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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optimization-Based Dynamic Voltage Support of Microgrids Using Energy Storage Systems

A microgrid network is characterized by a high R/X ratio, making the voltage more sensitive to active power changes compared to bulk power systems, where the voltage is regulated primarily by reactive power. Due to its sensitivity, voltage control approaches for microgrids should also consider the active power input coupling, making it very different from conventional power systems. Additionally, as the energy costs associated with active and reactive powers are different and the operational conditions of microgrids connected to active distribution systems vary over time, the ideal controller to provide voltage support must be flexible enough to handle these technical and operational constraints. This paper proposes a model predictive control approach to provide dynamic voltage support using energy storage systems. This approach uses a simplified predictive model of the system to solve the model predictive control problem. By proper selection of model predictive control weighting parameters, the quality of service provided can be adjusted to achieve the desired performance. A simulation study in MATLAB/Simulink validates the proposed approach for the Cordova, Alaska microgrid. Results show that the performance of the voltage support can be adjusted depending on the choice of weight and constraints of the controller.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2001

Membrane rejection of nitrogen compounds

Rejection characteristics of nitrogen compounds were examined for reverse osmosis, nanofiltration, and low-pressure reverse osmosis membranes. The rejection of nitrogen compounds is explained by integrating experimental results with calculations using the extended Nernst-Planck model coupled with a steric hindrance model. The molecular weight and chemical structure of nitrogen compounds appear to be less important in determining rejection than electrostatic properties. The rejection is greatest when the Donnan potential exceeds 0.05 V or when the ratio of the solute radius to the pore radius is greater than 0.8. The transport of solute in the pore is dominated by diffusion, although convective transport is significant for organic nitrogen compounds. Electromigration contributes negligibly to the overall solute transport in the membrane. Urea, a small organic compound, has lower rejection than ionic compounds such as ammonium, nitrate, and nitrite, indicating the critical role of electrostatic interaction in rejection. This suggests that better treatment efficiency for organic nitrogen compounds can be obtained after ammonification of urea.

NASA Discipline Life Support Systems↗
DOE OSTI2021

Detection of an Atmosphere on a Rocky Exoplanet

We report the detection of an atmosphere on a rocky exoplanet, GJ 1132 b, which is similar to Earth in terms of size and density. The atmospheric transmission spectrum was detected using Hubble WFC3 measurements and shows spectral signatures of aerosol scattering, HCN, and CH{sub 4} in a low mean molecular weight atmosphere. We model the atmospheric loss process and conclude that GJ 1132 b likely lost the original H/He envelope, suggesting that the atmosphere that we detect has been reestablished. We explore the possibility of H{sub 2} mantle degassing, previously identified as a possibility for this planet by theoretical studies, and find that outgassing from ultra-reduced magma could produce the observed atmosphere. In this way we use the observed exoplanet transmission spectrum to gain insights into magma composition for a terrestrial planet. The detection of an atmosphere on this rocky planet raises the possibility that the numerous powerfully irradiated super-Earth planets, believed to be the evaporated cores of sub-Neptunes, may, under favorable circumstances, host detectable atmospheres.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

Model Reduction for Control System Design

An approach and a technique for effectively obtaining reduced order mathematical models of a given large order model for the purposes of synthesis, analysis and implementation of control systems is developed. This approach involves the use of an error criterion which is the H-infinity norm of a frequency weighted error between the full and reduced order models. The weightings are chosen to take into account the purpose for which the reduced order model is intended. A previously unknown error bound in the H-infinity norm for reduced order models obtained from internally balanced realizations was obtained. This motivated further development of the balancing technique to include the frequency dependent weightings. This resulted in the frequency weighted balanced realization and a new model reduction technique. Two approaches to designing reduced order controllers were developed. The first involves reducing the order of a high order controller with an appropriate weighting. The second involves linear quadratic Gaussian synthesis based on a reduced order model obtained with an appropriate weighting.

