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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Demonstrating the Operational Value of Atmospheric Infrared Sounder (AIRS) Retrieved Profiles in the Pre-Convective Environment

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. One operational forecast challenge is forecasting convective weather in data-void regions such as large bodies of water (e.g. Gulf of Mexico). To address this forecast challenge, SPoRT produces a twice-daily three-dimensional analysis that blends a model first-guess from the Advanced Research Weather Research and Forecasting (WRF-ARW) model with retrieved profiles from the Atmospheric Infrared Sounder (AIRS) -- a hyperspectral sounding instrument aboard NASA's Aqua satellite that provides temperature and moisture profiles of the atmosphere. AIRS profiles are unique in that they give a three dimensional view of the atmosphere that is not available through the current rawinsonde network. AIRS has two overpass swaths across North America each day, one valid in the 0700-0900 UTC timeframe and the other in the 1900-2100 UTC timeframe. This is helpful because the rawinsonde network only has data from 0000 UTC and 1200 UTC at specific land-based locations. Comparing the AIRS analysis product with control analyses that include no AIRS data demonstrates the value of the retrieved profiles to situational awareness for the pre-convective (and convective) environment. In an attempt to verify that the AIRS analysis was a good representation of the vertical structure of the atmosphere, both the AIRS and control analyses are compared to a Rapid Update Cycle (RUC) analysis used by operational forecasters. Using guidance from operational forecasters, convective available potential energy (CAPE) was determined to be a vital variable in making convective forecasts and is used herein to demonstrate the utility of the AIRS profiles in changing the vertical thermodynamic structure of the atmosphere in the pre-convective and convective environment. CAPE is an important metric because of it is a quantitative measure of atmospheric stability, which is necessary information when forecasting for convective weather. Case studies from the summer of 2010 were examined, and most impact from the AIRS retrieved profiles occurred over the data-void Gulf of Mexico with fields of convective potential closer to the RUC than the CNTL. Mixed results were found when AIRS retrieved profiles were used over land, so more cases need to be examined to determine whether AIRS would be an effective tool over land. Additional analyses of problematic convective forecasts over the Gulf Coast will be needed to determine the operational impact of AIRS. SPoRT eventually plans to transition the AIRS product to select Weather Forecast Office (WFO) partners, pending the outcome of these additional analyses.

Kozlowski, Danielle M.↗
NASA NTRS2005

Latent Heating from TRMM Satellite Measurements

Rainfall production is a fundamental process within the Earth;s hydrological cycle because it represents both a principal forcing term in surface water budgets, and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations with the Tropics - as well as modify the energetic efficiencies of mid-latitude weather systems. This paper highlights the retrieval of observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing an accurate four-dimensional amount of rainfall over the global Tropics and sub-tropics - information which can be used to estimate the spacetime structure of latent heating across the Earth's low latitudes. A set of algorithm methodologies has and continues to be developed to estimate latent heating based on rain rate profile retrievals obtained from TRMM measurements. These algorithms are briefly described followed by a discussion of the foremost latent heating products that can be generate from them. The investigation then provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

Tao, W.-K.↗
DOE OSTI2025

Hydrogen density mapping in biomolecular crystals through dynamic nuclear polarization

Many fundamental biological processes, including those in photosynthetic reaction centers and enzyme active sites, involve charge and energy transfer, bond cleavage, protonation and hydrogen bonding. Because H atoms play such central roles in these reactions, accurately determining their positions is essential. Yet, conventional X-ray crystallography primarily resolves the heavy atoms in biological structures and provides limited insight into hydrogen, even at atomic resolution. Neutron macromolecular crystallography (NMC) overcomes this limitation by offering exceptional sensitivity to hydrogen and deuterium. Here, we present a theoretical framework for the development of dynamic nuclear polarization NMC (DNP-NMC) techniques, which exploit the alignment of neutron and proton nuclear spins to enhance and tune the hydrogen signal contribution. The DNP-NMC approach advances the resolution of H atoms within biomolecular crystals, whether bound to protein residues or present in solvent. The method establishes key relationships for the coherent structure factor of polarized neutron scattering from hydrogenous matter. It theoretically achieves full accuracy in phase reconstruction and offers a path to improve neutron structure determination, achieving accuracies exceeding ≳80% by incorporating titration states. Using a variant of the hybrid input/output phase-retrieval algorithm, it allows recovery of the hydrogen density with ≳90% phase accuracy. In conclusion, we further discuss sources of experimental uncertainty for the upcoming DNP-enabled, quasi-Laue IMAGINE-X experiment at Oak Ridge National Laboratory's High Flux Isotope Reactor.

