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At least 145 records · Page 8

NCERC 2024 Highlights

The National Nuclear Security Administration (NNSA) is entrusted with ensuring the safety, security, and reliability of the nation’s nuclear weapons stockpile while advancing programs aimed at reducing global nuclear proliferation. These critical mission objectives are achieved through the expertise of a highly skilled team of professionals. The operations at the National Criticality Experiments Research Center (NCERC) play a vital role in developing and enhancing knowledge and expertise in advanced nuclear technologies. NCERC supports a wide range of mission areas, including nuclear criticality safety, nuclear emergency response, and nuclear nonproliferation, safeguards, and arms control. It also provides support to the Department of Homeland Security, advances stockpile stewardship science, and delivers scientific expertise to other government agencies, such as NASA and the Defense Threat Reduction Agency. NCERC conducts experiments utilizing diverse nuclear materials, from small neutron-emitting sources for testing radiation detection equipment to larger quantities of uranium and plutonium for criticality experiments. A cornerstone of NCERC's mission portfolio includes the operation of four critical mass assembly machines—Planet, Comet, Flattop, and Godiva-IV—which are instrumental in advancing nuclear science and ensuring the nation’s nuclear security objectives.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Training the next generation of researchers in exploring cloud dynamics and microphysics using millimeter-wavelength radars

Millimeter-wavelength radars, with their ability to collect observations and high spatiotemporal resolution, have become cornerstone instruments for investigating cloud and precipitation microphysics and dynamics in the last two decades. Since the1990s the US Department of Energy Atmospheric Radiation Measurement (ARM) program has invested in mm-wavelength radar technology progressively adding scanning capability, additional frequencies and polarimetric capability. In addition, atmospheric observatories including those technologies have been operated overseas. Those technologies have enhanced our understanding of cloud and precipitation processes. Only a few universities operate those instruments and use them for educational purposes. The central role of mm- wavelength radars and their role will be further highlighted in the next decade. NASA and other international space agencies are planning to launch millimeter-wavelength (i.e., Ku, Ka, W, G- bands) Doppler radar in space to improve our understanding of cloud and precipitation formation, evolution and their impacts on global climate.

54 ENVIRONMENTAL SCIENCES↗

TChem v2.0 - A Software Toolkit for the Analysis of Complex Kinetic Models

TChem is an open source software library for solving complex computational chemistry problems and analyzing detailed chemical kinetic models. The software provides support for: complex kinetic models for gas-phase and surface chemistry; thermodynamic properties based on NASA polynomials; species production/consumption rates; stable time integrator for solving stiff time ordinary differential equations; and, reactor models such as homogenous gas-phase ignition (with analytical Jacobian matrices), continuously stirred tank reactor, plug-flow reactor. This toolkit builds upon earlier versions that were written in C and featured tools for gas-phase chemistry only. The current version of the software was completely refactored in C++, uses an object-oriented programming model, and adopts Kokkos as its portability layer to make it ready for the next generation computing architectures i.e., multi/many core computing platforms with GPU accelerators. We have expanded the range of kinetic models to include surface chemistry and have added examples pertaining to Continuously Stirred Tank Reactors (CSTR) and Plug Flow Reactor (PFR) models to complement the homogenous ignition examples present in the earlier versions. To exploit the massive parallelism available from modern computing platforms, the current software interface is designed to evaluate samples in parallel, which enables large scale parametric studies, e.g. for sensitivity analysis and model calibration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Novel Harsh Environment Materials and Fabrication Techniques for Wireless Sensor Applications (Final Report)

