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At least 739 records · Page 41

Clean Cities Coalitions 2020 Activity Report

The U.S. Department of Energy's (DOE) Office of Energy Efficiency and Renewable Energy's Vehicle Technologies Office (VTO) works with local Clean Cities coalitions across the country as part of its Technology Integration Program. These efforts help businesses and consumers make smarter/more-informed transportation energy choices that can save energy, lower costs, reduce reliance on imported oil, and reduce air emissions. This report summarizes the success and impact of coalition activities based on data and information provided in their annual progress reports.

33 ADVANCED PROPULSION SYSTEMS↗

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components. Third Annual Progress Report

Additive manufacturing (AM) of high-strength corrosion resistance alloys for nuclear energy applications, such as stainless steel and Inconel, is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Probability of crack initiation at the pore depends on size, shape, and orientation of the defect. Pulsed Infrared Thermography Imaging (PIT) provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PIT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PIT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PIT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PIT capabilities in detecting microscopic subsurface defects in metals, and classifying shapes and orientation of pores in thermal images. For detection of microscopic defects in PIT imaging data, we have developed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) image processing algorithm. We show that flat bottom hole (FBH) defects as small as 200µm in SS316 and IN718 specimens, can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature. For classification of defects shapes, we have previously developed thermal tomography (TT) algorithm to obtain depth reconstructions of material defects from data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Material Control & Accountancy for Molten Salt Reactors (FY2021 Report)

There is significant domestic and international interest, investment, and research and development momentum to pursue advanced nuclear reactor technologies. Molten salt reactor (MSR) concepts display the largest variability in fuel type and design features among the current advanced concepts. MSRs have been proposed with various core designs, sizes (power), and fuel cycles. Salt-fueled molten salt systems represent the only advanced reactor type with fuel that is not in a solid form during operation. These “liquid-fueled” MSRs are unique from perspectives of fuel fabrication, spent irradiated fuel and waste components, licensing, and material control and accountability (MC&A) including the potential of fissile material holdup. The liquid fuel salt is the defining distinction in comparison to other advanced reactors that propose TRI-structural ISOtropic particle fuel pebbles, various coolant options (e.g., molten salts or metals, high temperature gas), or small modular alternatives using solid fuel variants including both light water reactors and non-light water reactors. MSRs are appealing to the nuclear energy industry because of the diverse reactor characteristics they can support including various neutron energy spectra, fueling requirements, fuel cycles, and/or fuel utilization. However, because of the significant deviation and diversity of a salt-fueled system compared to traditional solid fuel light water-cooled reactors (LWRs), the history, regulatory licensing framework, modeling capabilities, and supporting engineering technology are either lacking or, in some cases, nonexistent. Therefore, the research community is actively supporting advanced MSR development on many of these fronts in particular to assist MSR vendors with licensing requirements. ORNL is leading the research and development of respective MC&A approaches for salt-fueled MSRs. This report summarizes the research performed at Oak Ridge National Laboratory (ORNL) under the US Department of Energy, Office of Nuclear Energy, Advanced Reactor Safeguards (ARS) program to investigate safeguards and security by design concepts, licensing and regulatory considerations, and dynamic system-level modeling to understand radioisotope concentrations for salt-fueled MSRs. The report builds upon the previous research and literature, identifies the MC&A challenges inherent to a salt-fueled MSR, reviews current regulatory frameworks for LWRs and their applicability towards salt-fueled MSRs, summarizes the status and progress of an MSR dynamic modeling tool, and discusses a prospective MC&A approach based on the Molten Salt Demonstration Reactor (MSDR) model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗

Alaska Ocean Cluster (Final CTAP2.0 Report)

Sandia provided technical assistance to the Alaska Ocean Cluster to assess potential market opportunities regarding byproducts of crab in the greater Alaska region. Crab contains a wide variety of proteins, chitin, lipids, minerals, and pigments. Currently, only a small portion of these components are utilized, primarily proteins associated with crab meat. Sandia provided an assessment of the current market landscape and opportunities related to crab byproducts including market size and applications. Sandia subject matter experts conducted an analysis and provide the Alaska Ocean Cluster team with a report describing the state of research and market opportunities offered by Alaska crab byproducts. The final report focused on market opportunities regarding chitosan production, chitin extraction, as well as an overview of the key market players and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

