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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11

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↗

Lawrence Livermore National Laboratory (2022 Annual Site Environment Report (ASER))

Lawrence Livermore National Laboratory (LLNL) is a premier research laboratory that is part of the National Nuclear Security Administration (NNSA) within the U.S. Department of Energy (DOE). As a national security laboratory, LLNL is responsible for ensuring that the nation’s nuclear weapons remain safe, secure, and reliable. The Laboratory also meets other pressing national security needs including countering the proliferation of weapons of mass destruction, strengthening homeland security, and conducting major research in atmospheric, earth, and energy sciences, bioscience and biotechnology, and engineering, basic science, and advanced technology. The Laboratory is managed and operated by Lawrence Livermore National Security, LLC (LLNS) and serves as a scientific resource to the U.S. government and a partner to industry and academia.

54 ENVIRONMENTAL SCIENCES↗

CSP Systems Analysis 2022-2024 (Final Technical Report)

The CSP Systems Analysis project estimates the current market cost of CSP subsystems and technologies for use by the DOE Program and within NREL analysis tools. The project addresses upgrades to NREL's System Advisor Model (SAM) related to CSP, as well as development of new modules within SAM to expand the types of CSP systems that can be simulated and new tools for evaluating CSP subsystem performance or optimizing CSP system layouts, for example, SolarPILOT and SolTrace. The project evaluates the potential cost and performance of new CSP-relevant technologies and generally includes assessment of CSP technologies in support of the DOE subprogram. A primary goal of the CSP System Analysis project is to provide timely and accurate cost data to the DOE to assess the current state of CSP technologies as well as predict performance and cost for pre-commercial and emerging technologies that may impact the industry. Prior work in this task has produced technology cost reports and roadmaps for DOE and highlighted promising research paths that could reduce overall CSP cost, such as the supercritical CO2 power cycle and molten-salt trough systems. CSP Systems Analysis produces modeling tools to evaluate the performance of CSP systems, subsystems, or components, and journal articles, conference papers, technical reports and databases to disseminate information to the CSP industry. CSP technology costs are estimated and tracked using these tools as well as analysis of literature and industry sources. The CSP modeling tools and NREL analysis results are used by researchers; government, financial, and industry analysts; and other CSP stakeholders. The purpose of this final technical report is to summarize the key accomplishments of the past three years of this project. The project was divided into seven separate tasks, and in what follows, we describe the background, objectives, key accomplishments, and path forward for each task within the project, with one section of this report summarizing each task.

14 SOLAR ENERGY↗

Hanford Site Raptor Nest Monitoring Report for Calendar Year 2022

The U.S. Department of Energy, Richland Operations Office (DOE-RL), conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOERL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act of 1969 (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act of 1980. DOE/EIS-0222, Final Hanford Comprehensive Land Use Plan Environmental Impact Statement, (CLUP) evaluates the potential environmental impacts associated with implementing a comprehensive land-use plan for the Hanford Site for at least the next 50 years and ensures that DOE-RL, its contractors, and other entities conduct activities on the Hanford Site in compliance with NEPA.

54 ENVIRONMENTAL SCIENCES↗

Hanford Reach Fall Chinook Salmon Redd Monitoring Report for Calendar Year 2022

The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act. DOE/EIS-0222, Final Hanford Comprehensive Land-Use Plan Environmental Impact Statement, (CLUP) evaluates the potential environmental impacts associated with implementing a comprehensive land-use plan for the Hanford Site for at least the next 50 years, and ensures that DOE-RL, its contractors, and other entities conduct activities on the Hanford Site in compliance with NEPA.

54 ENVIRONMENTAL SCIENCES↗

Hanford Site Freshwater Mussel Monitoring Report for Calendar Year 2022

The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and maintain data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provides baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site that is required for decision making under the National Environmental Policy Act of 1969 and Comprehensive Environmental Response, Compensation, and Liability Act of 1980. In addition, ecological monitoring helps ensure that DOE-RL, its contractors, and other entities conducting activities on the Hanford Site are in compliance with the Hanford Site Comprehensive Land Use Plan (DOE/EIS-0222-F). DOE-RL places priority on monitoring those plant and animal species or habitats with specific regulatory protections or requirements that are rare and/or declining (federal or state listed endangered, threatened, or sensitive species) or are of significant interest to federal, state, or tribal governments or the public.

