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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

InGaP/InGaAs-on-Ge Concentrator Solar Cell for Space Power Generation

The passivating front and back window layer of the top cell has been chosen. We have chosen to use InGaAs as the tunnel junction interconnect compound since it is easily degenerately doped. All of the dual junction cell structures were grown on GaAs substrates. Time constraints prevented us from completing the development of the GaAs-on-Ge growth process. Analysis of the I-V and EQE data, and comparison with computer-modeled data, shows that the performance of the dual-junction cell is still being controlled by the bottom cell, in spite of top cell thinning. Further improvement in the dual-junction cell efficiency is possible by thinning the front window.

Sinharoy, Samar↗
NASA NTRS2007

Improved Modeling of Land-Atmosphere Interactions using a Coupled Version of WRF with the Land Information System

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many hydrometeorological processes. Accurate and high-resolution representations of surface properties such as sea-surface temperature (SST), vegetation, soil temperature and moisture content, and ground fluxes are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of weather and climate phenomena. The NASA/NWS Short-term Prediction Research and Transition (SPORT) Center is currently investigating the potential benefits of assimilating high-resolution datasets derived from the NASA moderate resolution imaging spectroradiometer (MODIS) instruments using the Weather Research and Forecasting (WRF) model and the Goddard Space Flight Center Land Information System (LIS). The LIS is a software framework that integrates satellite and ground-based observational and modeled data along with multiple land surface models (LSMs) and advanced computing tools to accurately characterize land surface states and fluxes. The LIS can be run uncoupled to provide a high-resolution land surface initial condition, and can also be run in a coupled mode with WRF to integrate surface and soil quantities using any of the LSMs available in LIS. The LIS also includes the ability to optimize the initialization of surface and soil variables by tuning the spin-up time period and atmospheric forcing parameters, which cannot be done in the standard WRF. Among the datasets available from MODIS, a leaf-area index field and composite SST analysis are used to improve the lower boundary and initial conditions to the LIS/WRF coupled model over both land and water. Experiments will be conducted to measure the potential benefits from using the coupled LIS/WRF model over the Florida peninsula during May 2004. This month experienced relatively benign weather conditions, which will allow the experiments to focus on the local and mesoscale impacts of the high-resolution MODIS datasets and optimized soil and surface initial conditions. Follow-on experiments will examine the utility of such an optimized WRF configuration for more complex weather scenarios such as convective initiation. This paper will provide an overview of the experiment design and present preliminary results from selected cases in May 2004.

Case, Jonathan L.↗
NASA NTRS2007

Modeling and Flight Data Analysis of Spacecraft Dynamics with a Large Solar Array Paddle

The Advanced Land Observing Satellite (ALOS) was launched on January 24 2006 and has been operated successfully since then. This satellite has the attitude dynamics characterized by three large flexible structures, four large moving components, and stringent attitude/pointing stability requirements. In particular, it has one of the largest solar array paddles. Presented in this paper are flight data analyses and modeling of spacecraft attitude motion induced by the large solar array paddle. On orbit attitude dynamics was first characterized and summarized. These characteristic motions associated with the solar array paddle were identified and assessed. These motions are thermally induced motion, the pitch excitation by the paddle drive, and the role excitation. The thermally induced motion and the pitch excitation by the paddle drive were modeled and simulated to verify the mechanics of the motions. The control law updates implemented to mitigate the attitude vibrations are also reported.

Iwata, Takanori↗
NASA NTRS2008

Issues in Data Fusion for Satellite Aerosol Measurements for Applications with GIOVANNI System at NASA GES DISC

We look at issues, barriers and approaches for Data Fusion of satellite aerosol data as available from the GES DISC GIOVANNI Web Service. Daily Global Maps of AOT from a single satellite sensor alone contain gaps that arise due to various sources (sun glint regions, clouds, orbital swath gaps at low latitudes, bright underlying surfaces etc.). The goal is to develop a fast, accurate and efficient method to improve the spatial coverage of the Daily AOT data to facilitate comparisons with Global Models. Data Fusion may be supplemented by Optimal Interpolation (OI) as needed.

Gopalan, Arun↗
NASA NTRS2017

CO2 Capacity Sorbent Analysis Using Volumetric Measurement Approach

In support of air revitalization system sorbent selection for future space missions, Ames Research Center (ARC) has performed CO2 capacity tests on various solid sorbents to complement structural strength tests conducted at Marshall Space Flight Center (MSFC). The materials of interest are: Grace Davison Grade 544 13X, Honeywell UOP APG III, LiLSX VSA-10, BASF 13X, and Grace Davison Grade 522 5A. CO2 capacity was for all sorbent materials using a Micromeritics ASAP 2020 Physisorption Volumetric Analysis machine to produce 0 C, 10 C, 25 C, 50 C, and 75 C isotherms. These data are to be used for modeling data and to provide a basis for continued sorbent research. The volumetric analysis method proved to be effective in generating consistent and repeatable data for the 13X sorbents, but the method needs to be refined to tailor to different sorbents.

