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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Preliminary Assessment of Variable Speed Power Turbine Technology on Civil Tiltrotor Size and Performance

A Large Civil Tiltrotor (LCTR) conceptual design was developed as part of the NASA Heavy Lift Rotorcraft Systems Investigation in order to establish a consistent basis for evaluating the benefits of advanced technology for large tiltrotors. The concept has since evolved into the second-generation LCTR2, designed to carry 90 passengers for 1,000 nm at 300 knots, with vertical takeoff and landing capability. This paper performs a preliminary assessment of variable-speed power turbine technology on LCTR2 sizing, while maintaining the same, advanced technology engine core. Six concepts were studied; an advanced, single-speed engine with a conventional power turbine layout (Advanced Conventional Engine, or ACE) using a multi-speed (shifting) gearbox. There were five variable-speed power turbine (VSPT) engine concepts, comprising a matrix of either three or four turbine stages, and fixed or variable guide vanes; plus a minimum weight, twostage, fixed-geometry VSPT. The ACE is the lightest engine, but requires a multi-speed (shifting) gearbox to maximize its fuel efficiency, whereas the VSPT concepts use a lighter, fixed-ratio gearbox. The NASA Design and Analysis of Rotorcraft (NDARC) design code was used to study the trades between rotor and engine efficiency and weight. Rotor performance was determined by Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics (CAMRAD II), and engine performance was estimated with the Numerical Propulsion System Simulation (NPSS). Design trades for the ACE vs. VSPT are presented in terms of vehicle gross and empty weight, propulsion system weight and mission fuel burn for the civil mission. Because of its strong effect on gearbox weight and on both rotor and engine efficiency, rotor speed was chosen as the reference design variable for comparing design trades. Major study assumptions are presented and discussed. Impressive engine power-to-weight and fuel efficiency reduced vehicle sensitivity to propulsion system choice. The 10% weight penalty for multi-speed gearbox was more significant than most engine technology weight penalties to the vehicle design because drive system weight is more than two times engine weight. Based on study assumptions, fixed-geometry VSPT concept options performed better than their variable-geometry counterparts. Optimum design gross weights varied 1% or less and empty weights less than 2% among the concepts studied, while optimum fuel burns varied up to 5%. The outcome for some optimum configurations was so unexpected as to recommend a deeper look at the underlying technology assumptions.

Snyder, Christopher A.↗
NASA NTRS2014

Creating a Test Validated Structural Dynamic Finite Element Model of the Multi-Utility Technology Test Bed Aircraft

Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of Multi Utility Technology Test Bed, X-56A, aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of X-56A. The ground vibration test validated structural dynamic finite element model of the X-56A is created in this study. The structural dynamic finite element model of the X-56A is improved using a model tuning tool. In this study, two different weight configurations of the X-56A have been improved in a single optimization run.

structural dynamic model tuning↗
NASA NTRS2006

CO Signatures in Subtropical Convective Clouds and Anvils during CRYSTAL-FACE: An Analysis of Convective Transport and Entrainment using Observations and a Cloud-Resolving Model

Convective systems are an important mechanism in the transport of boundary layer air into the upper troposphere. The Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) campaign, in July 2002, was developed as a comprehensive atmospheric mission to improve knowledge of subtropical cirrus systems and their roles in regional and global climate. In situ measurements of carbon monoxide (CO), water vapor (H2Ov), and total water (H2Ot) aboard NASA's WB-57F aircraft and CO aboard the U.S. Navy's Twin Otter aircraft were obtained to study the role of convective transport. Three flights sampled convective outflow on 11, 16 and 29 July found varying degrees of CO enhancement relative to the free troposphere. A cloud-resolving model used the in situ observations and meteorological fields to study these three systems. Several methods of filtering the observations were devised here using ice water content, relative humidity with respect to ice, and particle number concentration as a means to statistically sample the model results to represent the flight tracks. A weighted histogram based on ice water content observations was then used to sample the simulations for the three flights. In addition, because the observations occurred in the convective outflow cirrus and not in the storm cores, the model was used to estimate the maximum CO within the convective systems. In general, anvil-level air parcels contained an estimated 20-40% boundary layer air in the analyzed storms.

