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At least 1,315 records · Page 73

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Greg Schuster↗

Analysis of Conservation Voltage Reduction under Inverter-Based VAR-Support [Slides]

Conservation voltage reduction (CVR) is a common technique used by utilities to strategically reduce demand during peak periods. As penetration levels of distributed generation (DG) continue to rise and advanced inverter capabilities become more common, it is unclear how the effectiveness of CVR will be impacted and how CVR interacts with advanced inverter functions. In this work, we investigated the mutual impacts of CVR and DG from photovoltaic (PV) systems (with and without autonomous Volt-VAR enabled). The analysis was conducted on an actual utility dataset, including a feeder model, measurement data from smart meters and intelligent reclosers, and metadata for more than 30 CVR events triggered by the utility over the year. The installed capacity of the modeled PV systems represented 66% of peak load, but reached instantaneous penetrations reached up to 2.5x the load consumption over the year. While the objectives of CVR and autonomous Volt-VAR are opposed to one another, this study found that their interactions were mostly inconsequential since the CVR events occurred when total PV output was low.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Refining Principal Stress Measurements in Reservoir Underburden in Regions of Induced Seismicity through Seismological Tools, Laboratory Experiments - Final Technical Report

This project developed methodologies to measure the in-situ principal stress in the deep subsurface through use of multiple independent, but complementary, seismic methods, laboratory verification, and development of theoretical frameworks. By leveraging existing regional and local datasets we developed, tested, and refined a set of diagnostic tools for determining the in-situ stress state with reduced uncertainty at and below reservoir depths (1.5-6 km). A set of novel tools was produced that are scale independent, such that their utility is equivalent on regional, field scale, and near borehole monitoring of principal stresses in reservoir underburden for carbon storage projects. During a 4-year Department of Energy (DOE) and Southern Company funded project, carried out by the Electric Power Research Institute (EPRI), Lawrence Livermore National Laboratory (LLNL), the University of Oklahoma (OU), and the U.S. Geological Survey (USGS), the project team developed methodologies to measure the far-field in-situ principal stress in the deep subsurface, leveraging induced seismicity data from waste-water disposal projects. These methodologies consisted in the use of well-established and technically advanced seismic processing methods, such as virtual seismometer method-moment tensor (VSM-MT) and shear wave splitting (SWS), that are adept at recovering the stress orientation and certain components of the stress tensor. These methods were applied to robust seismicity catalogs created with matched filter techniques near sites of active fluid disposal—a proxy for carbon storage sites where such datasets are more limited. Estimates of the stress orientation made with seismic processing tools were considered along with laboratory acoustic emission experiments conducted on rock samples from the region of interest. Stress orientations in the studied region do not vary significantly across distances of ~100 km, nor are they found to rotate through time as a consequence of local wastewater disposal, as previously speculated. Finally, the project team investigated the trade-offs among the different seismic methods and evaluated the range of uncertainty that is generated with these methodologies, which led to a practical use and refinement of the VSM-MT technique when it is applied to field datasets. Understanding the trade-offs between these different methods highlighted the potential benefits of improved quantification of uncertainties on stress field estimations.

58 GEOSCIENCES↗

2022 AI Testbed Expeditions Report

By exploiting the coherent properties of a light source, coherent diffraction imaging (CDI) is able to obtain the sample image at a nanoscale resolution using the measured diffraction pattern. Bragg Coherent Diffraction Imaging (BCDI) has become valuable for recovering the displacement and strain field of crystals, providing a valuable tool in material science and solid-state physics. X-ray ptychography is another emerging CDI technique that can produce a high-resolution image of the extended sample and has become popular in many research areas (e.g., materials science, biology, electronics, and optics characterization). CDI including BCDI and ptychography has become an established technique in Synchrotron Facilities including the Advanced Photon Source (APS) and will greatly benefit from the 100x coherent flux increase of the upcoming APS Upgrade (APSU). The current image formation process in CDI employs iterative phase retrieval algorithms, which is a time-consuming and computationally expensive process. Especially after APSU, the traditional iterative methods will not be able to match the experimental data acquisition speed. We employ deep learning (DL) approach to replace the iterative approaches, therefore allowing hundreds of times faster recovery of the object. We developed AutoPhaseNN, a DL-based approach which learns to solve the inverse problem without labeled data. Taking 3D BCDI as a representative technique, AutoPhaseNN has been demonstrated to be one hundred times faster than traditional iterative phase retrieval methods while providing comparable image quality. The current network is trained with 64 x 64 x 64 data size, to achieve higher resolution imaging, we will need to scale the network to input and train/infer 3D arrays of size 256 x 256 x 256 (today) and of size 2560x2560x2560 (APSU). However, the scalability of the network is restricted due to the memory-intensive training process. To perform the training for a 256 x 256 x 256 data size, the required memory exceeds the capacity of the current machine. In this project, we explore using Sambanova system to train the network for the direct data inversion for CDI.

