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Analytical Needs in a Sample Receiving Facility: Input from the MSR Operation Definition Team

The return of scientifically selected samples from Mars would provide a rare opportunity forinvestigation with the full range of the latest technology available, but to take full advantageof this opportunity, it is important to plan ahead to ensure the pristine nature of the samplesupon arrival within the Earth environment until scientific investigations can begin.The NASA/ESA science community-driven MSR Science Planning Group – Phase 2 (MSPG2)delivered recommendations and guidance regarding curation (1) and science (2, 3) activities tobe performed on the samples under containment. High-level requirements for the infrastruc-ture were also developed by MSPG2 (4). In order to prepare infrastructure-targeted input forthe ESA and NASA facility studies planned in the 2022-2023 timeframe, the agency-led MSROperational Scenarios Definition Team (MOSDT) was assembled to conceptualize the sampleoperations that will inform future architecture teams. Emphasis was placed on the respon-sibility of MOSDT to use community-defined requirements and to represent the view of the international scientific community.All necessary and sufficient instruments and analytical needs described in MSPG2 were inte-grated in MOSDT main deliverable, the operational workflow (see Hays et al, this conference).In MSPG2, notional instruments were split between curation analytical needs, and objective-driven (time-sensitive and sterilization-sensitive) science analytical needs. In MOSDT, whilethe first phases of curation, “pre-Basic Characterization” and “Basic Characterization” wererather streamlined and separate from other analytical needs, “Preliminary Examination” and“Science” instruments were not always physically segregated. In addition to the necessary andsufficient instruments described by MSPG2, the MOSDT recommended additional supportequipment for sterilization, cleanliness and contamination monitoring.It was sometimes necessary for the MOSDT to rely on assumptions to integrate instruments inthe activity workflow. In general, the assumptions were very conservative to limit contaminationand cross-contamination risks. It is expected that future work to refine limits of contaminationwill enable optimization of instrumentation.The community was consulted during the course of the MOSDT work. This abstract’s aimis two-fold: on one hand, inform the scientific community and overall MSR stakeholders, tobring their attention on the analytical needs currently considered as necessary and sufficient;on the other hand, to solicit feedback from a larger community audience to optimize and refineanalytical needs during the next phases of MSR ground-segment preparation.Disclaimer: The decision to implement Mars Sample Return will not be finalized until NASA’scompletion of the program’s National Environmental Policy Act (NEPA) process. This docu-ment is being made available for informational purposes only.[1] Tait et al. (2021) Preliminary planning for Mars Sample Return (MSR) curation activities ina Sample Receiving Facility (SRF). Astrobiology in press, doi:10.1089/ast.2021.0105. [2] Toscaet al. (2021) Time-sensitive aspects of Mars Sample Return (MSR) science. Astrobiologyin press, doi:10.1089/ast.2021.0115. [3] Velbel et al. (2021) Planning implications relatedto sterilization-sensitive science investigations associated with Mars Sample Return (MSR).Astrobiology in press, doi:10.1089/ast.2021.0113. [4] Carrier et al. (2021) Science and curationconsiderations for the design of a Mars Sample Return (MSR) Sample Receiving Facility (SRF).Astrobiology in press, doi:10.1089/ast.2021.0110.

Mars Sample Return↗

DOE OSTI2021

WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021 Version 2.0

This submission includes an update to the WHOLESCALESamples2021January.xls file where the strikes and dips initially reported have been corrected to comply with the right hand rule. The updated excel file and a link to the original submission are included in this report. The original submission "WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021" contains information on thirty-six rock samples collected from San Emidio, Nevada during January, 2021 for Subtask 2.3 of the WHOLESCALE project. The following resources include a .zip of rock sample photos taken in the field, a .zip of rock sample photos taken in the laboratory at UW-Madison, and an excel catalog of rock samples with information on sample name, rock type, coordinates of sample location, structural measurements, field notes, observations for plug preparation (e.g., weathering, ability to be cut and cored), and rock descriptions. It should be noted that not every sample was photographed in the field. Names and descriptions of rock formation units are taken from Rhodes et al. (2011). The README.txt file is a description of this submission.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Evaluating various composite sampling modes for detecting pathogenic SARS-CoV-2 virus in raw sewage