Lopez, Jimena P.↗
NASA NTRS2006

CO Signatures in Subtropical Convective Clouds and Anvils During CRYSTAL-FACE: An Analysis of Convective Transport and Entertainment Using Observations and a Cloud-Resolving Model

Convective systems are an important mechanism in the transport of boundary layer air into the upper troposphere. The Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) campaign, in July 2002, was developed as a comprehensive atmospheric mission to improve knowledge of subtropical cirrus systems and their roles in regional and global climate. In situ measurements of carbon monoxide (CO), water vapor (H20v), and total water (H20t) aboard NASA's . WB-57F aircraft and CO aboard the U.S. Navy's Twin Otter aircraft were obtained to study the role of convective transport. Three flights sampled convective outflow on 11, 16 and 29 July found varying degrees of CO enhancement relative to the fiee troposphere. A cloud-resolving model used the in situ observations and meteorological fields to study these three systems. Several methods of filtering the observations were devised here using ice water content, relative humidity with respect to ice, and particle number concentration as a means to statistically sample the model results to represent the flight tracks. A weighted histogram based on ice water content observations was then used to sample the simulations for the three flights. In addition, because the observations occurred in the convective outflow cirrus and not in the storm cores, the model was used to estimate the maximum CO within the convective systems. In general, anvil-level air parcels contained an estimated 20-40% boundary layer air in the analyzed storms.

Lopez, Jimena P.↗
DOE OSTI2023

Entropy-driven Optimal Sub-sampling of Fluid Dynamics for Developing Machine-learned Surrogates

Optimal sub-sampling of large datasets from fluid dynamics simulations is essential for training reduced-order machine learned models. A method using Shannon entropy was developed to weight flow features according to their level of information content, such that the most informative features can be extracted and used for training a surrogate model. The method is demonstrated in the canonical flow over a cylinder problem simulated with OpenFOAM. Both time-independent predictions and temporal forecasting were investigated as well as two types of prediction targets: local per-grid-point predictions and global per-time-step predictions. When tested on training a surrogate model, results indicate that our entropy-based sampling method typically outperforms random sampling and yields more reproducible results in less iterations. Finally, the method was used to train a surrogate model for modeling turbulence in magnetohydrodynamic flows, which revealed various challenges and opportunities for future research.

Brewer, Wes↗
DOE OSTI2025

Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach

Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing. Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.

Estela‐García, John E. [Polymer Engineering Center↗
DOE OSTI2019

Impact of climate change on European winter and summer flood losses

Climate change is expected to alter European floods and associated economic losses in various ways. Here we investigate the impact of precipitation change on European average winter and summer financial losses due to flooding under a 1.5 °C warming scenario (reflecting a projected climate in the year 2115 according to RCP2.6)and for a counterfactual current-climate scenario where the climate has evolved without anthropogenic influence (reflecting a climate corresponding to pre-industrial conditions). Climate scenarios were generated with the Community Atmospheric Model (CAM)version 5. For each scenario, we derive a set of weights that when applied to the current climate's precipitation results in a climatology that approximates that of the scenario. We apply the weights to annual losses from a well-calibrated (to the current climate)flood loss model that spans 50,000 years and re-compute the average annual loss to assess the impact of precipitation changes induced by anthropogenic climate change. The method relies on a large stochastic set of physically based flood model simulations and allows quick assessment of potential loss changes due to change in precipitation based on two statistics, namely total precipitation, and total precipitation of very wet days (defined here as the total precipitation of days above the 95th percentile of daily precipitation). We compute the statistics with the raw CAM precipitation and bias-corrected precipitation. Our results show that for both raw and bias-corrected statistics i)average flood loss in Europe generally tend to increase in winter and decrease in summer for the future scenario, and consistent with that change we also show that ii)average flood losses have increased (decreased)for winter (summer)from pre-industrial conditions to the current day. Finally, the magnitude of the change varies among scenarios and statistics chosen.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Compound pulse characteristics of a heterogeneous composite scintillator in a gamma-ray field

