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At least 469 records · Page 26

Sample Size Effects on Petrophysical Characterization and Fluid-to-Pore Accessibility of Natural Rocks

Laboratory-scale analysis of natural rocks provides petrophysical properties such as density, porosity, pore diameter/pore-throat diameter distribution, and fluid accessibility, in addition to the size and shape of framework grains and their contact relationship with the rock matrix. Different types of laboratory approaches for petrophysical characterization involve the use of a range of sample sizes. While the sample sizes selected should aim to be representative of the rock body, there are inherent limitations imposed by the analytical principles and holding capacities of the different experimental apparatuses, with many instruments only able to accept samples at the μm–mm scale. Therefore, a total of nine (three limestones, three shales, two sandstones, and one dolomite) samples were collected from Texas to fill the knowledge gap of the sample size effect on the resultant petrophysical characteristics. The sample sizes ranged from 3 cm cubes to <75 μm particles. Using a combination of petrographic microscopy, helium expansion pycnometry, water immersion porosimetry, mercury intrusion porosimetry, and (ultra-) small-angle X-ray scattering, the impact of sample size on the petrophysical properties of these samples was systematically investigated here. The results suggest that the sample size effect is influenced by both pore structure changes during crushing and sample size-dependent fluid-to-pore connectivity.

36 MATERIALS SCIENCE↗

Update on SRNL Support of Saltstone Sampling and Analysis - 16325

At the Savannah River Site, low-level waste is immobilized in cementitious waste form known as saltstone. The saltstone Performance Assessment models the performance of the waste form and other aspects of the Saltstone Disposal Facility over ten thousand years after closure to determine the transport history of radionuclides and other hazardous constituents in low-level waste. As part of an ongoing Performance Assessment Maintenance Plan, Savannah River Remediation with Savannah River National Laboratory, has designed a sampling and analyses plan to correlate the properties of field-emplaced samples and samples processed and cured in the laboratory. As part of the plan, SRR has retrieved field-emplaced samples from SDU 2A. Prior to analyzing the field emplaced samples, SRNL is developing the strategy, protocols and equipment necessary to retrieve, store in an inert environment, and analyze the three sample sets of interest outlined in the analysis plan. To date, the simulant saltstone samples have been analyzed for hydraulic conductivity, porosity, density, and other properties. This paper will give an update to the current protocols and equipment being utilized at Savannah River National Laboratory for storing and analyzing the field-emplaced and simulant samples, results from the simulant saltstone analyses, as well as analysis plans for the samples retrieved from the Saltstone Processing Facility and the field-emplaced samples. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sample Identifiers and Metadata to Support Data Management and Reuse in Multidisciplinary Ecosystem Sciences

Physical samples are foundational entities for research across biological, Earth, and environmental sciences. Data generated from sample-based analyses are not only the basis of individual studies, but can also be integrated with other data to answer new and broader-scale questions. Ecosystem studies increasingly rely on multidisciplinary team-science to study climate and environmental changes. While there are widely adopted conventions within certain domains to describe sample data, these have gaps when applied in a multidisciplinary context. In this study, we reviewed existing practices for identifying, characterizing, and linking related environmental samples. We then tested practicalities of assigning persistent identifiers to samples, with standardized metadata, in a pilot field test involving eight United States Department of Energy projects. Participants collected a variety of sample types, with analyses conducted across multiple facilities. We address terminology gaps for multidisciplinary research and make recommendations for assigning identifiers and metadata that supports sample tracking, integration, and reuse. Furthermore, our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data.

