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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Chemical-dynamical models of the Venus mesosphere based upon diurnal microwave CO variations

An attempt is made to explain the fact that the large variation in Venus CO abundance with planetary phase using a combination of photochemical and kinematical models. Present knowledge about the Venus mesosphere is first summarized, emphasizing the more completely measured lower and upper atmosphere. The predictions of Dickinson and Ridley's (1977) hydrodynamic modeling are compared to the results of microwave observations of CO. It is noted that the nightside CO bulge above 90-95 km altitude indicated by microwave measurements is a primary characteristic of these models, whereas the opposite phase behavior of CO between 80 and 90 km is not predicted by them. The result of diurnal photochemical models for the Venus mesosphere are presented and an attempt is made to reproduce the phase behavior of CO between 80 and 90 km in the Venus mesosphere. Possible diurnal variations due to chemistry and vertical eddy diffusion are considered.

Clancy, R. T.↗
NASA NTRS1984

Three dimensional global modeling of atmospheric CO2

The initial attempts to model the atmospheric CO2 distribution, including couplings to the ocean and biosphere as sources and sinks of atmospheric CO2, encourage the notion that this approach will lead to useful quantitative constraints on CO2 fluxes. Realization of this objective will require: (1) continued improvement in the realism of the global transport modeling; (2) extended timeline of atmospheric CO2 monitoring, which improved precision and improved definition of the uncertainties in the measured CO2 amounts; and (3) given an accurate knowledge of model capabilities and limitations and given a good understanding of CO2 observations and their limitations, there is a need for good ideas concerning what quantitative information on the carbon cycle can be inferred from global modeling.

Hanse, J.↗
NASA NTRS1991

Recursive renormalization group theory based subgrid modeling

Advancing the knowledge and understanding of turbulence theory is addressed. Specific problems to be addressed will include studies of subgrid models to understand the effects of unresolved small scale dynamics on the large scale motion which, if successful, might substantially reduce the number of degrees of freedom that need to be computed in turbulence simulation.

Zhou, YE↗
NASA NTRSDate not supplied

Enhancing Dataset Discovery and Usage Tracking in Earth Sciences: Integrating Knowledge Graphs and Large Language Models

NASA's Data Active Archive Centers (DAACs) have played a crucial role in supporting a wide range of applied research in Earth and Environmental sciences. To date, over 20,000 publications have been collected, citing more than 3,000 NASA Earth science datasets. We present an innovative approach that links datasets and collected publications through a knowledge graph (KG). This KG enables the tracking of dataset citations throughout the dataset's lifecycle, revealing patterns of dataset usage across various applied research areas. We fine-tuned the pre-trained NASA IMPACT INDUS-Base Retriever Large Language Model (LLM) using a set of labeled publication abstracts. Our results indicate that 87% of the publications were classified into one of twenty applied research areas, while the remaining 13% were categorized into non-applied research areas. The classified publications linked to datasets are used to discover datasets by users interested in specific applied research and by dataset providers to determine dataset usage for applications.

open-source↗
DOE OSTI2025

Leveraging transfer learning and leaf spectroscopy for leaf trait prediction with broad spatial, species, and temporal applicability

Accurate and reliable prediction of leaf traits is crucial for understanding plant adaptations to environmental variation, monitoring terrestrial ecosystems, and enhancing comprehension of functional diversity and ecosystem functioning. Currently, various approaches (e.g., statistical, physical models) have been developed to estimate leaf traits through hyperspectral remote sensing and leaf spectroscopy. However, the absence of high-performing, transferable, and stable models across various domains of space, plant functional types (PFTs) and seasons hinder our ability to quantify and comprehend spatiotemporal variations in leaf traits. This study proposes robust and highly transferable models for better predicting leaf traits with hyperspectral reflectance. Initially, three datasets were assembled, pairing common leaf traits — chlorophyll (Chla+b), carotenoids (Ccar), leaf mass per area (LAM), equivalent water thickness (EWT) — with leaf spectra measurements collected across diverse geographic locations in the U.S. and Europe, PFTs, and seasons. Measurements were acquired using spectroradiometers (e.g., ASD FieldSpec 3/4/Pro and SVC HR-1024i) with integrating spheres, leaf clips, and contact probes. Here, we then developed transfer learning-based hybrid models that incorporated the domain knowledge of radiative transfer models (RTMs) through pretraining processes and were well-constrained by fine-tuning with field measurements. Through comparison with other state-of-the-art statistical models, including partial-least squares regression (PLSR) and Gaussian Process Regression (GPR), as well as pure physical models, we found that the proposed transfer learning models achieved better predictive performance and higher transferability. Specifically, compared to other statistical models and pure RTMs, the transfer learning model exhibited higher coefficient of determination (R 2 ) values with range of 0.01 to 0.79, lower normalized root mean square error (NRMSE) with range of 0.06 % to 33.25 % in model performance. Additionally, the models exhibited improved transferability, with higher R 2 values range from 0.04 to 0.32, lower NRMSE range from 0.08 % to 30.81 %. The findings underscore that transfer learning models through integrating domain knowledge from RTMs and limited observations, can harness the advantages of both RTMs and statistical models and serve as a promising approach for effectively predicting leaf traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Roadmap for a Lightning Modeling Grand Challenge

