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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Oxidation states of iron in the terrestrial planets: Evidence and implications for accretion models

Analyses of Mars spectra reveal that primary minerals may be more iron rich than average basalts on Earth, and the oxidation state of iron in the pyroxines suggests equally high or higher oxygen fugacities on Mars than Earth. Analysis of Mercury spectra reveal that silicate iron contents are substantially lower than those on Mars. Mercury, however, probably has a substantial iron core. This is consistent with a lower oxidation state of iron on Mercury than on Mars. These findings are consistent with predictions of models of equilibrium condensation and homogeneous accretion. Those models predict that Mercury would have negligible Fe(2+) in silicates (Fe/Fe+Mg approx. 0.5). For Mercury iron should be virtually all metallic, while for Mars the iron would be all oxidized as FeS and silicate. Surface measurements of Fe/Fe+Mg on Venus, Earth, and Mars further support the predicted relative increase in Fe/Fe+Mg ratio (increased oxidation state) with distance from the Sun. The implied high oxygen fugacities on Mars (Fe(3+) in silicates) provide additional consistence with the model predictions.

Huguenin, R. L.↗
DOE OSTI2025

The Influence of Demographic Variables on the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA)

Building on our prior research with a national survey sample of 5385 US participants, the Pooled Rideshare Acceptance Model (PRAM) was built upon two factor analyses. This exploratory study extends the PRAM framework using the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA) to examine how 16 demographic variables influence and interact with the acceptance of Pooled Rideshare (PR), filling a gap in understanding user segmentation and personalization. Using a national sample of 5385 US participants, this methodological approach allowed for the evaluation of how PRAM variables such as safety, privacy, service experience, and environmental impact vary across diverse groups, including gender, generation, driver’s license, rideshare experience, education level, employment status, household size, number of children, income, vehicle ownership, and typical commuting practices. Factors such as convenience, comfort, and passenger safety did not show significant differences across the moderators, suggesting their universal importance across all demographics. Furthermore, geographical differences did not significantly impact the relationships within the model, suggesting consistent relationships across different regions. The findings highlight the need to move beyond a “one size fits all” approach, demonstrating that tailored strategies may be crucial for enhancing the adoption and satisfaction of PR services among various demographic groups. The analyses provide valuable insight for policymakers and rideshare companies looking to optimize their services and increase user engagement in PR.

moderator↗
NASA NTRS1993

Structural analysis of high-rpm composite propfan blades for a cruise missile wind tunnel model

Analyses were performed on a high-speed composite blade set for the Department of Defense Propfan Missile Interactions Project. The final design iteration, which resulted in the CM2D-2 blade design, is described in this report. Mode shapes, integral order excitation, and stress margins were examined. In addition, geometric corrections were performed to compensate for blade deflection under operating conditions with respect to the aerodynamic design shape.

Carek, David A.↗
DOE OSTI2021

HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses

Simple climate models (SCMs) are frequently used in research and decision-making communities because of their flexibility, tractability, and low computational cost. SCMs can be idealized, flexibly representing major climate dynamics as impulse response functions, or process-based, using explicit equations to model possibly nonlinear climate and Earth system dynamics. Each of these approaches has strengths and limitations. Here we present and test a hybrid impulse response modeling framework (HIRM) that combines the strengths of process-based SCMs in an idealized impulse response model, with HIRM's input derived from the output of a process-based model. This structure enables the model to capture some of the major nonlinear dynamics that occur in complex climate models as greenhouse gas emissions transform to atmospheric concentration to radiative forcing to climate change. As a test, the HIRM framework was configured to emulate the total temperature of the simple climate model Hector 2.0 under the four Representative Concentration Pathways and the temperature response of an abrupt 4 times CO 2 concentration step. HIRM was able to reproduce near-term and long-term Hector global temperature with a high degree of fidelity. Additionally, we conducted two case studies to demonstrate potential applications for this hybrid model: examining the effect of aerosol forcing uncertainty on global temperature and incorporating more process-based representations of black carbon into a SCM. The open-source HIRM framework has a range of applications including complex climate model emulation, uncertainty analyses of radiative forcing, attribution studies, and climate model development.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