54 ENVIRONMENTAL SCIENCES↗

Automated Radioanalytical System Incorporating Microwave-Assisted Sample Preparation, Chemical Separation, and Online Radiometric Detection for the Monitoring of Total 99Tc in Nuclear Waste Processing Streams

An automated fluidic instrument is described that rapidly determines the total 99Tc content of aged nuclear waste samples, where the matrix is chemically and radiologically complex and the existing speciation of the 99Tc is variable. The monitor links microwave-assisted sample preparation with an automated anion exchange column separation and detection using a flow-through solid scintillator detector. The sample preparation steps acidify the sample, decompose organics, and convert all Tc species to the pertechnetate anion. The column-based anion exchange procedure separates the pertechnetate from the complex sample matrix, so that radiometric detection can provide accurate measurement of 99Tc. We developed a preprogrammed spike addition procedure to automatically determine matrix-matched calibration. The overall measurement efficiency that is determined simultaneously provides a self-diagnostic parameter for the radiochemical separation and overall instrument function. Continuous, automated operation was demonstrated over the course of 54 h, which resulted in the analysis of 215 samples plus 54 hly spike-addition samples, with consistent overall measurement efficiency for the operation of the monitor. A sample can be processed and measured automatically in just 12.5 min with a detection limit of 23.5 Bq/mL of 99Tc in low activity waste (0.495 mL sample volume), with better than 10% RSD precision at concentrations above the quantification limit. This rapid automated analysis method was developed to support nuclear waste processing operations planned for the Hanford nuclear site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The effect of dogbone sample size in the tensile testing of TATB-based plastic‑bonded explosive materials

Mechanical properties are of interest for many plastic‑bonded explosive (PBX) materials with tensile properties being of particular interest. Direct tensile measurements using dogbone-shaped samples are considered the gold standard, but they are fairly large, making testing more costly and less desirable from a safety perspective. We investigated whether the measured tensile strength depends on the dogbone specimen size, which to our knowledge, has not been reported in the literature for PBX materials. Understanding this should inform the feasibility of employing smaller samples and how sample size should be considered when comparing PBX dogbone values in the literature. The TATB-based PBX dogbone sample size was varied by (a) scaling all dimensions proportionally and (b) varying only the length of the samples. It was observed that the measured tensile peak stress (strength) was a function of the sample size, and was more dependent on the diameter (cross-sectional area) than the length of the samples. Since peak stress is calculated as peak force normalized to the diameter of the sample, one might not expect an explicit diameter dependence for the peak stress. Therefore, these results suggest there may be an additional strengthening effect as the sample diameter is increased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A data-driven approach to sampling matrix selection for compressive sensing

Sampling is a fundamental aspect of any implementation of compressive sensing. Typically, the choice of sampling method is guided by the reconstruction basis. However, this approach can be problematic with respect to certain hardware constraints and is not responsive to domain-specific context. We propose a method for defining an order for a sampling basis that is optimal with respect to capturing variance in data, thus allowing for meaningful sensing at any desired level of compression. We focus on the Walsh-Hadamard sampling basis for its relevance to hardware constraints, but our approach applies to any sampling basis of interest. We illustrate the effectiveness of our method on the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset, the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset, and a Colorado State University Swiss Ranger depth image dataset. The spectral datasets consist of simulant experiments, including releases of chemicals such as GAA and SF6. We combine our sampling and reconstruction with the adaptive coherence estimator (ACE) and bulk coherence for chemical detection and we incorporate an algorithmic threshold for ACE values to determine the presence or absence of a chemical. We compare results across sampling methods in this context. We have successful chemical detection at a compression rate of 90%. For all three datasets, we compare our sampling approach to standard orderings of sampling basis such as random, sequency, and an analog of sequency that we term `frequency.' In one instance, the peak signal to noise ratio was improved by over 30% across a test set of depth images.

compressive sensing, hyperspectral imaging, Walsh-↗

SU-E-T-21: A Novel Sampling Algorithm to Reduce Intensity-Modulated Radiation Therapy (IMRT) Optimization Time