Enns, D. F.↗
NASA NTRS1991

The least-squares mixing models to generate fraction images derived from remote sensing multispectral data

Constrained-least-squares and weighted-least-squares mixing models for generating fraction images derived from remote sensing multispectral data are presented. An experiment considering three components within the pixels-eucalyptus, soil (understory), and shade-was performed. The generated fraction images for shade (shade image) derived from these two methods were compared by considering the performance and computer time. The derived shade images are related to the observed variation in forest structure, i.e., the fraction of inferred shade in the pixel is related to different eucalyptus ages.

Shimabukuro, Yosio Edemir↗
DOE OSTI2018

The Improved Thermal Conductivity of a Potting Material for High-Power Fast Warm-Up Cathodes

With higher power, frequency and longer life of microwave tubes, cathode heater assembly is being modified to enhance the warm-up performance and reliability, which are governed by ceramics thermal conductivity, electrical resistivity and shrinkage. In present work, a potting material with a high thermal conductivity of 22.14 W/(m K) and low linear shrinkage of 5.5% was prepared using two kinds of alumina powders with different size and morphology. Aqueous slurries were produced for centrifugal casting. The highest solid loading slurries with 70 vol.% were obtained. Green body with relative density above 70% was easily made from slurries using centrifugal casting. Relative sintered density reached 86.75% maximum without any sintering aids. Rheological behavior of slurries, potting microstructure, sintering shrinkage and thermal conductivity were analyzed. Continuous particle distribution, series and parallel models were used to guide the powders proportion and explain the thermal conductivity. The potting material thermal conductivity experimental data agreed with the series and parallel models when the weight parameter ξ was between 0.3 and 0.5.

36 MATERIALS SCIENCE↗
DOE OSTI2023

NeRVI: Compressive neural representation of visualization images for communicating volume visualization results

We present NeRVI, a new deep-learning approach that compresses a large collection of visualization images generated from time-varying data for communicating volume visualization results. Based on an image-based implicit neural representation, our approach represents tens of thousands of high-resolution rendering images parametrized by different parameters via a hybrid model of multilayer perceptrons and convolutional neural networks. Here, our model predicts images and corresponding masks, and the masks are utilized for loss computation and network training to capture fine structural details and small components. In conjunction with model quantization and weight encoding, NeRVI yields highly compact compressive neural representations while preserving the image fidelity well. We demonstrate the effectiveness of NeRVI with isosurface rendering and direct volume rendering images generated from multiple data sets and compare NeRVI with other state-of-the-art deep learning-based (InSituNet, SIREN, NeRF, and NeRV) methods. Quantitative and qualitative results show that NeRVI provides an alternative solution that augments domain scientists' ability to manage, represent, and communicate scientific visualization output.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

IoT-based retrofit information diffusion in future smart communities

Community-scale building retrofits are not merely scaled-up versions of single-building retrofits. They involve complex challenges, such as reconciling individual interests with collective goals and managing the dynamic interplay between buildings through mechanisms like power grids and social connections. Internet of Things (IoT) connectivity holds the potential to leverage these interplays to balance individual and collective interests effectively in smart communities. One critical aspect of this interplay is information diffusion, which shapes how retrofit decisions spread among neighbors, influencing individual choices and ultimately impacting community-level retrofit outcomes. In other words, IoT-based smart devices automatically push tailored retrofit notifications to homeowners, which completely changes the format of information diffusion in the future. To investigate this influence by such information diffusion, the study used CityBES to simulate energy performance for different retrofits and applied an information diffusion model to analyze how decisions spread in a networked community of 192 buildings. The diffusion process was modeled on a weighted, directed network, capturing the dynamics of information flow and decision-making across 16 scenarios. Individual retrofit benefits were evaluated through payback years, while community-level retrofit outcomes were assessed using greenhouse gas (GHG) emission reductions. The results demonstrate that easier information diffusion among neighbors encourages households to prioritize retrofit measures that align with the majority’s optimal choices, even at the expense of individual financial benefits. In this case, such collective prioritization enhanced community-level retrofit performance, increasing GHG emission reductions by up to 29.4 %. However, this improvement came with trade-offs, as the average payback period for households extended by approximately 1.74 years. These findings highlight the potential of IoT-based information diffusion in future smart communities to coordinate individual interests with collective goals, ultimately accelerating community-level building retrofits.