An evaluation of soundings, analyses and model forecasts derived from TIROS-N and NOAA-6 satellite data

TIROS-N and NOAA-6 temperature soundings over North America during three days in January 1980, and synoptic analyses and numerical-model forecasts derived from them, are compared with conventional data and analyses from NMC's limited-area fine-mesh model (LFM). The collocated sounding comparison revealed significant errors, especially near the surface and the tropopause. Satellite-derived thermal gradients were found to be weak, and thickness-analysis difference fields to propagate eastward, suggesting that sounding errors are correlated with synoptic patterns. The same pattern of anomalies is seen in the model forecasts. More detailed determinations of the correlation detected here could be used to optimize the assimilation of satellite soundings to conventional data.

Koehler, T. L.↗
DOE OSTI2020

Global gross primary production simulated by three terrestrial biosphere models to analyse smoothing of limiting rates

Processed global terrestrial gross primary production (GPP) from three terrestrial biosphere models (TBMs). Two simulations were run with each model, one that selects the rate limiting process of photosynthesis based on the minimum of the potential rates (following Farquhar et al. 1980) and the other that uses quadratic smoothing between the potential rates (following Collatz et al. 1991). The three TBMs are: 1) the Energy Exascale Earth System Model (E3SM) land model (ELM) (release: v1.1.0) (Burrows et al., 2020), a coupled carbon, nitrogen, and phosphorus model with sun/shade big-leaf canopy photosynthesis scaling. 2) The Functionally Assembled Terrestrial Ecosystem Simulator (FATES, tag: sci.1.30.0_api.8.0.0) (Koven et al., 2019), coupled with the Community Land Model (CLM, version 5; Lawrence et al., 2019), a carbon-only vegetation demography model with multi-leaf and multi-canopy layers for scaling photosynthesis, and with a leaf area index (LAI) optimisation scheme. 3) The Sheffield Dynamic Global Vegetation Model (SDGVM, tag: Walkeretal2020_GCB), a carbon-only model with multi-leaf-layer canopy photosynthesis scaling and also with an LAI optimisation scheme (Walker et al., 2017; Woodward & Lomas, 2004). These data were generated to evaluate the effect of Collatz smoothing of limiting rates on simulated GPP across a range of terrestrial biosphere models. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures and .RDS files, a binary format specific to R and read with the 'readRDS' function.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Coupled Influence of Thermal Physiology and Biotic Interactions on the Distribution and Density of Ant Species along an Elevational Gradient

A fundamental tenet of biogeography is that abiotic and biotic factors interact to shape the distributions of species and the organization of communities, with interactions being more important in benign environments, and environmental filtering more important in stressful environments. This pattern is often inferred using large databases or phylogenetic signal, but physiological mechanisms underlying such patterns are rarely examined. We focused on 18 ant species at 29 sites along an extensive elevational gradient, coupling experimental data on critical thermal limits, null model analyses, and observational data of density and abundance to elucidate factors governing species’ elevational range limits. Thermal tolerance data showed that environmental conditions were likely to be more important in colder, more stressful environments, where physiology was the most important constraint on the distribution and density of ant species. Conversely, the evidence for species interactions was strongest in warmer, more benign conditions, as indicated by our observational data and null model analyses. Our results provide a strong test that biotic interactions drive the distributions and density of species in warm climates, but that environmental filtering predominates at colder, high-elevation sites. Such a pattern suggests that the responses of species to climate change are likely to be context-dependent and more specifically, geographically-dependent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling and Analysing the Impact of Heat Pump Water Heaters on Distribution Systems Using GridLAB-D

