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At least 631 records · Page 35

Caution on Using Tetrahydrofuran for Processing Crystalline Silica Samples From Engineered Stone for XRD Analysis

Abstract We conducted laboratory experiments to investigate a suspected effect of tetrahydrofuran (THF) on quantifying crystalline silica in samples collected from working with engineered stone when THF is used to process samples prior to the X-ray diffraction (XRD) analysis. Two groups of samples from grinding either engineered stone or granite were simultaneously taken from a laboratory testing system, with one group of samples using THF for processing and another group using muffle furnace for ashing. For each stone type, we also tested four levels of respirable dust loading on the samples by varying the grinding time from 1 to 8 min. Statistical analysis of the experimental results on crystalline silica contents of the two groups of samples showed that the difference between the two methods was not significant (P ≥ 0.05) for the granite at all four levels of respirable dust loading and for the engineered stone at the two levels of respirable dust loading greater than 0.5 mg. However, the crystalline silica content from using THF processing was significantly lower (P = 0.001) than that from using muffle furnace ashing for engineered stone when the respirable dust loading levels were less than 0.5 mg. For the engineered stone dust samples with grinding times of 1 and 2 min, the average respirable dust loading was about 0.19 and 0.34 mg, respectively; while the crystalline silica content from using THF processing was 30.9 and 21.5% lower than that from using muffle furnace ashing, respectively. Since most full-shift samples from field assessments in this industry are expected to have respirable dust loading less than 0.5 mg, muffle furnace or radio frequency plasma ashing should be specified as the preferred sample processing method instead of the THF processing method for quantification of crystalline silica when engineered stone is expected to present to avoid artificially reduced silica content values, which are likely caused by the reactions between THF and the resins in engineered stone.

Public, Environmental & Occupational Health↗

Optimizing a magnitude-limited spectroscopic training sample for photometric classification of supernovae

ABSTRACT In preparation for photometric classification of transients from the Legacy Survey of Space and Time (LSST) we run tests with different training data sets. Using estimates of the depth to which the 4-m Multi-Object Spectroscopic Telescope (4MOST) Time Domain Extragalactic Survey (TiDES) can classify transients, we simulate a magnitude-limited sample reaching rAB ≈ 22.5 mag. We run our simulations with the software snmachine, a photometric classification pipeline using machine learning. The machine-learning algorithms struggle to classify supernovae when the training sample is magnitude limited, in contrast to representative training samples. Classification performance noticeably improves when we combine the magnitude-limited training sample with a simulated realistic sample of faint high-redshift supernovae observed from larger spectroscopic facilities; the algorithms’ range of average area under receiver operator characteristic curve (AUC) scores over 10 runs increases from 0.547–0.628 to 0.946–0.969 and purity of the classified sample reaches 95 per cent in all runs for two of the four algorithms. By creating new, artificial light curves using the augmentation software avocado, we achieve a purity in our classified sample of 95 per cent in all 10 runs performed for all machine-learning algorithms considered. We also reach a highest average AUC score of 0.986 with the artificial neural network algorithm. Having ‘true’ faint supernovae to complement our magnitude-limited sample is a crucial requirement in optimization of a 4MOST spectroscopic sample. However, our results are a proof of concept that augmentation is also necessary to achieve the best classification results.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of Potential-Induced Degradation in Soda-Lime Glass and Borosilicate-Glass Cu(In,Ga)Se 2 Samples

In this study, potential-induced degradation (PID) is investigated in small-size Cu(In,Ga)Se 2 (CIGS) submodules of individual cells. Samples with conventional soda-lime glass (SLG) and low-alkaline glass (borosilicate glass, BSG) were analyzed applying positive and negative 1000 V bias at 85 degrees C and low relative humidity after a heat-soaking phase. During the heat-soaking phase, BSG samples showed degradation, with variations in their dark current-voltage (I-V) curve parameters compared with the stability of SLG samples. During the PID stress phase, back-grounded SLG samples with -1000 V applied to the cell experienced fast degradation, with complete failure in 25 h, whereas, BSG samples only showed changes because of the dark heat environment. When grounded on their front face, SLG samples remained stable during more than 150 h of PID testing, beginning degradation after longer applications of stress. The analysis of the dark I-V curves of SLG samples through the single-diode model showed that an increase in saturation current J 0 occurs first, attributed to Na + ions migrating into the CdS/ZnO layer; later, a decrease in shunt resistance occurs. Lastly, the application of the model in BSG samples showed an increase in series resistance evaluated at 25 degrees C. When the bias is reversed, SLG samples gradually recover their performance.

