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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Development and Comparison of Purgeable Mercury Values in SRR Samples Measured by SRNL and Eurofins FGS

Savannah River Remediation (SRR) requested the development of mercury speciation capabilities at the Savannah River National Laboratory (SRNL) to support the Liquid Waste Operations at SRS. As part of that method development, SRR requested that SRNL Analytical Development (AD) compare their results with those obtained from their outside contract laboratory, Eurofins Frontier Global Sciences (FGS). This document reports on this method development work as well as the comparative analyses conducted between the two laboratories. Development, optimization, and validation were undertaken at SRNL to produce a method for the species-specific analysis of dissolved gaseous mercury (DGM) in samples from SRR. It was determined that DGM present in SRR samples represented a combination of various soluble and volatile mercury species- and is thus referred to in this document as purgeable mercury. A method has been developed and analytically validated for the analysis of purgeable mercury in caustic nuclear waste. Using multivariate optimization method, purge flow rate was determined to be highly correlated with increased response (p=0.023). Total recovery of spiked purgeable mercury from deionized water was 99.4 ±10.6% and 91.6 ±14.9% from spiked high-activity tank waste samples. Calibration, by external calibration and standard addition calibration, maintained a mean accuracy of 101 ±5% and 99.9 ±1.7%, respectively. This method represents a decrease in sample handling and processing over currently standard methods and represents a more amenable method for purgeable mercury analysis in liquid nuclear waste.1 An interlaboratory comparison was performed between SRNL and Eurofins FGS in the co-analysis of three quarterly Tank 50 samples. Two samples demonstrated no statistically significant difference (p=0.271, p=0.0811), with one sample biased 30% low to a statistically significant degree (p=0.0432). Large mean uncertainty was present in the results reported by both laboratories (±15% and 40% from SRNL and Eurofins), with no significant difference observed in uncertainty (p=0.934). Across all co-analyzed samples, no significantly difference was observed in precision (p=0.205) or reported values (p=0.352) between SRNL and Eurofins. These results indicate that SRNL-AD may provide data to the customer of statistically similar quality.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Enhancement of Structural Health Monitoring Framework by Optimizing Vibro-Acoustic Modulation Technique to Localize Alkali-Silica Reaction Degradation in Medium-Sized Concrete Samples

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Health monitoring of concrete structures is performed to understand the current condition of a structure based on heterogeneous measurements and then produce high confidence actionable information regarding structural integrity. This information can then be used to support operational and maintenance decisions. The objectives of this ongoing research project focus on health monitoring and data analytics of concrete slabs containing reactive aggregates and thus subjected to degradation due to alkali-silica reaction (ASR). A controlled concrete slab with four pockets of reactive aggregates (pure silica, wells, placitas, and spratt) was cast at Vanderbilt University and cured in representative conditions to accelerate degradation due to ASR. A set of four concrete samples were also cast and cured at the University of Alabama for ASR testing. Of these four samples, two slabs contained reactive aggregates while the other two had the non-reactive aggregate counterparts mixed throughout the samples. Vibro-acoustic methods were used on these slabs to locate large pockets of ASR within the reactive samples and determine the effects of rebar using the non-reactive slabs. Vibro-acoustic modulation (VAM) is a vibration-based NDE method that utilizes signatures of nonlinear dynamic interactions on contact surfaces of crack or delamination damage to detect and localize the damage. VAM analysis was conducted on both Vanderbilt and Alabama’s samples using multiple variables for damage detection and localization. The results from the data analysis of the NDE vibro-acoustic techniques on concrete slabs cured at Vanderbilt University and the University of Alabama are discussed in detail in this report. The major outcome of the analysis suggests that the VAM method can be used to detect damage within the concrete samples by comparing the results found in different sections of the samples. Results for damage localization are dependent on multiple variables used in the vibro-acoustic modulation experiments. Digital image correlation (DIC) is a three-dimensional, full-field, optical NDE technique to measure contour, deformation, vibration, and strain. The application of the digital image correlation technique to study ASR-related degradation on a large concrete sample at the University of Tennessee Knoxville is discussed and observations are presented in this report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Partial completion of post-irradiation examination of the ORNL samples