Purpose: The IMRT optimization problem requires substantial computer time to find optimal dose distributions because of the large number of variables and constraints. Voxel sampling reduces the number of constraints and accelerates the optimization process, but usually deteriorates the quality of the dose distributions to the organs. We propose a novel sampling algorithm that accelerates the IMRT optimization process without significantly deteriorating the quality of the dose distribution. Methods: We included all boundary voxels, as well as a sampled fraction of interior voxels of organs in the optimization. We selected a fraction of interior voxels using a clustering algorithm, that creates clusters of voxels that have similar influence matrix signatures. A few voxels are selected from each cluster based on the pre-set sampling rate. Results: We ran sampling and no-sampling IMRT plans for de-identified head and neck treatment plans. Testing with the different sampling rates, we found that including 10% of inner voxels produced the good dose distributions. For this optimal sampling rate, the algorithm accelerated IMRT optimization by a factor of 2–3 times with a negligible loss of accuracy that was, on average, 0.3% for common dosimetric planning criteria. Conclusion: We demonstrated that a sampling could be developed that reduces optimization time by more than a factor of 2, without significantly degrading the dose quality.

60 APPLIED LIFE SCIENCES↗

SPRUCE Peat Core Sample Collection Metadata, Marcell Experimental Forest, Minnesota, August 2025

This data set contains metadata associated with peat core samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B05LW. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > TERRESTRI↗

EVALUATION OF ARG-1 SAMPLES PREPARED BY CESIUM CARBONATE DISSOLUTION DURING THE ISOLOK SME ACCEPTABILITY TESTING

Evaluation of Defense Waste Processing Facility (DWPF) Chemical Process Cell (CPC) cycle time identified several opportunities to improve the CPC processing time. The Mechanical Systems & Custom Equipment Development (MS&CED) Section of the Savannah River National Laboratory (SRNL) recently completed the evaluation of one of these opportunities - the possibility of using an Isolok sampling valve as an alternative to the Hydragard valve for taking DWPF process samples at the Slurry Mix Evaporator (SME). The use of an Isolok for SME sampling has the potential to improve operability, reduce maintenance time, and decrease CPC cycle time. The SME acceptability testing for the Isolok was requested in Task Technical Request (TTR) HLW-DWPF-TTR-2010-0036 and was conducted as outlined in Task Technical and Quality Assurance Plan (TTQAP) SRNLRP-2011-00145. RW-0333P QA requirements applied to the task, and the results from the investigation were documented in SRNL-STI-2011-00693. Measurement of the chemical composition of study samples was a critical component of the SME acceptability testing of the Isolok. A sampling and analytical plan supported the investigation with the analytical plan directing that the study samples be prepared by a cesium carbonate (Cs{sub 2}CO{sub 3}) fusion dissolution method and analyzed by Inductively Coupled Plasma - Optical Emission Spectroscopy (ICP-OES). The use of the cesium carbonate preparation method for the Isolok testing provided an opportunity for an additional assessment of this dissolution method, which is being investigated as a potential replacement for the two methods (i.e., sodium peroxide fusion and mixed acid dissolution) that have been used at the DWPF for the analysis of SME samples. Earlier testing of the Cs{sub 2}CO{sub 3} method yielded promising results which led to a TTR from Savannah River Remediation, LLC (SRR) to SRNL for additional support and an associated TTQAP to direct the SRNL efforts. A technical report resulting from this work was issued that recommended that the mixed acid method be replaced by the Cs{sub 2}CO{sub 3} method for the measurement of magnesium (Mg), sodium (Na), and zirconium (Zr) with additional testing of the method by DWPF Laboratory being needed before further implementation of the Cs{sub 2}CO{sub 3} method at that laboratory. While the SME acceptability testing of the Isolok does not address any of the open issues remaining after the publication of the recommendation for the replacement of the mixed acid method by the Cs{sub 2}CO{sub 3} method (since those issues are to be addressed by the DWPF Laboratory), the Cs{sub 2}CO{sub 3} testing associated with the Isolok testing does provide additional insight into the performance of the method as conducted by SRNL. The performance is to be investigated by looking to the composition measurement data generated by the samples of a standard glass, the Analytical Reference Glass - 1 (ARG-1), that were prepared by the Cs{sub 2}CO{sub 3} method and included in the SME acceptability testing of the Isolok. The measurements of these samples were presented as part of the study results, but no statistical analysis of these measurements was conducted as part of those results. It is the purpose of this report to provide that analysis, which was supported using JMP Version 7.0.2.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Assessment of the Revised 3410 Building Filtered Exhaust Stack Sampling Probe Location

