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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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NASA NTRSDate not supplied

How Can We Harness the Power of Machine Learning With TEMPO Data?

There are many potential applications of machine learning for TEMPO data that include - Improve retrievals by reducing the effect of random instrument noise - Expand coverage by producing data in moderately cloudy conditions (see also Fasnacht et al. poster) - Help diagnose impacts of instrumental artifacts - Produce value-added products quickly by training on existing products from other sensors (land and ocean) - Speed up processing by training on products produced with full-physics algorithms (e.g., NO 2 slant column fitting may take ~1 hour/orbit but with a neural net it may take only minutes)

NO2↗
NASA NTRSDate not supplied

Development of a Photoacoustic Formaldehyde Monitor

Key indoor air quality pollutant formaldehyde (H 2 CO) is tracked on International Space Station (ISS) using passive badges returned to the ground periodically for analysis. The process is time-consuming both in preparation and for analysis upon return 6-12 months later. Badges also require precious crew time for deploy, retrieval and stow. As NASA’s focus in space exploration shifts to the Moon and Mars, archival sample return becomes increasingly impractical, so the aim of this project is to develop a highly reliable real-time analyzer for H 2 CO at low concentrations with data downlinked. Potential sources of H 2 CO include materials off gassing, use of formalin as a tissue fixative in biological payloads and overheating of acetal polymers. The Spacecraft Maximum Allowable Concentration (SMAC) for H 2 CO in air is 100 ppb for exposures of 7 days or longer. ISS concentrations of H 2 CO are running only 10 - 30 ppb in the recent several years but have spiked as high as 60 ppb. Gateway real time monitoring requirements for H 2 CO call for a range of 8 - 138 ppb. For this project, a concentration range of 5 - 500 ppb H 2 CO is targeted. The core tunable diode laser spectroscopy (TDLS) technology used for this project was developed by Vista Photonics through the NASA and US Navy Small Business Innovation Research (SBIR) programs. Monitors based on TDLS have been demonstrated on ISS, trialed on a nuclear submarine and are being certified as portable Anomaly Gas Analyzers (AGA) for both ISS and Orion. Initially, direct absorption TDLS was used exclusively in these devices. The H 2 CO target concentration, however, is low ppb, and a longer wavelength is required, so a photoacoustic spectroscopy (PAS) technique was adapted, where the laser excitation is detected by a sensitive microphone vs. a conventional photodetector. This paper will discuss the results of NASA-JSC laboratory testing of a prototype PAS based formaldehyde in air monitor and briefly discuss next steps.

Photoacoustic Formaldehyde Monitor↗
NASA NTRS2024

iGCE and MitoFlyght Spaceflight Missions: Unraveling Oxidative Stress Responses in Space

Thriving In DEep Space (TIDES) initiative aims to comprehensively understand how hostile environments such as the Moon and Mars affect human physiology. Here we present two NASA-selected spaceflight experiments under the TIDES portfolio, iGCE (Integrated Gravity Continuum Experiment) and MitoFlyght (Mitochondrial Investigation of Oxidative Stress in Flies). We hypothesize that exposure to spaceflight conditions induces oxidative stress responses that negatively impact physiology. The iGCE mission employs two well-established spaceflight models, Drosophila melanogaster and C.elegans, using Redwire’s Multi-use Variable-g Platform (MVP) hardware to assess changes in cardiac, muscle, and nervous systems across five different gravities: Hypergravity (2g), Earth (1g), Mars (0.37g), Moon (0.16g), and microgravity (ug). This mission focuses on uncovering alterations in protein homeostasis, autophagy, and mitochondrial function conserved across species. In the MitoFlyght mission to the ISS, Drosophila will be housed in the Vented Fly Box (VFB). This mission evaluates the oxidative stress response and autophagic pathway in muscle, heart, and nervous system. Additionally, we will (a) use the genetic mutant, Tor7/P to test whether increased autophagy is beneficial or a maladaptive response to the spaceflight stressors, and (b) utilize fly lines with tissue-specific expression (neuronal, muscle, and cardiac) of an antioxidant gene, SOD2 (superoxide dismutase) as a potential countermeasure. Data from these missions will be compared with previous LEO-based datasets to identify shared signatures. Furthermore, cross-species analysis of the transcriptomic data from other invertebrate and vertebrate spaceflight studies will help determine evolutionarily conserved pathways perturbed by space stressors. Overall, both these missions aim to provide crucial insights into the mechanisms underlying oxidative stress responses, synaptic changes, and heart and muscle deficits, facilitating the identification of diagnostic and therapeutic targets to mitigate the adverse health effects of long-duration space habitation. Ultimately, this research will enhance our ability to thrive in deep space and inform future missions.

