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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Dissolution of Light Curium Oxide with a Catalyzed Electrolytic Process

The ability to produce transcurium elements and isotopes, such as 249 Bk and 252 Cf, requires the appropriate feed material and a high thermal neutron flux. Currently, at Oak Ridge National Laboratory (ORNL), the High Flux Isotope Reactor (HFIR) provides one of the world’s highest steady state thermal neutron fluxes. The feed material consists of recycled curium from the decades of production of 249 Bk, 252 Cf, 253 Es, and 255/257 Fm at the Radiochemical Engineering Development Center (REDC). Over time, the feed material has been depleted and needs to be replenished. The current feed material is called “heavy recycled curium” and consists of over 50 wt% of 246/248 Cm isotopes. In order to replenish this stock material, additional curium is needed. The only curium material that is currently available consists predominantly (greater than 80 wt%) of 244 Cm. This material also contains 240 Pu from the radioactive decay of the 244 Cm. Because of the amount of 244 Cm is greater than 50% of the total Cm, this material is termed “light curium.” Today, 249 Bk and 252 Cf are produced in only two places in the world: the United States and Russia. In the United States, the US Department of Energy and its predecessors have made these isotopes and others available to research agencies and commercial users since the late 1960s as part of the Department of Energy heavy-element production program located at ORNL. Currently these materials are provided through the DOE Office of Science Nuclear Physics-Isotope Development and Production for Research and Applications and the Basic Energy Science-Heavy Element Chemistry. Feedstock for the production of 252 Cf and other transcurium element by-product isotopes was originally prepared by means of irradiation of multi-kilograms of 239 Pu in the large production reactors at the Savannah River Site. Products of the Savannah River Site irradiation were predominantly 242 Pu, 243 Am, and 244 Cm. These materials were shipped to ORNL for production of multi-milligram amounts per year of 252 Cf and other transcurium element isotopes by means of irradiation in the HFIR, followed by separation and purification processing in the Radiochemical Engineering Development Center (REDC). The transcurium element isotopes produced were distributed to other US and collaborating foreign laboratories for research studies to determine the nuclear and chemical properties of these rare materials. The Cm feed material plays a key role in the efficient production of 252 Cf. The early targets irradiated in HFIR contained only the 242 Pu, 243 Am, and 244 Cm produced at Savannah River Site, and the rate of production of 252 Cf was less than 1 mg per 8 g of target material as shown in Figure 1. Also, shown in Figure 1 is the significant difference in 252 Cf production between the light and heavy curium; it differs by approximately 2 orders of magnitude.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Cyberguardians Webinar

Robust solar industry growth is creating a shortage of U.S. workers who are knowledgeable in emerging Distributed Energy Resource (DER) technologies including networking, operational software, smart advanced inverters, smart advanced PV modules, and cybersecurity. Retraining military veterans and other qualified individuals to fill workforce gaps in those technologies is the project focus. The project leverages the experience and contributions of DER and cybersecurity experts, educational organizations offering accreditation, and groups serving our nation’s veterans to meet its goals. To bridge this workforce skills gap, the Cyberguardians and STEM Warriors project will establish a complete learning and career advancement system for veterans, transitioning military personnel and other qualified individuals into the DER workforce. The project will guide participants successfully through the process of program/vocation selection, curriculum enrollment, academic mentoring, degree or certificate attainment, job board enrollment, introduction to hiring managers at DER companies, and successful job acquisition. This webinar was used to promote the Cyberguardians program and to ensure ample news coverage to reach veterans, employers, and others that would benefit from this program.

14 SOLAR ENERGY↗
DOE OSTI2023

HIGH-LOW FIDELITY THERMAL HYDRAULIC COUPLING USING AI/MACHINE LEARNING ALGORITHMS

The primary goal of the US Department of Energy (DOE) office of Nuclear Energy Integrated Energy Systems (IES) program is to develop the tools and framework for coupling multi-scale and multi-physical thermal and electrical energy usage and storage systems. High- and low-fidelity (high–low) coupling is a key feature of multi-scale, multi-component systems and has been an important focus of research in the nuclear energy community for the past two decades. An essential feature of demonstrating the capability to couple high-fidelity and low-fidelity systems for real-time applications are surrogate/reduced order models (ROM). For the purposes of this study, surrogate models are essentially Blackbox models, typically developed using supervised Machine learning (ML) algorithms. The surrogate models can be used to mimic the response of high-fidelity models to represent large historical datasets and coupled with more general low-fidelity system models distributed as Functional Mock-up Interface (FMI) or Functional Mock-up Units (FMU) modules. The example is demonstrated with Spallation Neutron Source (SNS) First Target Station flow loop data. The flow loop is a liquid mercury loop with a pump, piping, heat exchange, and internal heat generation in the target window. This work elucidates some of the potential benefits and future needs of developing tools for high–low system coupling of energy systems.