Huang, Roger↗
NASA NTRS2017

CO2 Capacity Sorbent Analysis Using Volumetric Measurement Approach

In support of air revitalization system sorbent selection for future space missions, Ames Research Center (ARC) has performed CO2 capacity tests on various solid sorbents to complement structural strength tests conducted at Marshall Space Flight Center (MSFC). The materials of interest are: Grace Davison Grade 544 13X, Honeywell UOP APG III, LiLSX VSA-10, BASF 13X, and Grace Davison Grade 522 5A. CO2 capacity was for all sorbent materials using a Micromeritics ASAP 2020 Physisorption Volumetric Analysis machine to produce 0C, 10C, 25C, 50C, and 75C isotherms. These data are to be used for modeling data and to provide a basis for continued sorbent research. The volumetric analysis method proved to be effective in generating consistent and repeatable data for the 13X sorbents, but the method needs to be refined to tailor to different sorbents.

Air Revitalization↗
DOE OSTI2026

Modeling Framework for Data Center

This chapter highlights the critical need for advanced modeling of data centers due to their rapidly increasing energy consumption and impact on grid reliability. Driven by the demand for AI applications, data centers are projected to consume a significant portion of US energy by 2028, putting stress on an already challenged power grid. The chapter emphasizes the importance of "fast" time-scale models to understand the dynamic interactions between data centers and the grid, especially given the rapid power fluctuations of AI workloads. It outlines a modeling framework that includes both offline and real-time EMT domain simulations, detailing the necessary representations for various components like utility interfaces, transformers, IT loads, UPS, cooling loads, Battery Energy Storage Systems (BESS), generators, protection systems, and higher-level control systems. While standard simulation tools like PSCAD offer basic models, custom development is often required to accurately capture the unique and fast-changing behaviors of modern data centers. The chapter also discusses key metrics and test cases for validating these models, focusing on transient load responses, protection relay coordination, and demand flexibility. Finally, it addresses the challenges of modeling large-scale data centers, such as computational complexity and the trade-off between model fidelity and practicality, suggesting hybrid modeling approaches as a solution. The overarching goal is to create a robust framework that helps assess data center impacts on grid stability, identify vulnerabilities, and inform the development of standards for reliable integration of these large loads into the bulk power system.

25 ENERGY STORAGE↗
NASA NTRS2021

Assessment of RANS-based Transition Models based on Experimental Data of the Common Research Model with Natural Laminar Flow

Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework often rely upon transition correlations that were derived from a limited number of low-speed experiments and these models often fail to account for all of the relevant transition mechanisms and/or the variation in those mechanisms with respect to changes in the significant flow parameters. Available data from a recent experiment on the Common Research Model with Natural Laminar Flow (CRM-NLF) in the National Transonic Facility at the NASA Langley Research Center are used to assess the current transition modeling capability in NASA's OVERFLOW 2.3b solver for a swept wing configuration with nonzero taper and transonic cruise conditions. Specifically, the OVERFLOW solutions are used to evaluate the accuracy and robustness of the transport-equation-based transition models. Results highlight that the Spalart-Allmaras-based amplification factor transport (AFT-2017b) equation model and Menter’s shear-stress transport equation (SST2003)-based Langtry-Menter transition models (either with or without the modeling of crossflow transition) significantly underpredict the reported extent of laminar flow region over the entire span of the wing, irrespective of which instability mechanism(s) is expected to dominate the onset of the transition process. We show that the transition correlations underlying these models fail to account for the stabilizing effect of compressibility on the Tollmien-Schlichting transition, which is likely to be a major contributor to the underprediction of the laminar flow region on the CRM-NLF. The SST-2003-based Langtry-Menter model also appears to inaccurately predict the chordwise pressure variation along the majority of the wing span at all the flow conditions studied herein, due to how the turbulence intensity levels were enforced in the computations and how that was interfering with the functioning of the underlying turbulence model within the boundary layer. The AFT and Langtry-Menter models appear to be sensitive to the level of the freestream turbulence intensity, but the degree of sensitivity varies across the models.

