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This spring and summer, a series of uncrewed aerial system (UAS) flights will be made from the Blackwell Tonkawa Municipal Airport to the Southern Great Plains (SGP) atmospheric observatory. The SGP is operated by the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility.
The purpose of the Field Validation of Cloud Properties Sensor – SAIL campaign was to deploy Aerodyne’s extended-wavelength TWST cloud optical properties sensor (TWST-CPS) in an operationally relevant environment with co-located, externally validated sensors. Colocation with The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s deployment of its second Mobile Facility (AMF2) on the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign at Crested Butte, Colorado was ideal because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance over 440-1700 nm and retrieves cloud optical depth (COD), droplet effective radius (Reff), and thermodynamic phase (Phase). Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A low-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Instrument deployment to test robust operations and a new stray-light baffle design, and the continued development of analysis and retrieval algorithms using the data from this deployment, are central technical objectives of Aerodyne Research’s U.S. Department of Energy Small Business Innovative Research Phase 2 contract (DE-SC0020473, Low-cost shortwave spectroradiometer for retrieval of cloud properties).
The purpose of the Field Validation of Cloud Properties Sensor – SAIL campaign was to deploy Aerodyne’s extended-wavelength TWST cloud optical properties sensor (TWST-CPS) in an operationally relevant environment with co-located, externally validated sensors. Colocation with The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s deployment of its second Mobile Facility (AMF2) on the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign at Crested Butte, Colorado was ideal because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance over 440-1700 nm and retrieves cloud optical depth (COD), droplet effective radius (Reff), and thermodynamic phase (Phase). Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A low-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Instrument deployment to test robust operations and a new stray-light baffle design, and the continued development of analysis and retrieval algorithms using the data from this deployment, are central technical objectives of Aerodyne Research’s U.S. Department of Energy Small Business Innovative Research Phase 2 contract (DE-SC0020473, Low-cost shortwave spectroradiometer for retrieval of cloud properties).
Oxide dispersion strengthened (ODS) alloys are promising candidate materials for the next generation advanced nuclear reactors due to their superior irradiation resistance and mechanical properties. To better understand the effect of irradiation on MA956, it is essential to study higher dose (50-100 dpa) samples, so that the general trend of microstructural evolution and the resulting radiation-hardening can be deduced. Currently, ion irradiations are considered the only way to achieve doses beyond ~50 dpa in a practical time frame relevant to alloy and welding development programs. This dataset contains TEM characterization results of ODS MA956 samples that were ion irradiated under different conditions: Sample #5 (1.25 dpa at 190℃); Sample #9 (50 dpa at 190℃); Sample #15 (1.25dpa under 320℃); and Sample 17 (25 dpa at 320℃). TEM characterization focused on the irradiation induced defects (dislocation lines and loops) using the on-zone axis bright field STEM technique. These data were collected using a FEI Tecnai G2 F30 S/TEM at Microscopy and Characterization Suite (MaCS) at Center for Advanced Energy Studies (CAES), Idaho Falls, ID. This project (ion irradiation and TEM studies) was supported by the U.S. Department of Energy, Office of Nuclear Energy under DOE Idaho Operations Office Contract DE-AC07-05ID14517 as part of Nuclear Science User Facilities award #18-14784 (PI: Ramprashad Prabhakaran, PNNL).
Oxide dispersion strengthened (ODS) alloys are promising candidate materials for the next generation advanced nuclear reactors due to their superior irradiation resistance and mechanical properties. To better understand the effect of irradiation on MA956, it is essential to study higher dose (50-100 dpa) samples, so that the general trend of microstructural evolution and the resulting radiation-hardening can be deduced. Currently, ion irradiations are considered the only way to achieve doses beyond ~50 dpa in a practical time frame relevant to alloy and welding development programs. This dataset contains TEM characterization results of ODS MA956 samples that were ion irradiated under different conditions: Sample #5 (1.25 dpa at 190℃); Sample #9 (50 dpa at 190℃); Sample #15 (1.25dpa under 320℃); and Sample 17 (25 dpa at 320℃). TEM characterization focused on the irradiation induced defects (dislocation lines and loops) using the on-zone axis bright field STEM technique. These data were collected using a FEI Tecnai G2 F30 S/TEM at Microscopy and Characterization Suite (MaCS) at Center for Advanced Energy Studies (CAES), Idaho Falls, ID. This project (ion irradiation and TEM studies) was supported by the U.S. Department of Energy, Office of Nuclear Energy under DOE Idaho Operations Office Contract DE-AC07-05ID14517 as part of Nuclear Science User Facilities award #18-14784 (PI: Ramprashad Prabhakaran, PNNL).