Williams, Wesley↗
DOE OSTI2018

ARC algorithm: A novel approach to forecast and manage daily electrical maximum demand

This paper proposes an innovative algorithm for predicting short-term electrical maximum demand by using historical demand data. The ability to recognize in peak demand pattern for commercial or industrial customers would propose numerous direct and indirect benefits to the customers and utility providers in terms of demand reduction, cost control, and system stability. Prior works in electrical maximum demand forecasting have been mainly focused on seasonal effects, which is not a feasible approach for industrial manufacturing facilities in short-term load forecasting. The proposed algorithm, denoted as the Adaptive Rate of Change (ARC), determines the logarithmic rate-of-change in load profile prior to a peak by postulating the demand curve as a stochastic, mean-reverting process. The rationale behind this analysis, is that the energy efficient program requires not only demand estimation but also to warn the user of imminent maximum peak occurrence. This paper analyzes demand trend data and incorporates stochastic model and mean reverting half-life to develop an electrical maximum demand forecasting algorithm, which is statistically evaluated by cross-table and F-score for three different manufacturing facilities. Lastly, the aggregate results show an overall accuracy of 0.91 and a F-score of 0.43, which indicates that the algorithm is effective predicting peak demand in predicting peak demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Approximate Scheduling of DERs with Discrete Complex Injections

Rapid penetration of renewable energy based Distributed Energy Resources (DER) has the potential to exacerbate the challenges inherent in grid frequency and voltage regulation. However, their real time controllability can be leveraged to not only mitigate such challenges, but improve the economics and quality of grid operations. A plethora of DER scheduling algorithms have been developed for fast and efficient scheduling of these resources. These algorithms schedule the complex - real and reactive power injected into (or drawn from) the grid by the DERs under various cost objective functions and grid constraints. However, a vast majority of such algorithms assume the feasible range of power injections to be continuous. In reality, the control options available for several DERs form a discrete space. This implies that the feasible range of power injections also forms a discrete space. This makes DER scheduling an NP-hard problem. Integer/Mixed Integer program based algorithms, which guarantee optimality in the objective value, have been developed. But these are prohibitively expensive in terms of computational time requirements. On the other hand, fast heuristic based solutions have also been developed. But as they do not provide any guarantee on the optimality of the objective, or on satisfying the constraints, they are unreliable for grid operations. Recent works have developed approximation algorithms which offer the best of both the approaches above: (near) optimality and low computational complexity, both of which are governed by a user defined accuracy parameter ϵ. In this work, we significantly improve upon such existing works by developing an approximation algorithm which schedules DERs with complex injections (as opposed to only real injection) and whose runtime is polynomial (as opposed to exponential) in 1/ϵ. We provide theoretical analysis and support them with experimental results to validate the guarantees provided by our approximation algorithm.

14 SOLAR ENERGY↗
NASA NTRS1993

A solar photovoltaic power system for use in Antarctica

A solar photovoltaic power system was designed and built at the NASA Lewis Research Center as part of the NASA/NSF Antarctic Space Analog Program. The system was installed at a remote field camp at Lake Hoare in the Dry Valleys, and provided a six-person field team with electrical power for personal computers and printers, lab equipment, lighting, and a small microwave oven. The system consists of three silicon photovoltaic sub-arrays delivering a total of 1.5 kWe peak power, three lead-acid gel battery modules supplying 2.4 kWh, and an electrical distribution system which delivers 120 Vac and 12 Vdc to the user. The system was modularized for ease of deployment and operation. Previously the camp has been powered by diesel generators, which have proven to be both noisy and polluting. The NSF, in an effort to reduce their dependence on diesel fuel from both an environmental and cost standpoint, is interested in the use of alternate forms of energy, such as solar power. Such a power system also will provide NASA with important data on system level deployment and operation in a remote location by a minimally trained crew, as well as validate initial integration concepts.