Janani Iyer↗
DOE OSTI2019

Wide-field Multi-object Spectroscopy to Enhance Dark Energy Science from LSST

LSST will open new vistas for cosmology in the next decade, but it cannot reach its full potential without data from other telescopes. Cosmological constraints can be greatly enhanced using wide-field ($>20$ deg$^2$ total survey area), highly-multiplexed optical and near-infrared multi-object spectroscopy (MOS) on 4-15m telescopes. This could come in the form of suitably-designed large surveys and/or community access to add new targets to existing projects. First, photometric redshifts can be calibrated with high precision using cross-correlations of photometric samples against spectroscopic samples at $0 < z < 3$ that span thousands of sq. deg. Cross-correlations of faint LSST objects and lensing maps with these spectroscopic samples can also improve weak lensing cosmology by constraining intrinsic alignment systematics, and will also provide new tests of modified gravity theories. Large samples of LSST strong lens systems and supernovae can be studied most efficiently by piggybacking on spectroscopic surveys covering as much of the LSST extragalactic footprint as possible (up to $\sim20,000$ square degrees). Finally, redshifts can be measured efficiently for a high fraction of the supernovae in the LSST Deep Drilling Fields (DDFs) by targeting their hosts with wide-field spectrographs. Targeting distant galaxies, supernovae, and strong lens systems over wide areas in extended surveys with (e.g.) DESI or MSE in the northern portion of the LSST footprint or 4MOST in the south could realize many of these gains; DESI, 4MOST, Subaru/PFS, or MSE would all be well-suited for DDF surveys. The most efficient solution would be a new wide-field, highly-multiplexed spectroscopic instrument in the southern hemisphere with $>6$m aperture. In two companion white papers we present gains from deep, small-area MOS and from single-target imaging and spectroscopy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Snowmass2021 Cosmic Frontier White Paper: Enabling Flagship Dark Energy Experiments to Reach their Full Potential

A new generation of powerful dark energy experiments will open new vistas for cosmology in the next decade. However, these projects cannot reach their utmost potential without data from other telescopes. This white paper focuses in particular on the compelling benefits of ground-based spectroscopic and photometric observations to complement the Vera C. Rubin Observatory, as well as smaller programs in aid of a DESI-2 experiment and CMB-S4. These additional data sets will both improve dark energy constraints from these flagship projects beyond what would possible on their own and open completely new windows into fundamental physics. For example, additional photometry and single-object spectroscopy will provide necessary follow-up information for supernova and strong lensing cosmology, while highly-multiplexed spectroscopy both from smaller facilities over wide fields and from larger facilities over narrower regions of sky will yield more accurate photometric redshift estimates for weak lensing and galaxy clustering measurements from the Rubin Observatory, provide critical spectroscopic host galaxy redshifts for supernova Hubble diagrams, provide improved understanding of limiting astrophysical systematic effects, and enable new measurements that probe the nature of gravity. A common thread is that access to complementary data from a range of telescopes/instruments would have a substantial impact on the rate of advance of dark energy science in the coming years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

ASMS 2024 Investigation of Uranyl Perchlorate Anion Complexes in the Gas Phase via Infrared Multiphoton Dissociation and Collision Induced Dissociation

