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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States

While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across various regions and operating conditions to address knowledge gaps in total cost of ownership and operational range. First, real-world energy cost savings were determined: MHD fleets should experience energy cost savings each year from 2021 to 2035, regardless of vehicle platform, with the greatest savings seen in transit buses (up to USD 4459 annually) and HD trucks (up to USD 3284 annually). Second, to help fleets across various geographies throughout the U.S. assess the suitability of EVs for their year-round operating needs, operational range was modeled using the XGBoost algorithm (R2: 70%) given 22 input features relevant to vehicle efficiency. Finally, this paper recommends (1) that MHD fleets apply energy-saving practices to minimize the impacts of cold temperatures and high congestion levels on vehicle efficiency and range, and (2) that local hauling fleets select trucks with a nominal range nearly double the expected maximum daily range to account for range losses under local, urban driving conditions.

Qiu, Yin (ORCID:0009000900948794)↗
DOE OSTI2020

Lyapunov and Clearing Timescales in Planetary Chaotic Zones

Debris disks in planetary systems are known to possess gaps “opened” by planets in their close-to-coorbital neighborhoods; the gaps are free from low-mass material such as planetesimals. We consider the escape process of the initially zero-eccentric particles from the gap zone in a scenario consisting of two basic consequent stages: (1) the particle orbit's eccentricity is inflated, while its specific energy is relatively constant, and (2) the particle orbit's semimajor axis is inflated, while its specific angular momentum is relatively constant. During the first stage, the chaotic transport (diffusion) proceeds along the “staircase” of (p + 1):p (with integer p ≫ 1) overlapping particle–planet resonances, and during the second stage, it proceeds along the p:1 particle–planet resonance staircase. A specialized two-dimensional area-preserving map (a “tokamap” version) is derived to describe the first stage, while a multiharmonic Kepler map theory is used to describe the second stage. We derive the μ (mass parameter) scaling for the clearing timescale in the planetary chaotic zone. At small μ, it turns out to be inverse-quadratic in μ. The μ scaling for the Lyapunov timescale inside the gap is also derived. The derived scalings are in qualitative agreement with available numerical-experimental data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1983

Ionic composition of the earth's radiation belts

Several different ion species have been positively identified in the earth's radiation belts. Besides protons, there are substantial fluxes of helium, carbon and oxygen ions, and there are measurable quantities of even heavier ions. European, American and Soviet space experimenters have reported ion composition measurements over wide ranges of energies: at tens of keV (ring-current energies) and below, and at hundreds of keV and above. There is still a gap in the energy coverage from several tens to several hundreds of keV where little observational data are available. In this review emphasis is placed on the radiation belt ionic structure above 100 keV. Both quiet time conditions and geomagnetic storm periods are considered, and comparison of the available space observations is made with theoretical analysis of geomagnetically trapped ion spatial, energy and charge state distributions.

Spjeldvik, W. N.↗
NASA NTRS1988

KAM (Knowledge Acquisition Module): A tool to simplify the knowledge acquisition process

Analysts, knowledge engineers and information specialists are faced with increasing volumes of time-sensitive data in text form, either as free text or highly structured text records. Rapid access to the relevant data in these sources is essential. However, due to the volume and organization of the contents, and limitations of human memory and association, frequently: (1) important information is not located in time; (2) reams of irrelevant data are searched; and (3) interesting or critical associations are missed due to physical or temporal gaps involved in working with large files. The Knowledge Acquisition Module (KAM) is a microcomputer-based expert system designed to assist knowledge engineers, analysts, and other specialists in extracting useful knowledge from large volumes of digitized text and text-based files. KAM formulates non-explicit, ambiguous, or vague relations, rules, and facts into a manageable and consistent formal code. A library of system rules or heuristics is maintained to control the extraction of rules, relations, assertions, and other patterns from the text. These heuristics can be added, deleted or customized by the user. The user can further control the extraction process with optional topic specifications. This allows the user to cluster extracts based on specific topics. Because KAM formalizes diverse knowledge, it can be used by a variety of expert systems and automated reasoning applications. KAM can also perform important roles in computer-assisted training and skill development. Current research efforts include the applicability of neural networks to aid in the extraction process and the conversion of these extracts into standard formats.

