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DOE OSTI2023

Radiation Testing for High-Resolution Radiation-Hardened Camera System (Final CRADA Report)

The nuclear energy industry needs higher-image quality and higher rad-hard vision systems for refueling and inspection operations that are required every 12-18 months for all operating commercial reactors. During refueling operations, the serial numbers of fuel assemblies need to be visually verified in a challenging high radiation environment with dose rates on the order of 1kGy/hr. at the top of the core (approximately 10 days after shutdown). Vega Wave Systems has developed and built a radiation hard vision system that: 1. has high radiation hardness, 2. demonstrated best in the industry image quality, 3. has small size and weight, and 4. does not suffer from radiation-induced noise. ANL-1060 (02/13/2023) The proprietary Enduray vision system from Vega Wave Systems, Inc. is designed to withstand more than 400x the radiation level of the Vidicon-based systems, currently the highest radiation tolerant system in use today. The Van De Graaff (VDG) electron accelerator at Argonne National Laboratory is ideally suited for testing of Enduray vision system. VDG provides a broad band (up to 3 MeV) x-ray source that reasonably approximates the energy and spectrum of the gamma radiation expected at the top of a nuclear core 10 days after shutdown (~1kGy/hr.), is easily controlled for variable tests, and will not activate the parts under radiation for ease of timely and close inspection and characterization of the system in case of operational issues.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Selective Plasmon-Induced Oxidation of 4-Aminothiophenol on Silver Nanoparticles

Selectivity in plasmonic chemistry is typically achieved using bimetallic nanostructures. Herein, we show that monometallic silver nanoparticles can also drive highly selective interfacial transformations, oxidation reactions particularly. This is illustrated through a close inspection of tip-enhanced Raman spectral images of 4-aminothiophenol (ATP)-functionalized Au vs Ag nanoparticles. Further, we find that whereas the thoroughly described dimerization reaction to form 4,4’-dimercaptoazobenzene dominates the response on Au, highly selective oxidation on Ag nanoparticles exclusively leads to 4-nitrothiophenol. We explore the origin of the distinct reaction pathways on Ag vs Au nanostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Core-Level Spectroscopy with Hard and Soft X-rays on Phosphorus-Containing Compounds for Energy Conversion and Storage

The electronic properties of nine solid phosphorus (P)-containing compounds with varying oxidation states and chemical environments, including GaP (–III) , InP (–III) , red-P (0) , H 3 P (III) O 3 , Na 2 H 2 P 2 (IV) O 6 , H 3 P (V) O 4 , KH 2 P (V) O 4 , Na 2 HP (V) O 4 , and InP (V) O 4 , are investigated using X-ray absorption near-edge structure (XANES) spectroscopy in the hard (P K-edge) and soft X-ray regime (P L 2,3 - edge). We find shifts in the absorption-edge positions and correlate them with the ligands surrounding the P atom, likely causing a different core–hole interaction screening for different compounds. Complementing the experimental analysis, ab initio many-body calculations of XANES spectra provide insights into the excitonic nature of the observed spectral features and their impact on the electronic structure of the materials. Furthermore, we report on P K-edge XANES measurements on aqueous phosphorus-containing acids, including H 3 PO 3 , H 3 PO 4 , and their mixtures. At first sight, the spectra of the aqueous acids are similar to those of their solid counterparts. However, close inspection reveals a slight red shift of the absorption edge and the presence of fewer spectral features compared with spectra of the respective solids. Mixtures of aqueous acids display spectral features corresponding to the individual components, indicating the potential for speciation and quantification through fingerprinting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

DFT calculations and theory do not support enantiospecificity in NMR J-coupling constants

Distinguishing the enantiomers of small organic molecules is an industrially relevant problem with important implications for the health of the population. In a recent publication, Bouchard and co-workers have suggested that large differences in indirect spin-spin (J) coupling constants between enantiomers are possible. A close inspection of their work revealed significant flaws in their density functional theory (DFT) calculations and that the reported effects disappear with appropriate care. We thus conclude that enantiospecificity in spin-spin coupling constants has not be demonstrated either experimentally or theoretically.

