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At least 595 records · Page 33

Statistical analysis of the Nb 3 Sn strand production for the ITER toroidal field coils

The ITER toroidal field (TF) strand procurement initiated the largest Nb 3 Sn superconducting strand production hitherto. The industrial-scale production started in Japan in 2008 and finished in summer 2015. Six ITER partners (so-called Domestic Agencies, or DAs) are in charge of the procurement and involved eight different strand suppliers all over the world, of which four are using the bronze route (BR) process and four the internal-tin (IT) process. In total more than 500 tons have been produced including excess material covering losses during the conductor manufacturing process, in particular the cabling. The procurement is based on a functional specification where the main strand requirements like critical current, hysteresis losses, Cu ratio and residual resistance ratio are specified but not the strand production process or layout. We introduce the analysis on the data acquired during the quality control (QC) process that was carried out to ensure the same conductor performance requirements are met by the different strand suppliers regardless of strand design. The strand QC is based on 100% billet testing and on applying statistical process control (SPC) limits. Throughout the production, samples adjacent to the strand pieces tested by the suppliers are cross-checked ('verified') by their respective DAs reference labs. The level of verification was lowered from 100% at the beginning of the procurement progressively to approximately 25% during the final phase of production. Based on the complete dataset of the TF strand production, an analysis of the SPC limits of the critical strand parameters is made and the related process capability indices are calculated. In view of the large-scale production and costs, key manufacturing parameters such as billet yield, number of breakages and piece-length distribution are also discussed. Furthermore, the results are compared among all the strand suppliers, focusing on the difference between BR and IT processes. Following the completion of the largest Nb 3 Sn strand production, our experience gained from monitoring the execution of the QC activities and from auditing the results from the measurements is summarised for future superconducting strand material procurement activities.

Vostner, A.↗

Direct SERDS sensing of molecular biomarkers in plants under field conditions

Molecular biomarkers such as microRNAs (miRNAs) play important roles in regulating various developmental processes in plants. Understanding these pathways will help bioengineer designing organisms for efficient biomass accumulation. Current methods for RNA analysis require sample extraction and multi-step sample analysis, hindering work in field studies. Recent work in the incorporation of nanomaterials for plant bioengineering research is leading the way of an agri-tech revolution. As an example, surface-enhanced Raman scattering (SERS)–based sensors can be used to monitor RNA in vivo. However, the use of SERS in the field has been limited due to issues with observing Raman signal over complex background. To this end, shifted-excitation Raman difference spectroscopy (SERDS) offers an effective solution to extract the SERS signal from high background based on a physical approach. In this manuscript, we report the first application of SERDS on SERS sensors. We investigated this technique on SERS sensor developed for the detection of a microRNA biomarker, miR858. We tested the technique on in vitro samples and validated the technique by detecting the presence of exogenous miR858 in plants directly under ambient light in a growth chamber. The possibility of moving the detection of nucleic acid targets outside the constraints of laboratory setting enables numerous important bioengineering applications. Finally, such applications can revolutionize biofuel production and agri-tech through the use of nanotechnology-based monitoring of plant growth, plant health, and exposure to pollution and pathogens.

09 BIOMASS FUELS↗

Enhanced Magnetic Levitation and Guidance Force in MgB{sub 2} Bulks by Synthetic Engine Oil Immersion

We have used ‘Synthetic engine oil’ as a rich easily accessible carbon source and investigated the effect of engine oil on the microstructure, critical current density (J{sub c}), vertical levitation force (F{sub z}) and guidance force (F{sub x}) properties of MgB{sub 2} superconductor. The polycrystalline disk-shaped MgB{sub 2} bulk samples have been prepared using two-step solid-state reaction process. After the first heating process, MgB{sub 2} bulk samples immersed in the engine oil for different durations (30, 120, 300 and 1440 min). XRD analysis indicated the decreasing of lattice parameters of samples and confirmed C substitution in boron sites. Vertical levitation and guidance force measurements were carried out with both Field-cooling (FC) and zero-field-cooling (ZFC) regimes at different temperatures of 20, 24 and 28 K. It was found that engine oil addition slightly increases the levitation and guidance force properties. The F{sub z} values were obtained as 11.17 and 11.58 N for pure and MgB{sub 2} sample immersed for 30 min at 20 K in ZFC regime. In addition, the MgB{sub 2} sample immersed for 300 min in engine oil showed the highest J{sub c} value of 5.3×10{sup 4} A cm{sup − 2} at 15 K and self-field and showed the highest guidance force value of 4.14 N at 20 K. These finding suggest that synthetic engine oil is a cost-effective and promising method to improve the levitation and guidance force performance as well as the critical current density of MgB{sub 2} bulk superconductor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantifying Phospholipids in Organic Samples Using a Hydrophilic Interaction Liquid Chromatography–Inductively Coupled Plasma High-Resolution Mass Spectrometry (HILIC-ICP-HRMS) Method