36 MATERIALS SCIENCE↗

Advanced electromagnetic methods for aerospace vehicles

The Advanced Helicopter Electromagnetics is centered on issues that advance technology related to helicopter electromagnetics. Progress was made on three major topics: composite materials; precipitation static corona discharge; and antenna technology. In composite materials, the research has focused on the measurements of their electrical properties, and the modeling of material discontinuities and their effect on the radiation pattern of antennas mounted on or near material surfaces. The electrical properties were used to model antenna performance when mounted on composite materials. Since helicopter platforms include several antenna systems at VHF and UHF bands, measuring techniques are being explored that can be used to measure the properties at these bands. The effort on corona discharge and precipitation static was directed toward the development of a new two dimensional Voltage Finite Difference Time Domain computer program. Results indicate the feasibility of using potentials for simulating electromagnetic problems in the cases where potentials become primary sources. In antenna technology the focus was on Polarization Diverse Conformal Microstrip Antennas, Cavity Backed Slot Antennas, and Varactor Tuned Circular Patch Antennas. Numerical codes were developed for the analysis of two probe fed rectangular and circular microstrip patch antennas fed by resistive and reactive power divider networks.

Balanis, Constantine A.↗

Coded 16-CPFSK for downlink applications

A bandwidth-efficient constant-envelope Proof-of-Concept (POC) modem is described. The modem was developed on an Advanced Modulation Techniques Development contract for the NASA/Lewis Research Center. The POC modem employs 16-ary Continuous Phase Frequency Shift Keying (16-CPFSK) modulation. The 16 frequencies are spaced every 1/16th baud rate which produces a compact spectrum allowing 2 bits/sec/Hz operation. The modem is designed for 200 mb/s Time Division Multiple Access (TDMA) application with 100 MHz adjacent channel spacing. Overall rate 3.4 convolutional coding is incorporated. The demodulator differs significantly from typical quadrature phase detector approaches in that phase is coherently measured by processing the baseband output of a frequency discriminator. Baud rate phase samples for the baseband processor are subsequently decoded to yield the original data stream. The method of encoding onto the 16-ary symbol-ending phase nodes, together with convolutional coding gain, results in near Quadrature Phase Shift Keying (QPSK) theoretical performance. The modulated signal is of constant envelope; thus the power amplifier can be saturated for peak performance. The spectrum is inherently bandlimited and requires no RF filter for sidelobe containment. Two novel theoretical techniques are used in this 16-CPFSK modem: (1) coherent phase measurements are obtained by processing an FM discriminator baseband output; and (2) modulation is accomplished via a closed-loop-linearized voltage controlled oscillator (VCO).

Davis, Robert↗

The Earth Observing System AM Spacecraft - Thermal Control Subsystem

Mission requirements for the EOS-AM Spacecraft intended to monitor global changes of the entire earth system are considered. The spacecraft is based on an instrument set containing the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER), Clouds and Earth's Radiant Energy System (CERES), Multiangle Imaging Spectro-Radiometer (MISR), Moderate-Resolution Imaging Spectrometer (MODIS), and Measurements of Pollution in the Troposphere (MOPITT). Emphasis is placed on the design, analysis, development, and verification plans for the unique EOS-AM Thermal Control Subsystem (TCS) aimed at providing the required environments for all the onboard equipment in a densely packed layout. The TCS design maximizes the use of proven thermal design techniques and materials, in conjunction with a capillary pumped two-phase heat transport system for instrument thermal control.