The overarching goal of this project is to establish a center of excellence program at the University of Maine that is focused on Harsh Environmental Materials and Fabrication Techniques for Wireless Sensor Applications. UMaine is well-positioned to build on previous successes in the areas of materials science research and sensor engineering. Since 1980, the Laboratory for Surface Science & Technology (LASST) has been a very successful interdisciplinary UMaine research center with a well-established infrastructure to investigate surfaces, interfaces, thin films, and micro/nano-fabrication. This infrastructure established through NSF, DOE, DOD, NASA, the State of Maine, and industry includes (i) a 3,500 ft2 clean room with nano/microfabrication and photolithography instrumentation, (ii) thin film synthesis, processing and characterization, (iii) surface and thin film analytical chemistry tools, and (iv) device packaging, electronic testing, wireless devices, system fabrication, and sensor test facilities. This strong foundation is the basis for a planned significant growth in R&D capacity currently underway. To that end, since the start of this project in the Fall of 2019, LASST has undergone a transition to become a new interdisciplinary center at UMaine, named the Frontier Institute for Research in Sensor Technologies (FIRST). This new focus represents a commitment and investment by UMaine that aligns with the proposed DOE-EPSCoR theme, capitalizing on the state-of-the-art instrumentation to form an energized group of faculty and students pursuing advances in sensor materials, devices, and applications.

36 MATERIALS SCIENCE↗

Solid Rocket Propellant Fires Characterization, Final Scientific/Technical Report for 8 May 2014 through 4 October 2017

The Solid Rocket Propellant Fires Characterization Program continued the Johns Hopkins University Applied Physics Laboratory's (JHU/APL's) characterization of solid propellant fires under relevant accident conditions [at 1 atmosphere (atm) ambient pressure, in humid weather], with significant findings that have revolutionized the understanding of these fires and the response and behavior of plutonium dioxide (plutonia) surrogates in the fires. These findings have been disseminated in Department of Energy (DOE) internal working meetings and at technical interchange meetings (TIMs) with DOE, the Interagency Nuclear Safety Review Panel (INSRP), and NASA in support of the Presidential nuclear safety launch approval process for the Mars 2020 mission, as well as via several conference and journal papers.

10 SYNTHETIC FUELS↗

Amplitude Variability in gamma Dor and delta Sct Stars Observed by Kepler

The NASA Kepler spacecraft data revealed a large number of new multimode nonradially pulsating gamma Dor and delta Sct variable stars. The Kepler high-precision long time-series photometry makes it possible to study amplitude variations of the frequencies, and recent literature on amplitude and frequency variations in nonradially pulsating variables is summarized. Several methods are applied to study amplitude variability in about a dozen gamma Doradus or delta Scuti candidate variable stars observed for several quarters as part of the Kepler Guest Observer program. The magnitude and timescale of the amplitude variations are discussed, along with the presence or absence of correlations between amplitude variations for different frequencies of a given star. Proposed causes of amplitude spectrum variability that will require further investigation are also discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO 2 Emissions

Satellite data provides essential insights into the spatiotemporal distribution of CO 2 concentrations. However, many atmospheric inverse models fail to adequately incorporate the spatial and temporal correlations inherent in satellite observations and often lack rigorous methods for estimating parameters like spatial length scales. We introduce an inference model that processes the spatiotemporal covariance in satellite data and estimates hyperparameters such as covariance length scales. Our approach uses the Gaussian process (GP) machine learning (ML) and modern probabilistic programming languages (PPLs) to perform atmospheric inversions of emissions from satellite data. We develop a GP ML inversion system based on modern PPLs and the GEOS-Chem chemical transport model, simulating atmospheric CO 2 concentrations corresponding to the Orbiting Carbon Observatory-2/3 (OCO-2/3) data for July 2020. In our supervised learning framework, we treat the GEOS-Chem simulated data set as the target, with predictors derived by scaling the target with sector-specific factors hidden from the GP machine. Our results show that the GP model, combined with GPU-enabled PPLs, effectively retrieves true emission scaling factors and infers noise levels concealed within the data. This suggests that our method could be applied over larger areas with more complex covariance structures, enabling comprehensive analysis of the spatiotemporal patterns observed in OCO-2/3 and similar satellite data sets.