An important aspect of radiation detection in scintillators is the time dependence of emitted fluorescence, which results in characteristic measured pulse shape. In some materials, a relatively strong dependence of the scintillation pulse shape on stopping power exists, which can provide reliable identification of the incident particle. An alternative method to realize particle identification is by combining materials with different fluorescence lifetimes into heterogeneous structures. Such composite scintillators derive their properties from both the constituent material characteristics and the geometry of the composite structure. In composite scintillators with a high degree of heterogeneous loading, a superposition of fluorescence contributions originating in multiple materials, which is observed as single waveform with an intermediate pulse shape, may affect its ability to reject rays. We measure the time dependence of light output from a scintillator composed of 6 Li-containing glass shards and scintillating polyvinyl toluene and identify events that exhibit such compound behavior when exposed to rays and fast neutrons. We develop a modeling and simulation framework that reproduces the pulse shapes in heterogeneous scintillators and use it study the effect that the weight percentage of 6 Li glass has on rejection. The modeling framework is applied to the experimentally studied scintillator, finding a good agreement. Here, the developed modeling and simulation approach will help optimize the design of heterogeneous scintillators to meet the desired trade-o between neutron capture efficiency and -ray rejection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Tularosa Basin Play Fairway Analysis Data and Models

This submission includes raster datasets for each layer of evidence used for weights of evidence analysis as well as the deterministic play fairway analysis (PFA). Data representative of heat, permeability and groundwater comprises some of the raster datasets. Additionally, the final deterministic PFA model is provided along with a certainty model. All of these datasets are best used with an ArcGIS software package, specifically Spatial Data Modeler.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Deep Learning Image Segmentation for Atmospheric Rivers

Abstract The identification of atmospheric rivers (ARs) is crucial for weather and climate predictions as they are often associated with severe storm systems and extreme precipitation, which can cause large impacts on society. This study presents a deep learning model, termed ARDetect, for image segmentation of ARs using ERA5 data from 1960 to 2020 with labels obtained from the TempestExtremes tracking algorithm. ARDetect is a convolutional neural network (CNN)-based U-Net model, with its structure having been optimized using automatic hyperparameter tuning. Inputs to ARDetect were selected to be the integrated water vapor transport (IVT) and total column water (TCW) fields, as well as the AR mask from TempestExtremes from the previous time step to the one being considered. ARDetect achieved a mean intersection-over-union (mIoU) rate of 89.04% for ARs, indicating its high accuracy in identifying these weather patterns and a superior performance than most deep learning–based models for AR detection. In addition, ARDetect can be executed faster than the TempestExtremes method (seconds vs minutes) for the same period. This provides a significant benefit for online AR detection, especially for high-resolution global models. An ensemble of 10 models, each trained on the same dataset but having different starting weights, was used to further improve on the performance produced by ARDetect, thus demonstrating the importance of model diversity in improving performance. ARDetect provides an effective and fast deep learning–based model for researchers and weather forecasters to better detect and understand ARs, which have significant impacts on weather-related events such as floods and droughts.

Galea, Daniel↗
DOE OSTI2018

Short-term ozone exposure and asthma severity: Weight-of-evidence analysis

Highlights: • Evidence from multiple realms is integrated in the weight-of-evidence analysis. • Epidemiology suggests exacerbation events are associated with ambient ozone. • Experimental human and animal studies show pulmonary effects with high exposure. • The relevance of animal toxicity studies to human asthma is uncertain. • Evidence for causality between ambient ozone and asthma is {sup e}quipoise and above.” To determine whether evidence indicates that short-term exposure to ambient concentrations of ozone in the United States can affect asthma severity, we systematically reviewed published controlled human exposure, epidemiology, and animal toxicity studies. The strongest evidence for a potential causal relationship came from epidemiology studies reporting increased emergency department visits and hospital admissions for asthma following elevated ambient ozone concentrations. However, while controlled exposure studies reported lung function decrements and increased asthma symptoms following high ozone exposures 160–400 parts per billion [ppb]), epidemiology studies evaluating similar outcomes reported less consistent results. Animal studies showed changes in pulmonary function at high ozone concentrations (> 500 ppb), although there is substantial uncertainty regarding the relevance of these animal models to human asthma. Taken together, the weight of evidence indicates that there is at least an equal likelihood that either explanation is true, i.e., the strength of the evidence for a causal relationship between short-term exposure to ambient ozone concentrations and asthma severity is ''equipoise and above''.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