Shu, Lei↗
DOE OSTI2017

Cadmium and Alzheimer’s disease mortality in U.S. adults: Updated evidence with a urinary biomarker and extended follow-up time

Cadmium has been linked to impaired cognitive function in adults and may cause behavioral, physiological and molecular abnormalities characteristic of Alzheimer's disease (AD) in animals. Evidence linking cadmium and AD in humans is limited, but supportive. In the most recent epidemiologic study, blood cadmium in U.S. adults was positively associated with elevated AD mortality 7–13 years later. The association between urinary cadmium – an arguably more appropriate biomarker for studying chronic diseases – and AD mortality has not yet been explored. Further study of cadmium and AD mortality in an independent population, with longer follow-up, and stratified by sex is also needed. We sought to answer these questions using the U.S. National Health and Nutrition Examination Survey (NHANES) (1999–2006 cycles) and NHANES III (interviews in 1988–1994) datasets, separately linked to AD mortality as of 2011. We used survey-weighted Cox regression models predicting age at AD death and adjusted for race/ethnicity, sex, smoking status, education and urinary creatinine. An interquartile range (IQR; IQR=0.51 ng/mL) increase in urinary cadmium was associated with 58% higher rate of AD mortality (hazard ratio (HR)=1.58, 95% CI: 1.20, 2.09. p-value=0.0009, mean follow-up: 7.5 years) in NHANES 1999–2006 participants. In contrast, in NHANES III participants, an IQR (IQR=0.78 ng/mL) increase in urinary cadmium was not associated with AD mortality (HR=0.85, 95% CI: 0.63, 1.17, p-value=0.31, mean follow-up: 13 years). Also in the NHANES III sample however, when the maximum follow-up time was restricted to 12.7 years (i.e. the same as NHANES 1999–2006 participants) and urinary creatinine adjustments were not made, urinary cadmium was associated with elevated AD mortality (HR=1.11, 95% CI: 1.02, 1.20, p-value=0.0086). Our study partially supported an association between cadmium and AD mortality, but the sensitivity of results to follow-up time and creatinine adjustments necessitate cautious interpretation of the association. Further studies, particularly those on toxicological mechanisms, are required to fully understand the nature of the “cadmium-AD mortality” association. - Highlights: • Urine Cd positively associated with Alzheimer’s disease mortality in NHANES 99-06. • Urine Cd NOT associated with AD in NHANES III, except under some conditions. • Results partly supportive of “Cd-AD mortality” link. • Inconsistency and insufficient toxicological data suggest cautious interpretation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Traffic-related air pollution and childhood obesity in an Italian birth cohort

Highlights: • Few studies analyse the association between air pollution and children BMI. • We modelled traffic-related air pollution with land-use regression models. • Inverse Probability Weighting (IPW) has been used to control for selection bias. • No association was found between pollutants and ponderal excess parameters. Air pollution is associated with several adverse health outcomes in children, such as respiratory illnesses and cognitive development impairment. There are suggestions of an effect of traffic-related air pollution on the occurrence of childhood obesity, but the results are not consistent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗
DOE OSTI2017

Histologic Subtype in Core Lung Biopsies of Early-Stage Lung Adenocarcinoma is a Prognostic Factor for Treatment Response and Failure Patterns After Stereotactic Body Radiation Therapy