Kohout, Lisa L.↗
DOE OSTI2024

Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method

Electrochemical impedance spectroscopy (EIS) is a key tool across various scientific disciplines, including energy sciences, chemistry, and biology, enabling the analysis of electrochemical systems. However, conventional methods for interpreting EIS data are often complex and model dependent. The distribution of relaxation times (DRT) offers a non-parametric approach that simplifies the interpretation process by providing a timescale interpretation of EIS data. This article provides a comprehensive review of current methods for DRT inversion. Additionally, a survey of practitioners highlights key challenges in the field. Here, the findings underscore the need for standardized DRT analysis and benchmarks, as well as the development of automated analysis tools. These advancements would improve the usability and interpretability of EIS data. Ultimately, implementing these improvements could not only propel the field forward but also expand the application of DRT in scientific research by making it accessible to a broader range of researchers, including those without specialized expertise in programming or statistics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Diffusion and photon-stimulated desorption of CO on TiO2(110)

Thermal diffusion of CO adsorbed on rutile TiO2(110) was studied in the 20 - 110 K range using photon-stimulated desorption (PSD), temperature programmed desorption (TPD) and scanning tunneling microscopy. During UV irradiation, CO desorbs from certain photoactive sites (e.g. oxygen vacancies). This phenomenon was exploited to study CO thermal diffusion in three steps: first empty these sites during a first irradiation cycle, then replenish them with CO during annealing, and finally probe the active site occupancy in the second PSD cycle. The PSD and TPD experiments show that the CO diffusion rate correlates with the CO adsorption energy – stronger binding corresponds to slower diffusion. Increasing the CO coverage or hydroxylation of the surface decreases the CO binding and increases the CO diffusion rate. Relative to the reduced surface, the CO adsorption energy increases and the diffusion decreases on the oxidized surface. The CO diffusion kinetics can be modeled satisfactorily as an Arrhenius process with a “normal” prefactor (i.e. = 1012 s 1) and a Gaussian distribution of activation energies where the peak of the distribution is ~0.28 eV and the full width at half maximum (FWHM) is 0.1 eV at the lowest coverages. The observations are consistent with a significant electrostatic component of the CO binding energy on the TiO2(110) surface which is affected by changes in the surface dipole and dipole-dipole interactions.

Petrik, Nikolay G.↗
DOE OSTI2024

ORNL FY2024 Nuclear Data Evaluation Contributions: Cu, La, N, and Ta [Slides]

63,65 Cu angular distributions resolved for ENDF/B-VIII.1, consistent with both differential data and integral benchmark performance. 139 La RRR and URR evaluations will be merged with the LANL high energy evaluation, and to be submitted to the future ENDF-B release (post-VIII.1). 14 N RRR evaluation is planned to produce n+ 14 N, p+ 14 C, and a+ 11 B contributions to be submitted to the future ENDF-B release (post-VIII.1). 181 Ta covariances repaired and reported as intended in an errata to ENDF/B-VIII.1.

139-La↗
DOE OSTI2020

A Census of Star Formation in the Outer Galaxy. II. The GLIMPSE360 Field

We have conducted a study of star formation in the outer Galaxy from 65°< l < 265° in the region observed by the GLIMPSE360 program. This Spitzer warm mission program mapped the plane of the outer Milky Way with IRAC at 3.6 and 4.5 μm. We combine the IRAC, Wide-field Infrared Survey Explorer (WISE), and Two Micron All Sky Survey catalogs and our previous results from another outer Galaxy survey and identify a total of 47,338 young stellar objects (YSOs) across the field spanning >180° in Galactic longitude. Using the DBSCAN method on the combined catalog, we identify 618 clusters or aggregations of YSOs having five or more members. We identify 10,476 class I, 29,604 class II, and 7325 anemic class II/class III YSOs. The ratio of YSOs identified as members of clusters was 25,528/47,338, or 54%. We found that 100 of the clusters identified have previously measured distances in the WISE H ii survey. We used these distances in our spectral energy distribution (SED) fitting of the YSOs in these clusters, of which 96 had YSOs with <3σ fits. We used the derived masses from the SED model fits to estimate the initial mass function (IMF) in the inner and outer Galaxy clusters; dividing the clusters by galactocentric distances, the slopes were Γ = 1.87 ± 0.31 above 3 M {sub ⊙} for R {sub Gal} < 11.5 kpc and Γ = 1.15 ± 0.24 above 3 M {sub ⊙} for R {sub Gal} > 11.5 kpc. The slope of the combined IMF was found to be Γ = 1.92 ± 0.42 above 3 M {sub ⊙}. These values are consistent with each other within the uncertainties and with literature values in the inner Galaxy high-mass star formation regions. The slopes are likely also consistent with a universal Salpeter IMF.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