A total of six Grade 92 and two 800H samples were identified and secured as the selected ORNL samples, which were irradiated in the High Flux Isotope Reactor (HFIR) of ORNL to 0.46–14.66 dpa at 400 to ~720°C. The Grade 92 is an optimized heat and named as G92-2b. The two 800H samples have one sample as the standard solution-annealed condition and the other sample as a thermos-mechanically processed (TMP) condition with a maximized fraction of low-Σ coincidence site lattice (CSL) boundaries. Tensile tests were completed for the selected ORNL samples using the Irradiated Materials Examination and Testing (IMET) hot cell facility at ORNL. The G92-2b samples were tested at room temperature. The lower temperature irradiation at 400–496.7°C to 0.52–14.66 dpa resulted in minimal changes in tensile properties. However, the higher temperature irradiation at ~683.3–720°C to 0.46–14.63 dpa tended to reduce yield and tensile strength by about –136 to –311 MPa and plastic elongation with the increasing dose. The 800H and 800H-TMP samples were tensile-tested at their irradiation temperature 580°C, which showed >40% increase in yield and tensile strength with nearly 9% reduction in elongation for 800H-TMP compared with 800H.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Tank 22 Settled Sludge Core Sample Characterization and Testing

The Savannah River National Laboratory (SRNL) was requested by Savannah River Remediation (SRR) Engineering (SRR-E) to provide sample characterization and analyses of Tank 22 settled sludge core sample and the supernatant liquids (supernate) in support of Tank 22 re-baseline data, inhalation dose potential/hydrogen generation and suspension/removal of settled sludge from the bottom of Tank 22. The approximately 9.5 inches of intact Tank 22 core sample from SRR-E, after extrusion in the SRNL Shielded Cells, showed three visually different stratification layers or regions of solids in the extruded core material. Part of the initial physical characterization of these three segments of the Tank 22 core sample included density, weight percent total solids, particle size distribution, X-ray diffractions and scanning electron microscope of each segment material. Given the dissimilarity of the three Tank 22 segment materials after the physical characterization results and the fact that there was no clear line of demarcation to indicate where each segment began and ended across the entire length of the core sample, SRNL in conjunction with the SRR-E customer decided to blend all three segments of the material to form a composite Tank 22 core sample for further analysis and characterization without taking into consideration the proportional weight or mass contribution of each segment. This compositing approach assumes that the errors introduced in any characterization of the Tank 22 core sample will be comparable to the errors when the three segments are separated and combined proportionally by weight to form the composite Tank 22 sample. This compositing approach maximized the quantity of composited Tank 22 material needed for radionuclide and other physical characterizations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Summary of Analytical Results from Samples Supporting Tank Closure Cesium Removal (TCCR) Batch 3 and Modeling Results for Cs Loading on CST

Savannah River Remediation (SRR) is currently operating the Tank Closure Cesium Removal (TCCR) process to remove 137 Cs from tank waste supernate using an ion exchange process. As part of that process, Savannah River National Laboratory (SRNL) receives and analyzes samples in support of the qualification of each batch to be processed. SRNL recently received supernate samples retrieved from Tank 10H as well as in-tank batch contact samples for characterization in support of qualifying Batch 3 for processing through the TCCR unit. Some results from analysis of those samples have been previously reported. This report documents the remaining analyses of the in-tank batch contact samples as well as the results of ZAM (Zheng, Anthony, Miller) isotherm modeling performed for comparison to the measured results. Results of the additional analyses include analysis of the loading of other radionuclides besides 137 Cs on the crystalline silicotitanate (CST) contained within the in-tank batch contact test samples. Results from those analyses revealed the next highest contributor to the activity on the CST was 90 Sr with an average loading of 2.76E+08 dpm/g CST compared to 3.56E+10 dpm/g CST for the 137Cs. Isotopes of plutonium were also detected on the samples. ZAM modeling was performed using the measured composition of the Tank 10H Batch 3 qualification samples. The modeling predicted a maximum Cs loading approximately 2.2x higher than the measured result. This is a slightly lower ratio (expected/measured) compared to what was observed for the prior TCCR in-tank batch contact testing performed for Batches 1A and 2 where the ZAM results were 2.7-2.8x higher than the measured values.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Characterization Results for the March 2022 Tank Farm 3H Evaporator Overhead Sample