With the constant increase in energy demand, finding ways to reduce peak load and the energy-costs factors has become more imperative. Domestic water heating showcases a significant opportunity for such applications. Water heating is the second-highest energy consumer in the residential sector across the United States. Electric Water Heaters (EWHs), in particular, constitute nearly 43% of American household water heating energy consumption. Heat Pump Water Heater (HPWH), on the other hand, are an advanced water heating technology that has recently emerged in the United States residential market. The objectives of this work are to develop a HPWH model and build a case study that evaluates various penetration levels of HPWH in providing reduced peak load and cost-effective energy savings for both utilities and customers. The HPWH model was developed and integrated within the GridLAB-D simulation environment. The model behavior was then validated against a real HPWH unit at Portland State University (PSU). The case studies incorporated five HPWH penetration levels, ranging from 20% to 100%. In each case, EWHs were replaced with HPWHs. The results showed that a high penetration level of HPWHs can reduce the energy consumption on a distribution system to 38%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1985

Spectrophotometric and model-atmosphere analyses of the hot DO and DAO white dwarfs from the Palomar-Green survey

Recent optical and spectrophotometric observations of all currently known DAO and DO hot white dwarf candidates from the Palomar-Green Survey are presented. The optical observations were carried out using the Kitt Peak National Observatory Intensified Image Dissector Scanner (IIDS) system, the Multiple Mirror Telescope (MMT), and two photon-counting Reticon systems. Ultraviolet spectrophotometry was obtained using the International Ultraviolet Explorer (IUE) short-wavelength and long-wavelength cameras. The following spectroscopic subgroups were identified in the observations: the cool DO stars with spectra showing H I features together with He II + H blends; the hot DO stars, with spectra exhibiting weak He II (+H) lines; and hydrogen-rich DAO stars with broad H lines and sharp H II lines at 4686 A. A fourth subgroup of stars resembling PG 1159 with He at He II lines at 4686, and a C, N ion blend in the optical spectrum were also found. The spectroscopic data were analyzed in terms of a grid of hot, high-gravity LTE model atmospheres composed of a mixture of hydrogen and helium, and atmospheric parameters are deduced for each class of objects. On the basis of the model atmosphere analysis, the local space density of the DO stars is estimated to be 1.9-3.0 x 10 to the -7th per cubic pc, depending on the scale height.

Wesemael, F.↗
NASA NTRS2010

NASA Goddard Giovanni Support for YOTC

The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been twofold: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. In regards to the second challenge, it should be stressed that this problem will not be solved through the production and examination of one or a few high quality long-term records of fundamental quantities (e.g., SST, water vapor, cloud fraction). Rather, an alternative and more comprehensive paradigm is needed, one that integrates the multitude of applicable resources and measures of tropical convection in a manner that that can be better utilized by the diagnostic, modeling and forecasting communities to more completely and coherently focus on the problem.Because the goal of YOTC involves examining a scientifically complex, multi-scale process , rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO). The proposed dissemination framework for the YOTC satellite data archive is based on the Giovanni system. Giovanni is a web-based application developed by the NASA Goddard Earth Science (GES) Data and Information Service Center (DISC) that provides a simple and intuitive way to visualize, analyze, and access/download vast amounts of Earth science remote sensing data. A prototype YOTC Giovanni System (hereafter YOTC-GS) is in the process of being developed. YOTC-GS will provide access to level 2 (i.e. swath level data) and/or level 3 (i.e. gridded/mapped data) forms of satellite data, the choice or both depending on what is appropriate and relevant. The former is needed and better suited for detailed process examination, exploiting the highest temporal-spatial resolutions available and comparison to regional cloud-system resolving model / cloud resolving model (CSRM/CRM) model output. The latter is needed and more well suited for examination of phenomena, conditions and processes on large to global scales, and for comparisons to global model analyses, prediction and simulation output.

