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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Understanding the transient large amplitude oscillatory shear behavior of yield stress fluids

A full understanding of the sequence of processes exhibited by yield stress fluids under large amplitude oscillatory shearing is developed using multiple experimental and analytical approaches. A novel component rate Lissajous curve, where the rates at which strain is acquired unrecoverably and recoverably are plotted against each other, is introduced and its utility is demonstrated by application to the analytical responses of four simple viscoelastic models. Using the component rate space, yielding and unyielding are identified by changes in the way strain is acquired, from recoverably to unrecoverably and back again. The behaviors are investigated by comparing the experimental results with predictions from the elastic Bingham model that is constructed using the Oldroyd–Prager formalism and the recently proposed continuous model by Kamani, Donley, and Rogers in which yielding is enhanced by rapid acquisition of elastic strain. The physical interpretation gained from the transient large amplitude oscillatory shear (LAOS) data is compared to the results from the analytical sequence of physical processes framework and a novel time-resolved Pipkin space. The component rate figures, therefore, provide an independent test of the interpretations of the sequence of physical processes analysis that can also be applied to other LAOS analysis frameworks. Each of these methods, the component rates, the sequence of physical processes analysis, and the time-resolved Pipkin diagrams, unambigiously identifies the same material physics, showing that yield stress fluids go through a sequence of physical processes that includes elastic deformation, gradual yielding, plastic flow, and gradual unyielding.

Kamani, Krutarth M. (ORCID:0000000338975420)↗
NASA NTRS1960

The Solar Wind

Parker's model of a spherically expanding corona, the "solar wind," is compared with D. E. Blackwell's observations of the 1954 minimum equatorial corona. A significant discrepancy is found between the predicted and the observed electron densities at distances from the sun greater than 20 solar radii. Blackwell's data are found to be consistent with a model in which the corona expands mostly within a disk less than 25 solar radii thick, lying within the sun's equatorial plane. The thickness of the disk as a function of distance from the sun is qualitatively explained in terms of magnetic pressure. The solar wind is found to have a considerable effect on the lunar atmosphere. First, the calculated density of the lunar atmosphere is greatly reduced by collisions with protons in the solar wind. If the flux of particles in this wind has the conventional values ranging between 10(exp 10) to 10(exp 11) per sq cm-sec, the calculations yield a lunar pressure of 10(exp -13) atmosphere of argon, in agreement with the value predicted by Elsmore and Whitfield on the basis of observations on the occultation of radio stars. Second, following a suggestion by Gold, it was found that the collisions of solar-wind protons with the lunar surface produce an atmosphere of cold neutral hydrogen with a density of 10(exp 5) per cu cm at the lunar surface. The density falls off at greater distances in accordance with the inverse-square law. Estimates indicate that the interaction of solar particles with the neutral hydrogen will produce an extended lunar ionosphere with a density of the order of 400 protons/cu cm in the vicinity of the moon.

Herring, J. R.↗
DOE OSTI2026

Multi-trait multi-environment genomic prediction strategies for Miscanthus sacchariflorus

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.

genomic prediction (GP)↗
DOE OSTI2026

Rapid Characterization Tools for Process Optimization: Cooperative Research and Development (Final Report)

In this project Prenexus Health, Inc. (Prenexus) and NLR will develop rapid characterization tools to improve the Prenexus production process. First, we will develop a tool to predict the overall performance of the Prenexus manufacturing process converting high-fiber sugarcane to xylo-oligosaccharides (XOS) (both the overall process yield and the composition of the XOS product) using rapid characterization of the incoming feedstock and knowledge of key process parameters. This tool will dramatically increase Prenexus’ understanding of the overall process. Second, we will develop a tool to predict the concentration of soluble oligomeric and monomeric xylose and organic acids in multiple process streams at-line in the Prenexus process, enabling real-time process control of the conversion process.