On an annual basis, Savannah River Mission Completion (SRMC) provides 2H and 3H evaporator overhead samples to Savannah River National Lab (SRNL) to be analyzed per Section 5.2 of the Effluent Treatment Project (ETP) Waste Compliance Plan (WCP) and the Waste Acceptance Criteria (WAC). This report presents characterization results for the March 2022 3H evaporator overhead sample. The sample was clear and colorless with no visible solids. The results provide measurements for cesium-137 ( 137 Cs), strontium-90 ( 90 Sr), and iodine-129 ( 129 I) with the radionuclide concentration limits specified by the WAC. These analyses were performed on a single sample replicate. A summary of the analytical results for the 3H evaporator overhead sample includes the following. The measured cesium-137 activity in the 3H evaporator overhead sample is 4.59E+02 dpm/mL which is above the ETP WAC limit of 3.28E+02 dpm/mL. The strontium-90 activity in the 3H evaporator overhead sample is <2.95E+01 dpm/mL. This is below the ETP WAC limit of 1.76E+02 dpm/mL. The iodine-129 activity in the 3H evaporator overhead sample is <1.92E-02 dpm/mL. This is below the ETP WAC limit of 1.00E+00 dpm/mL.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Adaptive Sampling for In Situ Cloud Probe (Final Report)

Clouds play a leading role in the Earth's global energy and solar radiation balance and hydrological cycle. Improving cloud models requires detailed information on the cloud microphysical properties, such as droplet size distribution and number density, liquid water content and cloud composition (droplets, ice particles), which can only be provided by aerial in situ measurements. However, for many atmospheric measurement instruments, the lack of flexibility in selecting the operational mode during operation can lead to uncertainties in sampling and measurement characteristics under continuously varying atmospheric conditions. This SBIR project is developing an advanced, compact optical imaging technology for in situ characterization of cloud hydrometeors. The development involves a deep modification of the existing Mesa Photonics’ Cloud Droplet Measurement System (CDMS) in order to implement real-time automatic adaptive sampling based on the acquired in situ data and environmental parameters. The new system, CDMS-2, implements two measurement modes: side-scatter imaging for smaller hydrometeors and direct bright-field-illumination imaging for larger hydrometeors in a significantly larger sample volume. The system measures the droplet size distribution (DSD) and number density with an added capability of discriminating between liquid water and ice hydrometeors (based on polarization-resolved side-scatter imaging). The instrument will implement automatic switching or alternating between the regular side-scatter imaging mode and sparse/large hydrometeor mode (based on the acquired data). Other adaptive sampling capabilities include variable sample volume and dynamic range (based on the measured DSD). The preferred deployment platforms are uncrewed aircraft systems (UAS) and tethered balloon/kite systems (TBS). The Phase I project achieved (or exceeded) the goals listed in the Work Plan. A CDMS-2 laboratory prototype implementing the polarization-resolved side-scatter imaging mode and direct bright-field-illumination imaging mode was designed and built. Additional capabilities included the variable illumination pulse energy and sample volume. The smallest detectable droplet diameter was improved to 3–4 μm (from the nominal 10 μm value specified for the original CDMS). Discrimination between water droplets and ice particles was experimentally demonstrated. The Phase I prototype was extensively tested and calibrated in the laboratory and also tested in the Pi Cloud Chamber at Michigan Technological University (MTU). The two intensive experimental campaigns at MTU provided unique opportunities of testing the CDMS-2 laboratory prototype under realistic warm and mixed-phase cloud conditions (stable for long periods of time), testing different sampling modes and intercomparing the CDMS-2 prototype to other co-located cloud characterization instruments. The Phase I project successfully demonstrated the feasibility of the proposed technology and identified the engineering challenges of designing a field deployable prototype instrument in Phase II. The Phase I study provides a solid basis for development, characterization and field-testing of the proposed advanced cloud probe with adaptive sampling in Phase II followed by commercialization of the technology in Phase III.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