Here, in this study, a novel method using hydrophilic interaction liquid chromatography (HILIC) coupled with inductively coupled plasma high-resolution mass spectrometry (ICP-HRMS) was introduced for the quantification of phospholipids in oil samples. The method employed a bridged ethyl hybrid (BEH) stationary phase HILIC column with a tetrahydrofuran (THF)/water mobile phase, enhancing the solubility and detection of phospholipids. During the study, a gradient/matrix effect on ICP-HRMS sensitivity was observed and successfully compensated for experimentally, ensuring reliable quantification results. This approach has proven effective for a wide range of different oil samples including vegetable oils, animal fats, and phospholipid supplements. Notably, this method allowed the direct quantification of phospholipids in oil samples, bypassing the need for prior sample preparation methods, such as solid phase extraction (SPE), thereby streamlining the analytical process. The precision, accuracy, and reduced need for extensive sample preparation offered by this method mark a significant advancement in lipids analysis. Its robustness and broad applicability have substantial implications for industries such as food and renewable energy production, where both efficient and accurate lipid identification and quantification are crucial.

09 BIOMASS FUELS↗

In situ Raman spectroscopy for growth monitoring of vertically aligned multiwall carbon nanotubes in plasma reactor

Portable and highly sensitive Raman setup was associated with a plasma-enhanced chemical vapor deposition reactor enabling in situ growth monitoring of multi-wall carbon nanotubes despite the combination of huge working distance, high growth speed and process temperature and reactive plasma condition. Near Edge X-ray absorption fine structure spectroscopy was used for ex situ sample analysis as a complementary method to in situ Raman spectroscopy. The results confirmed the fact that the “alternating” method developed here can accurately be used for in situ Raman monitoring under reactive plasma condition. The original analytic tool can be of great importance to monitor the characteristics of these nanostructured materials and readily define the ultimate conditions for targeted results.

36 MATERIALS SCIENCE↗

Analytical capabilities for iodine detection: Review of possibilities for different applications

This Review summarizes a range of analytical techniques that can be used to detect, quantify, and/or distinguish between isotopes of iodine (e.g., long-lived 129 I, short-lived 131 I, stable 127 I). One reason this is of interest is that understanding potential radioiodine release from nuclear processes is crucial to prevent environmental contamination and to protect human health as it can incorporate into the thyroid leading to cancer. It is also of interest for evaluating iodine retention performances of next-generation iodine off-gas capture materials and long-term waste forms for immobilizing radioiodine for disposal in geologic repositories. Depending upon the form of iodine (e.g., molecules, elemental, and ionic) and the matter state (i.e., solid, liquid, and gaseous), the available options can vary. In addition, several other key parameters vary between the methods discussed herein, including the destructive vs nondestructive nature of the measurement process (including in situ vs ex situ measurement options), the analytical data collection times, and the amount of sample required for analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Geometrical-Based Generative Adversarial Network to Enhance Digital Rock Image Quality

X-ray microcomputed tomography (micro-CT) is a common tool for the study of porous media structures and properties. High-quality micro-CT data are required to accurately capture pore structures. Acquiring high-quality micro-CT data, however, is not always possible, owing to application limitations and experimental constraints. Therefore, we propose a geometrical-based generative adversarial network (GAN) to rapidly restore noisy micro-CT images to their clean counterparts. The training data and related ground-truth (GT) data are scanned for 7 min and 9.5 h, respectively. To evaluate the performance of the geometrical-based GAN, a 6003 voxel image that has never been used for training is reconstructed and compared with the corresponding GT image. Histogram matching and linear normalization are implemented to adjust the histogram of the reconstructed image to that of the GT image. A watershed-based segmentation method is then applied to delineate pore and solid phases. Lastly, we measure the Minkowski functionals and petrophysical properties, including absolute permeability, pore size distribution, drainage capillary pressure-saturation curve, and imbibition relative permeability, to estimate the physical accuracy of the denoised image. The results show that the proposed geometrical-based GAN can accurately restore noisy micro-CT data. By reducing the scanning time from 9.5 h to 7 min, the expenditure of collecting micro-CT can be decreased significantly. This is particularly important for applications where time-lapse images of a dynamic process are required, high-throughput imaging is necessary for real-time data analysis, or where the quantification of large sample volumes is required.