14 SOLAR ENERGY↗

Dynamic Importance Sampling

Dynamic Importance (DynIm) Sampling is a new approach for importance sampling in high-dimensional space. DynIm has two key characteristics. (1) Importance sampling: The notion of importance of candidate samples is used to guide the sampling, where importance is defined based on the (dis)similarity from previously selected samples (via Euclidean distance metric). (2) Dynamic sampling: The sampling can be performed dynamically, as new candidates are generated and new samples must be selected. DynIm was developed as part of a machine learning based coupling of scales in large multiscale simulations and can be used for a variety of applications.

Bhatia, Harsh↗

Results for the first quarter calendar year 2017 tank 50H salt solution sample

In this memorandum, the chemical and radionuclide contaminant results from the First Quarter Calendar Year 2017 (CY17) sample of Tank 50H salt solution are presented in tabulated form. The First Quarter CY17 Tank 50H samples [a 200 mL sample obtained 6” below the surface (HTF-50-17-7) and a 1 L sample obtained 66” from the tank bottom (HTF-50-17-8)] were obtained on January 15, 2017 and received at Savannah River National Laboratory (SRNL) on January 16, 2017. Prior to obtaining the samples from Tank 50H, a single pump was run at least 4.4 hours and the samples were pulled immediately after pump shut down. All volatile organic analysis (VOA) and semi-volatile organic analysis (SVOA) were performed on the surface sample and all other analyses were performed on the variable depth sample. The information from this characterization will be used by Savannah River Remediation (SRR) for the transfer of aqueous waste from Tank 50H to the Saltstone Production Facility, where the waste will be treated and disposed of in the Saltstone Disposal Facility. This memorandum compares results, where applicable, to Saltstone Waste Acceptance Criteria (WAC) limits and targets. The chemical and radionuclide contaminant results from the characterization of the First Quarter CY17 sampling of Tank 50H were requested by SRR personnel and details of the testing are presented in the SRNL Task Technical and Quality Assurance Plan (TTQAP). This memorandum is part of Deliverable 2 from SRR request. Data pertaining to the regulatory limits for Resource Conservation and Recovery Act (RCRA) metals will be documented at a later time per the TTQAP for the Tank 50H saltstone task.

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Addendum to Sampling and Analysis Plan (SAP) for Assessment of LANL-Derived Residual Radionuclides in Soils within Tract A-16-d for Land Conveyance and Transfer for Sewage Treatment Facility Area

This report summarizes the sampling design used, associated statistical assumptions, as well as general guidelines for conducting post-sampling data analysis. Sampling plan components presented here include how many sampling locations to choose and where within the sampling area to collect those samples. The type of medium to sample (i.e., soil, groundwater, etc.) and how to analyze the samples (in-situ, fixed laboratory, etc.) are addressed in other sections of the sampling plan.

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Analysis of Samples Collected from the Surface of Interim Storage Canisters at Calvert Cliffs in June 2017: Revision 01.

In June 2017, dust and salt samples were collected from the surface of Spent Nuclear Fuel (SNF) dry storage canisters at the Calvert Cliffs Nuclear Power Plant. The samples were delivered to Sandia National laboratories for analysis. Two types of samples were collected: filter-backed Scotch-Brite TM pads were used to collect dry dust samples for characterization of salt and dust morphologies and distributions; and Saltsmart TM test strips were used to collect soluble salts for determining salt surface loadings per unit area. After collection, the samples were sealed into plastic sleeves for shipping. Condensation within the sleeves containing the Scotch-Brite TM samples remobilized the salts, rendering them ineffective for the intended purpose, and also led to mold growth, further compromising the samples; for these reasons, the samples were not analyzed. The SaltSmart TM samples were unaffected and were analyzed by ion chromatography for major anions and cations. The results of those analyses are presented here.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Identification and Shipment Progress of the INL and LANL Samples to Be Received at ORNL