Chalmers, D.↗

Virtual acoustic displays

A 3D auditory display can potentially enhance information transfer by combining directional and iconic information in a quite naturalistic representation of dynamic objects in the interface. Another aspect of auditory spatial clues is that, in conjunction with other modalities, it can act as a potentiator of information in the display. For example, visual and auditory cues together can reinforce the information content of the display and provide a greater sense of presence or realism in a manner not readily achievable by either modality alone. This phenomenon will be particularly useful in telepresence applications, such as advanced teleconferencing environments, shared electronic workspaces, and monitoring telerobotic activities in remote or hazardous situations. Thus, the combination of direct spatial cues with good principles of iconic design could provide an extremely powerful and information-rich display which is also quite easy to use. An alternative approach, recently developed at ARC, generates externalized, 3D sound cues over headphones in realtime using digital signal processing. Here, the synthesis technique involves the digital generation of stimuli using Head-Related Transfer Functions (HRTF's) measured in the two ear-canals of individual subjects. Other similar approaches include an analog system developed by Loomis, et. al., (1990) and digital systems which make use of transforms derived from normative mannikins and simulations of room acoustics. Such an interface also requires the careful psychophysical evaluation of listener's ability to accurately localize the virtual or synthetic sound sources. From an applied standpoint, measurement of each potential listener's HRTF's may not be possible in practice. For experienced listeners, localization performance was only slightly degraded compared to a subject's inherent ability. Alternatively, even inexperienced listeners may be able to adapt to a particular set of HRTF's as long as they provide adequate cues for localization. In general, these data suggest that most listeners can obtain useful directional information from an auditory display without requiring the use of individually-tailored HRTF's.

Wenzel, Elizabeth M.↗

Chromosome aberrations induced by high-LET radiations

Measurements of chromosome aberrations in peripheral blood lymphocytes are currently the most sensitive and reliable indicator of radiation exposure that can be used for biological dosimetry. This technique has been implemented recently to study radiation exposures incurred by astronauts during space flight, where a significant proportion of the dose is delivered by high-LET particle exposure. Traditional methods for the assessing of cytogenetic damage in mitotic cells collected at one time point after exposure may not be suitable for measuring high-LET radiation effects due to the drastic cell cycle perturbations and interphase cell death induced by this type of exposure. In this manuscript we review the recent advances in methodology used to study high-LET induced cytogenetic effects and evaluate the use of chemically-induced Premature Chromosome Condensation (PCC) as an alternative to metaphase analysis. Published data on the cytogenetic effects of in vitro exposures of high-LET radiation is reviewed, along with biodosimetry results from astronauts after short or long space missions.

ISS Project↗

Large-Scale Hollow Retroreflectors for Lunar Laser Ranging at Goddard Space Flight Center

Laser ranging to the retroreflector arrays placed on the lunar surface by the Apollo astronauts and the Soviet Luna missions have dramatically increased our understanding of gravitational physics along with Earth and Moon geophysics, geodesy, and dynamics. Although the precision of the range measurements has historically been limited by the ground station capabilities, advances in the APOLLO instrument at the Apache Point facility in New Mexico is beginning to be limited by errors associated with the lunar arrays. We report here on efforts at Goddard Space Flight Center to develop the next generation of lunar retroreflectors. We will describe a new facility that is being used to design, assemble, and test large-scale hollow retroreflectors. We will also describe results from investigations into various bonding techniques used to assemble the open comer cubes and mirror coatings that have dust mitigation properties.