Ostrenga, Dana↗
DOE OSTI2018

Nonnegative tensor factorization for contaminant source identification

Unsupervised Machine Learning (ML) is becoming increasingly popular for solving various types of data analytics problems including feature extraction, blind source separation, exploratory analyses, model diagnostics, etc. In this work, we have developed a new unsupervised ML method based on Nonnegative Tensor Factorization (NTF) for identification of the original groundwater types (including contaminant sources) present in geochemical mixtures observed in an aquifer. Frequently, groundwater types with different geochemical signatures are related to different background and/or contamination sources. The characterization of groundwater mixing processes is a challenging but very important task critical for any environmental management project aiming to characterize the fate and transport of contaminants in the subsurface and perform contaminant remediation. This task typically requires solving complex inverse models representing groundwater flow and geochemical transport in the aquifer, where the inverse analysis accounts for available site data. Usually, the model is calibrated against the available data characterizing the spatial and temporal distribution of the observed geochemical types. Numerous different geochemical constituents and processes may need to be simulated in these models which further complicates the analyses. Additionally, the application of inverse methods may introduce biases in the analyses through the assumptions made in the model development process. Here, we substitute the model inversion with unsupervised ML analysis. The ML analysis does not make any assumptions about underlying physical and geochemical processes occurring in the aquifer. Our ML methodology, called NTFk, is capable of identifying (1) the unknown number of groundwater types (contaminant sources) present in the aquifer, (2) the original geochemical concentrations (signatures) of these groundwater types and (3) spatial and temporal dynamics in the mixing of these groundwater types. These results are obtained only from the measured geochemical data without any additional site information. In general, the NTFk methodology allows for interpretation of large high-dimensional datasets representing diverse spatial and temporal components such as state variables and velocities. NTFk has been tested on synthetic and real-world site three-dimensional datasets. Finally, the NTFk algorithm is designed to work with geochemical data represented in the form of concentrations, ratios (of two constituents; for example, isotope ratios), and delta notations (standard normalized stable isotope ratios).

58 GEOSCIENCES↗
NASA NTRS1992

LDEF geometry/mass model for radiation analyses

A three-dimensional geometry/mass model of LDEF is under development for ionizing radiation analyses. This model, together with ray tracing algorithms, is being programmed for use both as a stand alone code in determining three-dimensional shielding distributions at dosimetry locations and as a geometry module that can be interfaced with radiation transport codes.

Colborn, B. L.↗
DOE OSTI2019

Utah FORGE Phase Native State FALCON Model Files

The submission includes FALCON input file and mesh for the an initial pressure-temperature simulation, and a second set for pressure-temperature-displacement simulation. All simulations are steady state. Data and input for the FORGE Phase 2 native state model were compiled from historic and FORGE specific characterization efforts. The simulations look to find the in-situ pressure, temperature, and stress distributions in the vicinity of the Utah FORGE site. The purpose of the native state model was to establish a baseline for all other modeling analyses—so that the whole modeling team can start from a consistent set of conditions which makes for comparison of results more straightforward and meaningful. Requires the FALCON simulator which can be found in the "FALCON Simulator" link in the submission. Instructions for compiling and running FALCON can be found on the FORGE branch of the FALCON git repository in the README.

15 GEOTHERMAL ENERGY↗
NASA NTRS2018

Air Quality Modeling Using the NASA GEOS-5 Multispecies Data Assimilation System

The NASA Goddard Earth Observing System (GEOS) data assimilation system (DAS) has been expanded to include chemically reactive tropospheric trace gases including ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). This system combines model analyses from the GEOS-5 model with detailed atmospheric chemistry and observations from MLS (O3), OMI (O3 and NO2), and MOPITT (CO). We show results from a variety of assimilation test experiments, highlighting the improvements in the representation of model species concentrations by up to 50% compared to an assimilation-free control experiment. Taking into account the rapid chemical cycling of NO2 when applying the assimilation increments greatly improves assimilation skills for NO2 and provides large benefits for model concentrations near the surface. Analysis of the geospatial distribution of the assimilation increments suggest that the free-running model overestimates biomass burning emissions but underestimates lightning NOx emissions by 5-20%. We discuss the capability of the chemical data assimilation system to improve atmospheric composition forecasts through improved initial value and boundary condition inputs, particularly during air pollution events. We find that the current assimilation system meaningfully improves short-term forecasts (1-3 day). For longer-term forecasts more emphasis on updating the emissions instead of initial concentration fields is needed.

Keller, Christoph A.↗