Ferritic-martensitic steel Grade 92, with T91 as a reference, together with austenitic stainless steel (or Incoloy Alloy) 800H and its grain-boundary-engineered version 800H-TMP (ThermoMechanical Processing), is investigated in this project. A total of fifteen Grade 92 samples from two or three heats, four T91 samples from two heats, and six 800H and six 800H-TMP samples from one heat were selected, which were primarily irradiated in the Advanced Test Reactor of Idaho National Laboratory (INL), with the rest in the High Flux Isotope Reactor of Oak Ridge National Laboratory (ORNL), BOR-60 of Russia, and Phénix reactor of France. The samples were irradiated in the temperature range of 241 to 720°C and a dose range of 1.28 to ~70 displacements per atom. All the INL samples, most of the ORNL samples, and part of the LANL (Los Alamos National Laboratory) samples from the ATR, BOR-60 and Phénix reactors have been received at the Irradiated Materials Examination and Testing (IMET) hot cell facility and Low Activation Materials Design and Analysis (LAMDA) laboratory of ORNL. Post-irradiation examination of the received samples is in progress at ORNL. The effects of irradiation temperature, dose, reactor (e.g., dose rate, neutron-spectrum-induced difference in transmutation), TMP, and heats variation on the microstructures and mechanical properties of the samples will be evaluated.

36 MATERIALS SCIENCE↗

Analysis of Tank 30H (HTF-30-19-33, -34), Tank 32H (HTF-32-19-35, -36), and Tank 37H (HTF-37-19-53, -54) Samples for Support of the Evaporator Feed Qualification and Corrosion Control Programs for the 3H-Evaporator

SRNL analyzed samples from Tank 30H, Tank 32H, and Tank 37H to support the Evaporator Feed Qualification and Corrosion Control Programs for the 3H-Evaporator system. The six samples from Tanks 30H, 32H, and 37H all contain highly concentrated salt solutions with sodium concentrations ranging from 13.8 M to 16.9 M. Hydroxide is the dominant anion in all of the samples followed by nitrate and nitrite. The preponderance of the analytical determinations (density, anions, cations) on all three tanks show slightly higher concentrations of solute in the sub-surface sample than in the surface sample, indicating some stratification within the tanks. With the exception of the Tank 30H VDS, all of the samples are somewhat more concentrated compared with the compositions of the previous samples. The sum of the major cations versus the sum of the major anions show a difference of <5% for all of the samples indicating good data quality for the non-radioactive analytes in the table. The silicon concentrations measured in the VDS and surface samples from Tank 30H, Tank 32H, and Tank 37H were all below detection.

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Analysis of Tank 30H (HTF-30-19-33, -34), Tank 32H (HTF-32-19-35, -36), and Tank 37H (HTF-37- 19-53, -54) Samples for Support of the Evaporator Feed Qualification and Corrosion Control Programs for the 3H-Evaporator

SRNL analyzed samples from Tank 30H, Tank 32H, and Tank 37H to support the Evaporator Feed Qualification and Corrosion Control Programs for the 3H-Evaporator system. The six samples from Tanks 30H, 32H, and 37H all contain highly concentrated salt solutions with sodium concentrations ranging from 13.8 M to 16.9 M. Hydroxide is the dominant anion in all of the samples followed by nitrate and nitrite. The preponderance of the analytical determinations (density, anions, cations) on all three tanks show slightly higher concentrations of solute in the sub-surface sample than in the surface sample, indicating some stratification within the tanks. With the exception of the Tank 30H VDS, all of the samples are somewhat more concentrated compared with the compositions of the previous samples. The sum of the major cations versus the sum of the major anions show a difference of <5% for all of the samples indicating good data quality for the non-radioactive analytes in the table. The silicon concentrations measured in the VDS and surface samples from Tank 30H, Tank 32H, and Tank 37H were all below detection.

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High-Dimensional Spectral Sampling

A wide variety of applications in science and engineering depend on effectively and efficiently exploring high- dimensional parameter spaces. Common examples are uncertainty quantification, inverse problems, or various optimization approaches. In such applications, the first step is to create an initial uniform, random sampling of the space to create a baseline of knowledge. The simulations evaluated at these samples are then used for subsequent processing. In its most generic form, the goal of sampling is to produce the maximal amount of information with the minimal number of samples. However, despite being the first step and thus influencing the performance of the entire workflow, the quality of the initial sample designs is rarely analyzed or optimized. This project develops a new spectral sampling theory for analyzing and creating experiment designs in high-dimensional spaces. Further, new algorithms for estimating sample properties and sample synthesis are designed. Finally, applications of the proposed spectral sampling tools in surrogate modeling, scientific machine learning and image analysis are presented.