HAL/S is a programming language developed to satisfy the flight software requirements for the space shuttle program. The user's guide explains pertinent language operating procedures and described the various HAL/S facilities for manipulating integer, scalar, vector, and matrix data types.
NASA numerical aerodynamic simulation (NAS) facility described in 22-page report provides advanced computational aerodynamics service by mid- to late-1980's for use by government laboratories, industry, and academia. Facility continually upgraded as computer technology advances. Facility expected to begin operating by late 1985, supports both local and remote users.
In the aftermath of the March 2011 multi-unit accident at the Fukushima Daiichi nuclear power plant (Fukushima), the nuclear community has been reassessing certain safety assumptions about nuclear reactor plant design, operations and emergency actions, particularly with respect to extreme events that might occur and that are beyond each plant’s current design basis. Because of our significant domestic investment in nuclear reactor technology (99 operating reactors in the fleet of commercial LWRs with five under construction), the United States has been a major leader internationally in these activities. The U.S. nuclear industry is voluntarily pursuing a number of additional safety initiatives. The NRC continues to evaluate and, where deemed appropriate, establish new requirements for ensuring adequate protection of public health and safety in the occurrence of low probability events at nuclear plants; (e.g., mitigation strategies for beyond design basis events initiated by external events like seismic or flooding initiators). The DOE has also played a major role in the U.S. response to the Fukushima accident. Initially, DOE worked with the Japanese and the international community to help develop a more complete understanding of the Fukushima accident progression and its consequences, and to respond to various safety concerns emerging from uncertainties about the nature of and the effects from the accident. DOE R&D activities are focused on providing scientific and technical insights, data, analyses methods that ultimately support industry efforts to enhance safety. These activities are expected to further enhance the safety performance of currently operating U.S. nuclear power plants as well as better characterize the safety performance of future U.S. plants. In pursuing this area of R&D, DOE recognizes that the commercial nuclear industry is ultimately responsible for the safe operation of licensed nuclear facilities. As such, industry is considered the primary “end user” of the results from this DOE-sponsored work. The response to the Fukushima accident has been global, and there is a continuing multinational interest in collaborations to better quantify accident consequences and to incorporate lessons learned from the accident. DOE will continue to seek opportunities to facilitate collaborations that are of value to the U.S. industry, particularly where the collaboration provides access to vital data from the accident or otherwise supports or leverages other important R&D work. The purpose of the Reactor Safety Technology R&D is to improve understanding of beyond design basis events and reduce uncertainty in severe accident progression, phenomenology, and outcomes using existing analytical codes and information gleaned from severe accidents, in particular the Fukushima Daiichi events. This information will be used to aid in developing mitigating strategies and improving severe accident management guidelines for the current light water reactor fleet.
GaAs-based DC high voltage photo-guns used at accelerators with extensive user programs must exhibit long photocathode operating lifetime. Achieving this goal represents a significant challenge for proposed high average current facilities that must operate at tens of milliamperes or more. Specifically, the operating lifetime is dominated by ion back-bombardment of the photocathode from ionized residual gas. While numerous experiments have been performed to characterize the operating lifetime under various conditions, detailed simulations of the ion back-bombardment mechanism that explains these experiments are lacking. Recently, a new user routine was implemented using the code General Particle Tracer (GPT) to simulate electron impact ionization of residual beam line gas and simultaneously track the incident electron, the ejected electron, and the newly formed ion. This new routine was benchmarked against analytical calculations and then applied to experiments performed at the CEBAF injector at the Thomas Jefferson National Accelerator Facility to study the effectiveness of limiting ions from entering the cathode-anode gap using a positively biased anode. These simulations were performed using detailed 3D field maps produced with CST Microwave Studio describing the photo-gun electrostatics. Discussion of the experiment and the application of this new GPT routine to model the experiments will be presented at the workshop.
The North Slope of Alaska (NSA) atmospheric observatory, operated by the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) User Facility, is a measurement site in the Arctic that has been collecting crucial atmospheric data for more than 25 years. The central facility located in Utqiaġvik, Alaska (formerly known as Barrow) hosts a suite of instruments that are used to better understand arctic processes, which are often not well represented in earth system models. The NSA site sits only a few kilometers from the Arctic Ocean, which also makes it a prime location to study complex ocean-atmosphere-ice interactions. Arctic cloud and precipitation processes are also of scientific interest, and remote-sensing instruments including radars are a key component of the NSA instrument suite. One of the radars at NSA is the X-band Scanning ARM Precipitation Radar (XSAPR). This report evaluates one year of recent XSAPR data from April 2024 through April 2025 and details the process of generating b1-level data. This analysis marks the first effort by ARM staff to quality-control NSA XSAPR data with the goal of routinely producing b1-level data in the future depending on radar operations.