Gettig, Gary A.↗
NASA NTRS1993

Radiation effects in Ga(0.47)In(0.53)As solar cells

The effects of irradiating Ga(0.47)In(0.53)As p-i-n junctions with 1 MeV electrons were measured using Deep Level Transient Spectroscopy (DLTS) and both dark and illuminated (1 sun, air mass zero (AM0)) current-voltage (I-V) measurements. The I-V measurements were made over the range 100K less than T less than 350K. Temperature coefficients of the Ga(0.47)In(0.53)As photovoltaic parameters are presented which follow the same general behavior as other solar cell materials (e.g. Si and GaAs). Fits of the dark I-V data to the two term diode equation before irradiation were satisfactory, yielding an estimated band-gap energy of 0.79 eV. The recombination component of the dark current was found to increase linearly with fluence. DLTS detected two radiation-induced defect levels one shallow (E(sub c)-0.10 eV) and one near mid-gap (E(sub c)-0.29 eV), and it is the near mid-gap level which is expected to be the cause of the dark current increase. The radiation-induced degradation of the open circuit voltage is shown to be accurately predicted from the dark I-V measurements. The degradation of the open circuit voltage dominated the radiation response of the photovoltaic parameters while the short circuit current was only moderately degraded. This behavior is qualitatively explained in terms of the base thickness and dopant level. Appropriate changes in the device structure are suggested which should increase the radiation resistance. Isochronal thermal annealing induced recovery in the photovoltaic parameters at approximately 400K, coinciding with an annealing stage of the near mid-gap defect level.

Walters, R. J.↗
NASA NTRS1995

Large Scale Surface Radiation Budget from Satellite Observation

During the current reporting period, the focus of our work was on preparing and testing an improved version of our Surface Radiation Budget algorithm for processing the ISCCP D1 data routinely at the SRB Satellite Data Analysis Center (SDAC) at NASA Langley Research Center. The major issues addressed are related to gap filling and to testing whether observations made from ERBE could be used to improve current procedures of converting narrowband observations, as available from ISCCP, into broadband observations at the TOA. The criteria for selecting the optimal version are to be based on results of intercomparison with ground truth.

Pinker, R. T.↗
NASA NTRS2004

Advanced Life Support Systems

This presentation is planned to be a 10-15 minute "catalytic" focused presentation to be scheduled during one of the working sessions at the TIM. This presentation will focus on Advanced Life Support technologies key to future human Space Exploration as outlined in the Vision, and will include basic requirements, assessment of the state-of-the-art and gaps, and include specific technology metrics. The presentation will be technical in character, lean heavily on data in published ALS documents (such as the Baseline Values and Assumptions Document) but not provide specific technical details or build to information on any technology mentioned (thus the presentation will be benign from an export control and a new technology perspective). The topics presented will be focused on the following elements of Advanced Life Support: air revitalization, water recovery, waste management, thermal control, habitation systems, food systems and bioregenerative life support.

Barta, Daniel J.↗
NASA NTRS2017

Cross-Disciplinarity in the Advance of Antarctic Ecosystem Research

The biodiversity, ecosystem services and climate variability of the Antarctic continent, and the Southern Ocean are major components of the whole Earth system. Antarctic ecosystems are driven more strongly by the physical environment than many other marine and terrestrial ecosystems. As a consequence, to understand ecological functioning, cross-disciplinary studies are especially important in Antarctic research. The conceptual study presented here is based on a workshop initiated by the Research Programme Antarctic Thresholds - Ecosystem Resilience and Adaption of the Scientific Committee on Antarctic Research, which focused on challenges in identifying and applying cross-disciplinary approaches in the Antarctic. Novel ideas, and first steps in their implementation, were clustered into eight themes, ranging from scale problems, risk maps, organism and ecosystem responses to multiple environmental changes, to evolutionary processes. Scaling models and data across different spatial and temporal scales were identified as an overarching challenge. Approaches to bridge gaps in the research programmes included multi-disciplinary monitoring, linking biomolecular findings and simulated physical environments, as well as integrative ecological modelling. New strategies in academic education are proposed. The results of advanced cross-disciplinary approaches can contribute significantly to our knowledge of ecosystem functioning, the consequences of climate change, and to global assessments that ultimately benefit humankind.