Preston, Alix↗

Near Real Time Prospecting for Lunar Volatiles: Demonstrating RESOLVE Science in the Field

The Regolith and Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) project aims to demonstrate the utility of "in situ resource utilization". In situ resource utilization (ISRU) is a way to rebalance the economics of spaceflight by reducing or eliminating materials that must be brought up from Earth and placed on the surface of the Moon for human use. RESOLVE is developing a rover-borne payload that (1) can locate near subsurface volatiles, (2) excavate and analyze samples of the volatile-bearing regolith, and (3) demonstrate the form, extractability and usefulness of the materials. Such investigations are important not only for ISRU but are also critically important for understanding the scientific nature of these intriguing lunar polar volatile deposits. Temperature models and orbital data suggest near surface volatile concentrations may exist at briefly lit lunar polar locations outside persistently shadowed regions. A lunar rover could be remotely operated at some of these locations for the 4-7 days of expected sunlight at relatively low cost. In July 2012 the RESOLVE project conducted a full-scale field demonstration. In particular, the ability to perform the real-time measurement analysis necessary to search for volatiles and the ability to combine the various measurement techniques to meet the mission measurement and science goals. With help from the Pacific International Space Center for Exploration Systems (PISCES), a lunar rover prototype (provided by the Canadian Space Agency) was equipped with prospecting instruments (neutron spectrometer and near-infrared spectrometer), subsurface access and sampling tools, including both an auger and coring drill (provided by CSA) and subsurface sample analysis instrumentation, including a sample oven system, the Oxygen and Volatile Extraction Node (OVEN), and Gas Chromatograph / Mass Spectrometer system, the Lunar Advanced Volatile Analysis (LAVA) system. Given the relatively short time period this lunar mission is being designed to, prospecting needs to occur in near real-time. The two prospecting instruments are the neutron and NIR spectrometers. In the field demo a small radioactive source was provided the neutron flux. The NIR spectrometer, which includes its own light source, looks at surface reflectance for signatures of bound H20/0H and general mineralogy. Once a "hot spot" was found by the prospecting instruments, the drill could either auger or core. The auger drill worked to a depth of 50 cm and is monitored with a drill camera and the NIR spectrometer. As cuttings are brought up the NIR spectra is monitored. If a particular location is considered of high -interest then the decision to core could be made. The coring drill (a push-tube) allowed a meter sample to be acquired processed by the OVEN/LAVA sys-tem. This presentation will provide details as how these instruments worked together and how and if the planned measurements and science was obtained.

Elphic, Richard↗

Precision Measurement of the Neutron Magnetic Form Factor via the Ratio Method at Jefferson Lab Hall A

Protons and neutrons, collectively known as nucleons, are composed of quarks and gluons. The Sachs electromagnetic form factors encode information about the spatial distributions of charge and magnetization in the nucleon, particularly at low momentum transfer. In particular, the neutron magnetic form factor (GMn) provides crucial information about the distribution of magnetization inside the neutron and helps constrain theoretical models of nucleon structure. Quasi-elastic electron scattering from deuterium was measured up to Q^2=13.5 GeV^2 using the Super BigBite Spectrometer in Hall A at Jefferson Lab. In this work, the neutron magnetic form factor GMn was extracted at Q^2 = 3.0 GeV^2 and Q^2=4.5 GeV^2 using the Ratio Method. These results represent a subset of the full dataset collected in this experiment, which extended to significantly higher Q^2. The extracted GMn values agree with the existing global fit within approximately two standard deviations at Q^2=3.0 and show excellent agreement at Q^2=4.5. The measurements achieved systematic uncertainties of about 2% and statistical uncertainties below 0.5%, among the most precise determinations of GMn at these kinematics. These results demonstrate the robustness of the experimental technique and provide an important validation point for future extractions at higher Q^2, where data remain scarce. In addition, the GRINCH heavy gas Cherenkov detector—a key component of the experimental apparatus—was commissioned and achieved an electron detection efficiency of approximately 97%, supporting reliable particle identification. Together, the analysis presented here advances both our understanding of nucleon structure and the validation of the experimental methods and instrumentation used to access it.