2021 Report - SRNL Aging and Lifetimes program tritium aging studies on structural alloys

This report documents work performed in fiscal year 2021 at SRNL in support of the Aging and Lifetimes program. This work is part of an on-going collaboration between SRNL and SNL to understand tritium embrittlement of structural metals used in Gas Transfer System reservoirs, thereby informing lifetime assessments and predictions. In this effort, test coupons are pre-charged with tritium and allowed to age in a freezer to minimize tritium diffusion and off-gassing while allowing for born-in helium levels to systematically increase. Coupons are then removed periodically and tested to develop an understanding of how mechanical properties degrade as helium levels increase. This report summarizes test results from coupons which are in various stages of aging as they were tritium pre-charged in previous years. Tests were performed on 304L that was previously tritium pre-charged and allowed to age to nominally 300 appm helium. Specimens from this study were previously tested at 100 appm nominal helium content, and this new test point expands that study. Tensile testing of these heat treated 304L tubes (and welded tubes) aged to 100 appm helium were completed which provided a unique study of a diverse set of microstructures and yield strengths ranging from 200-800 MPa. Additionally, 304L notched and smooth tensile specimens aged to 300 appm helium were tensile tested to predetermined strains to provide for a systematic microscopy investigation of aging effects on microstructural damage in partnership with SNL. Testing was performed on 304L electron beam (EB) weld coupons as well as 21-6-9 annealed coupons that were thermally pre-charged in 2020. Tests on the EB welds were completed at 100 appm helium contents, and tests on the annealed 21-6-9 material were completed at 100, 200, and 300 appm helium. Table 0-1 provides the status of the ongoing tritium coupon aging studies. The table includes the year tritium pre-charging took place, the material, and the targeted helium concentrations (appm) for testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

FY21 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g., height, color and grayscale values; all as functions of a location in a plane projection). A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data, flag significant features, execute Machine Learning (ML) algorithms, output parameters for trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Features can be called out by user-specified thresholds, manual labeling or machine learning algorithms when they have been completed. The ability to rapidly label data is important because of the volume of data required for training machine learning algorithms. The GUI has the flexibility to allow addition of improved ML algorithms, methods for data visualization, and statistical computations. Statistical analyses via the GUI include areas of pits within a defined range of pit depths, correlations between Red-Green-Blue (RGB) or grayscale intensity and relative surface height, covariances between values associated with features, and feature histograms. The development of supervised machine learning algorithms, however, has been hindered by a lack of training data. The machine learning algorithms for crack identification are being refined but require improvements to the true positive rate for crack detection. This shortcoming is an artifact of the limited training data currently available, perhaps more so than the structure of the neural networks. At present, the best results are had from a consensus over an ensemble of randomly generated Deep Neural Network (DNN) or Convolutional Neural Network (CNN) algorithms. Although the consensus accuracy method has yielded optimum true positive and true negative rates in excess of 80%, additional validation testing is necessary. In addition to the suite of LCM data that was initially used, and which represents the majority of the work presented in this report, WAMS image data was also reviewed at a preliminary level. The review included a comparison between image resolution and dynamic range for each method. WAMS (ZON file) image data was found to have a pixel pitch of 3.69μm compared to 1 μm for the LCM (vk4 file) data, which implies a lower resolution for the WAMS images. Conversely, the ratio of dynamic range of the WAMS data to the LCM data was approximately 41:20 for height data, suggesting that information from WAMS should more accurately determine the depth of pits. At present, the significance of the greater dynamic range of the WAMS data relative to the LCM data has not yet been evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Policy, Regulatory, Legal, and Permitting Evaluation Task 6.0 (Technical Report)

This report revisits and updates work completed for the Phase I CarbonSAFE Illinois - East Sub Basin project, the precursor to the Phase II Wabash CarbonSAFE project; the current report summarizes the policy, regulatory, legal, and permitting considerations to-date as related to geologic CO 2 storage at the Wabash Valley Resources (WVR) gasification plant site in Vigo County, Indiana.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Marshall Islands Dose Assessment and Radioecology Program: Report on the (i) 2018 Visual Study of Exterior Concrete of the Cactus Crater Containment Structure (ii) Periodic Monitoring of Groundwater on Runit Island and (iii) Initial Health Risk Assessment from Contaminants in the Cactus Crater Containment Structure

In 2012, Congress passed P.L. 112-149, Insular Areas Act of 2011, which amended the Compact of Free Association Amendments Act of 2003 by assigning Cactus Crater containment monitoring and reporting requirements to the Secretary of Energy (Secretary). Effective January 1, 2012, the Secretary was required to “periodically (but not less frequently than every 4 years) conduct -- (I) a visual study of the concrete exterior of the Cactus Crater Containment Structure on Runit Island; and (II) a radiochemical analysis of the groundwater surrounding and in the Cactus Crater Containment Structure on Runit Island.” 48 U.S.C. 1921b(f)(1)(B)(i). The Secretary was also directed to submit to Congress a report describing the results of each visual survey and the radiochemical analysis and “a determination on whether the surveys and analyses indicate any significant change in the health risks to the people of Enewetak from the contaminants within the Cactus Crater Containment Structure.” 48 U.S.C. 1921b(f)(1)(B)(ii)(II).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (3 rd Annual Report)