CFD modeling↗
NASA NTRS2005

The semantic planetary data system

This paper will provide a brief overview of the PDS data model and the PDS catalog. It will then describe the implentation of the Semantic PDS including the development of the formal ontology, the generation of RDFS/XML and RDF/XML data sets, and the buiding of the semantic search application.

semantic↗
NASA NTRSDate not supplied

NASA Giovanni: Analyze, Compare, and Visualize 2000+ Earth Satellite and Model Variables Without Downloading Data and Software

Over vast oceans and remote continents, observations are often scarce and discontinuous. Satellite and model data play a critical role in research and applications. However, finding and accessing satellite and model data can be a daunting task for many, especially those outside the community. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA Science Mission Directorate Data Centers, provides Earth science data, information, and services to everyone such as researchers, application users, educators, and students. GES DISC archives and supports datasets applicable to several NASA Earth Science Focus Areas including Atmospheric Composition, Water & Energy Cycles, Carbon Cycle & Ecosystem, and Climate Variability. To facilitate data discovery, evaluation, and exploration, GES DISC has developed the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni), an online tool to analyze and visualize NASA remote sensing and model data without downloading data and software. As of this writing, over 2000 Earth satellite and model variables are available in Giovanni, including several wellknown NASA satellite missions (e.g., TRMM, GPM) and projects (e.g., MERRA-2, GPCP). Giovanni provides twenty-two plots that can be used to analyze, compare, and explore Earth data across different disciplines. Results can be shared with colleagues and downloaded for further analysis. Over the years, Giovanni has helped publish over 3000 referral papers. In this presentation, we will showcase key variables and plot types in Giovanni with examples. In particular, we will present several popular precipitation products from GPM and CPCP for evaluation and comparison.

data analysis↗
DOE OSTI2026

The critical role of soil moisture in compound hazards

Soil moisture regulates the exchange of energy, water, and carbon across land–vegetation–atmosphere interfaces. Extremes in soil moisture can amplify natural hazards through interactions with diverse Earth system processes. Despite its mechanistic importance, soil moisture remains underrepresented in hazard research and predictive frameworks. Here, in this study, we review our current understanding of the role of soil moisture in the evolution and onset of diverse compound hazards by synthesizing the latest findings from observational and modelling studies. We highlight key soil moisture mechanisms, including atmospheric feedbacks that amplify drought–heatwave–wildfire events, precipitation couplings that promote clustered storms, and threshold responses that drive vegetation die-offs, trigger landslides, and induce flooding. Persistent challenges in observational data, model representation and operational implementation have limited the integration of soil moisture into hazard early-warning systems. Addressing these gaps through advances in observations, data assimilation, and physics-based and data-driven modelling will enhance hazard prediction and preparedness in a rapidly changing world.

Li, Chuxuan [University of California, Los Angeles↗
NASA NTRS2006

Sensor to User - NASA/EOS Data for Coastal Zone Management Applications Developed from Integrated Analyses: Verification, Validation and Benchmark Report

The NASA Applied Sciences Program seeks to transfer NASA data, models, and knowledge into the hands of end-users by forming links with partner agencies and associated decision support tools (DSTs). Through the NASA REASoN (Research, Education and Applications Solutions Network) Cooperative Agreement, the Oceanography Division of the Naval Research Laboratory (NRLSSC) is developing new products through the integration of data from NASA Earth-Sun System assets with coastal ocean forecast models and other available data to enhance coastal management in the Gulf of Mexico. The recipient federal agency for this research effort is the National Oceanic and Atmospheric Administration (NOAA). The contents of this report detail the effort to further the goals of the NASA Applied Sciences Program by demonstrating the use of NASA satellite products combined with data-assimilating ocean models to provide near real-time information to maritime users and coastal managers of the Gulf of Mexico. This effort provides new and improved capabilities for monitoring, assessing, and predicting the coastal environment. Coastal managers can exploit these capabilities through enhanced DSTs at federal, state and local agencies. The project addresses three major issues facing coastal managers: 1) Harmful Algal Blooms (HABs); 2) hypoxia; and 3) freshwater fluxes to the coastal ocean. A suite of ocean products capable of describing Ocean Weather is assembled on a daily basis as the foundation for this semi-operational multiyear effort. This continuous realtime capability brings decision makers a new ability to monitor both normal and anomalous coastal ocean conditions with a steady flow of satellite and ocean model conditions. Furthermore, as the baseline data sets are used more extensively and the customer list increased, customer feedback is obtained and additional customized products are developed and provided to decision makers. Continual customer feedback and response with new improved products are required between the researcher and customer. This document details the methods by which these coastal ocean products are produced including the data flow, distribution, and verification. Product applications and the degree to which these products are used successfully within NOAA and coordinated with the Mississippi Department of Marine Resources (MDMR) is benchmarked.