NASA Power: Global Solar Insolation, Meteorological Parameter Data, and Web Services to Support Sustainable Building Design and Operations

The buildings industry is currently striving to adopt green solutions to make infrastructure more energy-efficient in order to meet the 2050 net-zero climate goals. This planning requires reliable environmental datasets that are crucial in designing, building, and maintaining our world’s-built environment, as well as other energy-related processes and investments. This webinar for the National Institute of Building Sciences provides an overview of NASA’s Prediction Of Worldwide Energy Resources (POWER) Project that informs decision-making and development for sustainable building design and operations by enabling public open discovery, efficient access, and convenient distribution of NASA’s Earth Observations and global atmospheric model datasets. POWER’s datastore is comprised of solar radiation and surface meteorology parameters, spanning nearly 40 years of hourly data, that are easily accessible via several access methods and tools to support three focus areas: 1) renewable energy deployment and management, 2) sustainable infrastructure, and 3) agroclimatology applications. POWER and NASA Earth Science both plan future data parameters, updated tools, and improved observations that could directly support U.S. and international sustainable development goals, climate strategies, and building information modeling. To this end, solar data from several NASA projects and meteorological data from NASA assimilation models have already been reformatted and disseminated to the public via a user-friendly web GIS-enabled based data portal through the POWER Project. POWER data is analysis-ready and accessible through an Application Programming Interface (API), ArcGIS Image Services, and the project’s Data Access Viewer enhanced (DAVe), an interactive online tool. The POWER DAVe also features data consistent with ASHRAE Climate Design Conditions and has developed web image services showing Building Climate Zones and their variability. Through those tools, the data can be downloaded into multiple formats that support the infrastructure community, including CSV and Energy Plus Weather (EPW). POWER’s entire data product catalog is available through Amazon Web Services (AWS) Open Data Registry (ODR) via a free and publicly accessible Simple Storage Service (S3). This webinar provides a full overview of the NASA POWER Project's data and services developed in collaboration with the sustainable infrastructure community. Examples of how the renewable energy and building communities have utilized POWER data products to make decisions and a preview of future data product expansion, including climate projections, and web services will also be provided. Additionally, use case stories from our broad community of users will be presented.

Paul W. Stackhouse↗
DOE OSTI2024

New U.S. Data Tools are Playing a Crucial Role in Decarbonizing Buildings at Speed, Scale, and Low Cost

Preparing buildings for retrofits traditionally requires expensive on-site audits or timeintensive simulation models. As a result, the majority of buildings fail to pursue cost-saving retrofits. To address these barriers, the U.S. Department of Energy (DOE) has introduced the Building Efficiency Targeting Tool for Energy Retrofits (BETTER)-a new, free, on-line tool that utilizes a data-driven analytical engine and user-friendly web interface to automatically analyze a building's monthly energy usage in response to weather conditions. The tool benchmarks a building's electric and fossil energy usage against peers; estimates energy, cost, and emissions reductions at the building and portfolio levels; recommends energy efficiency measures; and prioritizes buildings for net-zero energy retrofits. Thanks to interoperability with the DOE's Standard Energy Efficiency Data (SEED) platform, BETTER is supporting U.S. jurisdictions to prepare buildings for retrofit at speed, scale, and low cost to comply with energy policies. This paper discusses the use of BETTER and SEED by one of the branches of the California state government to streamline a retrofit program across 455 public non-residential buildings to align with state goals to reduce greenhouse gas emissions. It describes the organization's challenge to reduce energy consumption across a geographically diverse, aging portfolio; explores how BETTER and SEED improved workflow efficiency; presents preliminary results, including avoiding audit costs of $3.28 million and developing the groundwork for retrofit projects estimated to prevent emission of 2,271 t CO2e annually; and provides guidance for other jurisdictions seeking similar results.