U328 Electrical Reliability Project Soil Sampling and Analysis Plan

Lawrence Livermore National Laboratory's (LLNL’s) Project Management Office (PMO) is planning to install an underground electrical duct bank at the 3200 block of the Livermore Site (project). The proposed project will include a new electrical substation and feeders, demolition and replacement of the U328C utility building with a new structure to the west, re-routing of utilities, and update of the parking lot. This Sampling and Analysis Plan (SAP) outlines the procedures to collect and evaluate environmental samples for disposition of the excavated soil during the project and geotechnical samples for pavement design. This SAP has been prepared and is organized to be consistent with LLNL's Soils Screening and Management Plan (SSMP) (LLNL, 2022), as well as the U.S. Environmental Protection Agency's (EPA) Data Quality Objectives (DQO) process (EPA, 2006). In addition to the environmental samples, geotechnical samples will be collected by Consolidated Engineering Laboratories (CEL) on behalf of PMO. Geotechnical samples will be collected from a dedicated geotechnical boring location or co-located with environmental samples. Collection and evaluation of the geotechnical samples is determined by CEL and is therefore not discussed in this SAP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

(U) A General-Purpose Code for Correlated Sampling Using Batch Statistics with MCNP6 for Fixed-Source Problems

Correlated sampling can be used to reduce the uncertainty of a difference of tallies by taking advantage of the negative covariance term in the sandwich formula. Booth first showed how correlated sampling can be applied with batch statistics using MCNP’s tally fluctuation chart (TFC) to reduce the uncertainty of a difference of tallies in fixed-source problems. Booth presented a problem in which a 1273% uncertainty in a difference was reduced to 8% by accounting for correlations. Researchers He and Su recently studied correlated sampling using the TFC in MCNP version 5. They determined that the code did not print enough digits in the TFC tally means for accurate batch statistics in some cases. After modifying the source code, they concluded that “correlated sampling can yield a standard deviation of about one magnitude smaller than that predicted by the direct, un-correlated simulation when the changes in system response are small (say about 1%), which is equivalent to saving in CPU time by a factor of 100. Such saving [sic] becomes less significant as the change in system response becomes larger.” He and Su provided the formulas needed to apply batch statistics to compute the correlated uncertainty of a difference of tallies. In this report, we follow up on their work by providing the formulas needed to apply batch statistics to compute the correlated uncertainty of a ratio of tallies and of a difference of two tallies divided by a third tally. We extend these formulas to differences and ratios of ratios. These formulas are applied to reduce the uncertainty associated with calculating a relative sensitivity. He and Su did not investigate the accuracy of their correlated sampling uncertainty estimates. We use their test problems and evaluate the accuracy of the uncertainty estimates by comparing with results obtained from random sampling, and, in simple cases, with theoretical values of the “exact” uncertainties. We find that the uncertainties obtained from batch statistics are accurate as long as at least 100 batches are used. We present a new computer code, COSUBS (COrrelated Sampling Using Batch Statistics), that reads MCNP6 TFCs and applies correlated sampling using batch statistics for the tally combinations that the user specifies. COSUBS is a very general tool that compares all TFCs for a base case and one or two perturbed cases. It computes uncertainties for ratios if given only a base case. This report is organized as follows. The equations to apply batch statistics to the difference of random tallies are reviewed in Sec. II. Section III presents the equations for applying batch statistics to a ratio of random tallies; this is useful for computing relative sensitivities using a one-sided finite difference and the relative sensitivity using the differential operator method. Section IV presents the equations for applying batch statistics to a difference of two random tallies divided by a third; this is useful for computing a relative sensitivities using a central difference. Section V presents the equations for applying batch statistics to a difference of two ratios with four random tallies. Section VI presents the equations for applying batch statistics to a one-sided finite difference estimate of the relative sensitivity of a ratio (this uses four random tallies). Section VII presents the equations for applying batch statistics to a central difference estimate of the relative sensitivity of a ratio (this uses six random tallies). Section VIII presents the equations for applying batch statistics to a sum of random tallies. Section IX discusses how to apply batch statistics using MCNP6. Section X presents COSUBS, describing its command-line options and logic. Sections XI through XVI present numerical results for various test problems. Section XVII is a summary and conclusions. Appendix A derives the theoretical Monte Carlo tally variance given certain assumptions; these variances are used to verify the batch statistics for some of the problems. Appendix B lists the MCNP6 input for the unperturbed example problem. Appendix C presents modifications made to MCNP6.3 to support this work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Riverine Plastic Pollution: Field Sampling Protocol and Implementation in U.S. Rivers