Scaling↗
NASA NTRS2019

NASA Electronic Parts and Packaging (NEPP) Program Status and Technology Investments Overview

The presentation provides an updated, high-level overview of the NEPP Program. The latest organizational chart is presented that shows the names of the Program and Assistant Program Managers. Additionally, the recent work that is on-going with the updating of several NASA NPDs, NPRs and technical standards is reviewed. Internal and external organizational interfaces are described. Finally, the current technology focus areas are described. These areas include passives, wide-band gap power devices, processor units (CPUs and GPUs), 2.5D and 3D device architectures, memories, and data analytics.

NEPAG↗
NASA NTRS2022

MLtool: Universal Supervised Machine Learning Tool to Model Tabulated Data

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine learning↗
NASA NTRSDate not supplied

Quantifying Uncertainty in Particle Size Distribution Parameters Inferred from SAGE III/ISS Extinction Spectra

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on their microphysical properties such as particle size distribution (PSD). The PSD is a mathematical description of the relative abundance of different sized particles within a sampling volume. If the PSD is accurately known then other key modeling parameters (e.g., surface area density) can be derived. Occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts failed to address two key issues with this methodology: 1. The measurement uncertainty was not accounted for; 2. They assumed the PSDs to be single-mode only, while “real-world” PSDs are predominantly bi-modal. Accounting for both issues in the retrieval will yield an expanded solution space to the inferred PSD parameters; the question is “by how much?” To address this knowledge gap, we propose to carry out a series of simulations and, for every valid SAGE III/ISS data point, determine the range of PSD parameters that yield extinction spectra that are indistinguishable from the SAGE III/ISS data, within the limits of the reported uncertainty. Further, we will expand the solution space, for the first time, to include bimodal distributions. The results of this work will advance Earth system modeling/prediction capability through identifying the uncertainty of PSD parameter estimates using SAGE III/ISS data. The key benefits of this study over previous studies are twofold: 1. we will provide PSD estimates that include bimodal distributions in the solution space, 2. we will provide an uncertainty estimate for these parameters. The results of this study may be used directly in current and future climate and chemistry models.

SAGE III/ISS↗
NASA NTRS2022

MLtool Python Code

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine Learning↗
DOE OSTI2020

F2 extraction from Inclusive Cross Section Data at Large Bjorken x

While we have made significant progress in probing nuclear structure at low Bjorken x and high Q 2 , we still have gaps in our knowledge regarding the high Bjorken x and intermediate Q 2 kinematic region. This is not an accident, but instead due to the diffculty in assessing the non-perturbative region of nuclear physics. For this reason, the E12-10-002 experiment measured the H(e,e') and D(e,e') inclusive cross section in the resonance region. This will allow us to study both perturbative and non-perturbative physics in a kinematic region that lacks precision measurements. Measurements were made up to a Bjorken x of 0.99 and Q 2 up to 17 GeV 2 . These measurements are made using the independent HMS and SHMS spectrometers at the upgraded beam energy of 11 GeV in Hall C at Jefferson Lab. Further, we extract F 2 structure functions from the measured data and study the effect of their inclusion in a global Parton Distribution Function analysis.

Araiza Gonzalez, Fernando↗
NASA NTRSDate not supplied

Development and Initial Validation of HFBP-EM Short-Form Surveys

The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite includes self-report surveys designed to assess Behavioral Medicine (BMed) and Team risks for future exploration class missions. Survey data was collected during the Human Exploration Research Analog (HERA) Campaign 4 (C4), HERA Campaign 5 (C5), and during SIRIUS19 missions in the Russian Ground Based Experiment Complex, NEK. Crew time in spaceflight analogs and in spaceflight is typically limited. Extensive self-report surveys can be a significant burden to participants and are not operationally acceptable for spaceflight. The purpose of this project was to comprehensively assess the reliability and validity of the standard-length HFBP-EM surveys, identify acceptable short forms to administer during HERA C6, examine initial validation evidence for the proposed short form measures, and identify key measurement gaps in HFBP-EM coverage. In this presentation, we will report reliability and validity metrics of standard form data, describe the proposed new short forms, and present initial psychometric analyses supporting the use of these short forms.