This document is a roadmap for building an interconnected model of the physical processes that produce a lightning discharge, and its observable optical and radio signals. We call this a Lightning Modeling Grand Challenge, recognizing that significant effort and coordination of human and financial resources is required to realize the capability. The roadmap serves to outline the coordination of resources necessary to enable stitching together existing knowledge and model components to make a lightning prediction, and to test these predictions with observations. Such a capability does not currently exist. The roadmap is motivated not only by a spirit of scientific inquiry, but by practical challenges faced by US Federal and societal stakeholders. Advancements in lightning observations have outpaced our tests of integrated understanding, leaving many stakeholders unsure how to design their missions to properly detect and discriminate lightning, and unsure how to apply the sometimes-disagreeing lightning signals from diverse instruments. The time is right to connect existing theories and models to support stakeholders in understanding the signals they observe, for needs as diverse as climate monitoring, national security, weather forecasting, public safety, and protection of natural and built environments. The roadmap’s two main technical sections describe the components of a linked physical model, followed by a description of models of lightning signals and sensors that are driven by outputs from the physical model. The goal is to predict the time-varying physical properties of lightning that are self-consistent with the thunderstorm’s structure and dynamics. These lightning signals then propagate through the storm, with realistic dispersion and attenuation, to receivers on the ground or in space. At a high level, the model begins with weather (cloud) model output, including explicit prediction of the electrification of cloud particles. The cloud’s electrical structure drives a model of lightning physics, from initiation, through channel development, and discharges along those channels. Key lightning parameters, such as the temperature and currents in the channel, and their space and time distribution, are then used to produce optical and electromagnetic signal sources that propagate to modeled receivers. This architecture therefore generates a dataset suitable for comparison to existing and envisioned observing systems. The need for additional measurements and field campaigns to support model development is described. In each model sub-component, inputs, outputs, uncertainties, evaluation methods, and next steps are summarized, interleaved with references to the scientific literature. Identifying boundaries between the model sub-components aids in segmenting an integrated, complex model into practical work packages and system sub-components, allowing a diverse team to contribute and maintain the system. We estimate that at least five years of effort and a $\$$10M initial investment is necessary to make a significant step forward. Mechanisms to facilitate community coordination, including annual workshops and open-source code repositories, are described.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

The Extragalactic Background Light and the Gamma-ray Opacity of the Universe

The extragalactic background light (EBL) is one of the fundamental observational quantities in cosmology. All energy releases from resolved and unresolved extragalactic sources, and the light from any truly diffuse background, excluding the cosmic microwave background (CMB), contribute to its intensity and spectral energy distribution. It therefore plays a crucial role in cosmological tests for the formation and evolution of stellar objects and galaxies, and for setting limits on exotic energy releases in the universe. The EBL also plays an important role in the propagation of very high energy gamma-rays which are attenuated en route to Earth by pair producing gamma-gamma interactions with the EBL and CMB. The EBL affects the spectrum of the sources, predominantly blazars, in the approx 10 GeV to 10 TeV energy regime. Knowledge of the EBL intensity and spectrum will allow the determination of the intrinsic blazar spectrum in a crucial energy regime that can be used to test particle acceleration mechanisms and VHE gamma-ray production models. Conversely, knowledge of the intrinsic gamma-ray spectrum and the detection of blazars at increasingly higher redshifts will set strong limits on the EBL and its evolution. This paper reviews the latest developments in the determination of the EBL and its impact on the current understanding of the origin and production mechanisms of gamma-rays in blazars, and on energy releases in the universe. The review concludes with a summary and future directions in Cherenkov Telescope Array techniques and in infrared ground-based and space observatories that will greatly improve our knowledge of the EBL and the origin and production of very high energy gamma-rays.