MLExchange is a machine learning (ML) operations platform providing web user-interfaces (UIs) for data visualization and analysis pipelines at synchrotron facilities. Among these UIs is the segmentation app which helps synchrotron users utilize ML algorithms to automatically segment high-resolution scientific images with minimal manual annotation effort. In this work, we share code optimizations that significantly speed up the segmentation inference workflow of large data in short time. By optimizing the sequence of CPU-GPU data transfers and introducing CPU parallelization to key operations, we improve the per-device, per-image frame computational efficiency and observe close to 3×$$\times$$ speedup over the original segmentation inference workflow run time when utilizing a single GPU. Further adaptations enabling multi-GPU inference yield more than 40×$$\times$$ speedup with 100 GPUs compared to the optimized single GPU inference workflow. This acceleration of the segmentation inference workflow will provide MLExchange users with easy access to segmentation results with little wait time.
The X-ray & Cryogenic Facility (XRCF) Handbook is a guide for planning operations at the facility. A summary of the capabilities, policies, and procedures is provided to enhance project coordination between the facility user and XRCF personnel. This handbook includes basic information that will enable the XRCF to effectively plan and support test activities. In addition, this handbook describes the facilities and systems available at the XRCF for supporting test operations. 1.2 General Facility Description The XRCF was built in 1989 to meet the stringent requirements associated with calibration of X-ray optics, instruments, and telescopes and was subsequently modified in 1999 & 2005 to perform the challenging cryogenic verification of Ultraviolet, Optical, and Infrared mirrors. These unique and premier specialty capabilities, coupled with its ability to meet multiple generic thermal vacuum test requirements for large payloads, make the XRCF the most versatile and adaptable space environmental test facility in the Agency. XRCF is also recognized as the newest, most cost effective, most highly utilized facility in the portfolio and as one of only five NASA facilities having unique capabilities. The XRCF is capable of supporting and has supported missions during all phases from technology development to flight verification. Programs/projects that have benefited from XRCF include Chandra, Solar X-ray Imager, Hinode, and James Webb Space Telescope. All test programs have been completed on-schedule and within budget and have experienced no delays due to facility readiness or failures. XRCF is currently supporting Strategic Astrophysics Technology Development for Cosmic Origins. Throughout the years, XRCF has partnered with and continues to maintain positive working relationships with organizations such as ATK, Ball Aerospace, Northrop Grumman Aerospace, Excelis (formerly Kodak/ITT), Smithsonian Astrophysical Observatory, Goddard Space Flight Center, University of Alabama Huntsville, and more.
A hydrogen-evolving homogeneous Ni(P2N2)2 electrocatalyst with peripheral ester groups has been covalently attached to a 1,2,3-triazolyllithium-terminated glassy carbon electrode. The surface-confined complex is an electroctalyst for hydrogen evolution, showing onset of catalytic current at the same potential as the soluble parent complex. X-ray photoemission spectra show excellent agreement between the coupled and homogeneous species. Coverage approaches a dense monolayer. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Office of Basic Energy Sciences. Pacific Northwest National Laboratory is operated by Battelle for the US Department of Energy. The XPS measurements were performed at EMSL, a national scientific user facility sponsored by the Department of Energy's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory.