A new model for estimating total body water from bioelectrical resistance

Estimation of total body water (T) from bioelectrical resistance (R) is commonly done by stepwise regression models with height squared over R, H(exp 2)/R, age, sex, and weight (W). Polynomials of H(exp 2)/R have not been included in these models. We examined the validity of a model with third order polynomials and W. Methods: T was measured with oxygen-18 labled water in 27 subjects. R at 50 kHz was obtained from electrodes placed on the hand and foot while subjects were in the supine position. A stepwise regression equation was developed with 13 subjects (age 31.5 plus or minus 6.2 years, T 38.2 plus or minus 6.6 L, W 65.2 plus or minus 12.0 kg). Correlations, standard error of estimates and mean differences were computed between T and estimated T's from the new (N) model and other models. Evaluations were completed with the remaining 14 subjects (age 32.4 plus or minus 6.3 years, T 40.3 plus or minus 8 L, W 70.2 plus or minus 12.3 kg) and two of its subgroups (high and low) Results: A regression equation was developed from the model. The only significant mean difference was between T and one of the earlier models. Conclusion: Third order polynomials in regression models may increase the accuracy of estimating total body water. Evaluating the model with a larger population is needed.

Siconolfi, S. F.↗
NASA NTRS2004

Mathematical Description of Dendrimer Structure

Characteristics of starburst dendrimers can be easily attributed to the multiplicity of the monomers used to synthesize them. The molecular weight, degree of polymerization, number of terminal groups and branch points for each generation of a dendrimer can be calculated using mathematical formulas incorporating these variables. Mathematical models for the calculation of degree of polymerization, molecular weight, and number of terminal groups and branching groups previously published were revised and elaborated on for poly(amidoamine) (PAMAM) dendrimers, and introduced for poly(propyleneimine) (POPAM) dendrimers and the novel POPAM-PAMAM hybrid, which we call the POMAM dendrimer. Experimental verification of the relationship between theoretical and actual structure for the PAMAM dendrimer was also established.

Majoros, Istvan J.↗
NASA NTRS2010

Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction

An algorithm was developed to generate crop yield predictions from orbital remote sensing observations, by analyzing thousands of pixels per county and the associated historical crop yield data for those counties. The algorithm determines which pixels contain which crop. Since each known yield value is associated with thousands of individual pixels, this is a multiple instance learning problem. Because individual crop growth is related to the resulting yield, this relationship has been leveraged to identify pixels that are individually related to corn, wheat, cotton, and soybean yield. Those that have the strongest relationship to a given crop s yield values are most likely to contain fields with that crop. Remote sensing time series data (a new observation every 8 days) was examined for each pixel, which contains information for that pixel s growth curve, peak greenness, and other relevant features. An alternating-projection (AP) technique was used to first estimate the "salience" of each pixel, with respect to the given target (crop yield), and then those estimates were used to build a regression model that relates input data (remote sensing observations) to the target. This is achieved by constructing an exemplar for each crop in each county that is a weighted average of all the pixels within the county; the pixels are weighted according to the salience values. The new regression model estimate then informs the next estimate of the salience values. By iterating between these two steps, the algorithm converges to a stable estimate of both the salience of each pixel and the regression model. The salience values indicate which pixels are most relevant to each crop under consideration.

Wagstaff, Kiri L.↗
NASA NTRS1999

Frequency-Weighting Filter Selection, for H2 Control of Microgravity Isolation Systems: A Consideration of the "Implicit Frequency Weighting" Problem

Many space-science experiments need an active isolation system to provide them with the requisite microgravity environment. The isolation systems planned for use with the International Space Station (ISS) have been appropriately modeled using relative position, relative velocity, and acceleration states. In theory, frequency-weighting design filters can be applied to these state-space models, in order to develop optimal H2 or mixed-norm controllers with desired stability and performance characteristics. In practice, however, since there is a kinematic relationship among the various states, any frequency weighting applied to one state will implicitly weight other states. These implicit frequency-weighting effects must be considered, for intelligent frequency-weighting filter assignment. This paper suggests a rational approach to the assignment of frequency-weighting design filters, in the presence of the kinematic coupling among states that exists in the microgravity vibration isolation problem.