Dwek, Eli↗
NASA NTRS1992

Formalization and visualization of domain-specific software architectures

This paper describes a domain-specific software design system based on the concepts of software architectures engineering and domain-specific models and languages. In this system, software architectures are used as high level abstractions to formulate a domain-specific software design. The software architecture serves as a framework for composing architectural fragments (e.g., domain objects, system components, and hardware interfaces) that make up the knowledge (or model) base for solving a problem in a particular application area. A corresponding software design is generated by analyzing and describing a system in the context of the software architecture. While the software architecture serves as the framework for the design, this concept is insufficient by itself for supplying the additional details required for a specific design. Additional domain knowledge is still needed to instantiate components of the architecture and develop optimized algorithms for the problem domain. One possible way to obtain the additional details is through the use of domain-specific languages. Thus, the general concept of a software architecture and the specific design details provided by domain-specific languages are combined to create what can be termed a domain-specific software architecture (DSSA).

Bailor, Paul D.↗
NASA NTRS2020

The Earth Surface Mineral Dust Source Investigation: An Earth Science Imaging Spectroscopy Mission

The Earth Surface Mineral Dust Source Investigation, EMIT, is planned to operate from the International Space Station starting no earlier than the fall of 2021. EMIT will use visible to short wavelength infrared imaging spectroscopy to determine the mineral composition of the arid land dust source regions of the Earth to advance our knowledge of the radiative forcing effect of these aerosols. Mineral dust emitted into the atmosphere under high wind conditions is an element of the Earth system with many impacts to the Earth’s energy balance, atmosphere, surface, and oceans. The Earth’s mineral dust cycle with source, transport, and deposition phases are studied with advanced Earth System Models. Because the chemical composition, optical and surface properties of soil particles vary strongly with the mineral composition of the source, these models require knowledge of surface soil mineral dust source composition knowledge to accurately understand dust impacts on the Earth system now and in the future. At present, compositional knowledge of the Earth’s mineral dust source regions from existing data sets is uncertain as a result of limited measurements. EMIT will use spectroscopically derived surface mineral composition to update the prescribe boundary conditions for state-of-the-art Earth System Models. The EMIT-initialized models will be used to investigate the impact of direct radiative forcing in the Earth system that depends strongly on the composition of the mineral dust aerosols emitted into the atmosphere. These new measurements and related products will be used to address the EMIT science objectives and made available to the science community for additional investigations. An overview of the EMIT science, development, and mission is presented in this paper.

Green, Robert O.↗
DOE OSTI2026

Ontologies for Intelligent Data Science

As anyone even vaguely aware of current technology can tell you, machine learning (ML) and artificial intelligence (AI) have made exceptional breakthroughs in recent years. Generative artificial intelligence (GAI) emerged circa 2022 dominated by Large Language Models (LLMs) and generative tools for images emerged at about the same time.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Insights into Slip-Rate Time Functions, Rupture Parameter Correlations, and Ground Motions from Validated Multicycle Earthquake Ruptures

Earthquake strong-motion predictions using kinematic source modeling require knowledge of the slip-rate functions (SRFs) along the rupture and their distinct characteristics in asperities, background (off-asperity) areas and near the surface. Here, in this study we analyzed SRFs from well-validated, self-consistent, and fully dynamic rupture models from earthquake cycles obeying a rate-and-state friction law, from our companion study (Galvez et al., 2021). The shapes of SRFs in asperities are well described by the regularized Yoffe function (RYF), which has only two parameters: rise time T r and smoothing time T s , which control the generation of long- and short-period ground motions, respectively. In background areas, we demonstrate that, in addition to the primary rupture, multiple secondary ruptures may also nucleate from rupture heterogeneities related to asperities, resulting in SRFs with multiple peaks. Because it is impossible to fit a multiple-peak SRF by the single-peak RYF, we describe SRFs in background areas in an effective way by fitting their amplitude spectra with the RYF spectra. Such spectrally effective RYFs capture salient aspects of seismic-wave generation and can be used in rupture generators for strong motion prediction. We found that small T s values correlate with small characteristic weakening distances, large peak slip rates (PSRs), and large rupture velocities. T r values are larger in background areas and smaller in asperities. Within the shallow aseismic zone, T s values approximately quadruple whereas T r values approximately double. Because of this dominant T s increase, PSR values decrease in the near-surface zone. These features indicate that the generation of strong motions by the near-surface portions of the rupture is negligible in the studied scenarios.