Riverine plastic pollution is increasingly being recognized as a serious environmental concern. The flux of plastic from U.S. rivers into the oceans is estimated to be on the order of hundreds of tons per year. Plastic pollution has been detected in all major U.S. rivers but the observations did not measure metrics that could be used for mass flux calculations. The Department of Energy is addressing the problem of riverine plastic pollution with the Waterborne Plastics Resource Assessment and Debris Characterization (WaterPACT) project. Phase one of the WaterPACT project includes the development of a sampling protocol, field sampling events that implement the protocol, and numerical modeling studies. The field sampling will quantify and characterize the plastic pollution and the numerical modeling studies will analyze the movement of the plastic pollution by rivers. This report details the WaterPACT sampling protocol and its implementation in four major U.S. rivers. The WaterPACT sampling protocol was implemented in the Mississippi, Columbia, Delaware, and Los Angeles rivers with at least three sampling events in each river. The rivers represent four types ranging from the large Mississippi with its vast agricultural watershed to the small Los Angeles with its highly engineered urban waterway. The three sampling events covered a variety of discharge conditions from low drought flow to extreme storm events. The data obtained by the WaterPACT sampling of the four rivers will be combined to provide an invaluable dataset to researchers studying the source and chemical composition of plastic pollution and modelers estimating the flux of plastic being transported to and released into the oceans.

13 HYDRO ENERGY↗
DOE OSTI2023

Agricultural Ice Nuclei at Southern Great Plains Supplemental Sampling (AGINSGP-SUPP) Field Campaign Report

The Agricultural Ice Nuclei at Southern Great Plains Supplemental Sampling (AGINSGP-SUPP) field campaign took place from April 8 to April 28, 2022. It included sample collection and analysis of filter samples for ice-nucleating particle (INP) concentrations. By enabling quantification of INPs at warmer temperatures (i.e., T > 258 K), these samples complemented the real-time observations of INPs that were performed as part of the AGINSGP campaign during the same period. In addition to collecting ground-based samples, the campaign collected vertical samples of INPs aboard the Atmospheric Radiation Measurement (ARM) tethered balloon system (TBS) as shown in Figure 1. These vertical samples complemented the vertical profiling of aerosol properties that was supported under a related Facilities Integrating Collaborations for User Science (FICUS) proposal. The overall aim of these three campaigns was to improve understanding of the sources and variability in observed INP concentrations at ARM’s SGP observatory. For example, warm-temperature INPs in this agricultural region are thought to originate in part from regional emissions of fertile, agricultural soils containing high organic content. Laboratory experiments have shown that soil particles with high organic content are more efficient INPs than inorganic soils (e.g., Tobo et al. 2014). Quantification of warm-temperature INPs under ambient conditions currently can only be achieved via offline methods such as the ARM ice-nucleation spectrometer (INS). Therefore, offline sampling for the INS was required to complement the real-time INP measurements conducted during the AGINSGP campaign.

, tethered balloon system↗
DOE OSTI2026

Improvements in the Sample Space for the Backscattering Silicon Spectrometer (BASIS)

The increase in neutron flux at the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS), currently operating at 2.0 MW proton beam power, has created new opportunities for higher-throughput neutron scattering experiments while also increasing the importance of minimizing background scattering and optimizing sample-environment operations. To address these challenges on the Backscattering Silicon Spectrometer (BA-SIS), several upgrades were developed and evaluated, including boron carbide (B₄C) masking for flat-plate sample containers, multi-cell sample holders used with a vertically translating sample stick, and an automated helium pump and purge (HPP) system for closed-cycle refrigerators. Neutron diffraction measurements demonstrate that B₄C masks reduce background scattering by 49–67%, outperforming both borated aluminum and boron nitride masks while introducing no additional Bragg reflections within the instrument’s accessible Q-range. Commissioning tests of a double-cell flat-plate sample contain-er showed no measurable crosstalk between adjacent sample compartments and con-firmed stable thermal performance, enabling multiple samples to be measured without re-peated temperature cycling. In addition, the automated HPP system provided reproducible sample-space gas handling with approximately ±1 mbar precision while reducing the need for operator intervention and supporting remote operation. Together, these developments improve signal-to-noise performance, increase experimental throughput, and enhance operational efficiency at BASIS, supporting the instrument’s continued operation under higher neutron flux conditions.