97 MATHEMATICS AND COMPUTING↗

Solvent Hold Tank Sample Results for MCU-19-2-3-4 (January 2019), MCU-19-83-84-85 (February 2019), MCU-19-208-209-210 (March 2019) and MCU-19-138-139-140 (March special trim): Quarterly Report

A trend summary of three sets of Solvent Hold Tank (SHT) monthly samples (MCU-19-2-3-4, MCU-19-83-84-85, MCU-19-208-209-210); and a set from a special trim (MCU-19-138-139-140) are reported. Most of the conclusions are based on the March SHT sample (MCU-18-208-209-210). Analyses of the March SHT sample (MCU-19-208-209-210) indicated that the Modifier (Cs-7SB) and the Extractant (MaxCalix) concentrations were below their nominal recommended concentrations (169,000 mg/L and 46,900 mg/L, respectively) by 3% and 6%, respectively. The Suppressor (N,N’,N”–tris(3,7-dimethyloctyl)guanidine or TiDG) concentration has increased since the January 2019 measurement to 1141 mg/L, which is above the minimum recommended concentration (479 mg/L). These new concentrations are consistent with the concentrations observed when MCU was fully operational in 2016. The Semi-Volatile Organic Analysis (SVOA) did not detect any impurities. However, the Fourier Transform Hydrogen Nuclear Magnetic Resonance (FT-HNMR) analysis detected presence of phthalates at a few ppm. The impurity concentration was highest in the January sample and consistently detected in the February and March samples (but always registered as a few ppm or less). Another impurity observed in the samples was mercury. Based on the March SHT sample, up to 25 ± 5 micrograms of mercury per mL of solvent was detected (as the average of the Direct Mercury Analysis (DMA) and X-Ray Fluorescence (XRF) methods). The higher mercury concentration in the solvent (as determined in the last three-monthly samples) is possibly due to the higher mercury concentration in Salt Batches 9 and 10. The gamma concentration (~2.55E5 dpm/mL) measured in the March 2019 SHT samples was consistent with previous values observed when MCU was operating continuously (for example, between December 2016 and January 2017). Statistical analysis of the different analytical methods detected a bias (a statistical difference at 5% level) between the FT-HNMR and HPLC methods when measuring the MaxCalix and Modifier concentration; the FT-HNMR gave a higher concentration possibly due to peak overlapping in the measured data. A bias was also detected when measuring total mercury by the DMA method versus the XRF method with the XRF method reported higher mercury concentrations. The laboratory will continue to monitor the quality of the solvent for any new impurities or degradation of the solvent components.

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Solvent Hold Tank Sample Results for MCU-19-366- 367-368 (April 2019), MCU-19-469-470-471 (May 2019), MCU-19-524-525-526 (June 2019): Quarterly Report

A trend summary of three sets of Solvent Hold Tank (SHT) monthly samples MCU-19-366-367-368 (April), MCU-19-469-470-471 (May), and MCU-19-524-525-526 (June) are reported. Most of the conclusions are based on the June SHT sample (MCU-19-524-525-526). Analyses of the June SHT sample (MCU-19-524- 525-526) indicated that the Modifier (Cs-7SB) and the Extractant (MaxCalix) concentrations were below their nominal recommended concentrations (169,000 mg/L and 46,900 mg/L respectively) by 4% and 2% respectively but consistent with previously observed levels during normal runs. The Suppressor (N,N’,N”– tris(3,7-dimethyloctyl)guanidine or TiDG) concentration has decreased since the March 2019 measurement to 793 mg/L, which is above the minimum recommended concentration (479 mg/L). The Semi-Volatile Organic Analysis (SVOA) did not detect any impurities. However, the Fourier Transform Hydrogen Nuclear Magnetic Resonance (FT-HNMR) analysis detected presence of phthalates at a few ppm. The impurity concentration was highest in the April sample and consistently detected in the May and June samples (but always registered as a few ppm or less). Another impurity observed in the samples was mercury. Based on the June SHT sample, up to 25 ± 5 micrograms of mercury per mL of solvent was detected (as the average of the Direct Mercury Analysis (DMA) and X-Ray Fluorescence (XRF) methods). The higher mercury concentration in the solvent (as determined in the last three-monthly samples) is possibly due to the higher mercury concentration in Salt Batches 9 and 10. The gamma concentration (~2.90E4 dpm/mL) measured in the June 2019 SHT samples was consistent with previous values observed when the Modular Caustic-Side Solvent Extraction Unit (MCU) was operating continuously (for example, between December 2016 and January 2017). Statistical analysis of the different analytical methods detected a bias between the FT-HNMR and the High Performance Liquid Chromatography (HPLC) methods when measuring the MaxCalix and Modifier concentrations; the FT-HNMR gave a higher concentration possibly due to peak overlapping in the measured data. A bias was detected when measuring total mercury by the DMA method versus the XRF method with the XRF method reported higher mercury concentrations. The laboratory will continue to monitor the quality of the solvent for any new impurities or degradation of the solvent components.