Satnik, Maria [College of William and Mary, Willia↗

Advancing Aerosol Chemical Characterization and Vertical Profiling over the Southern Great Plains Using Uncrewed Aerial Sampling and Offline Aerosol Mass Spectrometry

Recent advancements in uncrewed aerial systems (UASs) and particulate matter (PM) analytical techniques have provided opportunities for atmospheric research. In this study, we deployed the Department of Energy’s fixed-wing ArcticShark UAS to examine PM 2.5 composition at varying altitudes─within and above the planetary boundary layer (PBL)─over the Southern Great Plains atmospheric observatory (SGP). A total of 22 flights were conducted across March, June, and August 2023. Composite filter samples were collected during each flight and analyzed with offline aerosol mass spectrometry (AMS), complemented by on-board real-time sensors and ground-based instrumentation, to provide a comprehensive view of regional aerosol characteristics. Results show clear vertical and seasonal differences in the aerosol composition. Relative to ground-level measurements, aloft samples exhibited shifts in the distribution of organic and inorganic PM, with the organic composition varying distinctly across seasons. Particulate organic nitrogen (ON) was elevated, with bulk compositions similar in March and June but strongly altered in August, likely driven by biomass burning and enhanced photochemical activity. Combined AMS and chemical ionization mass spectrometry analyses detected amines, amides, and amino acids. PM above the planetary boundary layer was enriched in oxidized organic aerosols, while ground-level PM contained higher nitrate and sulfate. Seasonal differences in aqueous-phase processing were also observed, which were strongest in March during persistent cloud cover and weaker in the drier August period, suggesting a shift from aqueous- to gas-phase SOA formation. In conclusion, these findings highlight the value of UAS in advancing PM measurements and vertical profiling of aerosol composition.

54 ENVIRONMENTAL SCIENCES↗

Retrieval of total precipitable water using radiometric measurements near 92 and 183 GHz

This paper describes a method for the retrieval of total precipitable water (W) in dry atmospheres, which relies on the strong water vapor absorption line at 183 GHz (for W less than 0.6 g/sq cm) and on the absorption near 90 GHz (for W above 0.6 g/sq cm). The method is very sensitive to the variations of W less than 0.5 g/sq cm and is complementary to the established methods that use the weak 22 GHz water vapor absorption line to retrieve W in the 1-6 g/sq cm. The technique was demonstrated by the analysis of two Advanced Microwave Moisture Sounder observations of dry atmospheres following cold-air outbreaks on March 13, 1983, and February 23, 1986.

Wang, J. R.↗

Informed unsupervised machine learning analysis of dislocation microstructure from high-resolution differential aperture X-ray structural microscopy data

This study leverages high-resolution differential-aperture X-ray structural microscopy (DAXM) to probe the local dislocation structure in deformed 304L-stainless steel at small strain, by measuring the lattice rotation and deviatoric elastic strain with a sub-micron resolution. For a single grain in a polycrystalline specimen, the measured lattice rotation field over the measured volume exhibited a multimodal distribution while the deviatoric elastic strain showed a single-mode distribution. An unsupervised Cauchy mixture machine learning model was developed to resolve the multimodal distribution of the lattice rotation. By mapping the lattice rotation data associated with each Cauchy peak in the model back onto the measured volume, we identify contiguous regions of the crystal rotated near the average values corresponding to the peaks of the overall rotation distribution. These regions represent the grain subdivision in the microstructure. Finally, the dislocation density tensor was also computed and its norm was laid over the rotation field to detect the subgrain boundaries. This step provided a validation of the Cauchy mixture model for the analysis of the lattice rotation distribution. The current study highlights the integration of advanced X-ray microscopy techniques with data-driven analysis methods to uncover detailed microstructure scales in deformed crystals.