dynamic nuclear polarization↗
DOE OSTI2025

Single-distance nano-holotomography with coded apertures

High-resolution phase-contrast 3D imaging using nano-holotomography typically requires collecting multiple tomograms at varying sample-to-detector distances, usually 3 to 4. This multi-distance approach limits temporal resolution, making it impractical for operando studies. Moreover, shifting the sample complicates reconstruction, requiring precise alignment, registration, and interpolation to correct for shift-dependent magnification on the detector. In response, we propose and validate through simulations a novel, to the best of our knowledge, single-distance approach that leverages coded apertures to structure beam illumination while the sample rotates. Finally, this approach relies on a joint reconstruction scheme, which integrates phase retrieval with 3D tomography, ensuring data consistency and achieving artifact-free reconstructions from a single distance, unlocking dynamic experiments.

Nikitin, Viktor [Argonne National Laboratory (ANL)↗
NASA NTRS1992

Long duration exposure facility post-flight thermal analysis, part 1

Results of the post-flight thermal analysis of the Long Duration Exposure Facility (LDEF) mission are presented. The LDEF mission thermal analysis was verified by comparing the thermal model results to flight data from the LDEF Thermal Measurements System (THERM). Post-flight calculated temperature uncertainties have been reduced to under +/- 18 F from the pre-flight uncertainties of +/- 40 F. The THERM consisted of eight temperature sensors, a shared tape recorder, a standard LDEF flight battery, and an electronics control box. The temperatures were measured at selected locations on the LDEF structure interior during the first 390 days of flight and recorded for post-flight analysis. After the LDEF retrieval from Space on 12 Jan. 1990, the tape recorder was recovered from the spacecraft and the data reduced for comparison to the LDEF predicted temperatures. The LDEF mission temperatures were calculated prior to the LDEF deployment on 7 Apr. 1980, and updated after the LDEF retrieval with the following actual flight parameter data: including thermal fluxes, spacecraft attitudes, thermal coatings degradation, and contamination effects. All updated data used for the calculation of post-flight temperatures is also presented in this document.

Berrios, William M.↗
NASA NTRS1992

Long duration exposure facility post-flight thermal analysis, part 2

Results of the post-flight thermal analysis for the Long Duration Exposure Facility (LDEF) mission are presented. The LDEF mission thermal analysis was verified by comparing the thermal model results to flight data from the LDEF Thermal Measurements System (THERM). Post-flight calculated temperature uncertainties have been reduced to under +/- 18 F from the pre-flight uncertainties of +/- 40 F. The THERM consisted of eight temperature sensors, a shared tape recorder, a standard LDEF flight battery, and an electronics control box. The temperatures were measured at selected locations on the LDEF structure interior during the first 390 days of flight and recorded for post-flight analysis. After the LDEF retrieval from Space on 12 Jan. 1990, the tape recorder was recovered from the spacecraft and the data reduced for comparison to the LDEF predicted temperatures. The LDEF mission temperatures were calculated prior to the LDEF deployment on 7 Apr. 1980, and updated after the LDEF retrieval with the following actual flight parameter data: thermal fluxes, spacecraft attitudes, thermal coatings degradation, and contamination effects. All updated data used for calculation of post-flight temperatures is also presented in this document.

Berrios, William M.↗
NASA NTRS2003

NASA's Scientific Agenda for GPM Mission

The objectives of the Global Precipitation Measurement (GPM) Mission are to: 1) Understand the horizontal and vertical structure of rainfall, its macro- and micro-physical nature, and its associated latent heating, 2) Train and calibrate retrieval algorithms for constellation radiometers, 3) Provide sufficient global sampling to significantly reduce uncertainties in short-term rainfall accumulations, and 4) Extend scientific and societal applications. The GPM mission design consists of a core satellite, constellation satellties, precipitation validation sites for error characterization, and a precipitation processing center. This viewgraph presentation profiles the science goals of the mission, and its capability for producing climate data and weather predictions.