Perras, Frédéric A. [Ames Laboratory (AMES), Ames,↗

DOE OSTI2022

Autonomous aerial flight path inspection using advanced manufacturing techniques

Robotic systems have shown capabilities to perform inspection tasks in dangerous and difficult-to-access environments, such as those found in different components of power plants. However, most of the current robotic inspection technology is designed for specific components. Aerial robots, commonly termed as Drones, have raised an option to inspect a wider range of structural components. Nevertheless, current aerial inspecting technology still relies on a human pilot with limited line of sight, field of view and a reduced perception as the drone flies away, which prevents performing close-quarter inspection in intricate, structurally complex and GPS-denied environments. This work introduces offline inspection path generation methods based on robotics-integrated to manufacturing techniques. One method uses computer-aided manufacturing (CAM) techniques and the other an additive manufacturing (AM) approach to generate the flight path. That is to say, the drone would fly along the path described by a 3D (Three Dimensional) printer’s extruder or a CNC (Computer Numerical Control) machining tool, enabling to fly very close the structure even in physical structures with a complex geometry. Once the trajectories are generated, they are introduced for its validation in the Gazebo robotics simulator. Simulation results demonstrate the proper performance of the method and confirm that this approach can be used for close inspection of structural components.

42 ENGINEERING↗

DOE OSTI2022

Autonomous Aerial Power Plant Inspection in GPS-denied Environments

Inspection of coal-fired power plants is frequently dangerous, includes difficult places to reach, and can turn expensive due to the downtimes and cost of inspection crew. Robotic systems have shown capabilities to address some of these issues, but most of the current robotic inspection technology in power plants is designed for specific components. Conversely, recent advances in machine vision have empowered aerial platforms for long-range, remotely-controlled, GPS-based inspections of industrial plants. This capability has led to wide spread utilization of aerial robots (commonly termed Drones, UVS or UAS) platforms for inspection in less challenging environments where both collision avoidance, and GPS reception are not significant issues. The challenge in adapting airborne technology for power plant inspection lies in internal structures and the complex network of piping, and distribution systems, which impose significant risks for collision and can hinder the reception and transmission of GPS signals. The current state of the art in aerial inspection technology within the energy sector is controlled via radio control, and utilizes GPS-based navigation, for inspection of large-scale plants such as offshore platforms and wind turbine parks. Nevertheless, close-range and autonomous inspection in the GPS-denied environments of power plants has not yet been achieved, as it requires precise guidance and navigation with real-time situational awareness and obstacle avoidance capabilities. This endeavor introduced the use of rotary wing flying robots, due to their station keeping and vertical take-off capabilities for power plant components inspection. To enable close quarter inspection two methods were used. One method uses the 3D CAD (Three-dimensional Computer-Aided Design) model of the asset to inspect to generate the UAV’s inspection path. To acquire, analyze and process the 3D model, first, the STL file is produced to obtain surface points and vectors normal to the surface. Later, by introducing other variables such as wall offset and a controlled trajectory between each outline and each subsequent layer, the flight path is generated. The proposed framework will generate a path that will pass as close as desired from the surface and navigate in intricate environments. A second method, use advanced manufacturing techniques such as CNC (Computer Numerical Control) and additive manufacturing. Once the inspection flight path is obtained, vision-based navigation systems are employed to have the UAV autonomously tracking the provided trajectory. Finally, Artificial Intelligence-enabled developments are in charge of detecting cracks and corrosion in structural components of power plants. The proposed methods are validated in simulations, laboratory and industrial setups, where it is shown that the developed systems acting together enable close-quarter autonomous aerial inspection and mapping in power plant assets. The system can be further improved by adding more sensors to navigate in different GPS-denied environments, with non-homogeneous lighting conditions, dust and in general situations where vision-based systems may fail.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Post-Closure Inspection (PCI) Letter Report for Closed Non-Resource Conservation and Recovery Act (RCRA) Corrective Action Units (CAUs) on the Nevada National Security Site (NNSS), for Calendar Year (CY) 2020

This letter report is for the following CAUs for CY 2020, including CAUs located on the Nevada Test and Training Range (NTTR) that are accessed through the NNSS Main Gate. Use restriction (UR) issues that were identified in the 2019 inspections were addressed in 2020.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