Machine learning; Lattice rotation; High-energy X-↗

Deep learning to estimate permeability using geophysical data

Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to estimate three-dimensional (3D) permeability fields from electrical potential difference measurements. Traditional inversion and data assimilation methods are used to ingest this ERT data into hydrogeophysical models to estimate permeability. Due to ill-posedness and the curse of dimensionality, existing inversion strategies provide poor estimates and low resolution of the 3D permeability field. Recent advances in deep learning provide us with powerful algorithms to overcome this challenge. This paper presents a deep learning (DL) framework to estimate the 3D subsurface permeability from time-lapse ERT data. To test the feasibility of the proposed framework, we train DL-enabled inverse models on simulation data. Each measurement in both synthetic and field data is standardized by removing the mean and scaling the time-series to unit variance. This pre-processing step is necessary to bring simulation data closer to field observations. Subsurface process models based on hydrogeophysics are used to generate this synthetic data. Training performed on limited simulation data resulted in the DL model over-fitting. An advanced data augmentation based on mixup is implemented to generate additional training samples to overcome this issue. This mixup technique creates weakly labeled (low-fidelity) samples from strongly labeled (high-fidelity) data. The weakly labeled training data is then used to develop DL-enabled inverse models and reduce over-fitting. As both time-lapse ERT (1133048 features/realization) and 3D permeability (585453 features/realization) data samples are from a high-dimensional space, principal component analysis (PCA) is employed to reduce dimensionality. Encoded ERT and encoded permeability are generated using the trained PCA estimators. A deep neural network is then trained to map the encoded ERT to encoded permeability. This mixup training and unsupervised learning allowed us to build a fast and reasonably accurate DL-based inverse model under limited simulation data. Results show that proposed weak supervised learning can capture salient spatial features in the 3D permeability field. Quantitatively, the average mean squared error (in terms of the natural log) on the strongly labeled training, validation, and test datasets is less than 0.5. The R 2 -score (global metric) is greater than 0.75, and the percent error in each cell (local metric) is less than 10%. Finally, an added benefit in terms of computational cost is that the proposed DL-based inverse model is at least O(10 4 ) times faster than running a forward model once it is trained. Data generation, DL model training, and hyperparameter tuning to identify optimal neural network architectures utilized high-performance computing resources while the DL inference is performed on a standard laptop. Approximately, O(10 5 ) processor hours are used for generating data and DL tuning and training. We acknowledge that the data generation and DL model development are expensive. But once a DL model is trained, it can be re-used for inversion rapidly for the given system, with set physics and domain. Note that traditional inversion may require multiple forward model simulations (e.g., in the order of 10 to 1000), which are very expensive. This computational savings ≈ O(10 5 ) – O(10 7 )) makes the proposed DL-based inverse model attractive for subsurface imaging and real-time ERT monitoring applications due to fast and yet reasonably accurate estimations of permeability field.

58 GEOSCIENCES↗

Longitudinal shaping of plasma waveguides using diffractive axicons for laser wakefield acceleration

New techniques for the optical generation of plasma waveguides—optical fibers for ultra-intense light pulses—have become vital to the advancement of multi-GeV laser wakefield acceleration. Here, we demonstrate the fabrication and characterization of a transmissive 8-level logarithmic diffractive axicon (LDA) for the generation of meter-scale plasma waveguides. These LDAs enable the formation of a Bessel-like beam with controllable start and end locations of the focal line and near-constant intensity on axis. We present measurements of the Bessel-like focal profile produced by the LDA and of the leading end of the plasma column generated by it. One important feature is the formation of a funnel-mouthed plasma channel entrance that can act as waveguide coupler. We also compare the diffraction efficiency of our 8-level LDA to 4-level and binary versions, with measurements comparing well to theory.

Tripathi, N.↗

FY23 Update: Surface Sampling Activities for the Canister Deposition Field Demonstration

This report describes the results of a field demonstration of the proposed surface sampling techniques and plan for the multi-year Canister Deposition Field Demonstration (CDFD). The CDFD will evaluate salt deposition rates on three commercial 32PTH2 NUHOMS welded stainless steel storage canisters in Advanced Horizontal Storage Modules. Exposure testing is planned for up to 10 years and will incorporate periodic surface sampling campaigns. 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 spent nuclear fuel (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. Previously, a preliminary sampling plan was developed, identifying possible sampling locations on the canister surfaces and sampling intervals; possible sampling methods were also described. Building from previous work, this report documents hand sampling from a spent nuclear fuel canister on a transfer skid mockup designed by Sandia National Laboratories. The sampling took place from a boom lift and salts were collected from mounted sample plates. The results of these efforts are presented in this report and compared to previous laboratory-controlled tests. 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.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