58 GEOSCIENCES↗

Photoproduction of the Σ + hyperon using linearly polarized photons with CLAS

Measurements of the polarization observables Σ, P, T, O x , O z for the reaction $\vec{γ}$ p → $K^0_S$Σ + using a linearly polarized photon beam of energy 1.1 to 2.1 GeV are reported. The measured data provide information on a channel that has not been studied extensively, but is required for a full coupled-channel analysis in the nucleon resonance region. Observables have been simultaneously extracted using likelihood sampling with a Markov-Chain Monte Carlo process. Angular distributions in bins of photon energy E γ are produced for each polarization observable. T, O x , and O z are first time measurements of these observables in this reaction. The extraction of Σ extends the energy range beyond a previous measurement. The measurement of P, the recoil polarization, is consistent with previous measurements. The measured data are shown to be significant enough to affect the estimation of the nucleon resonance parameters when fitted within a coupled-channels model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Laser Powder Bed Fusion of Steels for Nuclear Applications

This report provides an update on laser powder bed fusion of steels for nuclear applications. This report is a Milestone 3 deliverable in FY2024, under work package CT-24AN130401 to support research and qualification activities supported by the Advanced Materials and Manufacturing Technologies (AMMT) program here at Argonne National Laboratory (ANL). Continuing from FY23, the focus of FY24 for ANL includes further optimization of process parameters for three alloys: A709, G91, G92. The work package also includes fabricating test samples to conduct a thorough microstructural analysis and perform preliminary mechanical testing. For the same, we have used CALPHAD-based thermodynamic kinetic modeling to optimize the experimental activities.

36 MATERIALS SCIENCE↗

Human Liver Epithelial Cells (HuH7) Response to HCoV-229E Infection Epigenomics (ATAC-Seq) (ACS-DP4)

The purpose of this experiment was to evaluate how wild-type Human coronavirus strain 229E (HCoV-299E) infection alters chromatin accessibility in infected cells. Sample data was obtained from mock-infected cells, UV-inactivated virus treated cells, and replication competent HCoV-229E infected immortalized human liver cells (HuH7) at 24 hours post infection. Samples were processed using ATAC-seq methods for reported bar coded libraries. Sample data was acquired using an Illumina Hi-Seq 2500 sequencer system and further processed for ATAC-Seq expression analysis.

59 BASIC BIOLOGICAL SCIENCES↗

System and method for structural characterization of materials by supervised machine learning-based analysis of their spectra

A method of supervised machine learning-based spectrum analysis information, using a neural network trained with spectrum information, to identify a specified feature of a given material, a system for supervised machine learning-based spectrum analysis, and a method of training a neural network to analyze spectrum data. The method of supervised machine learning-base spectrum analysis comprises inputting into the neural network spectrum data obtained from a sample of the given material; and the neural network processing the spectrum data, in accordance with the training of the neural network, and outputting one or more values for the specified feature of the sample of the material. In an embodiment, the training set of data includes x-ray absorption spectroscopy data for the given material. In an embodiment, the training set of data includes electron energy loss spectra (EELS) data.

Frenkel, Anatoly↗

Magnetic Barkhausen noise characterization of two pipeline steels with unknown history

Highlights: • The hardness, microstructure, texture and MBN of two pipeline steels were analyzed. • The angular MBN results revealed possible manufacturing histories of the two pipelines. • The MBN is closely related to the processing history, microstructure and stress state. • The use of MBN technique can help address the integrity issues in the pipeline industry. Steel samples cut from two line pipes with unknown processing history were analyzed using magnetic Barkhausen noise (MBN), electron backscatter diffraction (EBSD) and Vickers hardness techniques on the pipe surface and on sections through the wall thickness. The results show that the MBN responses vary significantly not only between the two pipe steels, but also among different thickness layers of each steel. Both steels show considerable variations in MBN at different locations on the surfaces. For one steel, the surface MBN illustrates an inverse linear relationship with respect to the hardness, while the other does not depict such a relation since the variation in hardness at different locations is very small. Across the thickness, the microstructure (phase and grain size) of both steels is quite similar, but the texture shows significant differences. Again, there is a large difference in hardness across the thickness for one steel, while the other only shows very small variation in hardness across the thickness. The variations in average MBN across the wall thickness for both steels are quite large. Angular MBN measurements on the sectioned samples revealed significant discrepancies in the magnetic anisotropy in the two steels. Based on the analysis of the angular MBN data with respect to the single and dual easy axis models, one pipe can be determined to have been manufactured through a seam welding process, while the other may have been formed by spiral welding. Due to the residual stresses in the steel samples, the effect of the crystallographic texture on the anisotropy in MBN response has essentially been suppressed.