The code is written in Python and consists of the following pipeline that is implemented in Apache Airflow. This pipeline intends to understand the companies that are directly or indirectly involved with a type of critical infrastructure system at some point in that system's lifecycle. The pipeline takes a configuration file that specifies a list of initial companies to consider, a geographic region of interest, and a set of SEC form types as well as other data sources (e.g. CrunchBase) from which to extract entities and relations. There are four main components to this pipeline as currently implemented: Entity Extraction, Network Construction, Analysis, and Visualization. First, Entity Extraction, is implemented as the `topear-extract_organizations` Apache Airflow workflow. Given an initial query that specifies a geographic region of interest and a time interval, the software will extract CI facilities of interest and organizations that have a direct influence relationship to those facilities (e.g. ownership). During the course of the LDRD, we focused on Electric Vehicle charging stations and this information is available via the Department of Energy (DOE) database on fueling stations maintained by NREL. Within the context of the DOE CESER project, we have focused on Battery Energy Storage Systems (BESS). Second, the Network Extraction component will iteratively construct a social network graph given the set of organizations and people extracted in the previous step. Organizations (and eventually People if desired) are then fed as a query to the `topgear-construct_social_network` Apache Airflow workflow which given a set of initial companies and data sets (e.g. SEC EDGAR form types, OpenCorporates, Crunchbase). This Airflow workflow will iteratively query such data sources to discover relationships with new organizations and people. For example, this module can iteratively query SEC EDGAR for metadata that documents the number of each type of form for the given set of companies and their location. This forms metadata represents a catalog of data sources from SEC EDGAR for the extracted social network knowledge graph. The pipeline then downloads these forms from the website and saves them in a build directory for further processing. These documents are then parsed for entities and relations. Again, we note that in additional to SEC data sources, this step can also pull in information on organizations via API services such as CrunchBase and OpenCorporates or bulk data sources. At the end of this step, the resultant social network, the Critical Infrastructure network, and the edges that encode relationships between organizations and CI facilities, form the Adversarial Socio-Technical Network (ASTN) that informs the analysis. Third, the Analysis component processes these generated ASTN. Previously, that has included the ability to compare prevalence of different vendors for a given infrastructure component type across different regions as well as identify common public and private investors across those vendors. This was demonstrated for EV Charging Stations across several different metropolitan areas within an IEEE PES GridEdge publication. More recently, we have looked at ways to identify infrastructure owners and operators of BESS with the most nameplate capacity across different states as well as other indictors of risk resulting from changes in ownership over time. Finally, the Visualization component consists of an HTML/CSS/JS framework by which users can interact geospatial, operational, and organizational relationships across a given portfolio of Critical Infrastructure facilities. The objective is to provide a library of UI/UX modules that can be repurposed for stakeholder-specific dashboards. All of the modules are related via a common event model that enables UI actions in one view to percolate across the other views.
For more than 30 years the Los Alamos Neutron Science Center (LANSCE) has provided the scientific underpinnings in nuclear physics and material science needed to ensure the safety and surety of the nuclear stockpile into the future. In addition to national security research, the LANSCE User Facility has a vibrant research program in fundamental science, providing the scientific community with intense sources of neutrons and protons to perform experiments supporting civilian research and the production of medical and research isotopes. Five major experimental facilities operate simultaneously. These facilities contribute to the stockpile stewardship program, produce radionuclides for medical testing, and provide a venue for industrial users to irradiate and test electronics. In addition, they perform fundamental research in nuclear physics, nuclear astrophysics, materials science, and many other areas. The LANSCE User Program plays a key role in training the next generation of top scientists and in attracting the best graduate students, postdoctoral researchers, and early-career scientists. The U.S. Department of Energy (DOE), National Nuclear Security Administration (NNSA) —the principal sponsor of LANSCE—works with the Office of Science and the Office of Nuclear Energy, which have synergistic long-term needs for the linear accelerator and the neutron science that is the heart of LANSCE.
The TRACER-iso project took place from June 1 to September 30, 2022, as part of the intensive operational period (IOP) of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s TRacking Aerosol Convection interactions ExpeRiment (TRACER) at the main project site at the La Porte, Texas, municipal airport. The project sought to use measurements of the stable isotopic composition of water vapor to better understand cloud-aerosol interactions in deep convection in a polluted urban setting.
The SAGA editor provides a mechanism by which separate processes can be invoked during an editing session to traverse portions of the parse tree being edited. These processes, termed filter processes, read, analyze, and possibly transform the parse tree, returning the result to the editor. By defining new commands with the editor's user defined command facility, which invoke filter processes, authors of filter can provide complex operations as simple commands. A tree plotter, pretty printer, and Pascal tree transformation program were already written using this facility. The filter processes are introduced, parse tree structure is described and the library interface made available to the programmer. Also discussed is how to compile and run filter processes. Examples are presented to illustrate aspect of each of these areas.
Pegasus and the PegaStar integrated spacecraft bus are described, and an overview of integration and launch operations is provided. Payload design issues include payload volume and mass capability, payload interfaces, and design loads. Vehicle and payload processing issues include integration and handling methods, facilities, contamination control, and launch operations. It is noted that Pegasus provides small satellite users with a cost-effective means for delivering payloads into the specific orbits at the optimal time to meet the most demanding mission requirements. PegaStar provides a flexible cost-effective means for providing long-term on-orbit support while minimizing total program risk and cost.