A Lagrangian analysis of pockets of open cells over the southeastern Pacific

Abstract. Pockets of open cells (POCs) have been shown to develop within closed-cell stratocumulus (StCu), and a large body of evidence suggests that the development of POCs result from changes in small-scale processes internal to the boundary layer rather than large-scale forcings. Precipitation is widely viewed as a key process important to POC development and maintenance. In this study, GOES-16 satellite observations are used in conjunction with MERRA-2 winds to track and compare the microphysical and environmental evolution of two populations of closed-cell StCu selected by visual inspection over the southeastern Pacific Ocean: one group that transitions to POCs and another comparison group (CLOSED) that does not. The high spatiotemporal resolution of the new GOES-16 data allows for a detailed examination of the temporal evolution of POCs in this region. We find that POCs tend to develop near the coast, last tens of hours, are larger than 104 km2, and often (88 % of cases) do not re-close before they exit the StCu deck. Most POCs are observed to form at night and tend to exit the StCu during the day when the StCu is contracting in area. Relative to the CLOSED trajectories, POCs have systematically larger effective radii, lower cloud drop number concentrations, a comparable conditional in-cloud liquid water path, and a higher frequency of more intense precipitation. Meanwhile, no systematic environmental differences other than boundary layer height are observed between POC and CLOSED trajectories. Interestingly, there are no differences in reanalysis aerosol optical depth between both sets of trajectories, which may lead one to the interpretation that differences in aerosol concentrations are not influencing POC development or resulting in a large number that re-close. However, this largely depends on the reanalysis treatment of aerosol–cloud interactions, and the product used in this study has no explicit handling of these important processes. These results support the consensus view regarding the importance of precipitation on the formation and maintenance of POCs and demonstrate the utility of modern geostationary remote sensing data in evaluating the POC life cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Development of an Innovative Inspection Tool for Superheater Tubes in Fossil Fuel Power Plants

Fossil fuel power plants are complex systems containing multiple components that require periodic health monitoring. Failures in these systems can lead to increased downtime for the plant, reduction of power, and significant cost for repairs. Inspections of the plant’s superheater tubes are typically manual, laborious, and extremely time-consuming. This is due to their small diameter size (between 1.3 and 7.6 cm) and the coiled structure of the tubing. In addition, the tubes are often stacked close to each other, limiting access for external inspection. This paper presents the development and testing of an electrically powered pipe crawler that can navigate inside 5 cm diameter tubes and provide an assessment of their health. The crawler utilizes peristaltic motion within the tubes via interconnected modules for gripping and extending. The modular nature of the system allows it to traverse through straight sections and multiple 90° and 180° bends. Additional modules in the system include an ultrasonic sensor for tube thickness measurements, as well as environmental sensors, a light detecting and ranging (LiDAR) sensor, and camera. Furthermore, these modules utilize a gear system that allows for 360° rotation and provides a means to inspect the entire internal circumference of the tubes.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Region-Based Convolutional Neural Network for Wind Turbine Wake Characterization in Complex Terrain

We present a proof of concept of wind turbine wake identification and characterization using a region-based convolutional neural network (CNN) applied to lidar arc scan images taken at a wind farm in complex terrain. We show that the CNN successfully identifies and characterizes wakes in scans with varying resolutions and geometries, and can capture wake characteristics in spatially heterogeneous fields resulting from data quality control procedures and complex background flow fields. The geometry, spatial extent and locations of wakes and wake fragments exhibit close accord with results from visual inspection. The model exhibits a 95% success rate in identifying wakes when they are present in scans and characterizing their shape. To test model robustness to varying image quality, we reduced the scan density to half the original resolution through down-sampling range gates. This causes a reduction in skill, yet 92% of wakes are still successfully identified. When grouping scans by meteorological conditions and utilizing the CNN for wake characterization under full and half resolution, wake characteristics are consistent with a priori expectations for wake behavior in different inflow and stability conditions.

17 WIND ENERGY↗

DOE OSTI2025

Inspection and Mapping of Savannah River Site (SRS) Waste Tanks via Unmanned Aircraft System (UAS) – 25351

The CSTF at SRS contain 51 waste tanks with 8 closed waste tanks between FTF and HTF. SRMC is the LW contractor. The LW mission includes removing legacy nuclear waste from these tanks and treating it for final disposition. Once the bulk of the waste has been removed from a tank, it will undergo inspection and sampling to characterize the remaining waste in the tank prior to it being operationally closed. There are multiple points in the tank closure process where an inspection is performed, and there are multiple parts of a tank that get inspected. Waste tanks have a primary containment vessel (referred to as the “Primary”) and a secondary containment vessel (referred to as the “Annulus”) that surrounds the primary. Both of these sections of a tank receive multiple inspections throughout the closure process.