09 BIOMASS FUELS↗
DOE OSTI2025

Combining physics-based and data-driven models for quantitatively accurate plasma profile prediction that extrapolates well; with application to DIII-D, AUG, and ITER tokamaks

For design, scenario planning, and control, ITER and all other envisioned tokamaks rely on a variety of statistical and physics-based models to extrapolate to unseen regimes; most notably from low plasma current to high. A 'meta-learning' methodology for combining the accuracy of data-driven models with the generalizability of physics-based models is described and tested, yielding a 5–10 percent improvement in performance beyond either alone for the task of extrapolating time-dependent plasma profile prediction from low- to high- plasma current DIII-D tokamak discharges. Meanwhile, it is shown that both machine learning models extrapolated far-distribution and state-of-the-art 'physics-based' profile predictors fare worse than merely assuming plasma profiles do not change from their initial values. Finally, a variety of other mechanisms for helping data-driven models generalize—transfer learning, adding contextual information from physics simulators, and adding data from the ASDEX Upgrade tokamak—are attempted for similar extrapolation tasks but, in the methodology used in this paper, yield no significant improvement beyond simple data-driven models. Results are summarized in figures 15 and 16.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Case study on climate change effects and food security in Southeast Asia

Agriculture, a cornerstone of human civilization, faces rising challenges from climate change, resource limitations, and stagnating yields. Precise crop production forecasts are crucial for shaping trade policies, development strategies, and humanitarian initiatives. This study introduces a comprehensive machine learning framework designed to predict crop production. We leverage CMIP5 climate projections under a moderate carbon emission scenario to evaluate the future suitability of agricultural lands and incorporate climatic data, historical agricultural trends, and fertilizer usage to project yield changes. Our integrated approach forecasts significant regional variations in crop production across Southeast Asia by 2028, identifying potential cropland utilization. Specifically, the cropland area in Indonesia, Malaysia, Philippines, and Viet Nam is projected to decline by more than 10% if no action is taken, and there is potential to mitigate that loss. Moreover, rice production is projected to decline by 19% in Viet Nam and 7% in Thailand, while the Philippines may see a 5% increase compared to 2021 levels. Our findings underscore the critical impacts of climate change and human activities on agricultural productivity, offering essential insights for policy-making and fostering international cooperation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Systems-Level Modeling for CRISPR-Based Metabolic Engineering

The CRISPR-Cas system has enabled the development of sophisticated, multigene metabolic engineering programs through the use of guide RNA-directed activation or repression of target genes. To optimize biosynthetic pathways in microbial systems, we need improved models to inform design and implementation of transcriptional programs. Recent progress has resulted in new modeling approaches for identifying gene targets and predicting the efficacy of guide RNA targeting. Genome-scale and flux balance models have successfully been applied to identify targets for improving biosynthetic production yields using combinatorial CRISPR-interference (CRISPRi) programs. Here, the advent of new approaches for tunable and dynamic CRISPR activation (CRISPRa) promises to further advance these engineering capabilities. Once appropriate targets are identified, guide RNA prediction models can lead to increased efficacy in gene targeting. Developing improved models and incorporating approaches from machine learning may be able to overcome current limitations and greatly expand the capabilities of CRISPR-Cas9 tools for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

A critical examination of the validity of simplified models for radiant heat transfer analysis.

Examination of the directional effects of the simplified models by comparing the experimental data with the predictions based on simple and more detailed models for the radiation characteristics of surfaces. Analytical results indicate that the constant property diffuse and specular models do not yield the upper and lower bounds on local radiant heat flux. In general, the constant property specular analysis yields higher values of irradiation than the constant property diffuse analysis. A diffuse surface in the enclosure appears to destroy the effect of specularity of the other surfaces. Semigray and gray analyses predict the irradiation reasonably well provided that the directional properties and the specularity of the surfaces are taken into account. The uniform and nonuniform radiosity diffuse models are in satisfactory agreement with each other.

Toor, J. S.↗
NASA NTRS2018

Effects of Sample Holder Edge Geometry on Atomic Oxygen Erosion Yield of Pyrolytic Graphite Exposed in Low Earth Orbit

The measurement of the erosion yield (volume lost per incident atom) of polymers and carbon using low Earth orbital (LEO) atomic oxygen exposure has typically involved placing small samples in holders that have chamfered edges. The chamfered edges have sometimes cause the samples to tear by their perimeters. This paper reports an evaluation of the erosion profile of a LEO atomic oxygen exposed pyrolytic graphite sample to determine the extent to which the erosion yield is altered by the chamfer and what the expected erosion yield would be for large area samples. The results indicate that the durability of large area samples would be approx. 5.2% lower than predicted based on mass loss of small samples with exposed diameters of 0.838 inch (2.13 cm) and chamfered sample holders.