BETTER↗
DOE OSTI2022

Grid-Supportive Loads - A New Approach to Increasing Renewable Energy in Power Systems

This paper demonstrates the potential of inverter-based loads to support grid reliability during power system transients thereby enabling reliable integration of renewable energy in power systems. Such loads are referred to in this paper as grid-supportive loads (GSLs). A new GSL model is developed that simulates the transient response capabilities that can be programmed in electronic loads. The model’s design enables it to be easily integrated in widely used commercial power system transient analysis software. Theoretical expressions are derived that explain the workings of the GSL model. The performance, numerical stability, and impact of the GSL model is validated on 9-bus and 2000-bus synthetic power system models using generator tripping and bus fault disturbances. Results on the 2000 bus system show that in the absence of frequency support from wind/solar generation resources, just 20% of loads with grid-supportive capabilities can improve frequency response by up to 2000 MW/0.1 Hz and reduce deviation in frequency at nadir by up to 60% compared to the situation when GSLs are absent. Power system reliability also improves under fault events. Here, it is further shown that GSLs can aid in integrating more renewable generation without degrading the overall transient response of the power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Neutron Capture Energies for Flux Normalization and Approximate Model for Gamma-Smeared Power

The Consortium for Advanced Simulation of Light Water Reactors (CASL) Virtual Environment for Reactor Applications (VERA) neutronics simulator MPACT has used a single recoverable fission energy for each fissionable nuclide assuming that all recoverable energies come only from fission reaction, for which capture energy is merged with fission energy. This approach includes approximations and requires improvement by separating capture energy from the merged effective recoverable energy. This report documents the procedure to generate recoverable neutron capture energies and the development of a program called CapKappa to generate capture energies. Recoverable neutron capture energies have been generated by using CapKappa with the evaluated nuclear data file (ENDF)/B-7.0 and 7.1 cross section and decay libraries. The new capture kappas were compared to the current SCALE-6.2 and the CASMO-5 capture kappas. These new capture kappas have been incorporated into the Simplified AMPX 51- and 252-group libraries, and they can be used for the AMPX multigroup (MG) libraries and the SCALE code package. The CASL VERA neutronics simulator MPACT does not include a gamma transport capability, which limits it to explicitly estimating local energy deposition from fission, neutron, and gamma slowing down and capture. Since the mean free path of gamma rays is typically much longer than that for the neutron, and the total gamma energy is about 10% to the total energy, the gamma-smeared power distribution is different from the fission power distribution. Explicit local energy deposition through neutron and gamma transport calculation is significantly important in multi-physics whole core simulation with thermal-hydraulic feedback. Therefore, the gamma transport capability should be incorporated into the CASL neutronics simulator MPACT. However, this task will be timeconsuming in developing the neutron induced gamma production and gamma cross section libraries. This study is to investigate an approximate model to estimate gammasmeared power distribution without performing any gamma transport calculation. A simple approximate gamma smearing model has been investigated based on the facts that pinwise gamma energy depositions are almost flat over a fuel assembly, and assembly-wise gamma energy deposition is proportional to kappa-fission energy deposition. The approximate gamma smearing model works well for single assembly cases, and can partly improve the gamma smeared power distribution for the whole core model. Although the power distributions can be improved by the approximate gamma smearing model, still there is an issue to explicitly obtain local energy deposition. A new simple approach or gamma transport/diffusion capability may need to be incorporated into MPACT to estimate local energy deposition for more robust multi-physics simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1992

Application of theoretical models to active and passive remote sensing of saline ice

The random medium model is used to interpret the polarimetric active and passive measurements of saline ice. The ice layer is described as a host ice medium embedded with randomly distributed inhomogeneities, and the underlying sea water is considered as a homogeneous half-space. The scatterers in the ice layer are modeled with an ellipsoidal correlation function. The orientation of the scatterers is vertically aligned and azimuthally random. The strong permittivity fluctuation theory is used to calculate the effective permittivity and the distorted Born approximation is used to obtain the polarimetric scattering coefficients. Thermal emissions based on the reciprocity and energy conservation principles are calculated. The effects of the random roughness at the air-ice, and ice-water interfaces are explained by adding the surface scattering to the volume scattering return incoherently. The theoretical model, which has been successfully applied to analyze the radar backscatter data of first-year sea ice, is used to interpret the measurements performed in the Cold Regions Research and Engineering Laboratory's CRRELEX program.