54 ENVIRONMENTAL SCIENCES↗

Global Corn Heat Stress: Mean and SD of Degree Days Above 29°C based on NEX-GDDP-CMIP6 Climate Projections

Description This global dataset provides the estimated mean and standard deviation (SD) of corn heat stress (degree days above 29°C) for a set of climate models in NEX-GDDP-CMIP6 at 0.25-degree resolution. The NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6). The current dataset includes: Long-Term Average Degree Days Above 29°C- Historical Long-Term Average Degree Days Above 29°C- SSP245 Long-Term Standard Deviation of Degree Days Above 29°C- Historical Long-Term Standard Deviation of Degree Days Above 29°C- SSP245 The mean and SD are calculated over 1985-2014 for the historical period and over 2035-2064 for future projections. A full description of methods, including growing season, daily temperature distribution, and statistical coefficients, can be found in Haqiqi (2024). The source climate data are obtained from https://ds.nccs.nasa.gov/thredds2/catalog/catalog.html and are described in Thrasher et al (2022). The codes used to create this dataset are available at https://github.com/ihaqiqi/dd29c_nex_cmip6. Acknowledgments This work was supported by the US Department of Energy, Office of Science, Biological and Environmental Research Program, Earth and Environmental Systems Modeling, MultiSector Dynamics under Cooperative Agreement DE-SC0022141. The data processing, computation, and storage were completed on Purdue Anvil supercomputer and cyberinfrastructure supported by the National Science Foundation HDR award # 2118329: "NSF Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE)". References Haqiqi. I. (2024). Trade can buffer climate-induced risks and volatilities in crop supply. Environmental Research: Food Systems. https://doi.org/10.1088/2976-601X/ad7d12 Thrasher, B., Wang, W., Michaelis, A., Melton, F., Lee, T., & Nemani, R. (2022). NASA global daily downscaled projections, CMIP6. Scientific Data, 9(1), 262. https://doi.org/10.1038/s41597-022-01393-4

Climate Change↗

THE NASA AMES PAH IR SPECTROSCOPIC DATABASE VERSION 2.00: UPDATED CONTENT, WEB SITE, AND ON(OFF)LINE TOOLS

A significantly updated version of the NASA Ames PAH IR Spectroscopic Database, the first major revision since its release in 2010, is presented. The current version, version 2.00, contains 700 computational and 75 experimental spectra compared, respectively, with 583 and 60 in the initial release. The spectra span the 2.5-4000 μm (4000-2.5 cm{sup -1}) range. New tools are available on the site that allow one to analyze spectra in the database and compare them with imported astronomical spectra as well as a suite of IDL object classes (a collection of programs utilizing IDL's object-oriented programming capabilities) that permit offline analysis called the AmesPAHdbIDLSuite. Most noteworthy among the additions are the extension of the computational spectroscopic database to include a number of significantly larger polycyclic aromatic hydrocarbons (PAHs), the ability to visualize the molecular atomic motions corresponding to each vibrational mode, and a new tool that allows one to perform a non-negative least-squares fit of an imported astronomical spectrum with PAH spectra in the computational database. Finally, a methodology is described in the Appendix, and implemented using the AmesPAHdbIDLSuite, that allows the user to enforce charge balance during the fitting procedure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BRR Cask Use for Pu-238 Isotope Production

The Department of Energy (DOE), in partnership with its national laboratories and the National Aeronautics and Space Administration (NASA), is responsible to produce Pu-238 isotope in the United States for use in space exploration. Major activities in the DOE complex are focused at Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL). INL is responsible for storing Np-237 feedstock, irradiation qualification in the Advanced Test Reactor (ATR), and irradiating targets containing Np-237 to produce Pu-238. ORNL is responsible for target design, target fabrication, irradiation qualification in HFIR, and processing of targets to extract Pu-238 heat source material. A key part of the program lifecycle is moving irradiated targets from INL to ORNL. The BEA Research Reactor (BRR) cask was identified as a potential shipping cask for the transport of both unirradiated and irradiated targets between the project sites. This paper will discuss the production at INL and shipment of Pu-238 to ORNL using the BRR cask.