erosion yield↗
DOE OSTI2024

Utilization of Synthetic Near-Infrared Spectra via Generative Adversarial Network to Improve Wood Stiffness Prediction

Near-infrared (NIR) spectroscopy is widely used as a nondestructive evaluation (NDE) tool for predicting wood properties. When deploying NIR models, one faces challenges in ensuring representative training data, which large datasets can mitigate but often at a significant cost. Machine learning and deep learning NIR models are at an even greater disadvantage because they typically require higher sample sizes for training. In this study, NIR spectra were collected to predict the modulus of elasticity (MOE) of southern pine lumber (training set = 573 samples, testing set = 145 samples). To account for the limited size of the training data, this study employed a generative adversarial network (GAN) to generate synthetic NIR spectra. The training dataset was fed into a GAN to generate 313, 573, and 1000 synthetic spectra. The original and enhanced datasets were used to train artificial neural networks (ANNs), convolutional neural networks (CNNs), and light gradient boosting machines (LGBMs) for MOE prediction. Overall, results showed that data augmentation using GAN improved the coefficient of determination (R 2 ) by up to 7.02% and reduced the error of predictions by up to 4.29%. ANNs and CNNs benefited more from synthetic spectra than LGBMs, which only yielded slight improvement. All models showed optimal performance when 313 synthetic spectra were added to the original training data; further additions did not improve model performance because the quality of the datapoints generated by GAN beyond a certain threshold is poor, and one of the main reasons for this can be the size of the initial training data fed into the GAN. LGBMs showed superior performances than ANNs and CNNs on both the original and enhanced training datasets, which highlights the significance of selecting an appropriate machine learning or deep learning model for NIR spectral-data analysis. The results highlighted the positive impact of GAN on the predictive performance of models utilizing NIR spectroscopy as an NDE technique and monitoring tool for wood mechanical-property evaluation. Further studies should investigate the impact of the initial size of training data, the optimal number of generated synthetic spectra, and machine learning or deep learning models that could benefit more from data augmentation using GANs.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1985

Measurement and prediction of model-rotor flow fields

This paper shows that a laser velocimeter can be used to measure accurately the three-component velocities induced by a model rotor at transonic tip speeds. The measurements, which were made at Mach numbers from 0.85 to 0.95 and at zero advance ratio, yielded high-resolution, orthogonal velocity values. The measured velocities were used to check the ability of the ROT22 full-potential rotor code to predict accurately the transonic flow field in the crucial region around and beyond the tip of a high-speed rotor blade. The good agreement between the calculated and measured velocities established the code's ability to predict the off-blade flow field at transonic tip speeds. This supplements previous comparisons in which surface pressures were shown to be well predicted on two different tips at advance ratios to 0.45, especially at the critical 90 deg azimuthal blade position. These results demonstrate that the ROT22 code can be used with confidence to predict the important tip-region flow field, including the occurrence, strength, and location of shock waves causing high drag and noise.

Owen, F. K.↗
NASA NTRS1990

Prediction of blade-vortex interaction noise using airloads generated by a finite-difference technique

The present numerical finite-difference scheme for helicopter blade-load prediction during realistic, self-generated three-dimensional blade-vortex interactions (BVI) derives the velocity field through a nonlinear superposition of the rotor flow-field yielded by the full potential rotor flow solver RFS2 for BVI, on the one hand, over the rotational vortex flow field computed with the Biot-Savart law. Despite the accurate prediction of the acoustic waveforms, peak amplitudes are found to have been persistently underpredicted. The inclusion of BVI noise source in the acoustic analysis significantly improved the perceived noise level-corrected tone prediction.