54 ENVIRONMENTAL SCIENCES↗

Summer Bat Monitoring Report for Calendar Year 2022

Bats belong to the order Chiroptera, which means “hand-wing.” They use a thin membrane of skin stretched between their fingers to fly. All bat species known in the state of Washington are insectivorous and each bat can consume 600-1000 insects per hour while feeding. Bats typically give birth once per year to only one pup, making bat populations vulnerable to impacts and slow to recover. Several species of bats have been documented on the Hanford Site, with nine species identified during the Nature Conservancy surveys in 1997 and 1998, and an additional seven species listed as potentially present (Soll et al. 1999). Previous U.S. Department of Energy, Richland Operations Office (DOE-RL) acoustic surveys conducted in 2012 also confirmed the presence of the same nine species documented by Soll et al. (HNF-53759). In 2021, an additional species, the spotted bat, was observed roosting on the exterior of a facility by Hanford Site personnel; the species was confirmed via photograph by site biologists (Table 1).

54 ENVIRONMENTAL SCIENCES↗

Hanford Site Rare Plant Monitoring Report for Calendar Year 2022

Rare plants are monitored on the Hanford Site as distribution and abundance data of current and historic rare plant populations are necessary to make well-informed environmental and ecological resource management decisions. The Central Hanford Rare Plant Management Plan (DOE/RL-2021-35) guides rare plant monitoring methodology in the context of resource management at the Hanford Site. In 2022, a rare plant monitoring effort occurred on the portion of the Hanford Site (referred to herein as Central Hanford) managed by the U.S. Department of Energy, Richland Operations Office (DOE-RL; Figure 1). The goal of this effort was to revisit known occurrences of upland rare plant populations on Central Hanford to improve baseline information on locations of rare plant populations on the Hanford Site. Rare upland plants were thoroughly surveyed in 2021 but unusually low precipitation that year limited germination of many upland annual plants. Surveys in 2022 focused on rare upland annual species after the Hanford Site received higher than average spring precipitation that was expected to increase germination. Rainfall from April 2022 to June 2022 was 76% higher than average; however, these months were also colder than average. Winter rainfall from January 2022 to March 2022 was 84% lower than average. The high spring precipitation in 2022 appears to have triggered the germination of some populations of rare upland annuals but the dry winter and cold spring may have inhibited others. Population stability, viability, and threats were evaluated and will be used to inform future management of rare plant species.

54 ENVIRONMENTAL SCIENCES↗

SRS 2022 Annual Site Environmental Report (ASER)

ASER stands for the Annual Site Environmental Report and is the primary document that the U.S. Department of Energy uses to inform the public of environmental performance and conditions at SRS. • ASERs are required by U.S. Department of Energy to provide the public and stakeholders information on: – Environmental program performance – Site wide environmental monitoring and surveillance effectiveness – Compliance status with environmental standards and requirements • SRS published its first ASER in 1959

DAVIS, COLLEEN↗

Precursor Analysis Report: Industroyer2 and Wiper Malware Targeting Ukrainian Energy Provider 2022