Geosciences↗
NASA NTRS2016

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Future Suborbital Activities to Address Knowledge Gaps in Satellite and Model Assessments

Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles. Particles lofted into the mid-troposphere are transported westward over the South-East (SE) Atlantic, home to one of the three permanent subtropical stratocumulus (Sc) cloud decks in the world. The SE Atlantic stratocumulus deck interacts with the dense layers of BB aerosols that initially overlay the cloud deck, but later subside and may mix into the clouds. These interactions include adjustments to aerosol-induced solar heating and microphysical effects, and their global representation in climate models remains one of the largest uncertainties in estimates of future climate. Hence, new observations over the SE Atlantic have significant implications for global climate change scenarios. Our understanding of aerosol-cloud interactions in the SE Atlantic is hindered both by the lack of knowledge on aerosol and cloud properties, as well as the lack of knowledge about detailed physical processes involved. Most notably, we are missing knowledge on the absorptive and cloud nucleating properties of aerosols, including their vertical distribution relative to clouds, on the locations and degree of aerosol mixing into clouds, on the processes that govern cloud property adjustments, and on the importance of aerosol effects on clouds relative to co-varying synoptic scale meteorology. We discuss the current knowledge of aerosol and cloud property distributions based on satellite observations and sparse suborbital sampling. Recent efforts to make full use of A-Train aerosol sensor synergies will be highlighted. We describe planned field campaigns in the region to address the existing knowledge gaps. Specifically, we describe the scientific objectives and implementation of the five synergistic, international research activities aimed at providing some of the key aerosol and cloud properties and a process-level understanding of aerosol-cloud interactions over the SE Atlantic: NASA's ORACLES, the UK Met Office's CLARIFY-2016, the DoE's LASIC, NSF's ONFIRE, and CNRS' AEROCLO-SA.

aerosols↗
NASA NTRS2016

Trade-Space Analysis Tool for Constellations (TAT-C)

Traditionally, space missions have relied on relatively large and monolithic satellites, but in the past few years, under a changing technological and economic environment, including instrument and spacecraft miniaturization, scalable launchers, secondary launches as well as hosted payloads, there is growing interest in implementing future NASA missions as Distributed Spacecraft Missions (DSM). The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. In this first version of our Trade-space Analysis Tool for Constellations (TAT-C), we are investigating questions such as: How many spacecraft should be included in the constellation? Which design has the best costrisk value? The main goals of TAT-C are to: Handle multiple spacecraft sharing a mission objective, from SmallSats up through flagships, Explore the variables trade space for pre-defined science, cost and risk goals, and pre-defined metrics Optimize cost and performance across multiple instruments and platforms vs. one at a time.This paper describes the overall architecture of TAT-C including: a User Interface (UI) interacting with multiple users - scientists, missions designers or program managers; an Executive Driver gathering requirements from UI, then formulating Trade-space Search Requests for the Trade-space Search Iterator first with inputs from the Knowledge Base, then, in collaboration with the Orbit Coverage, Reduction Metrics, and Cost Risk modules, generating multiple potential architectures and their associated characteristics. TAT-C leverages the use of the Goddard Mission Analysis Tool (GMAT) to compute coverage and ancillary data, streamlining the computations by modeling orbits in a way that balances accuracy and performance.TAT-C current version includes uniform Walker constellations as well as Ad-Hoc constellations, and its cost model represents an aggregate model consisting of Cost Estimating Relationships (CERs) from widely accepted models. The Knowledge Base supports both analysis and exploration, and the current GUI prototype automatically generates graphics representing metrics such as average revisit time or coverage as a function of cost.

Science Data Processing↗
NASA NTRS1994

DIAMS revisited: Taming the variety of knowledge in fault diagnosis expert systems

The DIAMS program, initiated in 1986, led to the development of a prototype expert system, DIAMS-1 dedicated to the Telecom 1 Attitude and Orbit Control System, and to a near-operational system, DIAMS-2, covering a whole satellite (the Telecom 2 platform and its interfaces with the payload), which was installed in the Satellite Control Center in 1993. The refinement of the knowledge representation and reasoning is now being studied, focusing on the introduction of appropriate handling of incompleteness, uncertainty and time, and keeping in mind operational constraints. For the latest generation of the tool, DIAMS-3, a new architecture has been proposed, that enables the cooperative exploitation of various models and knowledge representations. On the same baseline, new solutions enabling higher integration of diagnostic systems in the operational environment and cooperation with other knowledge intensive systems such as data analysis, planning or procedure management tools have been introduced.