07 ISOTOPE AND RADIATION SOURCES↗

MOA-2007-BLG-400 A Super-Jupiter-mass Planet Orbiting a Galactic Bulge K-dwarf Revealed by Keck Adaptive Optics Imaging

We present Keck/NIRC2 adaptive optics imaging of planetary microlensing event MOA-2007-BLG-400 that resolves the lens star system from the source. We find that the MOA-2007-BLG-400L planetary system consists of a 1.71 ± 0.27M {sub Jup} planet orbiting a 0.69 ± 0.04M {sub ⊙} K-dwarf host star at a distance of 6.89 ± 0.77 kpc from the Sun. So, this planetary system probably resides in the Galactic bulge. The planet–host star projected separation is only weakly constrained due to the close-wide light-curve degeneracy; the 2σ projected separation ranges are 0.6–1.0 au and 4.7–7.7 au for close and wide solutions, respectively. This host mass is at the top end of the range of masses predicted by a standard Bayesian analysis. Our Keck follow-up program has now measured lens-source separations for six planetary microlensing events, and five of these six events have host star masses above the median prediction under the assumption that assumes that all stars have an equal chance of hosting planets detectable by microlensing. This suggests that more massive stars may be more likely to host planets of a fixed mass ratio that orbit near or beyond the snow line. These results also indicate the importance of host star mass measurements for exoplanets found by microlensing. The microlensing survey imaging data from NASA’s Nancy Grace Roman Space Telescope (formerly WFIRST) mission will be doing mass measurements like this for a huge number of planetary events.

47 OTHER INSTRUMENTATION↗

The Early Career Research Program Annual Progress Report: Using ARM Data and Multiscale Models to Advance the Understanding of Liquid-Phase Cloud Response to Aerosol Perturbation over Ocean and Land

This report is for the first fiscal year of this ECRP project. This ECRP project aims to study the response of liquid-phase clouds to aerosol perturbation and reduce the related uncertainty in the DOE Earth system model. During this fiscal year, this project mainly made progress on the tasks about observational analyses for Objective 1; and successfully set up two Large-Eddy Simulation (LES) models for Objective 2. A postdoctoral researcher and a graduate student summer intern are on board and fully dedicated to this project. In addition to internal collaboration within LLNL, this project has routinely maintained external collaboration with scientists from universities, NASA Langley Research Center, and other DOE national laboratories. For the next reporting period, we plan to complete the tasks scheduled for the second year. Furthermore, we will promote the findings to communities of interest and proactively seek new collaborations to increase the impact of this project.

54 ENVIRONMENTAL SCIENCES↗

PERIOD ERROR ESTIMATION FOR THE KEPLER ECLIPSING BINARY CATALOG

The Kepler Eclipsing Binary Catalog (KEBC) describes 2165 eclipsing binaries identified in the 115 deg{sup 2} Kepler Field based on observations from Kepler quarters Q0, Q1, and Q2. The periods in the KEBC are given in units of days out to six decimal places but no period errors are provided. We present the PEC (Period Error Calculator) algorithm, which can be used to estimate the period errors of strictly periodic variables observed by the Kepler Mission. The PEC algorithm is based on propagation of error theory and assumes that observation of every light curve peak/minimum in a long time-series observation can be unambiguously identified. The PEC algorithm can be efficiently programmed using just a few lines of C computer language code. The PEC algorithm was used to develop a simple model that provides period error estimates for eclipsing binaries in the KEBC with periods less than 62.5 days: log {sigma}{sub P} Almost-Equal-To - 5.8908 + 1.4425(1 + log P), where P is the period of an eclipsing binary in the KEBC in units of days. KEBC systems with periods {>=}62.5 days have KEBC period errors of {approx}0.0144 days. Periods and period errors of seven eclipsing binary systems in the KEBC were measured using the NASA Exoplanet Archive Periodogram Service and compared to period errors estimated using the PEC algorithm.