The Industroyer2 and Wiper Malware Targeting Ukrainian Energy Provider 2022 Precursor Analysis Report leverages publicly available information about the Industroyer2 cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. An adversary attempted to cause a blackout in Ukraine in April 2022 by using the Industroyer2 malware against a regional Ukrainian energy provider. The adversary targeted eight high-voltage electrical substations and utilized the malware in tandem with disk wipers for Windows, Linux, and Solaris operating systems in an attempt to make response and recovery efforts more difficult. The adversary reused a piece of the original Industroyer malware designed to open circuit breakers and de-energize target substations. The adversary gained initial access to the victim’s enterprise network through unknown means in February 2022 and was able to perform reconnaissance, pivot to the operations network, and reside in the system for at least 51 days. This gave the adversary a detailed understanding of the environment and allowed them to customize the Industroyer2 malware to the victim’s operations network. However, defenders detected and stopped the attack before the adversary could achieve their intended impact. Had the Industroyer2 attack been successful, it could have caused a blackout for more than two million people during the early stages of Russia’s invasion of Ukraine. Researchers and analysts identified 22 unique techniques (used in a sequence of 31 steps) utilized during the attack with a total of 297 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Twenty-three of the identified techniques used during the Industroyer2 cyber attack were precursors to the triggering event. Analysis identified 224 observables associated with these precursor techniques, 122 of which were assessed to have an increased likelihood of being perceived in the 51 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Annual Site Environmental Report: Pantex Plant

The 2022 Annual Site Environmental Report (ASER) summarizes Pantex’s status, data, and efforts for the environmental compliance, protection, and restoration programs. It has been prepared in accordance with DOE O 231.1B, Environment, Safety and Health Reporting, and DOE O 458.1, Radiation Protection of the Public and the Environment. These orders outline the requirements for environmental protection programs at DOE facilities to ensure that programs fully comply with applicable federal, state, and local environmental laws and regulations, executive orders, and DOE policies.

54 ENVIRONMENTAL SCIENCES↗

Roadmap for IES Modeling and Simulation Activities: Update 2023

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2020, a last comprehensive roadmap for the DOE-NE Integrated Energy Systems program was published. In 2017, a separate modeling and simulation capability development plan was published that was extensively updated in 2022. The current report incrementally updates the 2022 modeling and simulation capability roadmap. This is not a new report, but individual sections have been updated to reflect recent accomplishments and new directions of the program. The role of modeling and simulation within IES is to support the demonstration of new coupled integrated technologies along every step of the technology maturation from the strategic analysis of preferred system architecture to preliminary design, to laboratory testing, up to full commercial testing and integration. To achieve this role, modeling and simulation must be able to assess the technical performance and the economic viability of potential IES. Also, modeling and simulation must provide support for experimental evaluations (i.e., support component design and real-time operations of experimental demonstration systems). Finally, modeling and simulation can help scale-up experimental systems to the final commercial systems. This report details the current state of the modeling and simulation efforts within IES for the above-mentioned areas, provides a gap analysis, and proposes next steps for a time horizon over the next years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

2022 LANL Radionuclide Air Emissions Report (Rev. 2)

This report describes the emissions of airborne radionuclides from operations at Los Alamos National Laboratory (LANL) for calendar year 2022 and the resulting off-site dose from these emissions. This document fulfills the requirements established by the National Emissions Standards for Hazardous Air Pollutants in 40 CFR 61, Subpart H – Emissions of Radionuclides other than Radon from Department of Energy Facilities, commonly referred to as the Radionuclide NESHAP or Rad-NESHAP. Compliance with this regulation and preparation of this document is the responsibility of LANL’s Rad NESHAP compliance program, which is part of the Environmental Protection and Compliance (EPC) Division. The information in this report is required under the Clean Air Act and is being submitted to the U.S. Environmental Protection Agency (EPA) Headquarters and EPA Region 6. The highest effective dose equivalent (EDE) to an off-site member of the public was calculated using procedures specified by the EPA and described in this report. LANL’s EDE was 0.45 for 2022. The annual limit is 10 millirem per year, established by the EPA in 40 CFR 61 Subpart H. All measured air emissions are modeled to a single location, known as the Maximally Exposed Individual (MEI). During calendar year 2022, LANL continuously monitored radionuclide emissions at 27 “major” release points, or stacks. The Laboratory estimates emissions from an additional 34 “minor” release points using radionuclide usage source terms in lieu of stack monitoring. Also, LANL uses an EPA approved network of air samplers around the Laboratory perimeter to monitor ambient airborne levels of radionuclides. To provide data for dispersion modeling and dose assessment, LANL maintains and operates several meteorological monitoring towers. From these various systems, a comprehensive evaluation is conducted to calculate the MEI dose for the Laboratory. The MEI can be any member of the public at any off-site location where there is a residence, school, business, or office. In 2022, this MEI location was a business at 95 Entrada Drive, located in the eastern end of Los Alamos town site. The primary contributors to the off-site dose at this location are the ambient air data at that location combined with radioactive gas emissions from the LANSCE facility and the collected potential emissions from unmonitored (minor) sources. Overall, the MEI dose in 2022 is similar to that which has been observed in recent years, and it remains well below the EPA’s 10 millirem per year limit. Doses reported to the EPA for the past 10 years are shown in Table E1.