36 MATERIALS SCIENCE↗

Improved uranium isotopic ratio determinations for the liquid sampling-atmospheric pressure glow discharge orbitrap mass spectrometer by use of moving average processing

The liquid sampling-atmospheric pressure glow discharge (LS-APGD) is a versatile combined atomic and molecular (CAM) ionization source capable of ionizing elemental species, small polar compounds, low-polarity polycyclic aromatic hydrocarbons, and proteins. While the LS-APGD has been proven capable of determining the 235U/238U isotope ratio in enriched and natural uranium, recent efforts have strived to reduce the analysis time of individual measurements by employing higher-order data processing techniques, specifically, moving average methods. Additionally, the use of a moving average (of data windows of various widths) improves the precision of the ratio measurements and reduces the number of scans needed to be collected to generate high-precision results. Additionally, use of the moving average minimizes the quantity of sample that needs to be analyzed while reducing the measurement time. These reductions have allowed isotope ratio (IR) determinations to be made using injections instead of direct infusion of the analyte. For example, employing a 40-point window width in the moving average to direct infusion data reduced the percent relative standard deviation (% RSD) of the 235U/238U values from 3.4% to 0.5%. For the injection of a 100 μL aliquot, the % RSD was reduced from 5.3% to 0.7%.

74 ATOMIC AND MOLECULAR PHYSICS↗

Raman Spectroscopy for the On Line Analysis of Oxidation States of Oxygen Carrier Particles

The need for cleaner energy systems, including CO 2 capture technologies, is driving the current development of new combustion approaches such as chemical looping combustion (CLC). This process is based on using oxygen carrier particles (OCPs) such as iron oxides, copper oxides, calcium sulfates, etc. to provide the oxygen for the combustion process. In order to optimize the overall process performance, it is critical that the properties of the oxygen carriers are well-defined and maintained for their specific purpose during the different stages of the CLC process. One of the critical properties of the oxygen carrier is its oxidation state (e.g., content of Fe 2 O 3 vs. Fe 3 O 4 ) as it affects the fundamental operation of the CLC process. Unfortunately, the ability to make on-line measurements of the oxidation state of oxygen carriers is lacking and new sensors need to be developed. Our goal is to develop a sensor for the on-line analysis of the oxidation state of oxygen carrier particles and to demonstrate its feasibility. Oxygen carrier particles (OCPs) of interest include iron oxides, copper oxides, and calcium sulfate, with particle sizes typically less than 0.5 mm diameter. The expected operating conditions of the sensor include OCP temperatures in the range of 800 °C to 1000 °C, and pressures of about 10 atm. The expected results are to be of a statistical nature, providing relative concentrations of the different oxidation states. These requirements make a strong case for using non-contact, stand-off, pulsed Raman spectroscopy as a sensor for the high-temperature on-line analysis of oxygen carrier particles. In order to achieve our goal, we have set up and tested a pulsed Raman spectroscopy system in combination with a pressurized high-temperature sample chamber, and have taking initial Raman spectra of various materials at high temperature. We are now in the process of optimizing the operating parameters such as laser wavelength, laser intensity, collection optic design, focal spot size, data acquisition, etc. We will also develop an analysis procedure for the interpretation of the Raman spectra. Typical Raman spectra consist of a convolution of background signal and multiple individual spectra. In order to extract relevant information such as the concentration ratio of a material in different oxidation states, we need to process (background subtraction, deconvolution, fitting, etc.) the measured data. In addition, statistical modeling and multivariate calibration need to be performed to correctly analyze the Raman spectra.

