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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 937 records · Page 52

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NASA NTRS1991

Observations on practical turbulence modeling for high-speed jet/plume flowfields

An overview is presented of the current status in terms of simulating basic high-speed/straightback free jet flowfields with two-equation turbulence models. A building-block approach is described which provides a systematic method of calibrating such turbulence models. Data to support this approach focuses on obtaining turbulence modeling capabilities to reproduce basic mean flow structure for simple flows before progressing to more complex problems. For transverse jets and wall jets, new building-blocks of data are necessary with turbulence modeling capabilities unifying the free jet building-blocks discussed, and fundamental boundary layer and shock/boundary layer interaction building-blocks resulting from other studies.

Dash, Sanford M.↗

DOE OSTI2025

Reconstruction framework advancements to support streaming for the ePIC detector at the EIC

The ePIC collaboration adopted the JANA2 framework to manage its reconstruction algorithms. This framework has since evolved substantially in response to ePIC’s needs. There have been three main design drivers: integrating cleanly with the Podio-based data models and other layers of the key4hep stack, enabling external configuration of existing components, and supporting timeframe splitting for streaming readout. The result is a unified component model featuring a new declarative interface for specifying inputs, outputs, parameters, services, and resources. This interface enables the user to instantiate, configure, and wire components via an external file. One critical new addition to the component model is a hierarchical decomposition of data boundaries into levels such as Run, Timeframe, PhysicsEvent, and Subevent. Two new component abstractions, Folder and Unfolder, are introduced in order to traverse this hierarchy, e.g. by splitting or merging. The pre-existing components can now operate at different event levels, and JANA2 will automatically construct the corresponding parallel processing topology. This means that a user may write an algorithm once, and configure it at runtime to operate on timeframes or on physics events. Overall, these changes mean that the user requires less knowledge about the framework internals, obtains greater flexibility with configuration, and gains the ability to reuse the existing abstractions in new streaming contexts.

Brei, Nathan [Thomas Jefferson National Accelerato↗

DOE OSTI2022

Simulated tree recruitment at PA-BCI under four precipitation scenarios

Simulated recruitment rates are provided for four tropical tree plant functional types (PFTs) which vary in drought and shade tolerance, at Barro Colorado Island, Panama (PA-BCI). Recruitment rates are predicted using the Tree Recruitment Scheme (TRS; Hanbury-Brown et al., 2022) and model data output from the Ecosystem Demography model version 2 with hydrodynamics (ED2; Medvigy et al., 2009, Powell et al., 2018). Predictions of recruitment are provided under four precipitation scenarios: “BASE” = recycled 2008-2014 observed meteorology (Faybishenko & Paton, 2021), “SYN-ENSO” = two exceptionally strong El Niño events within 30 years (Powell et al., 2018), “WET” = 30% increase in precipitation compared to BASE, and DRY-DS = dry season (January–April) precipitation reduced by 75% compared to BASE. In addition to recruitment rates, this dataset provides TRS predictions of PFT-specific seed bank and seedling pool dynamics (tracked in units of carbon) and ED predictions of understory photosynthetically active radiation and soil matric potential at 6 cm soil depth.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Future Response of Coastal Wetlands to Environmental Stresses: Algorithm Comparison of Numerical Models

Coastal wetlands are a critical component of the earth system that strongly influence the global water and biogeochemical cycles. They are also likely important sentinel of climate change. Because eco-geomorphological processes have long been recognized to be important for coastal wetland survival under accelerated sea-level rise (SLR), many eco-geomorphology models have been developed to assess the impact of climate change on coastal wetlands. Although these models differ substantially in complexity and numerical methods, few studies have investigated the algorithm-level uncertainties in these models. In this study, we developed a multiple-algorithm model framework of coastal wetlands that represents coastal hydrodynamics (such as water level, significant wave height and bottom shear stress) and four eco-geomorphological processes: mineral accretion, organic matter accretion, storm surge erosion and landward migration. We validated the model at three representative coastal wetland sites (Venice Lagoon, Plum Island Estuary and Hunter Estuary) for hydrodynamics, mineral accretion and organic matter accretion. Through model-data comparison, we showed that the model can well capture the dynamics of hydrodynamical and eco-geomorphological conditions in the study sites. Importantly, analysis of the multiple-algorithm simulations suggests that differences in the process representation of mineral and organic matter accretion may contribute to the recent contradicting predictions of coastal wetland evolution under accelerated SLR.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

NSSDC Data Listing

Data available from the National Space Science Data Center (NSSDC) are listed. The spacecraft, principal investigator, the experiment, and time span of the data are given. A listing is also included of ground-based data, models, computer routines and composite spacecraft data that are available from NSSDC.

Source record↗

NASA NTRS1980

National Space Science Data Center (NSSDC) Data Listing

Satellite and nonsatellite data available from the National Space Science Data Center are listed. The Satellite Data listing includes the spacecraft name, launch date, and an alphabetical list of experiments. The Non-Satellite Data listing contains ground based data, models, computer routines, and composite spacecraft data. The data set name, data form code, quantity of data, and the time space covered are included in the data sets of both listings where appropriate. Geodetic tracking data sets are also included.

Source record↗

NASA NTRS1981

NSSDC Data listing

A convenient reference to space science and supportive data available from the National Space Science Data Center (NSSDC) is provided. Satellite data are organized by NSSDC spacecraft common name. The launch date and NSSDC ID are given. Experiments are listed alphabetically by the principal investigator or team leader. The experiment name and NSSDC ID, data set ID, data set name, data form code, quantity of data, and the time span of the data as verified by NSSDC are shown. Ground-based data, models, computer routines, and composite spacecraft data that are available from NSSDC are listed alphabetically by discipline, source, data type, data content, and data set. The data set name, data form code, quantity of data, and the time span covered where appropriate are included.

Source record↗

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 OSTI2021

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository: Preprint

The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.

access↗

DOE OSTI2021

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository

access↗

DOE OSTI2023

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Abstract Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Ueyama, Masahito↗

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↗