Smith, Eric A.↗
NASA NTRS2013

Fuzzy Reasoning to More Accurately Determine Void Areas on Optical Micrographs of Composite Structures

Accomplishing the best-performing composite matrix (resin) requires that not only the processing method but also the cure cycle generate low-void-content structures. If voids are present, the performance of the composite matrix will be significantly reduced. This is usually noticed by significant reductions in matrix-dominated properties, such as compression and shear strength. Voids in composite materials are areas that are absent of the composite components: matrix and fibers. The characteristics of the voids and their accurate estimation are critical to determine for high performance composite structures. One widely used method of performing void analysis on a composite structure sample is acquiring optical micrographs or Scanning Electron Microscope (SEM) images of lateral sides of the sample and retrieving the void areas within the micrographs/images using an image analysis technique. Segmentation for the retrieval and subsequent computation of void areas within the micrographs/images is challenging as the gray-scaled values of the void areas are close to the gray-scaled values of the matrix leading to the need of manually performing the segmentation based on the histogram of the micrographs/images to retrieve the void areas. The use of an algorithm developed by NASA and based on Fuzzy Reasoning (FR) proved to overcome the difficulty of suitably differentiate void and matrix image areas with similar gray-scaled values leading not only to a more accurate estimation of void areas on composite matrix micrographs but also to a faster void analysis process as the algorithm is fully autonomous.

Dominquez, Jesus A.↗
NASA NTRS1986

Parallel structures in human and computer memory

If one thinks of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library. One recognizes a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. A computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do is constructed. Such a memory is remarkably similiar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. It is concluded that the frame problem of artificial intelligence could be solved by the use of such a memory if one were able to encode information about the world properly.

Kanerva, P.↗
NASA NTRS2019

Integrated Multi-Satellite Evaluation for the Global Precipitation Measurement: Impact of Precipitation Types on Spaceborne Precipitation Estimation

Integrated multi-sensor assessment is proposed as a novel approach to advance satellite precipitation validation in order to provide users and algorithm developers with an assessment adequately coping with the varying performances of merged satellite precipitation estimates. Gridded precipitation rates retrieved from space sensors with quasi-global coverage feed numerous applications ranging from water budget studies to forecasting natural hazards caused by extreme events. Characterizing the error structure of satellite precipitation products is recognized as a major issue for the usefulness of these estimates. The Global Precipitation Measurement (GPM) mission aims at unifying precipitation measurements from a constellation of low-earth orbiting (LEO) sensors with various capabilities to detect, classify and quantify precipitation. They are used in combination with geostationary observations to provide gridded precipitation accumulations. The GPM Core Observatory satellite serves as a calibration reference for consistent precipitation retrieval algorithms across the constellation. The propagation of QPE uncertainty from LEO active/passive microwave (PMW) precipitation estimates to gridded QPE is addressed in this study, by focusing on the impact of precipitation typology on QPE from the Level-2 GPM Core Observatory Dual-frequency Precipitation Radar (DPR) to the Microwave Imager (GMI) to Level-3 IMERG precipitation over the Conterminous U.S. A high-resolution surface precipitation used as a consistent reference across scales is derived from the ground radar-based Multi-Radar/Multi-Sensor. While the error structure of the DPR, GMI and subsequent IMERG is complex because of the interaction of various error factors, systematic biases related to precipitation typology are consistently quantified across products. These biases display similar features across Level-2 and Level-3, highlighting the need to better resolve precipitation typology from space and the room for improvement in global-scale precipitation estimates. The integrated analysis and framework proposed herein applies more generally to precipitation estimates from sensors and error sources affecting low-earth orbiting satellites and derived gridded products.

Rainfall↗
NASA NTRS2020

Integrated Multi-satellite Evaluation for the Global Precipitation Measurement: Impact of Precipitation Types on Spaceborne Precipitation Estimation

An integrated multi-sensor assessment is proposed as a novel approach to advance satellite precipitation validation in order to provide users and algorithm developers with an assessment adequately coping with the varying performances of merged satellite precipitation estimates. Gridded precipitation rates retrieved from space sensors with quasi-global coverage feed numerous applications ranging from water budget studies to forecasting natural hazards caused by extreme events. Characterizing the error structure of satellite precipitation products is recognized as a major issue for the usefulness of these estimates. The Global Precipitation Measurement (GPM) mission aims at unifying precipitation measurements from a constellation of low-earth orbiting (LEO) sensors with various capabilities to detect, classify and quantify precipitation. They are used in combination with geostationary observations to provide gridded precipitation accumulations. The GPM Core Obser­vatory satellite serves as a calibration reference for consistent precipitation retrieval algorithms across the constellation. The propagation of QPE uncertainty from LEO active/passive microwave (PMW) precipitation estimates to gridded QPE is addressed in this study, by focusing on the impact of precipitation typology on QPE from the Level-2 GPM Core Observatory Dual-frequency Precipitation Radar (DPR) to the Microwave Imager (GMI) to Level-3 IMERG precipitation over the Conterminous U.S. A high-resolution surface precipitation used as a consistent reference across scales is derived from the ground radar-based Multi-Radar/Multi­Sensor. While the error structure of the DPR, GMI and subsequent IMERG is complex because of the interaction of various error factors, systematic biases related to precipitation typology are consistently quantified across products. These biases display similar features across Level-2 and Level-3, highlighting the need to better resolve precipitation typology from space and the room for improvement in global­scale precipitation estimates. The integrated analysis and framework proposed herein applies more generally to precipitation estimates from sensors and error sources affecting low-earth orbiting satellites and derived gridded products.