54 ENVIRONMENTAL SCIENCES↗

Fusion Materials Semiannual Progress Report for the Period Ending December 31, 2022

This is the seventy-third in a series of semiannual technical progress reports on fusion materials science activity supported by the Fusion Energy Sciences Program of the U.S. Department of Energy. It covers the period ending December 31, 2022. This report focuses on research addressing the effects on materials properties and performance of exposure to the neutronic, thermal and chemical environments anticipated in the chambers of fusion experiments and energy systems. This research is a major element of the national effort to establish the materials knowledge base for an economically and environmentally attractive fusion energy source. Research activities on issues related to the interaction of materials with plasmas are reported separately. The results reported are the products of a national effort involving a number of national laboratories and universities. A large fraction of this work, particularly in relation to fission reactor irradiations, is carried out collaboratively with partners in Japan, Russia, and the European Union. The purpose of this series of reports is to provide a working technical record for the use of program participants, and to provide a means of communicating the efforts of fusion materials scientists to the broader fusion community, both nationally and worldwide. This report has been compiled by Stephanie Melton, Oak Ridge National Laboratory. Her efforts, and the efforts of the many persons who made technical contributions, are gratefully acknowledged.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Long-run Marginal Emission Rates for Electricity - Workbooks for 2022 Cambium Data

These workbooks contain modeled estimates of long-run marginal emission rates (LRMER) for the contiguous United States. A LRMER is an estimate of the rate of emissions that would be either induced or avoided by a change in electric demand, taking into account how the change could influence both the operation as well as the structure of the grid (i.e., the building and retiring of capital assets, such as generators and transmission lines). It is therefore distinct from the more-commonly-known short-run marginal, which treat grid assets as fixed. Long-run marginal emissions rates are generally appropriate to use when trying to comprehensively estimate the impact of a long-lived (i.e., more than several years) intervention. There are two workbooks that supply the data at two different geographic resolutions: states and GEA regions (20 regions that are similar to, but not exactly the same as, the US EPA's eGRID regions). For more data underlying these emissions factors, see the Cambium 2022 project at https://scenarioviewer.nrel.gov/. For more details on input assumptions and methodology see the associated report (Cambium 2022 Scenario Descriptions and Documentation, https://www.nrel.gov/docs/fy23osti/84916.pdf). This data is planned to be updated annually. Information on the latest versions can be found at https://www.nrel.gov/analysis/cambium.html.

01 COAL, LIGNITE, AND PEAT↗

Measurement of the free neutron lifetime in a magneto-gravitational trap with in situ detection

Here, in this study, we publish three years of data from the UCNτ experiment performed at the Los Alamos Ultracold Neutron Facility at the Los Alamos Neutron Science Center. These data are in addition to our previously published data. Our goals in this paper are to better understand and quantify systematic uncertainties and to improve the lifetime statistical precision. We previously reported a value from our 2017–2018 data for the neutron lifetime of 877.75 ± 0.28 (statistical) +0.22–0.16 (systematic) s. We have collected an additional three years of data reported here for the first time. When all the data from UCNτ are averaged for 2017, 2018, 2020, 2021, and 2022, we report an updated value for the lifetime of 877.83 ± 0.22 (statistical)+0.20–0.17 (systematic) s. We utilized improved monitor detectors, reduced our correction due to UCN upscattering on residual gas, and employed four different UCN detector geometries both to reduce the correction required for rate dependence and to explore potential contributions due to phase space evolution.

Cabibbo-Kobayashi-Maskawa matrix↗