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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 OSTI2025

Front-end engineering design (FEED) studies: a quantitative analysis

NETL has devised a methodology for normalizing FEED study metrics of interest and allowing cautious quantitative comparison across FEED studies. This presentation introduces the novel quantitative comparison methodology and presents results from utilizing this methodology to examine data presented in recent FEED study reports. The quantitative methodology developed for the examination of FEED study performance and cost also allows comparison of real-world performance and costs against NETL TEA model predicted performance and cost. Learnings from examining NETL model predicted performance and cost versus real world reported values are highlighted. These learnings provide insight into NETL TEA model uncertainty and highlight opportunities for further model development.

FEED Studies↗
NASA NTRS1999

Five-Hole Flow Angle Probe Calibration for the NASA Glenn Icing Research Tunnel

A spring 1997 test section calibration program is scheduled for the NASA Glenn Research Center Icing Research Tunnel following the installation of new water injecting spray bars. A set of new five-hole flow angle pressure probes was fabricated to properly calibrate the test section for total pressure, static pressure, and flow angle. The probes have nine pressure ports: five total pressure ports on a hemispherical head and four static pressure ports located 14.7 diameters downstream of the head. The probes were calibrated in the NASA Glenn 3.5-in.-diameter free-jet calibration facility. After completing calibration data acquisition for two probes, two data prediction models were evaluated. Prediction errors from a linear discrete model proved to be no worse than those from a full third-order multiple regression model. The linear discrete model only required calibration data acquisition according to an abridged test matrix, thus saving considerable time and financial resources over the multiple regression model that required calibration data acquisition according to a more extensive test matrix. Uncertainties in calibration coefficients and predicted values of flow angle, total pressure, static pressure. Mach number. and velocity were examined. These uncertainties consider the instrumentation that will be available in the Icing Research Tunnel for future test section calibration testing.

Gonsalez, Jose C.↗
DOE OSTI2023

Explainability and extrapolation of machine learning models for predicting the glass transition temperature of polymers

Abstract Machine learning (ML) offers promising tools to develop surrogate models for polymers' structure–property relations. Surrogate models can be built upon existing polymer data and are useful for rapidly predicting the properties of unknown polymers. The accuracy of such ML models appears to depend on the feature space representation of polymers, the range of training data, and learning algorithms. Here, we establish connections between these factors for predicting the glass transition temperature (T g ) of polymers. Our analysis suggests linear models with fewer fitting parameters are as accurate as nonlinear models with many hidden and unexplainable parameters. Also, the performance of a monomer topology‐based ML model is found to be qualitatively identical to that of a physicochemical descriptor‐based ML model. We find that the ML models's performance in the extrapolative region is enhanced as the property range of the training data increases. Moreover, we establish newT g – polymer chemistry correlations via ML. Our work illustrates how ML can advance the fundamental understanding of polymer structure–property correlations and its efficacy for extrapolation problems.

Polymer Science↗
DOE OSTI2017

Strong Stellar-driven Outflows Shape the Evolution of Galaxies at Cosmic Dawn

We study galaxy mass assembly and cosmic star formation rate (SFR) at high redshift (z ≳ 4), by comparing data from multiwavelength surveys with predictions from the GAlaxy Evolution and Assembly (gaea) model. gaea implements a stellar feedback scheme partially based on cosmological hydrodynamical simulations, which features strong stellar-driven outflows and mass-dependent timescales for the re-accretion of ejected gas. In previous work, we have shown that this scheme is able to correctly reproduce the evolution of the galaxy stellar mass function (GSMF) up to z ∼ 3. We contrast model predictions with both rest-frame ultraviolet (UV) and optical luminosity functions (LFs), which are mostly sensitive to the SFR and stellar mass, respectively. We show that gaea is able to reproduce the shape and redshift evolution of both sets of LFs. We study the impact of dust on the predicted LFs, and we find that the required level of dust attenuation is in qualitative agreement with recent estimates based on the UV continuum slope. The consistency between data and model predictions holds for the redshift evolution of the physical quantities well beyond the redshift range considered for the calibration of the original model. In particular, we show that gaea is able to recover the evolution of the GSMF up to z ∼ 7 and the cosmic SFR density up to z ∼ 10.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Investigating the Dynamic Compaction Behavior of Brittle Powders

The compression of porous materials to full density is a complex physical and mechanical process. Modeling efforts to capture the compaction behavior of distended solids (e.g., porous materials or powders) have produced a variety of compaction models, each functionalized to address specific compaction mechanisms. Of the available models, those suited for high-strain-rate deformation associated with shock loading have generally been developed for ductile materials. Compaction models for brittle materials have only been developed for quasistatic loading conditions. No predictive models currently exist that successfully capture the physical processes and mechanics for shock compaction of brittle distended materials, such as sand and oxide powders. The primary hindrance in producing a dynamic compaction model for brittle distended materials is the lack of availability of high-fidelity, high-precision shock compaction data for validation. The proposed work is aimed at alleviating this issue by developing a high-precision testing method in combination with high-fidelity analysis methods to accurately and precisely determine the shocked state of an ideal test material, ceria powder, under uniaxial strain dynamic compaction. The measured shock compaction data from these brittle powder experiments is then used in initial computations to design a cylindrically converging shock compaction experiment within situ time-resolved shocked density measurements, employing proton radiography. The preliminary experimental and computational results obtained from these uniaxial strain dynamic compaction and cylindrically converging shock compaction experiments are presented. An experimental and computational path forwards to predictive model development is then proposed.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Meridional Distribution of CH3C2H and C4H2 in Saturn's Stratosphere from CIRS/Cassini Limb and Nadir Observations