Purpose: Stereotactic body radiation therapy (SBRT) has emerged as an effective treatment for early-stage lung cancer. The histologic subtype of surgically resected lung adenocarcinoma is recognized as a prognostic factor, with the presence of solid or micropapillary patterns predicting poor outcomes. We describe the outcomes after SBRT for early-stage lung adenocarcinoma stratified by histologic subtype. Methods and Materials: We identified 119 consecutive patients (124 lesions) with stage I to IIA lung adenocarcinoma who had undergone definitive SBRT at our institution from August 2008 to August 2015 and had undergone core biopsy. Histologic subtyping was performed according to the 2015 World Health Organization classification. Of the 124 tumors, 37 (30%) were a high-risk subtype, defined as containing a component of solid and/or micropapillary pattern. The cumulative incidences of local, nodal, regional, and distant failure were compared between the high-risk and non–high-risk adenocarcinoma subtypes using Gray's test, and multivariable-adjusted hazard ratios (HRs) were estimated from propensity score–weighted Cox regression models. Results: The median follow-up for the entire cohort was 17 months and for surviving patients was 21 months. The 1-year cumulative incidence of and adjusted HR for local, nodal, regional, and distant failure in high-risk versus non–high-risk lesions was 7.3% versus 2.7% (HR 16.8; 95% confidence interval [CI] 3.5-81.4), 14.8% versus 2.6% (HR 3.8; 95% CI 0.95-15.0), 4.0% versus 1.2% (HR 20.9; 95% CI 2.3-192.3), and 22.7% versus 3.6% (HR 6.9; 95% CI 2.2-21.1), respectively. No significant difference was seen with regard to overall survival. Conclusions: The outcomes after SBRT for early-stage adenocarcinoma of the lung correlate highly with histologic subtype, with micropapillary and solid tumors portending significantly higher rates of locoregional and metastatic progression. In this context, the histologic subtype determined from core biopsies is a prognostic factor and could have important implications for patient selection, adjuvant treatment, biopsy methods, and clinical trial design.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

How does urbanization affect CO 2 emissions of central heating systems in China? An assessment of natural gas transition policy based on nighttime light data

Understanding the different impacts of urbanization on sectorial carbon dioxide (CO 2 ) emissions at different spatial scales is of great importance for the evaluation of energy transition policies and reduction of environmental inequality. However, how urbanization affects the CO 2 emissions of central heating systems at high spatial resolution in China has not been fully studied before. Based on satellite-observed NPP-VIIRS nighttime light (NTL) data, we develop a 5 km x 5 km annual CO 2 emission inventory for coal boilers, thermal power plants (TPPs), and natural gas boilers in China's central heating systems for the period 2012-2017 by using the geographical and temporally weighted regression (GTWR) model. It is observed that nonurban areas generated 2-4 times the CO 2 emissions of coal boilers in urban areas. The largest increments of CO 2 emissions of gas boilers are observed in urban areas of the eastern (6.80 times) and central regions (2.86 times) in 2013-2014, due to the clean heating policy in the "2 + 26" cities in China. The effects of urbanization on CO 2 emissions from natural gas boilers are approximately 2-3 times those of coal boilers, and the differences are largest in western cities with only minor differences in northeastern cities. Overall, our results will aid in designing low-carbon development goals and provide micro-level information on central heating facilities in urbanized and less developed regions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Macrovoid resolved simulations of transport through HPRO relevant membrane geometries

Modeling the transport properties such as diffusivity and permeability of high pressure reverse osmosis (HPRO) membranes is critical for the selection and manufacture of membranes suitable for operation under high pressure. These properties can be significantly affected by the changes in heterogeneous pore structures due to compaction. Here, the modeling platform presented in this work resolves the two scale porosity in HPRO relevant membranes. A synthetic membrane geometry is constructed based on available experimental visualizations of pore structures. The simulations directly capture the flow channeling that results from a combination of material properties and geometric features of the macrovoids. A parametric study is presented to account for the transition of flow characteristics from a material governed regime to a macrovoid governed regime. Permeability of the membrane is evaluated using the simulation data and compared with an existing model that scales with the square of tortuosity over a range of material properties. The model is found to perform well under a narrow range of tortuosity while deviating from the calculated permeabilities at extreme conditions. The effective permeability of the membrane is found to vary by at least two orders of magnitude between the two flow regimes. It is also observed that tortuosity is a bounded property with its upper limit determined by the macrovoid geometry. Consequently, the tortuosity based correlations fail near a flow regime that is mainly governed by the macrovoids. The modeled permeability can be more than an order of magnitude smaller than the simulation result. A new model based on flux-weighted porosity of a membrane is introduced and its correlation with tortuosity is studied. The model agrees with the simulated data as, in addition to tortuosity, it also accounts for the flux partition within and outside the flow channels. Such correlations enable extending the existing understanding of flow characteristics to enhance predictability of porous media models.