Inadequate sampling approaches to wastewater analyses can introduce biases, leading to inaccurate results such as false negatives and significant over- or underestimation of average daily viral concentrations, due to the sporadic nature of viral input. To address this challenge, we conducted a field trial within the University of Tennessee residence halls, employing different composite sampling modes that encompassed different time intervals (1 h, 2 h, 4 h, 6 h, and 24 h) across various time windows (morning, afternoon, evening, and late-night). Our primary objective was to identify the optimal approach for generating representative composite samples of SARS-CoV-2 from raw wastewater. Utilizing reverse transcription-quantitative polymerase chain reaction, we quantified the levels of SARS-CoV-2 RNA and pepper mild mottle virus (PMMoV) RNA in raw sewage. Our findings consistently demonstrated that PMMoV RNA, an indicator virus of human fecal contamination in water environment, exhibited higher abundance and lower variability compared to pathogenic SARS-CoV-2 RNA. Significantly, both SARS-CoV-2 and PMMoV RNA exhibited greater variability in 1 h individual composite samples throughout the entire sampling period, contrasting with the stability observed in other time-based composite samples. Through a comprehensive analysis of various composite sampling modes using the Quade Nonparametric ANCOVA test with date, PMMoV concentration and site as covariates, we concluded that employing a composite sampler during a focused 6 h morning window for pathogenic SARS-CoV-2 RNA is a pragmatic and cost-effective strategy for achieving representative composite samples within a single day in wastewater-based epidemiology applications. This method has the potential to significantly enhance the accuracy and reliability of data collected at the community level, thereby contributing to more informed public health decision-making during a pandemic.

sampling timing↗

DOE OSTI2019

Effect of Cesium Substitution on the Superconducting Properties of Bi-2212 Samples Prepared Via Solid-State Reaction and Laser Floating Zone Technique

In this work, the effect of cesium substitution on the structural and superconducting properties of Bi{sub 2}Sr{sub 2}Ca{sub 1-x}Cs{sub x}Cu{sub 2}O{sub +y} (where x = 0.0, 0.025, 0.050, 0.075, 0.10, 0.125, and 0.15) samples prepared by the solid-state reaction route and by directional growth using the laser floating zone (LFZ) technique has been studied. X-ray diffraction has shown that both kinds of samples present the 2212 phase as the major one, with pseudo tetragonal structure, accompanied by minor amounts of (Sr,Ca)CuO{sub 2} and Bi{sub 2}(Sr,Ca){sub 4}O{sub 6 + d} secondary phases. SEM-EDX results indicate that Bi-2212 phase is the major one, with small amounts of secondary phases. Cs substitution diminishes the size and content of secondary phases. Magnetization measurements reflect different behavior for sintered and LFZ grown samples. Although the diamagnetic transition is very wide for the former samples, it is very sharp for the last ones. The critical onset temperatures, T{sub C}, are around 80 and 90 K, for sintered and LFZ grown samples, respectively. Moreover, M–H measurements indicate that LFZ grown samples exhibit larger areas than the sintered ones. The intragranular critical current, J{sub C}, calculated from the M–H loops and Bean’s formula, is maximum for x = 0.025Cs sintered and x = 0.05Cs LFZ grown samples. The maximum pinning forces, F{sub Pmax}, determined in these samples are higher than those obtained in undoped ones, reaching 9 × 10{sup 7} Oe*A/cm{sup 2} and 10 × 10{sup 8} Oe*A/cm{sup 2}, at 10 K, for sintered and LFZ grown samples, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

A sample holder for simultaneous Raman and neutron vibrational spectroscopy

We have built a sample holder (called a center stick or sample stick) for performing simultaneous Raman and neutron vibrational spectroscopy on samples of material at the VISION neutron vibrational spectrometer of the Spallation Neutron Source at Oak Ridge National Laboratory. This equipment holds material samples in the neutron beam within the cryogenic environment of the VISION spectrometer, allowing for samples to be studied at temperatures as low as 5 K. It also provides the capability for gas to be loaded to or evacuated from the sample while it is loaded at VISION. The optical components for directing and filtering light are located within the cryogenic volume, in physical proximity to the sample. We describe the construction of this sample holder and discuss our first measurements of simultaneous Raman and neutron vibrational spectra. Here, the samples that we report on were of 4-nitrophenol at a temperature of 20 K and of cryogenic hydrogen of a number of different orthohydrogen fractions.