In order to support the air emissions permit for the 3410 Building, Pacific Northwest National Laboratory performed a series of tests in the exhaust air discharge from the reconfigured 3410 Building Filtered Exhaust Stack. The objective was to determine whether the location of the air sampling probe for emissions monitoring meets the applicable regulatory criteria governing such effluent monitoring systems. In particular, the capability of the air sampling probe location to meet the acceptance criteria of ANSI/HPS N13.1-2011 , Sampling and Monitoring Releases of Airborne Radioactive Substances from the Stack and Ducts of Nuclear Facilities was determined. The qualification criteria for these types of stacks address 1) uniformity of air velocity, 2) sufficiently small flow angle with respect to the axis of the duct, 3) uniformity of tracer gas concentration, and 4) uniformity of tracer particle concentration. Testing was performed to conform to the quality requirements of NQA-1-2000. Fan configurations tested included all fan combinations of any two fans at a time. Most of the tests were conducted at the normal flow rate, while a small subset of tests was performed at a slightly higher flow rate achieved with the laboratory hood sashes fully open. The qualification criteria for an air monitoring probe location are taken from ANSI/HPS N13.1-2011 and are paraphrased as follows with key results summarized: 1. Angular Flow—The average air velocity angle must not deviate from the axis of the stack or duct by more than 20°. Our test results show that the mean angular flow angles at the center two-thirds of the ducts are smaller than 4.5% for all testing conditions. 2. Uniform Air Velocity—The acceptance criterion is that the COV of the air velocity must be ≤ 20% across the center two thirds of the area of the stack. Our results show that the COVs of the air velocity across the center two-thirds of the stack are smaller than 2.9% for all testing conditions. 3. Uniform Concentration of Tracer Gases—The uniformity of the concentration of potential contaminants is first tested using a tracer gas to represent gaseous effluents. The tracer is injected downstream of the fan outlets and at the junction downstream fan discharges meet. The acceptance criteria are that 1) the COV of the measured tracer gas concentration is ≤20% across the center two-thirds of the sampling plane and 2) at no point in the sampling plane does the concentration vary from the mean by >30%. Our test results show that 1) the COV of the measured tracer gas concentration is < 2.9% for all test conditions and 2) at no point in the sampling plane does the concentration vary from the mean by >6.5%. 4. Uniform Concentration of Tracer Particles—Tracer particles of 10-μm aerodynamic diameter are used for the second demonstration of concentration uniformity. The acceptance criterion is that the COV of particle concentration is ≤ 20% across the center two thirds of the sampling plane. Our test results indicate that the COV of particle concentration is <9.9% across the center two-thirds of the sampling plane among all testing conditions. Thus, the reconfigured 3410 Building Filtered Exhaust Stack was determined to meet the qualification criteria given in the ANSI/HPS N13.1-2011 standard. Changes to the system configuration or operations outside the bounds described in this report (e.g., exhaust stack velocity changes, relocation of sampling probe, and addition of fans) may require re-testing or re-evaluation to determine compliance.

3410 building↗

Interpretation of stable isotope, denitrification, and groundwater age data for samples collected from Sandia National Laboratories /New Mexico (SNL/NM) Burn Site Groundwater Area of Concern