42 ENGINEERING↗
DOE OSTI2021

Human Mobility to Parks Under the COVID-19 Pandemic and Wildfire Seasons in the Western and Central United States

In 2020, people's health suffered a great crisis under the dual effects of the COVID-19 pandemic and the extensive, severe wildfires in the western and central United States. Parks, including city, national, and cultural parks, offer a unique opportunity for people to maintain their recreation behaviors following the social distancing protocols during the pandemic. However, massive forest wildfires in western and central US, producing harmful toxic gases and smoke, pose significant threats to human health and affect their recreation behaviors and mobility to parks. In this study, we employed the geographically and temporally weighted regression (GTWR) Models to investigate how COVID-19 and wildfires jointly shaped human mobility to parks, regarding the number of visits per capita, dwell time, and travel distance to parks, during June - September 2020. We detected strong correlations between visitations and COVID-19 incidence in southern Montana, western Wyoming, Colorado, and Utah before August. However, the pattern was weakened over time, indicating the decreasing trend of the degree of concern regarding the pandemic. Moreover, more park visits and lower dwell time were found in parks further away from wildfires and less air pollution in Washington, Oregon, California, Colorado, and New Mexico, during the wildfire season, suggesting the potential avoidance of wildfires when visiting parks. This study provides important insights on people's responses in recreation and social behaviors when facing multiple severe crises that impact their health and wellbeing, which could support the preparation and mitigation of the health impacts from future pandemics and natural hazards.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Lattice thermal conductivity of nanograined half-Heusler solid solutions

We report a phenomenological model of atomic weight, lattice constant, temperature, and grain size to calculate the high-temperature lattice thermal conductivity of nanograined solid solutions. The theoretical treatment developed here is reasonably consistent with the experimental results of n-type MNiSn and p-type MCoSb alloys, where M is the combination of Hf, Zr, and Ti. For disordered half-Heusler alloys with moderated grain sizes, we predict that the reduction in lattice thermal conductivity due to grain boundary scattering is independent of the scattering parameter, which characterizes the phonon scattering cross section of point defects. In addition, the lattice thermal conductivity falls off with temperature as T{sup –1∕2} around the Debye temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Reducing the negative human-health impacts of bioenergy crop emissions through region-specific crop selection

An expected global increase in bioenergy-crop cultivation as an alternative to fossil fuels will have consequences on both global climate and local air quality through changes in biogenic emissions of volatile organic compounds (VOCs). While greenhouse gas emissions may be reduced through the substitution of next-generation bioenergy crops such as eucalyptus, giant reed, and switchgrass for fossil fuels, the choice of species has important ramifications for human health, potentially reducing the benefits of conversion due to increases in ozone (O₃) and fine particulate matter (PM₂̣₅) levels as a result of large changes in biogenic emissions. Using the Community Earth System Model we simulate the conversion of marginal and underutilized croplands worldwide to bioenergy crops under varying future anthropogenic emissions scenarios. A conservative global replacement using high VOC-emitting crop profiles leads to modeled population-weighted O₃ increases of 5–27 ppb in India, 1–9 ppb in China, and 1–6 ppb in the United States, with peak PM₂̣₅ increases of up to 2 μgm⁻³. We present a metric for the regional evaluation of candidate bioenergy crops, as well as results for the application of this metric to four representative emissions profiles using four replacement scales (10–100% maximum estimated available land). Finally, we assess the total health and climate impacts of biogenic emissions, finding that the negative consequences of using high-emitting crops could exceed 50% of the positive benefits of reduced fossil fuel emissions in value.

09 BIOMASS FUELS↗