Investigation of Uranyl Perchlorate Anion Complexes in the Gas Phase via Infrared Multiphoton Dissociation and Collision Induced Dissociation Brittany D. M. Hodges, Christopher A. Zarzana, JungSoo Kim, Jonathan Martens, and W. C. M. Berden Introduction (120 words max) Effects of electronic structure on chemical bonding and reactivity play critical roles shaping the chemical bonding and reactivity behaviors of heavy elements. Understanding the role of f electrons in bond formation between the actinide-series elements like uranium with other ligands is critical for solving technical challenges associated with these heavy elements, important to nuclear fuel cycles, efficient separations of rare earth metals, and understanding the chemistry of stored nuclear fuels and related environmental management sites. In this study, we further examine the interactions between uranyl and the perchlorate ion in order to understand the structures of these ions through the use of IRMPD. Here we report the IRMPD spectra of [UO2(ClO4)3]-, [UO3(ClO4)2]-, and a proposed transition state. Methods (120 word max) IRMPD spectra and CID spectra were acquired using a Bruker amaZon QIT/MS instrument at the Free-Electron Lasers for Infrared eXperiments (FELIX) laboratory at Radboud University. The FELIX QIT/MS is modified to allow for the high-intensity tunable IR beam from FELIX to be directed into the ion packet, resulting in multiphoton dissociation that is measured only when the IR frequency is in resonance with an adequately high absorption vibrational mode of the mass-selected complex. DFT geometry optimizations and frequency calculations using the Gaussian suite of programs were performed using B3LYP, TPSSh, and PBE0 level of theory with 6-31+G(d) basis for the O, C, H, and N atoms and the SDD basis set for U. The SDD basis set employs the Stuttgart/Dresden effective core potential. Preliminary Data or Plenary Speakers Abstract (300 words max) Metal ion clusters of uranyl perchlorate were formed via direct electrospray ionization. For each metal ligand complex of interest, the parent ion was isolated and collision induced dissociation fragmentation and Infrared Multiphoton Dissociation (IRMPD) fragmentation spectra were acquired. Results presented here are the first look at the IRMPD spectra of [UO3(ClO4)2]-, [UO2(ClO4)3]-. Structures were examined using Gaussian at different levels of theory B3LYP level of theory, TPPSh and PBE0 levels, to reflect the behaviors of uranium metal ligand complexes most accurately. In these structures, we identified an overlap between each of these uranyl stretches resulting in their largely being obscured by a perchlorate mode. The CID product spectra agree with similar structures reported by Groenewold for uranyl nitrate in 2006 (10.1021/ja058106n).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine Learning for Well Log Analysis in Uranium Mining

This project explores the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate well log analysis for uranium mining. Geophysical log data—spontaneous potential, resistivity, and gamma ray—were used to classify lithology, correlate well logs and identify roll front zonation patterns, which are critical for locating uranium ore bodies. Supervised ML algorithms such as eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Random Forest were trained to classify lithology with high accuracy. Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks were also used for role front zone identification. Moreover, a Fast Dynamic Time Warping (FastDTW) algorithm was employed for well log correlation. Additionally, sample lag was addressed using dynamic programming. Results demonstrate the potential of AI and ML to streamline well log analysis and enhance uranium exploration workflows.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1995

Visualization of the electrostatic potential distribution in both polar ionospheres using multiple satellite measurements

During the time from December 1991 through March 1992, there were four operational DMSP satellites in polar orbit. All four satellites carried the Special Sensor-Ions, Electrons, Scintillation (SSIES) plasma package which included an ion drift meter. Data from the drift meter, combined with the magnetic field data, allowed the calculation of the electrostatic potential in the ionosphere along the satellite's path. Simultaneous polar coverage by four satellites was unprecedented, providing researchers with almost continuous monitoring of the potential distribution in both hemispheres for the four month period. Combining the magnitude and location of the potential data from each of the four satellites in order to examine the varying potential distribution pattern in both hemispheres presented a major challenge in data visualization. The problem was solved by developing a three-dimensional presentation of the data where the potentials are color coded and represented by the vertical dimension. This paper presents examples from a computer animation of several days of data demonstrating evolution of the size and shape of the potential distribution, along with how these changes correspond to variations in other geophysical parameters, such as the IMF orientation and the K(sub p) index.