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Solvent Hold Tank Sample Results for MCU-19-569-571 (December 2019), MCU-20-1-28 (January 2020), and MCU-20-29-30-31 (June 2020) (Quarterly Report)

A trend summary of three Solvent Hold Tank (SHT) monthly samples MCU-19-569-570-571 (December 2019), MCU-20-1-28 (January 2020), and MCU-20-29-30-31 (June 2020) are reported. Most of the conclusions are based on the June 2020 SHT sample (MCU-20-29-30-31). Analyses of the June 2020 SHT sample indicated that the Modifier (Cs-7SB) and the Extractant (MaxCalix) concentrations were above their nominal recommended concentrations (169,000 mg/L and 46,900 mg/L respectively) by 6% and 7% respectively. The Suppressor (N,N’,N”–tris(3,7-dimethyloctyl)guanidine or TiDG) concentration has remained at 833 ± 16 mg/L, but it is above the minimum recommended concentration (479 mg/L). The Semi-Volatile Organic Analysis (SVOA) and FT-HNMR did not detect any organic impurities. Another impurity observed in the samples was mercury. Based on the June 2020 SHT sample, up to 23 ± 5 micrograms of mercury per gram of solvent (or 19 ± 4 mg/L) was detected. The mercury concentration steadily decreased from 34.8 ug/g solvent (or 21.9 mg/L) in the December 2019 SHT sample to 34.8 ug/g solvent (or 19 mg/L) in the June 2020 SHT sample. The gamma concentration (~3.33E4 dpm/mL) measured in the June 2020 SHT samples was consistent with previous values observed when MCU was idle (for example, between February 2017 and August 2017). If additional SHT samples become available, the laboratory will continue to monitor the quality of the solvent for any new impurities or degradation of the solvent components.

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Reference document for LANL stack sampling and ANSI N13.1 (Article) Gielow RL and McNamee MR 1993. Numerical Flue Gas Flow Modeling for Continuous Emissions Monitoring Applications. EPRI CEM Users Group Meeting. Baltimore. RP1961-13

American National Standard N13.1 “sets forth guidelines and performance criteria for sampling the emissions of airborne radioactive substances in the air discharge ducts and stacks of nuclear facilities. Emphasis is on extractive sampling from a location in a stack or duct where the contaminant is well mixed. At such a location, sampling may be conducted at a single point. This standard provides performance-based criteria for the use of air sampling probes, transport lines, sample collectors, sample monitoring instruments, and gas flow measuring methods. This standard also covers sampling program objectives, quality assurance issues, developing air sampling action levels, system optimization, and system performance verification. Workplace, containment, and environmental air monitoring are not addressed. Specific sample analysis methods and the reporting or interpreting of results are also not addressed.” (HPS 2011).

61 RADIATION PROTECTION AND DOSIMETRY↗

Soil Sampling Results for Closure of a Portion of Solid Waste Management Unit #16