Jalarvo, Niina [ORNL] (ORCID:0000000306446866)↗
DOE OSTI2025

Computational Fluid Dynamics Modeling to Facilitate Qualification of Stack Sampling Probe Location

Computational fluid dynamics (CFD) modeling was used to help evaluate modifications to a radiological effluent stack and assist with establishing a stack sampling location that met the mixing criteria for qualification. Requirements for stack sampling location are listed in the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-2021 standard. Modeling was performed to help develop a suitable design for increasing building ventilation for the radiological effluent stack. The ANSI/HPS N13.1-2021 criteria for the air monitoring probe location are that the coefficient of variation of velocity uniformity, gaseous tracer uniformity, and particulate tracer uniformity must be less than or equal to 20%. Furthermore, no point in the sampling location may have a gaseous tracer concentration that varies from the mean concentration by more than 30%. Additionally, the flow angle at the sampling location must not be more than 20 degrees. The ANSI/HPS N13.1-2021 standard allows for models (physical or computational) to be employed to perform the full suite of qualification tests, followed by a more limited set of verification tests on the actual stack to qualify the stack sampling location. Here, a series of computational model simulations were employed to evaluate the stack qualification criteria. Significant time and re-source savings are achieved using CFD modeling. CFD modeling demonstrated that the stack meets the criteria at the sample probe location. Verification tests were performed on the modified stack to measure the velocity uniformity and flow angle at the stack sampling location, and results demonstrated that the CFD model results may be used to support the qualification of the stack sampling location.

Air Monitoring↗
DOE OSTI2013

Adaptive Sampling Algorithms for Probabilistic Risk Assessment of Nuclear Simulations

Nuclear simulations are often computationally expensive, time-consuming, and high-dimensional with respect to the number of input parameters. Thus exploring the space of all possible simulation outcomes is infeasible using finite computing resources. During simulation-based probabilistic risk analysis, it is important to discover the relationship between a potentially large number of input parameters and the output of a simulation using as few simulation trials as possible. This is a typical context for performing adaptive sampling where a few observations are obtained from the simulation, a surrogate model is built to represent the simulation space, and new samples are selected based on the model constructed. The surrogate model is then updated based on the simulation results of the sampled points. In this way, we attempt to gain the most information possible with a small number of carefully selected sampled points, limiting the number of expensive trials needed to understand features of the simulation space. We analyze the specific use case of identifying the limit surface, i.e., the boundaries in the simulation space between system failure and system success. In this study, we explore several techniques for adaptively sampling the parameter space in order to reconstruct the limit surface. We focus on several adaptive sampling schemes. First, we seek to learn a global model of the entire simulation space using prediction models or neighborhood graphs and extract the limit surface as an iso-surface of the global model. Second, we estimate the limit surface by sampling in the neighborhood of the current estimate based on topological segmentations obtained locally. Our techniques draw inspirations from topological structure known as the Morse-Smale complex. We highlight the advantages and disadvantages of using a global prediction model versus local topological view of the simulation space, comparing several different strategies for adaptive sampling in both contexts. One of the most interesting models we propose attempt to marry the two by obtaining a coarse global representation using prediction models, and a detailed local representation based on topology. Our methods are validated on several analytical test functions as well as a small nuclear simulation dataset modeled after a simplified Pressurized Water Reactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Strain Measurement of Geological Samples Subjected to Triaxial Stresses Experienced During Hydraulic Loading