Pierre-Emmanuel Kirstette↗
NASA NTRS2021

Discrete anisotropic radiative transfer modelling of solar-induced chlorophyll fluorescence: Structural impacts in geometrically explicit vegetation canopies

Solar-induced fluorescence (SIF) is a subtle but informative optical signal of vegetation photosynthesis. Remotely sensed SIF integrates environmental, physiological and structural changes that alter photosynthesis at leaf, plant and canopy scales. Radiative transfer models are ideally suited to investigate the complex sources of variability in the SIF signal to guide the interpretation of SIF retrievals from airborne and space-borne platforms. Here, we coupled the Fluspect-Cx model of leaf optical properties and chlorophyll-a fluorescence with the Discrete Anisotropic Radiative Transfer (DART) model to upscale SIF from individual leaves to three-dimensional (3D) structurally explicit canopies. For one-dimensional homogeneous (turbid-like) canopies, DART-SIF was nearly identical to SIF simulated in two existing models, SCOPE and mSCOPE (RMSE <0.221 W./sq.m.μm.sr). DART simulations in geometrically explicit 3D canopies offered four important insights regarding the influence of vegetation structure on the multi-angular top-of-canopy SIF signal. First, changes in the 3D canopy architecture of maize crops, represented by leaf density (leaf area index), and plant clumping (canopy closure) had a larger impact on SIF than the modelled photosynthetic efficiency distinction between sun-adapted and shade-adapted foliage. Second, clumping of leaves at the crop and stand levels was identified as one of the key driving factors of multi-angular anisotropy of red and far-red SIF (686 and 740 nm) for both maize and eucalyptus canopies. Third, non-photosynthetic woody material had a significant impact on top-of-canopy SIF in modelled 3D forest stands. Wood shadowing decreased the photosynthetically active radiation absorbed by green leaves, and consequently the SIF emissions, by 10% in sparse and 17% in dense eucalyptus stands. The wood obstruction (blocking) effect, quantified as a relative difference of SIF escape probabilities from canopies with and without wood in the nadir viewing direction, decreased far-red SIF by 4–6% but it had a smaller and sometimes positive influence (by less than 2%) on red SIF. Fourth, DART 3D radiative budget profiles revealed that the majority of the SIF signal from a dense eucalyptus stand originated from the top 25% of the simulated canopy. Interestingly, the introduction of bark-covered woody elements did not alter the simulated balance and omnidirectional escape factor of red SIF in this upper canopy part but did raise significantly both of them in case of far-red SIF. These results demonstrate the importance of 3D radiative transfer and radiative budget simulations for investigating SIF interactions in structurally complex plant canopies and for a better understanding of spatiotemporal and multi-angular remote sensing SIF observations.

Zbyněk Malenovský↗
NASA NTRS2001

Columnar Aerosol Single-Scattering Albedo and Phase Function Retrieved from Sky Radiance Over the Ocean: Measurements of African Dust

The single-scattering albedo and phase function of African mineral dust are retrieved from ground-based measurements of sky radiance collected in the Florida Keys. The retrieval algorithm employs the radiative transfer equation to solve by iteration for these two properties which best reproduce the observed sky radiance using an assumed aerosol vertical structure and measured aerosol optical depth. Thus, no assumptions regarding particle size, shape, or composition are required. The single-scattering albedo, presented at fourteen wavelengths between 380 and 870 nm, displays a spectral shape expected of iron-bearing minerals but is much higher than current dust models allow. This indicates the absorption of light by mineral dust is significantly overestimated in climate studies. Uncertainty in the retrieved albedo is less than 0.02 due to the small uncertainty in the solar-reflectance-based calibration (12.2%) method employed. The phase function retrieved at 860 nm is very robust under simulations of expected experimental errors, indicating retrieved phase functions at this wavelength may be confidently used to describe aerosol scattering characteristics. The phase function retrieved at 443 nm is very sensitive to expected experimental errors and should not be used to describe aerosol scattering. Radiative forcing by aerosol is the greatest source of uncertainty in current climate models. These results will help reduce uncertainty in the absorption of light by mineral dust. Assessment of the radiative impact of aerosol species is a key component to NASA's Earth System Enterprise.