20 FOSSIL-FUELED POWER PLANTS↗

An Efficient Algorithm for Automatic Structure Optimization in X-ray Standing-Wave Experiments

We present that x-ray standing-wave photoemission experiments involving multilayered samples are emerging as unique probes of the buried interfaces that are ubiquitous in current device and materials research. Such data require for their analysis a structure optimization process comparing experiment to theory that is not straightforward. In this work, we present a new computer program for optimizing the analysis of standing-wave data, called SWOPT, that automates this trial-and-error optimization process. The program includes an algorithm that has been developed for computationally expensive problems: so-called black-box simulation optimizations. It also includes a more efficient version of the Yang X-ray Optics Program (YXRO) [Yang, S.-H., Gray, A.X., Kaiser, A.M., Mun, B.S., Sell, B.C., Kortright, J.B., Fadley, C.S., J. Appl. Phys. 113, 1 (2013)] which is about an order of magnitude faster than the original version. Human interaction is not required during optimization. We tested our optimization algorithm on real and hypothetical problems and show that it finds better solutions significantly faster than a random search approach. The total optimization time ranges, depending on the sample structure, from minutes to a few hours on a modern laptop computer, and can be up to 100x faster than a corresponding manual optimization. Finally, these speeds make the SWOPT program a valuable tool for realtime analyses of data during synchrotron experiments.

36 MATERIALS SCIENCE↗

Rapid processing of 85 Kr/Kr ratios using Atom Trap Trace Analysis

In this paper, we report a methodology for measuring 85 Kr/Kr isotopic abundances using Atom Trap Trace Analysis (ATTA) that increases sample measurement throughput by over an order of magnitude to six samples per 24 h. The noble gas isotope 85 Kr (half-life = 10.7 years) is a useful tracer for young groundwater in the age range of 5–50 years. ATTA, an efficient and selective laser-based atom counting method, has recently been applied to 85 Kr/Kr isotopic abundance measurements, requiring 5–10 μL of krypton gas at STP extracted from 50 to 100 L of water. Previously, a single such measurement required 48 h. In conclusion, our new method demonstrates that we can measure 85 Kr/Kr ratios with 3–5% relative uncertainty every 4 h, on average, with the same sample requirements.

54 ENVIRONMENTAL SCIENCES↗

Robust Solar Receivers Using MAX Phase Materials

This work was supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy under the Solar Energy Technologies Office Award Number 35928. The objective of the proposed effort was to develop and optimize additive manufacturing technologies for low-cost fabrication of high-temperature receivers using MAX phase-based materials (Ti 3 SiC 2 and Ti 3 AlC 2 ). MAX phase materials are a group of ternary metal carbides and nitrides where M stands for an early transition metal element, A is a group 13–16 element, and X is C and/or N. In Phase 1, the binder jetting additive manufacturing process was used to synthesize and characterize the Ti 3 SiC 2 MAX phase material. The typical process involved first producing a TiC preform using binder jetting followed by infiltration of the preform with silicon melt to form Ti 3 SiC 2 in situ. The reaction-infiltrated samples showed formation of MAX phase in the sample core; however, the surface showed cracking. Various process conditions—cooling rates, hold times, Si proportion, etc.—were varied to minimize the surface cracking. The fabricated MAX phase core was characterized by microstructure analysis and evaluations of mechanical properties such as hardness and thermal shock. In Phase 2, the focus included fabrication of Ti 3 SiC 2 MAX phase materials by spark plasma sintering (SPS) and synthesis of Ti 3 AlC 2 MAX phase materials by the Al melt infiltration process. It is expected that Al infiltration will not cause sample cracking, since Al does not expand during solidification. In addition, other processing approaches were investigated to fabricate the MAX phase materials, such as SPS with a graphite bedding approach for producing short-length Ti 3 AlC 2 MAX phase tubes for demonstration of prototypical Concentrating Solar Power receiver tubes. Fabricated samples underwent thermo-mechanical testing to validate the materials for the solar receiver application at temperatures >1000°C. In Phase 3, the effort focused on the development and optimization of the Ti-Al-C MAX phase composite material using the Al melt infiltration approach. We started with optimization of precursor powders and making preform structures by either pressing them in a die or using the binder jetting additive manufacturing process followed by Al melt infiltration. In addition, we investigated the formation of preform structures by cold isostatic pressing followed by Al melt infiltration for making Ti-Al-C MAX phase composite. Thermo-mechanical characterizations, such as creep, strength, and thermal shock, were conducted to establish the structures’ performance.