Tadghighi, Hormoz↗
NASA NTRS2019

Audibility of Multiple, Low-Frequency Tonal Signals in Noise

The main purpose of this study is to examine the audibility of multiple, low-frequency tones that are placed in distinct auditory channels. Three experiments are described, the goals of which are to determine if the presence of sound in multiple channels results in enhanced audibility and to assess the applicability of the Statistical Summation Model (SSM) to this frequency range. This model predicts that for the case of multiple signals that are in separate auditory channels, implying statistical independence, each with sensitivity value d prime of i, the resulting total sensitivity is given by the square root of the sum of the squares of the individual d prime of i values. In common with previous studies conducted at higher frequencies, the signals are pure tones and the maskers are broadband noise. The requirement that low frequency tones be placed in separate auditory filters limited the number of tones to a maximum of three. The first of the three experiments measured the change in masked thresholds for two- and three-tone signals relative to the level of the equally-detectable single tones. The multiple tone signals were composed of combinations of 55, 120 and 200 Hz tones. The measured changes in thresholds exceeded those predicted by the SSM, although they did not differ statistically from the model predictions. The second experiment employed the same overall approach but acquired more data and concentrated on the three-tone signal. Once again, the measured changes in masked threshold exceeded the model predictions, this time to a statistically-significant degree. Two issues were postulated with the potential to yield inflated changes in masked threshold: interaction between tones resulting in perceptible intermodulation/difference tones, and the assumption that the tones were in distinct auditory filters and statistically independent of one another. The third experiment used two sets of three-tone signals to address these latter concerns. The first set of three tones was composed of harmonically related tone frequencies of 55, 110 and 165 Hz, which was an attempt to reduce effects of intermodulation difference tones. The second set of three tones was chosen to be 110, 220 and 330 Hz, again reducing effects of difference tones, but also providing greater separation between tones. Results for the first set of three tones compared to those of the earlier experiments indicated that intermodulation was not an important effect. The second set of three tones (110, 220, 330 Hz) yielded changes in masked thresholds that, on average, were in good agreement with the SSM, although intersubject variability was large and prohibited a definitive conclusion regarding the concern that tone spacing was inadequate. The results of the three experiments showed that the masked threshold of sounds with multiple (two or three) equally-detectable low frequency tones was lower than those of the single tones. In other words, it is clear that audibility is enhanced by the presence of signals in multiple auditory filters. This finding is consistent with most previous research conducted at higher frequencies. In contrast with previous research, test subjects were, on average, able to detect multitone sounds at lower levels than those predicted using the SSM. Analyses that included Monte Carlo simulations showed that normally distributed errors in the single tone thresholds result in biased estimates of the thresholds of multitone sounds. This phenomenon is likely responsible for at least a substantial fraction of the unexpected deviation of measurements from SSM predictions.

Rafaelof, Menachem↗
NASA NTRS1987

An aerothermodynamic study of slender conical vehicles

A numerical study was performed to assess the applicability of some current techniques which can be used for aerothermal predictions over slender spherically blunted cones. Predictions using a viscous-shock-layer method and several engineering approaches were compared with experimental results from flight and ground-based tests, with each other, and with other detailed results. Good agreement was obtained in comparisons with laminar and turbulent heating data from the Reentry F flight vehicle and with the wind-tunnel data. In particular, the viscous-shock-layer method was shown to yield excellent comparisons and should be useful in providing detailed flowfield and surface values for slender blunted cones. Additional predictions were obtained with these methods for two 5-deg half-angle cones with different nose radii to illustrate the effects of nose bluntness and angle of attack on drag and heat transfer. These results demonstrate the benefit of nose blunting with respect to heating and drag for laminar and transitional flow at zero-lift conditions and the benefit of heating reduction at angle of attack. Detailed comparison of the engineering code predictions with the viscous-shock-layer results for these additional cases generally showed good agreement except for the laminar prodictions at angle of attack on the forward cone surface. Nonequilibrium calculations at 0-deg angle of attack showed that substantial benefits of low surface catalysis existed only in the nose-dominated region.

Thompson, R. A.↗
NASA NTRS1995

The use of cowl camber and taper to reduce rotor/stator interaction noise

The project had two specific technical objectives: (1) to develop a realistic three-dimensional model of tonal noise due to rotor/stator interaction, as the input field for predictions of diffraction and dissipation by a lined cowl; and (2) to determine whether the generator curve of that cowl, or duct, could be 'steered' to yield substantially lower values of propulsor noise along the engine's fore and aft open sectors. The more general and important aim of their research is to provide the commercial aircraft industry with a useful predictive tool to help it meet its noise-reduction goals. The work has produced a tractable and yet realistic model of rotor/stator interaction noise. The blades in the fan stage are radially divergent, twisted, and of realistically wide chords to match the high frequencies and speeds of the sound-production process. The resulting three-dimensional acoustic nearfield insonifies the interior wall of the diffracting cowl, whose shape, incidentally, does not affect fore or aft noise significantly (but other factors do).