This report combines and summarizes results for two groundwater-sampling events (October 2012 and October/November 2015) from the Sandia National Laboratories/New Mexico (SNL/NM) Burn Site Groundwater (BSG) Area of Concern (AOC) located in the Lurance Canyon Arroyo southeast of Albuquerque, NM in the Manzanita Mountains. The first phase of groundwater sampling occurred in October 2012 including samples from 19 wells at three separate sites that were analyzed by the Environmental Radiochemistry Laboratory at Lawrence Livermore National Laboratory as part of a nitrate Monitored Natural Attenuation (MNA) evaluation. The three sites (BSG, Technical Area-V, and Tijeras Arroyo) are shown on the regional hydrogeologic map and described in the Sandia Annual Groundwater Monitoring Report. The first phase of groundwater sampling included six monitoring wells at the Burn Site, eight monitoring wells at Technical Area-V, and five monitoring wells at Tijeras Arroyo. Each groundwater sample was analyzed using the two specialized analytical methods, age-dating and denitrification suites. In September 2015, a second phase of groundwater sampling took place at the Burn Site including 10 wells sampled and analyzed by the same two analytical suites. Five of the six wells sampled in 2012 were resampled in 2015. This report summarizes results from two sampling events in order to evaluate evidence for in situ denitrification, the average age of the groundwater, and the extent of recent recharge of the bedrock fracture system beneath the BSG AOC.

54 ENVIRONMENTAL SCIENCES↗

Biological Sampling Variability Study

There are many sources of variability that exist in the sample collection and analysis process. This paper addresses many, but not all, sources of variability. The main focus of this paper was to better understand and estimate variability due to differences between samplers. Variability between days was also studied, as well as random variability within each sampler. Experiments were performed using multiple surface materials (ceramic and stainless steel), multiple contaminant concentrations (10 spores and 100 spores), and with and without the presence of interfering material. All testing was done with sponge sticks using 10-inch by 10-inch coupons. Bacillus atrophaeus was used as the BA surrogate. Spores were deposited using wet deposition. Grime was coated on the coupons which were planned to include the interfering material (Section 3.3). Samples were prepared and analyzed at PNNL using CDC protocol (Section 3.4) and then cultured and counted. Five samplers were trained so that samples were taken using the same protocol. Each sampler randomly sampled eight coupons each day, four coupons with 10 spores deposited and four coupons with 100 spores deposited. Each day consisted of one material being tested. The clean samples (no interfering materials) were run first, followed by the dirty samples (coated with interfering material). There was a significant difference in recovery efficiency between the coupons with 10 spores deposited (mean of 48.9%) and those with 100 spores deposited (mean of 59.8%). There was no general significant difference between the clean and dirty (containing interfering material) coupons or between the two surface materials; however, there was a significant interaction between concentration amount and presence of interfering material. The recovery efficiency was close to the same for coupons with 10 spores deposited, but for the coupons with 100 spores deposited, the recovery efficiency for the dirty samples was significantly larger (65.9% - dirty vs. 53.6% - clean) (see Figure 4.1). Variance component analysis was used to estimate the amount of variability for each source of variability. There wasn’t much difference in variability for dirty and clean samples, as well as between materials, so these results were pooled together. There was a significant difference in amount of concentration deposited, so results were separated for the 10 spore and 100 spore deposited tests. In each case the within sampler variability was the largest with variances of 426.2 for 10 spores and 173.1 for 100 spores. The within sampler variability constitutes the variability between the four samples of similar material, interfering material, and concentration taken by each sampler. The between sampler variance was estimated to be 0 for 10 spores and 1.2 for 100 spores. The between day variance was estimated to be 42.1 for 10 spores and 78.9 for 100 spores. Standard deviations can be calculated in each case by taking the square root of the variance.

59 BASIC BIOLOGICAL SCIENCES↗

Data Validation Package, April and June 2016 Groundwater and Surface Water Sampling at the Gunnison, Colorado, Processing Site, October 2016