79 ASTRONOMY AND ASTROPHYSICS↗

Technology readiness levels for advanced nuclear fuels and materials development

The Technology Readiness Level (TRL) process is used to quantitatively assess the maturity of a given technology. It was pioneered by the National Aeronautics and Space Administration (NASA) in the 1980s to develop and deploy new systems for space applications. The process was subsequently adopted by the Department of Defense (DoD) to develop and deploy new technology and systems for defense applications as well as the Department of Energy (DOE) to evaluate the maturity of new technologies in major construction projects. Advanced nuclear fuels and materials development is a critical technology needed for improving the performance and safety of current and advanced reactors, and ultimately closing the nuclear fuel cycle. Because deployment of new nuclear fuel forms requires a lengthy and expensive research, development, and demonstration program, applying the TRL concept to the advanced fuel development program is very useful as a management, communication and tracking tool. Furthermore, this article provides examples regarding the methods by which TRLs are currently used to assess the maturity of nuclear fuels and materials under development in the DOE Fuel Cycle Research and Development (FCRD) Program within the Advanced Fuels Campaign (AFC).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

New Generator Technology

New generator technology project is driven by the need to be able to remotely deploy generator technology where it is needed, when it is needed. Both the military and aid programs that provide assistance after disasters could use the ability to deploy energy generation that fits the needs of the situation. Currently, pre-specified generators are deployed, sometime more than half way around the world to provide electricity. Through our Phase-I to Phase III DARPA grant, we will provide a mechanism where a 3d print station and raw materials could be shipped to a deployment site and remotely deployed personnel. These remote personnel can collaborate with engineers at a home location where 3d print plans can be optimized for the remote purpose. The plans can then be sent electronically to the remote location for printing, much like NASA sent the plans for a socket wrench to the International Space Station for printing in . If multiple generators need to be deployed at different remote locations, within miles of each other the printer rig can be moved to print the generators where they are needed. 3d printing is growing in the field of manufacturing. 3d printing has matured to the point where many types of materials are now available for many types of manufacturing. Both magnetic and electrically conductive material materials have recently been developed which can now lead to 3d printing of engines and generators. Our project will provide a successful printer rig that can be remotely deployed, to print a generator design in the field as well as provide a process for deploying the printed generator as well. This Systems Engineering Management Plan(SEMP) will provide the planning required for a Phase I DARPA grant that may also include goals for Phase II and Phase II grants. The SEMP provides a proposed project schedule, references, system engineering processes, specialty engineering system deployment and product support sections. Each section will state how our company will provide the necessary services to make this project succeed.

3D printing, manufacturing, generator technology, ↗

An Early Quantum Computing Proposal

The D-Wave 2X is the third generation of quantum processing created by D-Wave. NASA (with Google and USRA) and Lockheed Martin (with USC), both own D-Wave systems. Los Alamos National Laboratory (LANL) purchased a D-Wave 2X in November 2015. The D-Wave 2X processor contains (nominally) 1152 quantum bits (or qubits) and is designed to specifically perform quantum annealing, which is a well-known method for finding a global minimum of an optimization problem. This methodology is based on direct execution of a quantum evolution in experimental quantum hardware. While this can be a powerful method for solving particular kinds of problems, it also means that the D-Wave 2X processor is not a general computing processor and cannot be programmed to perform a wide variety of tasks. It is a highly specialized processor, well beyond what NNSA currently thinks of as an “advanced architecture.”A D-Wave is best described as a quantum optimizer. That is, it uses quantum superposition to find the lowest energy state of a system by repeated doses of power and settling stages. The D-Wave produces multiple solutions to any suitably formulated problem, one of which is the lowest energy state solution (global minimum). Mapping problems onto the D-Wave requires defining an objective function to be minimized and then encoding that function in the Hamiltonian of the D-Wave system. The quantum annealing method is then used to find the lowest energy configuration of the Hamiltonian using the current D-Wave Two, two-level, quantum processor. This is not always an easy thing to do, and the D-Wave Two has significant limitations that restrict problem sizes that can be run and algorithmic choices that can be made. Furthermore, as more people are exploring this technology, it has become clear that it is very difficult to come up with general approaches to optimization that can both utilize the D-Wave and that can do better than highly developed algorithms on conventional computers for specific applications. These are all fundamental challenges that must be overcome for the D-Wave, or similar, quantum computing technology to be broadly applicable.