S T Bell↗
DOE OSTI2020

Fine Structures in the Main Sequence Revealed by Gaia Data Release 2

The Hertzsprung–Russell diagram (HRD) is fully examined using the Fourier analysis. This work shows more stars are above the gap in the lower main sequence than below it, and this implies that stars spend more time above the gap while they undergo variability associated with the {sup 3}He instability. The enhanced HRD also shows the width of the gap is not linear and depends on the G{sub BP}−G{sub RP} color up until G{sub BP}−G{sub RP}=2.7. Beyond this color limit, the gap is hardly seen. Besides, a new low density region is revealed for the first time centered at M {sub G} ≈ 10.7 and G {sub BP} − G {sub RP} ≈ 2.8, which is below the lower right corner of the gap. This work also shows that the main sequence appears to have fine stripes where stellar densities are relatively low or high compared to their adjacent regions on the main sequence. These stripes can be seen throughout the main sequence of stars redder than G {sub BP} − G {sub RP} = 0.8 and are not limited to any specific color or spectral type. Slopes of these features are different from the main sequence, but are pretty consistent throughout the main sequence, with a few exceptions. We are perplexed by these new features, but the complexities of stellar atmospheric features and opacities of dwarfs may have caused these patterns.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2013

The Collection 6 'dark-target' MODIS Aerosol Products

Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time as we have introduced algorithm changes, we have also accounted for upstream changes including: new instrument calibration, revised land-sea masking, and changed cloud masking. Upstream changes also impact the coverage and global statistics of the retrieved AOD. Although our responsibility is to the DT code and products, we have also added a product that merges DT and DB product over semi-arid land surfaces to provide a more gap-free dataset, primarily for visualization purposes. Preliminary validation shows that compared to surface-based sunphotometer data, the C6, Level 2 (along swath) DT-products compare at least as well as those from C5. C6 will include new diagnostic information about clouds in the aerosol field, including an aerosol cloud mask at 500 m resolution, and calculations of the distance to the nearest cloud from clear pixels. Finally, we have revised the strategy for aggregating and averaging the Level 2 (swath) data to become Level 3 (gridded) data. All together, the changes to the DT algorithms will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. Changes in calibration will have more impact to Terras time series, especially over land. This will result in a significant reduction in artificial differences in the Terra and Aqua datasets, and will stabilize the MODIS data as a target for AEROCOM studie

Aerosol retrieval algorithms↗
NASA NTRS2016

Mechanotransductive Regulation of Gap-Junction Activity Between MLO-Y4 Osteocyte-Like and MC3T3-E1 Osteoblast-Like Cells in Three-Dimensional Co-Culture.