This event included annual sampling of groundwater and surface water locations at the Gunnison, Colorado, Processing Site. Sampling and analyses were conducted as specified in Sampling and Analysis Plan for US Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lm/downloads/sampling-and­ analysis-plan-us-department-energy-office-legacy-management-sites). Samples were collected from 28 monitoring wells, three domestic wells, and six surface locations in April at the processing site as specified in the draft 2010 Ground Water Compliance Action Plan for the Gunnison, Colorado, Processing Site. Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. Domestic wells 0476 and 0477 were sampled in June because the homes were unoccupied in April, and the wells were not in use. Duplicate samples were collected from locations 0126, 0477, and 0780. One equipment blank was collected during this sampling event. Water levels were measured at all monitoring wells that were sampled. See Attachment 2, Trip Reports for additional details. The analytical data and associated qualifiers can be viewed in environmental database reports and are also available for viewing with dynamic mapping via the GEMS (Geospatial Environmental Mapping System) website at http://gems.lm.doe.gov/#. No issues were identified during the data validation process that requires additional action or follow-up. An assessment of anomalous data is included in Attachment 3. Interpretation and presentation of results, including an assessment ofthe natural flushing compliance strategy, will be reported in the upcoming 2016 Verification Monitoring Report. U.S.

54 ENVIRONMENTAL SCIENCES↗

Data Validation Package October 2015 Groundwater and Surface Water Sampling at the Monticello, Utah, Processing Site January 2016

Sampling Period: October 12–14, 2015. This semiannual event includes sampling groundwater and surface water at the Monticello Mill Tailings Site. Sampling and analyses were conducted as specified in the 2004 Monticello Mill Tailings Site Operable Unit III Post-Record of Decision Monitoring Plan, Draft Final and Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated). Samples were collected from 52 of 61 planned locations (15 of 17 former mill site wells, 17 of 18 downgradient wells, 9 of 9 downgradient permeable reactive barrier wells, 2 of 7 seeps and wetlands, and 9 of 10 surface water locations). Locations MW00-07, Seep 1, Seep 2, Seep 3, Seep 5, Seep 6, SW00-01, T01-13, and T01-19 were not sampled because of insufficient water availability. All samples were filtered as specified in the monitoring plan. Duplicate samples were collected from surface water location W3-04 and from monitoring wells 82-08, 92-09, and 92-10. Water levels were measured at all but one sampled well and an additional set of wells. The contaminants of concern (COCs) for the Monticello Mill Tailings Site are arsenic, manganese, molybdenum, nitrate + nitrite as nitrogen (nitrate + nitrite as N), selenium, uranium, and vanadium. Time-concentration graphs of the COCs for all groundwater and surface water locations are included in this report. Locations with COCs that exceeded remediation goals are listed.

2015 Monticello↗

Nevada National Security Site Integrated Groundwater Sampling Plan, Revision 1, with ROTC-1

The purpose of the Nevada National Security Site (NNSS) Integrated Groundwater Sampling Plan (referred to herein as the Plan) is to provide a comprehensive, integrated approach for collecting and analyzing groundwater samples to meet the needs and objectives of the U.S. Department of Energy (DOE), Environmental Management (EM) Nevada Program’s Underground Test Area (UGTA) Activity. Implementation of this Plan will provide high-quality data required by the UGTA Activity for ensuring public protection in an efficient and cost-effective manner. The Plan is designed to ensure compliance with the UGTA Quality Assurance Plan (QAP) (NNSA/NFO, 2015). The Plan’s scope comprises sample collection and analysis requirements relevant to assessing both the extent of groundwater contamination from underground nuclear testing and impact of testing on water quality in downgradient communities. This Plan identifies locations to be sampled by corrective action unit (CAU) and location type, sampling frequencies, sample collection methodologies, and the constituents to be analyzed. In addition, the Plan defines data collection criteria such as well purging, detection levels, and accuracy requirements/recommendations; identifies reporting and data management requirements; and provides a process to ensure coordination between NNSS groundwater sampling programs for sampling analytes of interest to UGTA. Information used in the Plan development—including the rationale for selection of wells, sampling frequency, and the analytical suite—is discussed under separate cover (N-I, 2014) and is not reproduced herein.