4-nitrophenol↗

DOE OSTI2025

Three-Dimensional Heat Flux and Thermal Analysis of Angled Tungsten Samples on DIII-D

ITER-grade tungsten and dispersoid-strengthened tungsten samples with the top surface angled at ~15° towards the incident plasma flux were exposed to 9 H-mode discharges with edge-localized modes (ELMs) in the lower divertor of DIII-D tokamak using the Divertor Material Evaluation System (DiMES). Surface damage included cracking and flaking of material on the two samples farthest away from the plasma strike point, and significant melting of the two samples closest to the strike point. Heat flux and thermal analysis tools new to DIII-D have been applied to better understand this material response and to help optimize the exposure conditions for future experiments. SMITER field-line tracing simulations based on IRTV data and EFIT equilibria estimate an average inter-ELM perpendicular heat flux, 𝑞⊥,𝑖nter−𝐸LM , on the angled surfaces of 10.1 – 19.6 MW/m² for a majority of the 9 discharges, increasing to 15.6 – 24.5 MW/m² for the single, higher-power shot where samples melted. Fast camera data showed shallow intra-ELM melting and re-solidification, which transitioned to bulk inter-ELM melting with melt motion in the 𝐽⃗ 𝑥 𝐵⃗ direction. About 50% of the protruding volume of the most affected sample was displaced via melt-motion. SIERRA thermal modeling software was able to reproduce an onset time of melting consistent with fast camera data and final sample conditions, within < 200 ms. Maximum surface temperatures of 3122 K and 2787 K are estimated for the samples farthest away from the strike point, while the closest samples achieve melting at 4067 ms and 4750 ms into the ~5000 ms plasma exposure. A +10% increase in both the SMITER 𝑞⊥,𝑖nter−𝐸LM calculations and the estimated ELM heat loads 𝑞⊥, 𝐸LM was required to achieve this result, which is within the uncertainty of the diagnostic data but likely accounts for non-ideal geometry effects plus other physics uncertainties not included in this first iteration of modeling. This work provided valuable estimates of the 3D temperature evolution to help better understand the observed surface morphology and internal recrystallization of samples, which are discussed in detail in a complementary manuscript [1]. Benchmarking efforts with more diagnosed DIII-D experiments are underway to further refine the SMITER and SIERRA models for DiMES. Future use of these tools will enable researchers to precisely target heat flux exposure conditions in DIII-D to test, but not exceed, the thermomechanical limitations of novel plasma-facing materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

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↗

DOE OSTI2021

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↗

DOE OSTI2018

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↗

DOE OSTI2020

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↗

DOE OSTI2014

Results of stainless steel canister corrosion studies and environmental sample investigations