Cell and animal studies conducted onboard the International Space Station and formerly on Shuttle flights have provided groundbreaking data illuminating the deleterious biological response of bone to mechanical unloading. However the intercellular communicative mechanisms associated with the regulation of bone synthesis and bone resorption cells are still largely unknown. Connexin-43 (CX43), a gap junction protein, is hypothesized to play a significant role in osteoblast and osteocyte signaling. The purpose of this investigation was to evaluate within a novel three-dimensional microenvironment how the osteocyte-osteoblast gap-junction expression changes when cultures are exposed to exaggerated mechanical load. MLO-Y4 osteocyte-like cells were cultured on a 3D-Biotek polystyrene insert and placed in direct contact with an MC3T3-E1 pre-osteoblast co-cultured monolayer and exposed to 48 h of mechanical stimulation (pulsatile fluid flow (PFF) or monolayer cyclic stretch (MCS)) then evaluated for viability, proliferation, metabolism, and CX43 expression. Mono-cultured MLO-Y4 and MC3T3-E1 control experiments were conducted under PFF and MCS stimulation to observe how strain application stimuli (PFF cell membrane shear or MCS cell focal adhesion/attachment loading) initiates different signaling pathways or downstream regulatory controls. TotalLive cell count, viability and metabolic reduction (Trypan Blue, LIVEDead and Alamar Blue analysis respectively) indicate that mechanical activation of MC3T3-E1 cells inhibits proliferation while maintaining an average 1.04E4 reductioncell metabolic rate, *p0.05 n4. MLO-Y4s in monolayer culture increase in number when exposed to MCS loading but the percent of live cells within the population is low (46.3 total count, *p0.05 n4), these results may indicate an apoptotic signaling cascade. PFF stimulation of the three-dimensional co-cultures elicits a universal increase in CX43 in MLO-Y4 and MC3T3-E1 cells, illustrated by immunohistological observation. Increased CX43 expression is also observed with the three-dimensional co-cultures with MC3T3-E1 MCS stimulation but the increased gap-junction protein presence was limited to the osteoblast-osteocyte interface region. Previously reported PCR evaluation of osteogenic markers further corroborate that the co-cultured populations communicative networks play a role in translating mechanical signals to molecular messaging. These findings suggests an osteocyte-osteoblast gap-junction signaling feedback mechanism may regulate mechanotransduction of apoptosis initiation and transcription of cytokine signaling proteins responsible for stem cell niche recruitment much more directly than previously believed.

mechanical loading↗
NASA NTRS2016

Mechanotransductive Regulation of Gap-Junction Activity Between MLO-Y4 Osteocyte-Like and MC3T3-E1 Osteoblast-Like Cells in Three-Dimensional Co-Culture

Cell and animal studies conducted onboard the International Space Station and formerly on Shuttle flights have provided groundbreaking data illuminating the deleterious biological response of bone to mechanical unloading. However the intercellular communicative mechanisms associated with the regulation of bone synthesis and bone resorption cells are still largely unknown. Connexin-43 (CX43), a gap junction protein, is hypothesized to play a significant role in osteoblast and osteocyte signaling. The purpose of this investigation was to evaluate within a novel three-dimensional microenvironment how the osteocyte-osteoblast gap-junction expression changes when cultures are exposed to exaggerated mechanical load. MLO-Y4 osteocyte-like cells were cultured on a 3D-Biotek polystyrene insert and placed in direct contact with an MC3T3-E1 pre-osteoblast co-cultured monolayer and exposed to 48 h of mechanical stimulation (pulsatile fluid flow (PFF) or monolayer cyclic stretch (MCS)) then evaluated for viability, proliferation, metabolism, and CX43 expression. Mono-cultured MLO-Y4 and MC3T3-E1 control experiments were conducted under PFF and MCS stimulation to observe how strain application stimuli (PFF cell membrane shear or MCS cell focal adhesionattachment loading) initiates different signaling pathways or downstream regulatory controls. TotalLive cell count, viability and metabolic reduction (Trypan Blue, LIVEDead and Alamar Blue analysis respectively) indicate that mechanical activation of MC3T3-E1 cells inhibits proliferation while maintaining an average 1.04E4 reductioncell metabolic rate, *p0.05 n4. MLO-Y4s in monolayer culture increase in number when exposed to MCS loading but the percent of live cells within the population is low (46.3 total count, *p0.05 n4), these results may indicate an apoptotic signaling cascade. PFF stimulation of the three-dimensional co-cultures elicits a universal increase in CX43 in MLO-Y4 and MC3T3-E1 cells, illustrated by immunohistological observation. Increased CX43 expression is also observed with the three-dimensional co-cultures with MC3T3-E1 MCS stimulation but the increased gap-junction protein presence was limited to the osteoblast-osteocyte interface region. Previously reported PCR evaluation of osteogenic markers further corroborate that the co-cultured populations communicative networks play a role in translating mechanical signals to molecular messaging. These findings suggests an osteocyte-osteoblast gap-junction signaling feedback mechanism may regulate mechanotransduction of apoptosis initiation and transcription of cytokine signaling proteins responsible for stem cell niche recruitment much more directly than previously believed.

Juran, C. M.↗