Hall, Callie↗
DOE OSTI2024

Earth System Reanalysis in Support of Climate Model Improvements

Recent climate model developments, established through increased model resolution, have led to substantial improvements in model simulations of the time-evolving, coupled Earth system and its subcomponents. However, regardless of resolution, climate models will always produce climate features and variability that differ from the real world and will be prone to biases. This is due to many remaining uncertainties, such as in parametric and structural model uncertainty, in the initial conditions prescribed, and in the prescribed (scenario) forcing which varies on decadal to centennial timescales. Further model improvements are expected to arise specifically from improved representation of physical processes realized through model-data fusion. This will create an unprecedented opportunity to better exploit a large array of Earth observations, from in situ measurements to weather radars and satellite observations, as the resolved scales of the models approach those of the observations. For this, climate DA will be the central tool to bring models and observations into consistency, by improving initial conditions, inferring uncertain model parameters and structure, and quantifying uncertainty. Generally, there will be advantages and complementarities of adjoint-based smoother approaches, ensemble-based filter approaches, or new ML-inspired approaches. Yet, the ever-increasing model resolution will present growing challenges arising from computational cost, calling for new ways of performing data assimilation and model optimization. Using the complementarity in a hybrid approach, blending tools and concepts from variational, ensemble and ML methods might be what is required in the future. In this context ML could be important to handle non-linear responses, and to better approximate non-Gaussian distributions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Contrast Gain Control Model Fits Masking Data

We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.

Watson, Andrew B.↗
DOE OSTI2024

Impact of Vegetation Assimilation on Flash Drought Characteristics across the Continental United States

Predicting and managing the impacts of flash droughts is difficult owing to their rapid onset and intensification. Flash drought monitoring often relies on assessing changes in root-zone soil moisture. However, the lack of widespread soil moisture measurements means that flash drought assessments often use process-based model data like that from the North American Land Data Assimilation System (NLDAS). Such reliance opens flash drought assessment to model biases, particularly from vegetation processes. Here, we examine the influence of vegetation on NLDAS-simulated flash drought characteristics by comparing two experiments covering 1981–2017: open loop (OL), which uses NLDAS surface meteorological forcing to drive a land surface model using prognostic vegetation, and data assimilation (DA), which instead assimilates near-real-time satellite-derived leaf area index (LAI) into the land surface model. The OL simulation consistently underestimates LAI across the United States, causing relatively high soil moisture values. Both experiments produce similar geographic patterns of flash droughts, but OL produces shorter duration events and regional trends in flash drought occurrence that are sometimes opposite to those in DA. Across the Midwest and Southern United States, flash droughts are 4 weeks (about 70%) longer on average in DA than OL. Moreover, across much of the Great Plains, flash drought occurrence has trended upward according to the DA experiment, opposite to the trend in OL. This sensitivity of flash drought to the representation of vegetation suggests that representing plants with greater fidelity could aid in monitoring flash droughts and improve the prediction of flash drought transitions to more persistent and damaging long-term droughts.

Drought↗
NASA NTRS2005

Generating Solid Models from Topographical Data

A method of generating solid models of terrain involves the conversion of topographical data into a form useable by a rapid-prototyping (RP) machine. The method was developed to enable the use of the RP machine to make solid models of Martian terrain from Mars Orbiter laser-altimeter topographical data. The method is equally applicable to the generation of models of the terrains of other astronomical bodies, including other planets, asteroids, and Earth. Topographical data describe a terrain in terms of a set of three-dimensional coordinates [e.g., Cartesian (x,y,z) or polar (latitude, longitude, radius) coordinates] of points or nodes on the terrain surface. The input data for the RP machines are required to provide a three-dimensional description, not of a single surface, but of a volume in this case, a ground volume that underlies the terrain surface. The description is required to be in the form of triangular elements that connect the nodes of all the surfaces and that completely bound the volume, with no open areas, no overlap of triangles, and no extraneous geometric elements. The software used in the present model-generation method was written in IDL - an advanced programming language that affords a number of tools, including subroutines that triangularize surfaces. The software creates a volume from the topographical surface data by adding sides to the edges of the terrain surface and joining the sides with a bottom surface. Each of the sides is triangularized by use of IDL subroutines, and then the software searches for extraneous elements and removes them. Topographical data are usually presented in a grid corresponding to polar coordinates, so that a model generated from such data is equivalent to a topographical map in Mercator projection. However an RP machine is fully capable of including the curvature of a planetary body in a model that it makes. Therefore, the software also offers a capability to transform the topographical data to a projection onto a surface having a curvature corresponding to that of the surface of the modeled planet.

Keller, John W.↗