphous, product. Incorporation of technetium (NaTcO 4 )-containing simulated eluate was evaluated for two of these glasses. Technetium was not retained well in these glasses, confounding the previous conclusion that Tc volatilization during vitrification can be reduced by appropriate selection of low-temperature glasses. Preliminary data for additional low-temperature glass compositions and recommendations for future work are provided. This report is a deliverable associated with requisition 55068-004-03 NFE-17-0020 "Candidate Low-T Glass Waste Forms for EMF Bottoms On-Site Disposition Alternative."
Background for TRL 0-1 Research: we require a simple regional source discriminant that has a predictive capability and a quantifiable screening performance (probability of correct attribution); Challenge: many local and near-regional source discriminants do not test source mechanism; rather, they test depth. Such empirically validated discriminants are not all theoretically justified; and, Proposal: we test Rayleigh wave radiation patterns for any significant deviation from circular shape as a discriminant.
We have made significant progress toward the development of an integrated nucleic acid amplification system for Autonomous Medical Devices Incorporated (AMDIs) Optikus handheld diagnostic device. In this effort, we developed a set of loop-mediated isothermal amplification (LAMP) primers for SARS-CoV-2 and then demonstrate amplification directly on a surface acoustic wave (SAW) sensor. We built associated hardware and developed a C-code to control the amplification process. The goal of this project was to develop a nucleic amplification assay that is compatible with SAW sensors to enable both nucleic and serological testing in a single handheld diagnostic device. Toward this goal, AMDI is collaborating Sandia National Laboratories to develop a rapid, portable diagnostic screening device that utilizes Sandias unique surface acoustic wave biosensor (SAW) for COVID-19 detection. Previously, the SANDIA- AMDI SAW sensor has successfully detected multiple high-profile bacteria viruses, including Ebola, HIV, Sin Nombre, and Anthrax. Over the last two years, AMDI and SANDIA have significantly improved the sensitivity and detection capability of the SAW biosensor and have also developed a modular hand-held, portable platform called the Optikus, which uses CD microfluidics and handheld instrumentation to automate all sample preparation, reagent introduction, sample delivery, and measurement for a number of different assay targets. We propose to use this platform for the development of a rapid (%3C30 minutes), point-of-care diagnostic test for detection of COVID-19 from nasal swab samples.
Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.
Machine learning can be used to screen millions of compounds and unearth relationships between electronic structure, chemistry, thermodynamic stability, formability and band gap. We know how to calculate thermodynamic stability and calculate approximate band gap, but it is very complicated to estimate synthesizability.
The Regional Resiliency Assessment Program (RRAP) is a cooperative assessment of specific critical infrastructure within a designated geographic area and a regional analysis of the surrounding infrastructure that addresses a range of infrastructure resilience issues that could have regionally and nationally significant consequences. In 2018, DHS’s Cybersecurity and Infrastructure Security Agency (CISA) sponsored the Oregon Transportation Systems RRAP project in coordination with the Office of the Governor (under the oversight of the state resilience officer), the Oregon Office of Emergency Management (OEM), the Oregon Department of Transportation (ODOT), and other regional stakeholders (CISA 2021). This project focuses on assessing the impacts of a Cascadia Subduction Zone (CSZ) earthquake on state transportation systems and, in particular, how those impacts may affect the ability of emergency response efforts to move supplies into the region. The intended outcome of this analysis is the prioritization of transportation routes and modes for additional planning, investment, hardening, or other activities to enhance their resilience—and therefore, to enhance their ability to support response and recovery efforts following a CSZ earthquake. An important part of this transportation system-level assessment has been to assess the seismic vulnerability of the state highway system. In doing so, the RRAP project team used the Bridge Seismic Screening Tool (BSST) to assess, at a system-level, the potential impacts that a CSZ earthquake could have on state highway bridges (Bergerson et al. 2019).1 Argonne National Laboratory (Argonne), in collaboration with the Washington State Department of Transportation (WSDOT), originally developed the BSST as part of the 2017 Washington State Transportation Systems RRAP project, a sister project to the 2018 Oregon Transportation Systems RRAP project. Argonne updated the BSST during this more recent project in Oregon based on feedback from stakeholders and subject matter experts (SMEs) on the original version of the tool. The first step in the BSST is to assess the seismic vulnerability of roadway bridges following a CSZ earthquake to determine a projected or potential damage state. Damage states then help determine approximate reopening times for bridge crossings.2 This document provides details on the BSST methodology, the implementation of that tool to analyze the projected damage incurred in a CSZ earthquake scenario, and the determination of corresponding reopening times of interstate, state highway, and local bridges following such an event.
The purpose of this environmental calculation file (ECF) is to document the assumptions, inputs, methodology, equations, and results of a screening level ecological risk assessment (SLERA) conducted for eight of 12 representative waste sites within the newly formed 200 IA-1 Operable Unit (OU); the remaining four waste sites lacked soil data within the shallow vadose zone and were not further evaluated. The SLERA was conducted to evaluate ecological receptor exposure and potential risk using soil data for radionuclides and nonradionuclides occurring within the shallow vadose zone (0 to 15 ft) soil of the OU. The representative Hanford ecological receptors evaluated are: plants, soil invertebrates, California quail (Callipepla californica), Meadowlark (Sturnella neglecta), Killdeer (Charadrius vociferus), Red-tailed hawk (Buteo jamaicensis), Great Basin pocket mouse (Perognathus parvus), Deer mouse (Peromyscus maniculatus), Grasshopper mouse (Onychomys leucogaster), and badger (Taxidea taxus). During the SLERA, detected soil sample results from the shallow vadose zone were used to calculate Hazard Quotients (HQs) for nonradionuclides and Sum of Fractions (SOF) for radionuclides. The results of this SLERA support the preparation of DOE/RL-2020-51, 200-IA-1 Operable Unit Focused Feasibility Study.