Cattrall, Christopher↗
NASA NTRS1987

A rudimentary database for three-dimensional objects using structural representation

A database which enables users to store and share the description of three-dimensional objects in a research environment is presented. The main objective of the design is to make it a compact structure that holds sufficient information to reconstruct the object. The database design is based on an object representation scheme which is information preserving, reasonably efficient, and yet economical in terms of the storage requirement. The determination of the needed data for the reconstruction process is guided by the belief that it is faster to do simple computations to generate needed data/information for construction than to retrieve everything from memory. Some recent techniques of three-dimensional representation that influenced the design of the database are discussed. The schema for the database and the structural definition used to define an object are given. The user manual for the software developed to create and maintain the contents of the database is included.

Sowers, James P.↗
NASA NTRS2015

Structural Sizing Methodology for the Tendon-Actuated Lightweight In-Space MANipulator (TALISMAN) System

The Tendon-Actuated Lightweight In-Space MANipulator (TALISMAN) is a versatile long-reach robotic manipulator that is currently being tested at NASA Langley Research Center. TALISMAN is designed to be highly mass-efficient and multi-mission capable, with applications including asteroid retrieval and manipulation, in-space servicing, and astronaut and payload positioning. The manipulator uses a modular, periodic, tension-compression design that lends itself well to analytical modeling. Given the versatility of application for TALISMAN, a structural sizing methodology was developed that could rapidly assess mass and configuration sensitivities for any specified operating work space, applied loads and mission requirements. This methodology allows the systematic sizing of the key structural members of TALISMAN, which include the truss arm links, the spreaders and the tension elements. This paper summarizes the detailed analytical derivations and methodology that support the structural sizing approach and provides results from some recent TALISMAN designs developed for current and proposed mission architectures.

Jones, Thomas C.↗
DOE OSTI2026

AstraAI v1

AstraAI is an open-source, structure-aware AI coding agent designed for large scientific and DOE-HPC codebases such as AMReX-based applications. Unlike general-purpose coding assistants, AstraAI combines retrieval-augmented generation (RAG) with compiler-level Abstract Syntax Tree (AST) analysis to perform precise, scope-constrained code modifications. It identifies exact function spans, enforces locality of edits, and maintains cross-file invariants, enabling deterministic and build-safe transformations in complex C++/GPU environments. AstraAI is intended for developers working on large, evolving HPC frameworks where correctness, reproducibility, and structural integrity are critical. Typical use cases include modifying physics kernels, updating GPU device lambdas, and performing multi-file refactors without breaking compilation or runtime semantics. Compared to conventional LLM-based coding agents - even those with repository access - AstraAI provides structural guarantees rather than free-form text patches. It minimizes unintended diffs, prevents scope drift, preserves formatting and build stability, and reduces structural hallucinations. By integrating compiler tooling directly into the generation loop, AstraAI transforms AI-assisted coding from probabilistic text editing into deterministic, structure-preserving program transformation suitable for mission-critical scientific software.

Natarajan, Mahesh [Lawrence Berkeley National Labo↗
NASA NTRS2003

Using Cloud Top Pressures Derived from Raman Scattering in the UV for the OMI Total Column Ozone Retrievals

The OMI cloud pressure product is necessary for accounting for cloud effects on the mission- critical total ozone product. One of the OM1 cloud pressure algorithms uses UV measurements to derive cloud pressures from the high frequency structure of top- of-atmosphere reflectance caused by rotational Raman scattering (RRS) in the atmosphere. RRS results in filling-in of Fraunhofer lines in the backscatter UV spectra (also known as the Ring effect). The magnitude of filling-in of the Fraunhofer lines is roughly proportional to the average number of solar photon scatterings in the atmosphere above the clouds. This property of RRS is used to deduce an effective cloud pressure. The cloud pressure algorithm retrieves the cloud pressure and cloud fraction using a concept of the Mixed Lambert Equivalent Reflectivity (MLER) also used for the TOMS-V8 OM1 total column ozone algorithm. Currently, this OMI total column ozone algorithm utilizes information about cloud top pressures from a climatology based on IR measurements. The IR-derived cloud top pressure is known to be lower than UV-derived cloud top pressure because UV radiation penetrates clouds deeper than IR radiation. That is why the UV-derived cloud pressure may be more consistent withthe total ozone algorithm. We estimate total column ozone differences caused by replacing the cloud pressure climatology with cloud pressures retrieved from GOME data same as used for retrieval of ozone.

Joiner, J.↗