Hairston, Marc R.↗
NASA NTRS1985

Develop a plan for establishing global aerosol backscatter coefficient data base

A potential improvement on measuring atmospheric winds by using a coherent Doppler system has led to a need for detailed knowledge concerning the aerosol backscattering characteristics, especially at CO2 wavelengths. In order to meet this requirement, a plan of study has been developed to establish a global data base of atmospheric aerosol backscattering coefficients.

Chang, Ho-Pen↗
NASA NTRS1974

Use of potential flow theory to evaluate subsonic inlet data from a simulator-powered nacelle at cruise conditions

Incompressible potential flow theory corrected for compressibility effects, using the Lieblein-Stockman compressibility correction, was used to predict surface and flow field static pressures for a subsonic inlet at cruise conditions. The calculated internal and external surface static pressures were in good agreement with data at most conditions. The analysis was used to determine the capture stream-tube location and static-pressure distribution. Additive drag coefficients obtained from these results were consistently higher than those obtained using one-dimensional compressible flow theory. Increasing the distance between the inlet and boattail increased the cowl drag force. The effect of the boundary layer on internal and external surface static-pressure distributions was small at the design cruise condition. The analytical results may be used as an aid to data reduction and for predicting inlet mass flow, stagnation point location, and inlet additive drag.

Bober, L. J.↗
NASA NTRS1977

Experiments in data collection technology using satellites

A variety of techniques potentially useful to data collection have been tested. An automatic data collection platform with a minicomputer collects and preprocesses data, then sends desired information when interrogated through a communication satellite. Position surveillance by tone-code ranging through communication satellites is automatic, real time and accurate. Emergency medical data transmissions from ambulances to hospitals can be extended to rural and remote areas by direct satellite links. A small platform can send emergency-related data through a satellite while the satellite is routinely relaying powerful communication signals. A low orbit satellite provides means to locate existing emergency locator beacons.

Anderson, R. E.↗
DOE OSTI2015

Data And Informatics Working Group On Virtual Data Integration Workshop Report

This report is the outcome of a workshop that was commissioned by the Department of Energy’s Climate and Environmental Sciences Division (CESD) to examine current and future data infrastructure requirements that would be foundational to achieving CESD’s scientific mission goals. Over the past several years, data volumes in CESD disciplines have risen sharply to unprecedented levels (tens of petabytes). So too has the complexity and diversity of the research data (simulation, observation, and reanalysis) needing to be captured, stored, verified, analyzed, and integrated. With the trends of increased data volume (in the hundreds of petabytes), more complex analysis processes, and growing crossdisciplinary collaborations, it is timely to investigate whether the CESD community has the right computational and data support to realize the full scientific potential from its data collections. In recognition of the challenges, a partnership is forming across CESD and with national and international agencies to investigate the viability of creating an integrated, collaborative data infrastructure: a virtual laboratory. The overarching goal of this report is to identify the community’s key data technology requirements and high-priority development needs for sustaining and growing their scientific discovery potential. The report also aims to map these requirements to existing solutions and to identify gaps in current services, tools, and infrastructure that will need to be addressed in the short, medium, and long term so as not to impede scientific progress

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Assessing the Wind Energy Potential in Bangladesh: Enabling Wind Energy Development with Data Products