Hampton, Roy David↗
NASA NTRS2000

Frequency-Weighting Filter Selection for H2 Control of Microgravity Isolation Systems: A Consideration of the "Implicit Frequency Weighting" Problem

Many space-science experiments need an active isolation system to provide them with the requisite microgravity environment. The isolation system planned for use with the International Space Station (ISS) have been appropriately modeled using relative position, relative velocity, and acceleration states. In theory, frequency-weighting design filters can be applied to them state-space models, In order to develop optimal H2 or mixed-norm controllers with desired stability and performance characteristics. In practice. however, since there Is a kinematic relationship among the various states. any frequency weighting applied to one state will implicitly weight other states. These implicit frequency-weighting effects must be considered, for intelligent frequency-weighting filter assignment. This paper suggests a rational approach to the assignment of frequency-weighting design filters, in the presence of the kinematic coupling among states that exists in the microgravity vibration isolation problem.

Hampton, R. David↗
DOE OSTI2012

THE CONTRIBUTION OF TP-AGB AND RHeB STARS TO THE NEAR-IR LUMINOSITY OF LOCAL GALAXIES: IMPLICATIONS FOR STELLAR MASS MEASUREMENTS OF HIGH-REDSHIFT GALAXIES

Using high spatial resolution Hubble Space Telescope WFC3 and Advanced Camera for Surveys imaging of resolved stellar populations, we constrain the contribution of thermally pulsing asymptotic giant branch (TP-AGB) stars and red helium burning (RHeB) stars to the 1.6 {mu}m near-infrared (NIR) luminosities of 23 nearby galaxies, including dwarfs and spirals. The TP-AGB phase contributes as much as 17% of the integrated F160W flux, even when the red giant branch is well populated. The RHeB population contribution can match or even exceed the TP-AGB contribution, providing as much as 21% (18% after a statistical correction for foreground) of the integrated F160W light. We estimate that these two short-lived phases may account for up to 70% of the rest-frame NIR flux at higher redshift. The NIR mass-to-light (M/L) ratio should therefore be expected to vary significantly due to fluctuations in the star formation rate (SFR) over timescales from 25 Myr to several Gyr, an effect that may be responsible for some of the lingering scatter in NIR galaxy scaling relations such as the Tully-Fisher and metallicity-luminosity relations. We compare our observational results to predictions based on optically derived star formation histories and stellar population synthesis (SPS) models, including models based on the 2008 Padova isochrones (used in popular SPS programs) and the updated 2010 Padova isochrones, which shorten the lifetimes of low-mass (old) low-metallicity TP-AGB populations. The updated (2010) SPS models generally reproduce the expected numbers of TP-AGB stars in the sample; indeed, for 65% of the galaxies, the discrepancy between modeled and observed numbers is smaller than the measurement uncertainties. The weighted mean model/data number ratio for TP-AGB stars is 1.5 (1.4 with outliers removed) with a standard deviation of 0.5. The same SPS models, however, give a larger discrepancy in the F160W flux contribution from the TP-AGB stars, overpredicting the flux by a weighted mean factor of 2.3 (2.2 with outliers removed) with a standard deviation of 0.8. This larger offset is driven by the prediction of modest numbers of high-luminosity TP-AGB stars at young (<300 Myr) ages. The best-fit SPS models simultaneously tend to underpredict the numbers and fluxes of stars on the RHeB sequence, typically by a factor of 2.0 {+-} 0.6 for galaxies with significant numbers of RHeBs. Possible explanations for both the TP-AGB and RHeB model results include (1) difficulties with measuring the SFHs of galaxies especially on the short timescales over which these stars evolve (several Myr), (2) issues with the way the SPS codes populate the color-magnitude diagrams (e.g., how they handle pulsations or self-extinction), and/or (3) lingering issues with the lifetimes of these stars in the stellar evolution codes. Coincidentally these two competing discrepancies-overprediction of the TP-AGB and underprediction of the RHeBs-result in a predicted NIR M/L ratio largely unchanged for a rapid SFR, after correcting for these effects. However, the NIR-to-optical flux ratio of galaxies could be significantly smaller than AGB-rich models would predict, an outcome that has been observed in some intermediate-redshift post-starburst galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