This progress report describes work being done at Sandia National Laboratories (SNL) to assess the localized corrosion performance of container/cask materials used in the interim storage of used nuclear fuel. The work involves both characterization of the potential physical and chemical environment on the surface of the storage canisters and how it might evolve through time, and testing to evaluate performance of the canister materials under anticipated storage conditions. To evaluate the potential environment on the surface of the canisters, SNL is working with the Electric Power Research Institute (EPRI) to collect and analyze dust samples from the surface of in-service SNF storage canisters. In FY 13, SNL analyzed samples from the Calvert Cliffs Independent Spent Fuel Storage Installation (ISFSI); here, results are presented for samples collected from two additional near-marine ISFSI sites, Hope Creek NJ, and Diablo Canyon CA. The Hope Creek site is located on the shores of the Delaware River within the tidal zone; the water is brackish and wave action is normally minor. The Diablo Canyon site is located on a rocky Pacific Ocean shoreline with breaking waves. Two types of samples were collected: SaltSmart™ samples, which leach the soluble salts from a known surface area of the canister, and dry pad samples, which collected a surface salt and dust using a swipe method with a mildly abrasive ScotchBrite™ pad. The dry samples were used to characterize the mineralogy and texture of the soluble and insoluble components in the dust via microanalytical techniques, including mapping X-ray Fluorescence spectroscopy and Scanning Electron Microscopy. For both Hope Creek and Diablo Canyon canisters, dust loadings were much higher on the flat upper surfaces of the canisters than on the vertical sides. Maximum dust sizes collected at both sites were slightly larger than 20 μm, but Phragmites grass seeds ~1 mm in size, were observed on the tops of the Hope Creek canisters. At both sites, the surface dust could be divided into fractions generated by manufacturing processes and by natural processes. The fraction from manufacturing processes consisted of variably-oxidized angular and spherical particles of stainless steel and iron, generated by machining and welding/cutting processes, respectively. Dust from natural sources consisted largely of detrital quartz and aluminosilicates (feldspars and clays) at both sites. At Hope Creek, soluble salts were dominated by sulfates and nitrates, mostly of calcium. Chloride was a trace component and the only chloride mineral observed by SEM was NaCl. Chloride surface loads measured by the Saltsmart™ sensors were very low, less than 60 mg m –2 on the canister top, and less than 10 mg m –2 on the canister sides. At Diablo Canyon, sea-salt aggregates of NaCl and Mg-SO 4 , with minor K and Ca, were abundant in the dust, in some cases dominating the observed dust assemblage. Measured Saltsmart™ chloride surface loads were very low (<5 mg m –2 ); however, high canister surface temperatures damaged the Saltsmart™ sensors, and, in view of the SEM observations of abundant sea-salts on the package surfaces, the measured surface loads may not be valid. Moreover, the more heavily-loaded canister tops at Diablo Canyon were not sampled with the Saltsmart™ sensors. The observed low surface loads do not preclude chloride-induced stress corrosion cracking (CISCC) at either site, because (1) the measured data may not be valid for the Diablo Canyon canisters; (2) the surface coverage was not complete (for instance, the 45º offset between the outlet and inlet vents means that near-inlet areas, likely to have heavier dust and salt loads, were not sampled); and (3) CISCC has been experimentally been observed at salt loads as low as 5-8 mg/m 2 . Experimental efforts at SNL to assess corrosion of interim storage canister materials include three tasks in FY14. First, a full-diameter canister mockup, made using materials and techniques identical to those used to make interim storage canisters, was designed and ordered from Ranor Inc., a cask vendor for Areva/TN. The mockup will be delivered prior to the end of FY14, and will be used for evaluating weld residual stresses and degrees of sensitization for typical interim storage canister welds. Following weld characterization, the mockup will be sectioned and provided to participating organizations for corrosion testing purposes. A test plan is being developed for these efforts. In a second task, experimental work was carried out to evaluate crevice corrosion of 304SS in the presence of limited reactants, as would be present on a dustcovered storage canister. This work tests the theory that limited salt loads will limit corrosion penetration over time, and is a continuation of work carried out in FY13. Laser confocal microscopy was utilized to assess the volume and depth of corrosion pits formed during the crevice corrosion tests. Results indicate that for the duration of the current experiments (100 days), no stifling of corrosion occurred due to limitations in the amount of reactants present at three different salt loadings. Finally, work has been carried out this year perfecting an instrument for depositing sea-salts onto metal surfaces for atmospheric corrosion testing purposes. The system uses an X-Y plotter system with a commercial airbrush, and deposition is monitored with a quartz crystal microbalance. The system is capable of depositing very even salt loadings, even at very low total deposition rates.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

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.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

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.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

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↗

DOE OSTI2019

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↗

DOE OSTI2019

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.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

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

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

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↗