Nuclear power plants collect and store large volumes of heterogeneous data from various components and systems. With recent advances in machine learning (ML) techniques, these data can be leveraged to develop diagnostic and short-term forecasting models to better predict future equipment condition. Maintenance operations can then be planned in advance whenever degraded performance is predicted, thus resulting in fewer unplanned outages and the optimization of maintenance activities. This enables lower maintenance costs and improves the overall economics of nuclear power. This report primarily focuses on developing a short-term forecasting process that leverages a feature selection process to distill large volumes of heterogeneous data and predict specific equipment parameters. A variety of feature selection methods, including Shapley Additive Explanations (SHAP) and variance inflation factor (VIF), were used to select the optimal features as inputs for three ML methods: long short-term memory (LSTM) networks, support vector regression (SVR), and random forest (RF). Each combination of model and input features was used to predict a pump bearing temperature both 1 and 24 hours in advance, based on actual plant system data. The optimal inputs for the LSTM and SVR were selected using the SHAP values, while the optimal input for the RF consisted solely of the response variable itself. Each model produced similar 1-hour-ahead predictions, with root mean square errors (RMSEs) of roughly 0.006. For the 24-hour-ahead predictions, differences could be seen between LSTM, SVR, and RF, as reflected by model performances of 0.036 ± 0.014, 0.0026 ± 0, and 0.063 ± 0.004 RMSE, respectively. As big data and continuous online monitoring become more widely available, the proposed feature selection process can be used for many applications beyond the prediction of process parameters within nuclear infrastructure. This report summarizes the Fiscal Year 2021 research progress encompassing the (1) data cleaning and feature selection necessary for ML applications; (2) development of short-term forecasting models to predict future plant process parameters for both single and multiple time steps ahead; and (3) validation of the feature selection methods and short-term forecasting models given new data from different systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Attenuator, PC-2.92mm, Fixed (Proficiency Test Report; PT ID Number 6679665)

The PSL has reviewed the documentation and data provided by NNSS–Livermore Operations with respect to this proficiency test. This proficiency test was performed to assess NNSS–Livermore Operations’ ability to perform scattering parameter calibrations. The level of documentation was satisfactory. On 12/28/2021, NNSS–Livermore Operations reported the data for the proficiency test conducted on the attenuator. NNSS–Livermore Operations performed this proficiency test using an Anritsu vector network analyzer, an electronic calibration module, and verification kit. The PSL used a Keysight vector network analyzer and mechanical calibration kit. The PSL results included in this proficiency test report were taken on June 23, 2020.

42 ENGINEERING↗

Historic Buildings Report: Five-Year Preservation Planning for Manhattan Project National Historical Park Sites

This report offers a preservation maintenance plan for the next five years for buildings and structures included in or eligible for inclusion in the Manhattan Project National Historical Park at Los Alamos National Laboratory. There are twenty-three buildings, structures, and ruins of previously standing buildings covered within this report. Many of the preservation maintenance issues addressed here concern problems with health and live safety of staff and visitors alike, and also structural concerns that affect the long-term preservation of these important buildings.

42 ENGINEERING↗

R&D to Ensure a Scientific Basis for Qualification Tests and Standards (Final Report: FY19-FY22)

This is the final technical report for the FY19-FY21 research program "R&D to Ensure a Scientific Basis for Qualification Tests and Standards." This research was performed because project return on investment in a photovoltaic (PV) system depends increasingly on maintaining high energy yields, and the system lifetime is a major factor in levelized cost of electricity (LCOE). Thus, the rate of PV deployment and the success of these assets depends upon reliable long-term power generation. This program advances PV module reliability of commercial products through identification of reliability needs, characterization that provides scientific understanding of targeted degradation mechanisms, and translation of those data into practical and predictive test protocols and standards. This report describes program scope, results, milestones, and accomplishments over the three-year period of performance.

14 SOLAR ENERGY↗

2021 NIRT Mini Drill (After Action Report)

During the summer and fall of 2021, several functional area drills were held that focused on exercising Consequence Management’s (CM) ability to extract and use data from RadResponder for the purpose of answering intermediate-phase questions presented as technical inject requests for information (RFI) in Sandia National Laboratories (SNL) Consequence Management Operational System (COSMOS) software. The scenario chosen was that of Northern Lights 2016 (NL16) which was a large-scale nuclear power plant (NPP) release exercise in the state of Minnesota. The NL16 data was extracted from the Radiological Assessment and Monitoring System (RAMS) event where it was created and was reformatted for implanting to a new RadResponder event. Next, the beta-version of a laboratory sample data simulator was used to generate more sample data that was injected to the event. Five “mini-drills” were devised with each prompt defined by a data-based need. For each drill, a team of assessment and NARAC scientists worked the problem using the drill prompt and the available data in RadResponder. The teams held a kickoff meeting, had several days to work the problem, and then reported their results as well as observations in a hotwash. Several areas for improvement in both the software and process were identified during the course of these drills. This report will document the process of addressing each RFI and the discovered gaps in both software capability and methodology so that they can be considered for future development and investment by the CM and NIRT programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