36 MATERIALS SCIENCE↗

Distribution Development for Residual Inventory at the New York West Valley Site - 20400

The New York State Energy Research and Development Authority (NYSERDA) is the owner of the Western New York Nuclear Service Center (WNYNSC), a 1,351 ha site located approximately 48 km south of Buffalo, New York. In 1962, Nuclear Fuel Services, Inc. (NFS) entered into Agreements with the Atomic Energy Commission and New York State to construct the first commercial reprocessing plant of nuclear fuel in the United States. NFS, a private company, built and operated the spent fuel reprocessing plant and waste disposal facilities, processing 640 Mg of spent nuclear fuel from 1966 to 1972 under an Atomic Energy Commission license. Nuclear fuel reprocessing operations ended in 1972 and never reopened, leaving behind radioactive and chemical wastes. Operations led to contamination in a number of facilities and locations. Some of that contamination has migrated from waste disposal zones to other layers, formations, and features on and off the WNYNSC. Phase I decommissioning activities are ongoing and involve the removal of a number of areas and structures that have been associated with contamination. The purpose of this work is to outline the approach for characterizing contamination not associated with disposed wastes, contaminated structures, or specific releases. In this work, the term, residual radiological activity, is used to describe environmental contamination that exists subsequent to the completion of Phase I decommissioning activities, that is not associated with disposed wastes, contaminated structures, or specific releases. Contamination from the Site was quantified relative to data that characterize the concentrations of radionuclides that exist in background. Background concentrations are those present in the area but having no influence from Site related activities. The existence of residual radiological activity that is elevated relative to background has the potential to contribute to future risks to human health and the environment. As a consequence, the residual inventory information is used to inform the West Valley Probabilistic Performance Assessment (PPA) model to characterize potential future risks to human health and the environment. The centralized West Valley Data Management System (DMS) was the source of information for the data assembled in this analysis. The DMS is a fairly large compilation consisting of thousands of records from investigation studies, with sample dates ranging from 1990 to present. Samples from monitoring wells, boreholes, geoprobe studies, surface water, surface soils, storm water outfalls, ventilation stack filters, plant and animal tissues, and more are included in the DMS. Results are typically reported in units of activity per unit volume. For the purpose of the analyses presented here, all results were converted into consistent units of pCi per unit volume. Since 1990, data have been collected from various locations across the WNYNSC at different times with varying frequency over the course of several decades. As a consequence, a number of potential issues can arise with respect to the assembly of a dataset that is deemed adequate for the characterization of residual radiological activity. These issues were assessed and resolved to the extent possible through careful consideration of the properties of the distributions. The intent was to use data which characterize the current state of the Site. Radionuclides can be designated to one of several groups depending on their origin. In this work the groups considered were 1) Naturally Occurring Radioactive Material (NORM), 2) fallout, and 3) Other (including power plant, medical research, etc). This grouping is a useful construct with respect to the interpretation of fixed laboratory results. For example, NORM radionuclides that exist within a decay chain should have approximately equivalent distributions of concentrations if they are representative of background conditions. Insights such as these can be used as a check to identify sample results that need to be further investigated or omitted due to issues associated with reported results from fixed laboratory analyses. This type of analysis provided a foundation for the assessment of the adequacy of sample results for use in subsequent components of an assessment. The general process for the assessment of residual radiological contamination at the Site consists of a sequence of several steps. First, for each analyte, several statistical tests were performed to assess the weight of evidence against the null hypothesis that the mean of the distribution of concentrations was equal to zero. If the mean of the distribution of concentrations for a given radionuclide was not found to be greater than zero, then it was removed from consideration as a component of the residual radiological contamination. If there was significant evidence to reject the hypothesis of the mean being equal to zero, the second step was to compare the distribution of the data from the Site to that of the corresponding background. A suite of tests was used to compare the distributions of the site and background data. The results of these tests were collectively used to determine if site data are elevated relative to background. The third step was to develop distributions using a Bayesian framework to characterize the distribution of mean of the increment present above background for each of the radionuclides. The Bayesian model implemented allowed for the comparison of site-specific records to background concentrations to better approximate contamination attributed to the Site. A final screening step was employed for radionuclides that exceed background. This screening step compared 95% upper confidence limits (UCLs) from the increment distribution developed in the previous step to the risk screening levels. This approach yields a list of analytes that were determined to be elevated relative to background.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