Understanding stress and strain relationships and having the ability to predict these quantities for known load conditions is crucial to all geomechanical and, in some instances, reservoir flow applications. The constitutive equations governing the deformation of geological materials are typically adequate for bulk or large scale deformation and stress analyses. However, these rules are generally less precise in their ability to make accurate predictions in physical processes where highly localized material heterogeneity exists or where the presence of geometric irregularities such as micro-cracks may be present. This is especially relevant to EGS where hydraulic fracture propagation models are needed to develop optimal reservoir creation strategies and where fracture permeability is significantly influenced by regional stress states and may affect reservoir operation strategies. The deficiencies of the models used to describe these physical processes are a practical reality necessitated by the manner in which rock properties must be obtained. Conventional rock mechanics tests subject samples to controlled load conditions and measure bulk deformations of the sample or more localized deformations only on exposed surfaces of the sample. They are currently unable to comprehensively map the deformation state within the sample. For processes such as fracture, however, the state of a particular region within the rock drives the overall failure behavior of the sample. The authors believe that possessing a means to measure strains within samples subjected to hydraulic fracture loading conditions will provide a useful tool for understanding the localized effects not captured by conventional techniques and may serve as a method for improving hydraulic fracture models. An ongoing effort at Oak Ridge National Laboratory endeavors to develop a neutron diffraction based strain measurement capability to interrogate the strain state of a geological sample, at arbitrary internal locations, subjected to a triaxial stress state. The basis of the method and initial results for simple load conditions were reported at last year s Stanford Geothermal Workshop. This work will report results from recent neutron diffraction strain measurement experiments in which marble samples were subjected to load conditions more representative of hydraulic fracturing operations within a pressure cell specially designed for the reported strain measurement technique.

An, Ke↗
DOE OSTI2019

Proteomic Sample Preparation Techniques: Towards Forensic Proteomic Applications

Proteomic sample preparation techniques rely on dynamic multi-step processes that are sample type dependent. Forensic proteomic applications comprise diverse sample types and therefore require numerous sample preparation workflows. A sample may need pre-treatment steps to solubilize proteins from a solid surface, for example - from clothing, from a swab, or off of a filter. A sample may need to be disrupted or homogenized to liberate proteins trapped in cells. Or a sample may need additional processing steps, such as organic extraction, to isolate proteins from small molecule contaminants which interfere with mass spectrometry (MS) measurements. Following these pre-treatment steps, proteins are reduced, denatured, alkylated, and enzymatically digested. The resulting peptide mixture can be desalted by solid phase extraction or fractionated prior to liquid chromatography MS-based proteomic characterization. Here we detail each step of this multi-stage sample type dependent processing.

Nicora, Carrie D.↗
DOE OSTI2023

Sampling synchronization through GPS signals

A method uses a distributed data acquisition system with multiple, physically unconnected, data acquisition units, that can be in wireless communication with a remote host, to timestamp measurement data with sub-microsecond time base accuracy of sampling clock relative to an absolute timeframe. A current absolute time is derived from messages received from a satellite radio beacon positioning system (GPS). Measurement data is sampled by each unit at a specified sampling rate. Using hardware logic, batches of sampled data are associated with corresponding timestamps representing the absolute time at which the data was sampled. Data and timestamps may be transmitted to the host. A time offset bias is compensated by comparing timestamps against a nominal time based on start time and nominal sampling rate. The sampling clock rate may be disciplined using time pulses from the GPS receiver. An initial start of data sampling by all units can also be synchronized.

Zhuge, James Q.↗
DOE OSTI2016

Colonie FUSRAP Site - Radioactive Dust Sampling of Residential and Commercial Properties - 16384

The Colonie Formerly Utilized Sites Remedial Action Program (FUSRAP) Site is located in the Town of Colonie, Albany County, New York. The U.S. Army Corps of Engineers (USACE) is currently addressing environmental contamination associated with the Site. The area surrounding the Site consists of residential and commercial properties, known as vicinity properties (VPs). Cleanup activities have been completed on many of these VPs under the FUSRAP to address depleted uranium contamination. Soil remediation activities have been substantially completed at the Colonie FUSRAP Site and its VPs under the FUSRAP. Recent studies performed by an independent party and under FUSRAP identified uranium within indoor dust in residencies and businesses in the immediate vicinity of the Site. The studies were limited to non-living areas such as basement window sills, garages, and attics. This paper discusses the indoor dust sampling and analysis, in support of the Remedial Investigation (RI) for the VPs, and presents sampling results. The indoor dust sample media presented many technical challenges regarding sampling design, data reduction, and data interpretation. In addition, because the RI is focused on numerous resident-owned, rental, and commercial properties, challenges where presented regarding right-of-entry to sample. Isotopic uranium ratios observed in the majority of the samples are indicative of the depleted uranium contaminant, even at trace levels. While the sampling and analysis methods were effective at identifying depleted uranium in the majority of the samples, preliminary property-specific risk assessment results do not indicate the presence of depleted uranium in sufficient concentrations to pose unacceptable risk to VP inhabitants. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