The U.S. Department of Energy/National Nuclear Security Administration (DOE/ NNSA) and National Technology & Engineering Solutions of Sandia, LLC (NTESS), the management and operating contractor for Sandia National Laboratories/California (SNL/CA), has prepared this soil sampling results report for closure of a portion of Solid Waste Management Unit (SWMU) #16. The entire network of SNL/CA sanitary sewer lines, including building laterals, was identified as SWMU #16 under a Resource Conservation and Recovery Act (RCRA) Facility Assessment conducted for SNL/CA in April 1991 (DOE 1992). Along with the previous SWMU #16 investigation results (SNL/CA 2019), the results of this investigation are intended to support closure decisions by the San Francisco Bay Regional Water Quality Control Board (RWQCB), as discussed below. SNL/CA personnel completed upgrading its sanitary sewer discharge network in 2019. These upgrades included installing new sections of underground lines and decommissioning certain sections of the old piping system by capping in place. To date, several sections of the sewer line have been abandoned-in-place by capping as new sewer lines were installed or flow was rerouted to other existing lines. To formally close these abandoned sections of the sewer line, the RWQCB required that SNL/CA personnel collect soil samples to be analyzed for contaminants potentially released from the sewer lines. SNL/CA personnel hired Weiss Associates (Weiss) of Emeryville, California to prepare a sampling and analysis plan, implement the sampling plan and report the results of the investigation under Purchase Order #2166257. The Sampling and Analysis Plan for Partial Closure of Solid Waste Management Unit #16 (SAP) was submitted to the RWQCB on August 14, 2020 by Weiss on behalf of SNL/CA. The RWQCB approved the SAP on September 30, 2020 after Weiss updated the method detection limit and reporting limits for total polychlorinated biphenyls (PCBs) and individual aroclors. Soil sampling was conducted in accordance with the SAP except that fewer locations were sampled due to site constraints, as discussed below. This report presents the results of the sampling effort and documents all associated field activities including borehole clearing, soil sample collection, storage and transportation to the analytical laboratories, borehole backfilling and surface restoration, and storage of investigation-derived waste (IDW) for future profiling and disposal by SNL/CA waste management personnel.

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Development of Surface Sampling Techniques for the Canister Deposition Field Demonstration (FY22 Update)

This report describes the proposed surface sampling techniques and plan for the multi-year Canister Deposition Field Demonstration (CDFD). The CDFD is primarily a dust deposition test that will use three commercial 32PTH2 NUHOMS welded stainless steel storage canisters in Advanced Horizontal Storage Modules, with planned exposure testing for up to 10 years at an operating ISFSI site. One canister will be left at ambient condition, unheated; the other two will have heaters to achieve canister surface temperatures that match, to the degree possible, spent nuclear fuel (SNF) loaded canisters with heat loads of 10 kW and 40 kW. Surface sampling campaigns for dust analysis will take place on a yearly or bi-yearly basis. The goal of the planned dust sampling and analysis is to determine important environmental parameters that impact the potential occurrence of stress corrosion cracking on SNF dry storage canisters. Specifically, measured dust deposition rates and deposited particle sizes will improve parameterization of dust deposition models employed to predict the potential occurrence and timing of stress corrosion cracks on the stainless steel SNF canisters. The size, morphology, and composition of the deposited dust and salt particles will be quantified, as well as the soluble salt load per unit area and the rate of deposition, as a function of canister surface temperature, location, time, and orientation. Previously, a preliminary sampling plan was developed, identifying possible sampling locations on the canister surfaces and sampling intervals; possible sampling methods were also described. Further development of the sampling plan has commenced through three different tasks. First, canister surface roughness, a potentially important parameter for air flow and dust deposition, was characterized at several locations on one of the test canisters. Second, corrosion testing to evaluate the potential lifetime and aging of thermocouple wires, spot welds, and attachments was initiated. Third, hand sampling protocols were developed, and initial testing was carried out. The results of those efforts are presented in this report. The information obtained from the CDFD will be critical for ongoing efforts to develop a detailed understanding of the potential for stress corrosion cracking of SNF dry storage canisters.

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Analysis of Tank 38H (HTF-38-24-53, -56) and Tank 43H (HTF-43-24-54, -55) Samples for Support of the Enrichment Control and Corrosion Control Programs

Savannah River National Laboratory analyzed samples from Tank 38H and Tank 43H to support the Enrichment Control Program (ECP) and Corrosion Control Program (CCP). The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased from the previous Tank 38H surface sample. The current Tank 38H subsurface sample shows similar Na, free hydroxide, and anions in comparison to the previous subsurface sample. However, the 38H subsurface sample shows lower concentrations of Al, Ca, Fe, Mn, and Si in comparison to the previous Tank 38H subsurface sample. Measurement of the wt.% insoluble solids in the Tank 38H subsurface sample and associated uncertainty analysis indicates that the calculated average wt.% insoluble solids is 0.45 ± 0.75 wt.%. Significant differences in the concentrations of major components between the Tank 38H surface and subsurface samples indicate significant stratification of solution species between these two locations within Tank 38H.

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