54 ENVIRONMENTAL SCIENCES↗

BY-110 Headspace Sampling Comparison Test: Volume 1

The Hanford Tank Operations Contractor, Washington River Protection Solutions, conducted comparison tests of two Hanford Waste tank vapor sampling systems to determine the relative differences in quantifying Chemicals of Potential Concern (COPC) while sampling the same waste tank. The systems are the traditional in situ, inline headspace sampling (HS) method and the recently developed slipstream sampling unit for testing respirator chemical cartridges known as the cartridge test (CT) rig. The comparison test was performed to determine if results obtained using the CT rig are similar to results obtained using the traditional HS method. Using the CT rig would provide efficiencies in headspace vapors sampling such as applying ALARA principles, minimizing worker entries to the tank farms, and eliminating the physical strain of manually lowering the headspace sampling bundles into the waste tanks. Six sampling events were conducted during January and February 2018 to collect headspace vapor samples from Hanford tank BY-110 with the two systems. Pacific Northwest National Laboratory was tasked with conducting an analysis of the analytical results to assess the comparability of the sampling methods and make recommendations on future testing or deployment of the CT method.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

BY-110 Headspace Sampling Comparison Test: Volume 2: Raw Data

The Hanford Tank Operations Contractor, Washington River Protection Solutions, conducted comparison tests of two Hanford Waste tank vapor sampling systems to determine the relative differences in quantifying Chemicals of Potential Concern (COPC) while sampling the same waste tank. The systems are the traditional in situ, inline headspace sampling (HS) method and the recently developed slipstream sampling unit for testing respirator chemical cartridges known as the cartridge test (CT) rig. The comparison test was performed to determine if results obtained using the CT rig are similar to results obtained using the traditional HS method. Using the CT rig would provide efficiencies in headspace vapors sampling such as applying ALARA principles, minimizing worker entries to the tank farms, and eliminating the physical strain of manually lowering the headspace sampling bundles into the waste tanks. Six sampling events were conducted during January and February 2018 to collect headspace vapor samples from Hanford tank BY-110 with the two systems. Pacific Northwest National Laboratory was tasked with conducting an analysis of the analytical results to assess the comparability of the sampling methods and make recommendations on future testing or deployment of the CT method.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Whole genome sequencing of Mycobacterium bovis directly from clinical tissue samples without culture

Advancement in next generation sequencing offers the possibility of routine use of whole genome sequencing (WGS) for Mycobacterium bovis (M. bovis) genomes in clinical reference laboratories. To date, the M. bovis genome could only be sequenced if the mycobacteria were cultured from tissue. This requirement for culture has been due to the overwhelmingly large amount of host DNA present when DNA is prepared directly from a granuloma. To overcome this formidable hurdle, we evaluated the usefulness of an RNA-based targeted enrichment method to sequence M. bovis DNA directly from tissue samples without culture. Initial spiking experiments for method development were established by spiking DNA extracted from tissue samples with serially diluted M. bovis BCG DNA at the following concentration range: 0.1 ng/μl to 0.1 pg/μl (10 –1 to 10 –4 ). Library preparation, hybridization and enrichment was performed using SureSelect custom capture library RNA baits and the SureSelect XT HS2 target enrichment system for Illumina paired-end sequencing. The method validation was then assessed using direct WGS of M. bovis DNA extracted from tissue samples from naturally (n = 6) and experimentally (n = 6) infected animals with variable Ct values. Direct WGS of spiked DNA samples achieved 99.1% mean genome coverage (mean depth of coverage: 108×) and 98.8% mean genome coverage (mean depth of coverage: 26.4×) for tissue samples spiked with BCG DNA at 10 –1 (mean Ct value: 20.3) and 10 –2 (mean Ct value: 23.4), respectively. The M. bovis genome from the experimentally and naturally infected tissue samples was successfully sequenced with a mean genome coverage of 99.56% and depth of genome coverage ranging from 9.2× to 72.1×. The spoligoyping and M. bovis group assignment derived from sequencing DNA directly from the infected tissue samples matched that of the cultured isolates from the same sample. Our results show that direct sequencing of M. bovis DNA from tissue samples has the potential to provide accurate sequencing of M. bovis genomes significantly faster than WGS from cultures in research and diagnostic settings.

59 BASIC BIOLOGICAL SCIENCES↗