USAID Bangladesh and the U.S. Department of Energy’s National Renewable Energy Laboratory partnered with the Government of Bangladesh to develop a national wind resource assessment. The assessment used sophisticated resource modeling that was validated by a ground measurement campaign. Results from the project included a long-term, correlated wind data set; validated high-resolution wind resource maps; and publicly available data accessible through the RE Data Explorer (https://www.re-explorer.org/). The Renewable Energy (RE) Data Explorer allows users to access and download the Bangladesh wind resource assessment data and related geographic information system (GIS) data sets and perform customized technical potential analyses. Figure ES-1 is an example wind resource map for Bangladesh that can be created with the RE Data Explorer. This project improved upon existing global data sets by using best-in-class modeling techniques and analysis. Global models are good first steps in predicting wind resources in various parts of the world, but they do not generate the accuracy needed to reduce project risk and stimulate renewable investment. This project improved the quality of modeled wind resource data for Bangladesh. In addition to the modeling effort, the project team used a multi-year, local data-collection campaign to validate the model and further improve the accuracy of the data sets. The measurement campaign consisted of nine meteorological sites representing all geographical regions of the country. Seven meteorological towers and one remote-sensing, sonic detection and ranging unit (deployed at two sites) collected the data. Site-selection criteria focused on geographic diversity and proximity to existing transmission lines. Figure ES-1 shows measurement locations. The measurement campaign spanned June 2014 through December 2017. The results of the Bangladesh wind resource assessment will help Bangladesh overcome significant energy challenges. Its energy sector suffers from power shortages, increasing demand, decreasing domestic natural gas reserves, and inadequate transmission infrastructure. As part of a comprehensive plan to overcome these challenges, Bangladesh has committed that 10% of the total generation capacity will be renewable energy by 2021 (Power Division 2016). High-quality renewable energy resource data and other GIS data, such as those developed in this assessment, are important if Bangladesh wishes to reach its 10% renewable energy capacity target. These data support informed decision making, ranging from policy and investment decisions to reliable power sector planning. Specifically, the Bangladesh wind resource assessment will help reduce technical risk and encourage private-sector interest in the nascent wind market in Bangladesh. In addition, the Government of Bangladesh may use the results of the wind resource assessment to develop well-designed policies that could encourage investment in wind energy. This report provides a comprehensive description of the Bangladesh wind resource assessment, including details on the modeling approach and methods, instrumentation, data quality-control techniques, and resulting data sets.

17 WIND ENERGY↗
DOE OSTI2025

The HydroBio Dataset: a new data resource for evaluating existing and potential hydropower capacity and freshwater biodiversity in the conterminous United States

Hydropower is a critical source of affordable and reliable electricity and energy system stability services in the United States. Opportunities to expand US hydropower production include retrofitting existing non-powered dams to produce power, retrofitting existing hydropower dams to improve efficiency or increase capacity, or constructing new hydropower infrastructure on currently unregulated river reaches. We created the HydroBio Dataset, which summarizes existing and potential hydropower capacity and freshwater biodiversity at the sub-basin scale in the conterminous US to contextualize existing and potential grid contributions with the freshwater ecosystems in which dams are situated. We demonstrate a use-case of this dataset by rescaling and comparing potential non-powered dam nominal capacity to rarity-threat-weighted freshwater species richness for sub-basins where both types of data exist. On average, normalized freshwater biodiversity exceeded normalized potential non-powered dam nominal capacity in these sub-basins. Potential non-powered dam nominal capacity was concentrated in sub-basins in the Upper Mississippi and Ohio hydrologic regions while freshwater biodiversity was concentrated in the South Atlantic-Gulf, Ohio, and Tennessee hydrologic regions. Additionally, non-powered dams and existing hydropower dams are located in sub-basins with similar indices of freshwater biodiversity. The HydroBio Dataset adds an additional ecological dimension of context to our understanding of current and potential future US hydropower capabilities and is a valuable decision support tool for stakeholders tasked with balancing gains in services to the US power grid with the public and environmental benefits of freshwater ecosystems.

Biodiversity↗
NASA NTRS1980

Alias lock behavior of sampled-data Costas loops

The potential false-lock problem associated with the sampled data type of Costas loop implementation is addressed in this paper. The term 'alias lock' is used here to differentiate this type of false lock behavior from the data sideband false lock behavior of analog Costas loops. It is shown that the sampled-data version of the conventional Costas loop, sampled at a rate 1/T(s), can alias lock at frequencies that are multiples of 1/2T(s) away from the carrier frequency. It is also shown that the alias lock problem of the sampled data version of the Costas loop with hard-limited in-phase channel is further compounded by the potential occurrence of false lock frequencies at rational multiples of 1/2T(s) away from the carrier. The false lock S-curves of I-Q loops and decision-directed I-Q loops are investigated in detail, with and without additive noise. Close agreement between theory and earlier experimental results is also demonstrated.

Simon, M. K.↗