97 MATHEMATICS AND COMPUTING↗

Study of Compatibility of Stainless Steel Weld Joints with Liquid Sodium-Potassium Coolants for Fission Surface Power Reactors for Lunar and Space Applications

To make a manned mission to the surface of the moon or to Mars with any significant residence time, the power requirements will make a nuclear reactor the most feasible source of energy. To prepare for such a mission, NASA has teamed with the DOE to develop Fission Surface Power technology with the goal of developing viable options. The Fission Surface Power System (FSPS) recommended as the initial baseline design includes a liquid metal reactor and primary coolant system that transfers heat to two intermediate liquid metal heat transfer loops. Each intermediate loop transfers heat to two Stirling heat exchangers that each power two Stirling converters. Both the primary and the intermediate loops will use sodium-potassium (NaK) as the liquid metal coolant, and the primary loop will operate at temperatures exceeding 600°C. The alloy selected for the heat exchangers and piping is AISI Type 316L stainless steel. The extensive experience with NaK in breeder reactor programs and with earlier space reactors for unmanned missions lends considerable confidence in using NaK as a coolant in contact with stainless steel alloys. However, the microstructure, chemical segregation, and stress state of a weld leads to the potential for corrosion and cracking. Such failures have been experienced in NaK systems that have operated for times less than the eight year goal for the FSPS. For this reason, it was necessary to evaluate candidate weld techniques and expose welds to high-temperature, flowing NaK in a closed, closely controlled system. The goal of this project was to determine the optimum weld configuration for a NaK system that will withstand service for eight years under FSPS conditions. Since the most difficult weld to make and to evaluate is the tube to tube sheet weld in the intermediate heat exchangers, it was the focus of this research. A pumped loop of flowing NaK was fabricated for exposure of candidate weld specimens at temperatures of 600°C, the expected temperature within the intermediate heat exchangers. Since metal transfer from a high-temperature region to a cooler region is a predominant mode of corrosion in liquid metal systems, specimens were placed at zones in the loop at the above temperature to evaluate the effects of both alloy component leaching and metal deposition. Microstructural analysis was performed to evaluate weld performance on control weld specimens. The research was coordinated with Oak Ridge National Laboratory (ORNL) where most of the weld samples were prepared. In addition, ORNL participated in the loop operation to assist in keeping the testing relevant to the project and to take advantage of the extensive experience in liquid metal research at ORNL.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

MeVPrtl: An Event Generator for Dark Sector Particles in the Short-Baseline Neutrino Program

MeVPrtl is a modular event generator of beyond the Standard Model (BSM) physics particles developed for use in the Short-Baseline Neutrino (SBN) Program. A large class of BSM physics models predict that new particles could be produced in the intense Booster Neutrino Beam (BNB) and Neutrinos at the Main Injector (NuMI) beams at Fermilab, travel to the SBN Program detectors, and decay into Standard Model (SM) particles. These new physics models are motivated by dark matter, the neutrino mass scale, and a solution to the strong CP problem. MeVPrtl provides an interface to implement the overlapping phenomenology of these models, and to connect them with meson flux inputs and object outputs used by the SBN Program's LArSoft-based detector simulation. Implementations for the Higgs portal, heavy neutral lepton, and heavy QCD axion models exist within MeVPrtl. In this paper these implementations and their validation, as well as details of the MeVPrtl interface, are specified.

Abratenko Ao, P.↗