Haziza, M.↗
NASA NTRS1991

A numerical procedure for recovering scattering coefficients from measurements with wide-beam antennas

A numerical procedure for estimating true scattering coefficients, sigma0, from measurements made using wide-beam antennas is discussed. The use of wide-beam antennas results in an inaccurate estimate of sigma0. To reduce this error, the authors propose a correction procedure that estimates the error resulting from the use of narrow-beam approximation and utilizes the error to obtain a more accurate estimate of sigma0. An exponential model is assumed to take into account the variation of sigma0 with incidence angles, and the model parameters are estimated from measured data. Based on the model and knowledge of the antenna pattern, the procedure calculates the error due to the narrow-beam approximation. The procedure is shown to provide a significant improvement in the estimation of sigma0 obtained in wide-beam antennas. The proposed procedure is also shown to be insensitive to the assumed sigma0 model.

Wang, Qinglin↗
NASA NTRS1989

Automated monitor and control for deep space network subsystems

The problem of automating monitor and control loops for Deep Space Network (DSN) subsystems is considered and an overview of currently available automation techniques is given. The use of standard numerical models, knowledge-based systems, and neural networks is considered. It is argued that none of these techniques alone possess sufficient generality to deal with the demands imposed by the DSN environment. However, it is shown that schemes that integrate the better aspects of each approach and are referenced to a formal system model show considerable promise, although such an integrated technology is not yet available for implementation. Frequent reference is made to the receiver subsystem since this work was largely motivated by experience in developing an automated monitor and control loop for the advanced receiver.

Smyth, P.↗
NASA NTRS1991

A numerical procedure for recovering true scattering coefficients from measurements with wide-beam antennas

A numerical procedure for estimating the true scattering coefficient, sigma(sup 0), from measurements made using wide-beam antennas. The use of wide-beam antennas results in an inaccurate estimate of sigma(sup 0) if the narrow-beam approximation is used in the retrieval process for sigma(sup 0). To reduce this error, a correction procedure was proposed that estimates the error resulting from the narrow-beam approximation and uses the error to obtain a more accurate estimate of sigma(sup 0). An exponential model was assumed to take into account the variation of sigma(sup 0) with incidence angles, and the model parameters are estimated from measured data. Based on the model and knowledge of the antenna pattern, the procedure calculates the error due to the narrow-beam approximation. The procedure is shown to provide a significant improvement in estimation of sigma(sup 0) obtained with wide-beam antennas. The proposed procedure is also shown insensitive to the assumed sigma(sup 0) model.

Wang, Qinglin↗
NASA NTRSDate not supplied

Discovering Research Areas in Dataset Applications Through Knowledge Graphs and Large Language Models

Scientific datasets are increasingly cited in peer-reviewed journal publications, facilitating easy access to research utilizing those datasets. Datasets undergo a life cycle where older versions of datasets are replaced by newer versions often due to improvements in data resolution, algorithms, and other factors. Unlike peer reviewed documents registered with a single Digital Unique Identifier (DOI), datasets can be updated over time and the newer version of the datasets are registered with a new DOI which is not necessarily linked to the previous version of the dataset. It is challenging when publications citing a dataset need to be traced over the entire life cycle of that dataset. We provide an innovative approach to link the dataset versions and publications using a knowledge graph (KG). KG can help to trace the dataset cited in publications over the entire dataset life cycle and shed light into dataset usage in various applied research areas. We fine-tuned the pretrained NASA IMPACTINDUS Large Language Model (LLM) on a set of labeled publications abstracts. Our results showed that 87% of the publications were classified into one of twenty applied research areas, while the remaining 13% were classified into non-applied research areas. By linking datasets to applied research areas through the KG and employing Global Change Master Directory(GCMD), a well-established controlled vocabulary of scientific keywords describing Earth science datasets, we contribute to a transparent and advanced search and discovery mechanism for datasets across the Earth data ecosystem. The integrated KG and LLM approach is now incorporated and operational in dataset publication management at one of NASA’s Earth science data archival centers.

data provenance↗