Martinez, R.↗
NASA NTRS2000

Hierarchical Statistical 3D ' Atomistic' Simulation of Decanano MOSFETs: Drift-Diffusion, Hydrodynamic and Quantum Mechanical Approaches

When MOSFETs are scaled to deep submicron dimensions the discreteness and randomness of the dopant charges in the channel region introduces significant fluctuations in the device characteristics. This effect, predicted 20 year ago, has been confirmed experimentally and in simulation studies. The impact of the fluctuations on the functionality, yield, and reliability of the corresponding systems shifts the paradigm of the numerical device simulation. It becomes insufficient to simulate only one device representing one macroscopical design in a continuous charge approximation. An ensemble of macroscopically identical but microscopically different devices has to be characterized by simulation of statistically significant samples. The aims of the numerical simulations shift from predicting the characteristics of a single device with continuous doping towards estimating the mean values and the standard deviations of basic design parameters such as threshold voltage, subthreshold slope, transconductance, drive current, etc. for the whole ensemble of 'atomistically' different devices in the system. It has to be pointed out that even the mean values obtained from 'atomistic' simulations are not identical to the values obtained from continuous doping simulations. In this paper we present a hierarchical approach to the 'atomistic' simulation of aggressively scaled decanano MOSFETs. A full scale 3D drift-diffusion'atomostic' simulation approach is first described and used for verification of the more economical, but also more restricted, options. To reduce the processor time and memory requirements at high drain voltage we have developed a self-consistent option based on a thin slab solution of the current continuity equation only in the channel region. This is coupled to the Poisson's equation solution in the whole simulation domain in the Gummel iteration cycles. The accuracy of this approach is investigated in comparison with the full self-consistent solution. At low drain voltage only single solution of the nonlinear Poisson equation is sufficient to extract the current with satisfactory accuracy. A pilot version of a hydrodynamic 'atomistic' simulator has been developed in order to study the effect of the nonequilibrium, non local transport in decanano MOSFETs on the random dopant induced current fluctuations. For the first time we have also applied the density gradient approach in 3D to investigate the effect of the quantum confinement on the threshold voltage fluctuations. The developed 'atomistic' simulation techniques have been applied to study various fluctuation resistant MOSFET architectures including epitaxial and delta doped devices.

Asenov, Asen↗
DOE OSTI2022

Probing strangeness canonical ensemble with K - , Φ(1020) and Ξ - production in Au+Au collisions at $\sqrt{^S{NN}}$ = 3 GeV

We report on the first multi-differential measurement of φ meson and Ξ - hyperon production as well as the φ/K - and φ/Ξ - ratio in Au+Au collisions at $\sqrt{^S{NN}}$ = 3 GeV with the STAR experiment under its fixed target configuration at RHIC. φ mesons and Ξ - hyperons are measured through their hadronic decay channels, φ → K+K - and Ξ - → Λπ - . The transverse kinetic energy spectra of K - , φ and Ξ - are presented in different centrality and rapidity intervals. The total production yields and the ratios within a 4π coverage are calculated and compared to thermal model predictions. A calculation within the grand canonical ensemble framework shows a clear discrepancy from our measurement. Our data favor the canonical ensemble approach employing local strangeness conservation with a small strangeness correlation length (r c ≤ 4.2 fm) in 0–10% central Au+Au collisions at $\sqrt{^S{NN}}$ = 3 GeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

The UV Photoinduced Ring-Closing Reaction of Cyclopentadiene Probed with Ultrafast Electron Diffraction

Conjugated cyclic organic molecules are common across many fields such as pharmaceuticals, are naturally occurring in biological systems, and are used in synthetic materials. One particular area of interest from a photochemical point of view is the formation of highly strained cyclic organics. We investigate the photoinduced reaction of cyclopentadiene, a five-membered organic ring molecule which can form strained three and four carbon rings after photoexcitation with UV light, with the gas-phase ultrafast electron diffraction instrument at the SLAC MeV-UED facility. Electron diffraction offers a direct probe sensitive to the nuclear geometry during the reaction, allowing for the determination of the distribution of products formed following photoexcitation. We observe the simultaneous formation of the highly strained ring- closed bicyclo[2.1.0]pentene and vibrationally hot cyclopentadiene within the temporal resolution of the experiment, and determine the relative yield of all reaction products. Furthermore, the experimental results are in good agreement with the predictions of trajectory simulations.

Computational Chemistry↗