Murphy, Lucas D. [Savannah River Mission Completio↗

DOE OSTI2021

Next-to-$\mathrm{MHV}$ Yang-Mills kinematic algebra

Kinematic numerators of Yang-Mills scattering amplitudes possess a rich Lie algebraic structure that suggest the existence of a hidden infinite-dimensional kinematic algebra. Explicitly realizing such a kinematic algebra is a longstanding open problem that only has had partial success for simple helicity sectors. In past work, we introduced a framework using tensor currents and fusion rules to generate BCJ numerators of a special subsector of NMHV amplitudes in Yang-Mills theory. Here we enlarge the scope and explicitly realize a kinematic algebra for all NMHV amplitudes. Master numerators are obtained directly from the algebraic rules and through commutators and kinematic Jacobi identities other numerators can be generated. Inspecting the output of the algebra, we conjecture a closed-form expression for the master BCJ numerator up to any multiplicity. We also introduce a new method, based on group algebra of the permutation group, to solve for the generalized gauge freedom of BCJ numerators. It uses the recently introduced binary BCJ relations to provide a complete set of NMHV kinematic numerators that consist of pure gauge.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

A New Way to Discover Strong Gravitational Lenses: Pairwise Spectroscopic Search from DESI DR1

We present a new method to search for strong gravitational-lensing systems by pairing spectra that are close together on the sky in a spectroscopic survey. We visually inspect 26,621 spectra in the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 that are selected in this way. We further inspect the 11,848 images corresponding to these spectra in the DESI Legacy Imaging Surveys Data Release 10, and obtain 2046 conventional strong gravitational lens candidates, of which 1906 are new. This constitutes the largest sample of lens candidates identified to date in spectroscopic data. Besides the conventional candidates, we identify a new class of systems that we term “dimple lenses.” These systems have a low-mass foreground galaxy as a lens, typically smaller in angular extent and fainter compared with the lensed background source galaxy, producing subtle surface brightness indentations in the latter. We report the discovery of 318 of these “dimple lens” candidates. We suspect that these represent dwarf galaxy lensing. With follow-up observations, they could offer a new avenue to test the cold dark matter model by probing their mass profiles, stellar mass–halo mass relation, and halo mass function for M Halo ≲ 10 13 M ⊙ . Thus, in total, we report 2164 new lens candidates. Our method demonstrates the power of pairwise spectroscopic analysis and provides a pathway complementary to imaging-based and single-spectrum lens searches.

Hsu, Yuan-Ming 許淵明 [National Taiwan University, Ta↗

DOE OSTI2026

NeuDiff Agent: a governed AI workflow for single-crystal neutron crystallography

Large-scale facilities increasingly face analysis and reporting latency as a limiting step in scientific throughput, particularly for structural studies that require iterative reduction, integration, refinement and validation. To improve the time to result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source. NeuDiff Agent takes instrument data through reduction, integration, refinement and validation to a validated crystal structure and a publication-ready CIF. NeuDiff Agent coordinates established crystallographic tools under explicit governance by restricting actions to allowlisted tools, enforcing fail-closed verification gates at key workflow boundaries, and capturing complete provenance for inspection, auditing and controlled replay. The present benchmark is limited to structural crystallography for periodic structures; magnetic structure analysis and incommensurate or superspace refinement are outside the scope of the current workflow. Performance is assessed using a fixed prompt protocol and repeated end-to-end runs with two large language model backends, with user and machine time partitioned and intervention burden and recovery behaviors quantified under gating. In a reference-case benchmark, NeuDiff Agent reduces wall time from 435 min (manual) to 86.5 ± 4.7 to 94.4 ± 3.5 min (4.6–5.0× faster) while producing a validated CIF with no checkCIF level A or B alerts. These results establish a practical route to deploy agentic AI in facility crystallography while preserving traceability and publication-facing validation requirements.

Xiao, Zhongcan [ORNL] (ORCID:0000000220761961)↗

DOE OSTI2021

Preprocessing for Unintended Conducted Emissions Classification with ResNet

Characterization of Unintended Conducted Emissions (UCE) from electronic devices is important when diagnosing electromagnetic interference, performing nonintrusive load monitoring (NILM) of power systems, and monitoring electronic device health, among other applications. Prior work has demonstrated that UCE analysis can serve as a diagnostic tool for energy efficiency investigations and detailed load analysis. While explaining the feature selection of deep networks with certainty is often not fully comprehensive, or in other applications, quite lacking, additional tools/methods for further corroboration and confirmation can help further the understanding of the researcher. This is true especially in the subject application of the study in this paper. Often the focus of such efforts is the selected features themselves, and there is not as much understanding gained about the noise in the collected data. If selected feature and noise characteristics are known, it can be used to further shape the design of the deep network or associated preprocessing. This is additionally difficult when the available data are limited, as in the case which the authors investigated in this study. Here, the authors present a novel work (which is a proposed complementary portion of the overall solution to the deep network classification explainability problem for this application) by applying a systematic progression of preprocessing and a deep neural network (ResNet architecture) to classify UCE data obtained via current transformers. By using a methodical application of preprocessing techniques prior to a deep classifier, hypotheses can be produced concerning what features the deep network deems important relative to what it perceives as noise. For instance, it is hypothesized in this particular study as a result of execution of the proposed method and periodic inspection of the classifier output that the UCE spectral features are relatively close to each other or to the interferers, as systematically reducing the beta parameter of the Kaiser window produced progressively better classification performance, but only to a point, as going below the Beta of eight produced decreased classifier performance, as well as the hypothesis that further spectral feature resolution was not as important to the classifier as rejection of the leakage from a spectrally distant interference. This can be very important in unpredictable low-FNR applications, where knowing the difference between features and noise is difficult. As a side-benefit, much was learned regarding the best preprocessing to use with the selected deep network for the UCE collected from these low power consumer devices obtained via current transformers. Baseline rectangular windowed FFT preprocessing provided a 62% classification increase versus using raw samples. After performing a more optimal preprocessing, more than 90% classification accuracy was achieved across 18 low-power consumer devices for scenarios in which the in-band features-to-noise ratio (FNR) was very poor.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Building ControlScore: General Service Administration Office Building Deployment