New Industry Partnerships: Solar Energy Technologies Office Support for Early Projects in the Energy Systems Integration Facility: An Agreement Closeout Summary Report

The U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) Solar Energy Technologies Office (SETO)-funded New Industry Partnerships (NIPs) agreement established multiple new cooperative research projects with industry partners. Each project demonstrated the use of the National Renewable Energy Laboratory's Energy Systems Integration Facility (ESIF) as a national asset for research and development, testing, and validation of new technologies to support high penetrations of solar energy on the electric grid. The agreement was launched in 2013 and represented the SETO portion of the DOE EERE-wide Integrated Network Testbed for Energy Grid Research and Technology Experimentation (INTEGRATE) program. The focus of INTEGRATE was on multi-energy system testing and on testing the interactions of energy systems with information technology, communications, and telecommunications (ICT) systems. The NIPs agreement was a bit different from traditional research projects because it was specifically structured to enable partnerships for ESIF testing and as such required at least a 1:1 funds-in cost share from industry partners. In the end, the project engaged six different industry partnerships and resulted in testing a large number of innovative technologies. These included tiny inverters; power-to-gas technologies; and advanced simulation, analysis, and power-hardware-in-the-loop testing techniques. The agreement also provided significant impact for both research and industrial communities. This summary report provides a brief, high-level overview of these projects and their highlights along with lists of citations and other impacts. Readers are referred to the corresponding project reports for more in-depth information.

14 SOLAR ENERGY↗

Panorama 360 (Final Report)

This final technical report from the lead institution, USC grant #DE-SC0012636, serves as the final technical report for collaborative institution UNC-CH grant #DE-SC0012390. The goal was to develop a repository and associated capabilities for data collection, ingestion, and analysis for a broad class of DOE applications that span experimental and simulation science workflows. In particular, this work focuses on workflows that include experimental data generation at DOE facilities. The main activities of Panorama 360 include the development of: (1) A distributed repository that stores different types of workflow execution data (e.g., point and time series performance traces at fine- and coarse-grained levels); (2) A set of open-source data capture, curation, and publishing tools fully integrated with a state-of-the-art workflow management system that automates data ingestion to the repository and enables users to discover, query, and process data from the repository; (3) A set of analysis algorithms and machine learning based tools to perform analysis and characterization of the gathered data, which can be used to detect anomalous performance or system faults; and (4) Best practices and recommendations for workflow evaluation, analysis, execution, and architectures.

97 MATHEMATICS AND COMPUTING↗

Attenuator, PC-2.92mm, Fixed (Proficiency Test Report: Document # 6679664_11752120)

The PSL has reviewed the documentation and data provided by NNSS–Livermore Operations with respect to this proficiency test. This proficiency test was performed to assess NNSS–Livermore Operations’ ability to perform scattering parameter calibrations. The level of documentation was satisfactory. On 5/19/2020, NNSS–Livermore Operations reported the data for the proficiency test conducted on the attenuator. NNSS–Livermore Operations performed this proficiency test using an Anritsu vector network analyzer, an electronic calibration module, and verification kit. The PSL used a Keysight vector network analyzer and mechanical calibration kit. The PSL results included in this proficiency test report were taken on June 23, 2020.

47 OTHER INSTRUMENTATION↗

Quantitative Performance Assessment of Proxy Apps and Parents (Report for ECP Proxy App Project Milestone ADCD-504-11)

The ECP Proxy Application Project has an annual milestone to assess the state of ECP proxy applications. Our FY21 milestone (ADCD-504-11) proposed to: "Assess the performance and fidelity of proxy applications, including those in the ECP Proxy App Suite, relative to the ECP Application workload on heterogeneous platforms. Use proxy applications and selected ECP applications to assess the utility of critical elements of the Exascale toolchain, especially tools used to collect performance data. Identify gaps in coverage and/or common situations in which proxies may fail to adequately represent ECP applications." To satisfy this milestone, the following specific tasks were completed: Study ability of MACSio to represent I/O workloads of adaptive mesh codes; Prepare report on assessed performance and debugging tools; Perform cosine similarity study on Intel and P9 and submit paper; Complete LDMS/GPU subcontract, complete and receive report; Complete validation of LDMS data collection for GPUs and submit paper; and Perform cosine similarity study on GPUs.

97 MATHEMATICS AND COMPUTING↗