Han, H. C.↗
NASA NTRSDate not supplied

PRIMA: The PRobe Far-Infrared Mission for Astrophysics

PRIMA is a far-infrared observatory concept being developed to address timely and fundamental questions about the growths of galaxies and solar systems and their constituents. It will observe the build-up of heavy elements, dust, stars, and black holes in galaxies and their interrelationships, and trace the masses and water contents of protoplanetary disks to probe the growths of solar systems. The majority of observing time will be devoted to Guest Observer programs to enable the astrophysics community to identify and plan the most critical observations, with focused PI programs to address key science with rapid releases of data to inform community planning. PRIMA will have spectral, hyperspectral imaging, and polarimetric capabilities, enabled now for the first time by extraordinary progress in kinetic inductance detector (KID) array technology over the last two decades. The 2.0-meter telescope will be cooled to < 5 K to take maximum advantage of the KID sensitivities. For observations of atomic fine-structure lines, molecular lines, and solid-state emission and absorption bands, R = 200 spectral coverage will range from approximately 25 µm to 200 µm, with a high-resolution mode across the entire band that will have a spectral resolving power of a few thousand at 100 µm. R ~ 10 moderate-resolution (hyperspectral) imaging will range from 25 to 80 µm for rest-frame, mid- and far-infrared spectral energy distribution measurements to probe dust grain composition and disambiguate star formation and active galactic nuclei in galaxies. Polarimetric observations of large areas of Galactic molecular clouds and the Magellanic Clouds from 80 to ~200 µm will bridge between the large-scale polarimetry of the interstellar medium from cosmic microwave background observatories and protostellar disk-scale interferometric observations to probe magnetic fields at the critical scales at which clouds collapse to form stars. An overview of PRIMA’s basic design and capabilities will be presented. Other posters in this session describe PRIMA science, technology, and instrumentation in greater depth.

Jason Glenn↗
DOE OSTI2021

Decentralized Low-Rank State Estimation for Power Distribution Systems

This article considers the low-observability state estimation problem in power distribution networks and develops a decentralized state estimation algorithm leveraging the matrix completion methodology. Matrix completion has been shown to be an effective technique in state estimation that exploits the low dimensionality of the power system measurements to recover missing information. This technique can utilize an approximate (linear) load flow model, or it can be used with no physical models in a network where no information about the topology or line admittance is available. The direct application of matrix completion algorithms requires solving a semi-definite programming (SDP) problem, which becomes computationally challenging for large networks. We therefore develop a decentralized algorithm that capitalizes on the popular proximal alternating direction method of multipliers (proximal ADMM). The method allows us to distribute the computation among different areas of the network, leading to a scalable algorithm. By doing all computations at individual control areas and only communicating with neighboring areas, the algorithm eliminates the need for data to be sent to a central processing unit and thus increases efficiency and contributes to the goal of autonomous control of distribution networks. We illustrate the advantages of the proposed algorithm numerically using standard IEEE test cases.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

The Psyche Gamma-Ray and Neutron Spectrometer

A Gamma-Ray and Neutron Spectrometer (GRNS) instrument has been developed as part of the science payload for NASA’s Discovery Program Psyche mission to the M-class asteroid (16) Psyche. The GRNS instrument is designed to measure the elemental composition of Psyche with the goal to understand the origin of this mysterious, potentially metal-rich planetary body. The GRNS will measure the near-surface abundances for the elements Ni, Fe, Si, K, S, Al, and Ca, as well as the spatial distribution of Psyche’s metal-to-silicate fraction (or metal fraction). These measurements address three of the five Psyche mission science objectives: determine if Psyche is a core; determine whether small metal bodies incorporate light elements into the metal phase; and determine whether Psyche was formed under reducing conditions. The Gamma-Ray Spectrometer (GRS) uses a cryocooled, high-purity Ge (HPGe) sensor to detect cosmic-ray generated gamma rays in the 60 to 9000-keV energy range. The HPGe sensor is surrounded by a borated plastic anticoincidence shield that provides three functions: active background rejection from charged particle interactions in the HPGe sensor; fast neutron measurements; and direct measurements of the incident galactic cosmic ray flux. The Neutron Spectrometer (NS) uses three 3 He gas proportional sensors, each with different material wraps to measure thermal (<0.4 eV), low-energy epithermal (0.4 eV to 1 keV), and high-energy epithermal (up to 100 keV) neutrons. This paper provides an overview of the Psyche GRNS, including: its science and measurement objectives; the design of the instrument hardware, software, and operation; pre-launch performance measurements and its initial performance in space; and an overview of its data products and expected operation for different Psyche mission phases.

Engineering - Instrumentation related to nuclear s↗