Improvements to building control systems can lead to energy savings and increased occupant comfort. In an optimized system, process variables such as air temperature will closely follow their desired setpoints and avoid excess energy use. Typically, experts must manually inspect individual control loops to identify poor performance and opportunities for improvement. However, this approach is difficult in modern buildings that have a prohibitively large number of controllers. To address this issue, Pacific Northwest National Laboratory (PNNL) created the ControlScore concept, which takes operating data from the many controllers within a building and generates standardized scores for each loop on a scale of 0 to 10 (a score of 0 indicates poor control, a score of 10 indicates good control). PNNL applied the Building ControlScore application to all available data from a General Services Administration office building within the period of January 1, 2023, to March 9, 2023. The building scored a 4.7 overall, with all 74 of the building’s loops fitting a roughly normal distribution centered around 5. These results indicate that the analyzed systems have below-average performance with room for improvement, especially in the poorly scored systems. Airflow loops tended to have much lower scores than zone temperature loops. The lowest and highest performing systems in the building section were identified, as were all loops with a score less than 1. While the ControlScore identifies loops and systems that aren’t meeting their designated setpoints, it does not indicate the cause of those issues. For example, consider a supply air terminal unit’s airflow loop that received a low score due to it delivering less air than specified by the setpoint. The lower-than-desired airflow could be due to equipment limitations (e.g., the terminal unit or duct serving is too small to accommodate that airflow), malfunctioning equipment (e.g., a stuck damper or bad sensor), or something else entirely. The ControlScore does not diagnose problems it simply identifies the symptoms that can be explored and addressed by building operators.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Building ControlScore: Research Laboratory Building Deployment

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

3013 Inner Container Closure Weld Region (ICCWR) Characterization by Wide Area 3D Measurement System (WAMS) Analysis (FY21 Progress Report)

As part of the 3013 Surveillance Program, through-wall penetration from stress corrosion cracking (SCC) of the 3013 inner containers has been identified as the most credible condition for failure withing the 50- years lifetime. Chlorides contained in Pu-bearing material, together with intra-canister humidity levels, metallurgical conditions, and internal stresses have been found to produce corrosion in the Inner Container Closure Weld Region (ICCWR) of the 3013 canister system. A Laser Confocal Microscope (LCM) is used as part of the 3013 Surveillance Program protocol to identify the prevalence of corrosion and corrosionrelated cracking in the ICCWR2. With the LCM, a close visual examination is made of the ICCWR surface along with measurements of corrosion-related features. LCM inspections produce immense amounts of image data that is time intensive to analyze. There is also a 9-year backlog of images, with approximately 49 canisters that must be evaluated. To expedite data analysis and reduce the amount of generated data, a Wide Area 3D Measurement System (WAMS) microscope has been added to the examination protocol. Although WAMS is a lower resolution microscope, small features of interest can be still identified. The advantage of collecting data for the full circumference using the WAMS is that it can take about 1/16 of the time needed with the LCM. Both systems offer capabilities that combined can be utilized to expedite the examination of the ICCWR. The WAMS is an efficient system for screening and identification of corrosion features while the LCM can be utilized to obtain higher resolution images areas identified by the WAMS. This report explains and justifies the data collection methods used with the WAMS. It includes a summary of the data generated by WAMS in FY21. The goals set for data collection in FY21 were met. A total of twenty-two DE’s were imaged, and analysis was carried out on eleven samples. The analyzed samples showed large numbers of potential cracks and pits distributed throughout the surfaces. Lastly, to explain the advantages of the WAMS, its capabilities were compared to those of a simpler microscope. Micrographs of the samples imaged in FY21 and those analyzed are included in the appendices.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