Limb and nadir spectra acquired by Cassini/CIRS (Composite InfraRed Spectrometer) are analyzed in order to derive, for the first time, the meridional variations of diacetylene (C4H2) and methylacetylene (CH3C2H) mixing ratios in Saturn's stratosphere, from 5 hPa up to 0.05 hPa and 80 deg S to 45 deg N. We find that the C4H2 and CH3C2H meridional distributions mimic that of acetylene (C2H2), exhibiting small-scale variations that are not present in photochemical model predictions. The most striking feature of the meridional distribution of both molecules is an asymmetry between mid-southern and mid-northern latitudes. The mid-southern latitudes are found depleted in hydrocarbons relative to their northern counterparts. In contrast, photochemical models predict similar abundances at north and south mid-latitudes. We favor a dynamical explanation for this asymmetry, with upwelling in the south and downwelling in the north, the latter coinciding with the region undergoing ring shadowing. The depletion in hydrocarbons at mid-southern latitudes could also result from chemical reactions with oxygen-bearing molecules. Poleward of 60 deg S, at 0.1 and 0.05 hPa, we find that the CH3C2H and C4H2 abundances increase dramatically. This behavior is in sharp contradiction with photochemical model predictions, which exhibit a strong decrease towards the south pole. Several processes could explain our observations, such as subsidence, a large vertical eddy diffusion coefficient at high altitudes, auroral chemistry that enhances CH3C2H and C4H2 production, or shielding from photolysis by aerosols or molecules produced from auroral chemistry. However, problems remain with all these hypotheses, including the lack of similar behavior at lower altitudes. Our derived mean mixing ratios at 0.5 hPa of (2.4 +/- 0.3) 10(exp -10) for C4H2 and of (1.1 +/- 0.3) 10(exp -9) for CH3C2H are compatible with the analysis of global-average ISO observations performed by Moses et al. Finally, we provide values for the ratios [CH3C2H]/[C2H2] and [C4H2]/[C2H2] that can constrain the coupled chemistry of these hydrocarbons.

Guerlet, Sandrine↗
NASA NTRS1983

Potential impact of remote sensing data on sea-state analysis and prediction

The severe North Atlantic storm which damaged the ocean liner Queen Elizabeth 2 (QE2) was studied to assess the impact of remotely sensed marine surface wind data obtained by SEASAT-A, on sea state specifications and forecasts. Alternate representations of the surface wind field in the QE2 storm were produced from the SEASAT enhanced data base, and from operational analyses based upon conventional data. The wind fields were used to drive a high resolution spectral ocean surface wave prediction model. Results show that sea state analyses would have been vastly improved during the period of storm formation and explosive development had remote sensing wind data been available in real time. A modest improvement in operational 12 to 24 hour wave forecasts would have followed automatically from the improved initial state specification made possible by the remote sensing data in both numerical and sea state prediction models. Significantly improved 24 to 48 hour wave forecasts require in addition to remote sensing data, refinement in the numerical and physical aspects of weather prediction models.

Cardone, V. J.↗
DOE OSTI2018

Magnetic Inflation and Stellar Mass. II. On the Radii of Single, Rapidly Rotating, Fully Convective M-Dwarf Stars

Main-sequence, fully convective M dwarfs in eclipsing binaries are observed to be larger than stellar evolutionary models predict by as much as 10%–15%. A proposed explanation for this discrepancy involves effects from strong magnetic fields, induced by rapid rotation via the dynamo process. Although, a handful of single, slowly rotating M dwarfs with radius measurements from interferometry also appear to be larger than models predict, suggesting that rotation or binarity specifically may not be the sole cause of the discrepancy. We test whether single, rapidly rotating, fully convective stars are also larger than expected by measuring their Rsin i distribution. We combine photometric rotation periods from the literature with rotational broadening (vsin i) measurements reported in this work for a sample of 88 rapidly rotating M dwarf stars. Using a Bayesian framework, we find that stellar evolutionary models underestimate the radii by 10%--15%{sub −2.5}{sup +3}, but that at higher masses (0.18 < M < 0.4 M {sub Sun}), the discrepancy is only about 6% and comparable to results from interferometry and eclipsing binaries. At the lowest masses (0.08 < M < 0.18 M {sub Sun}), we find that the discrepancy between observations and theory is 13%–18%, and we argue that the discrepancy is unlikely to be due to effects from age. Furthermore, we find no statistically significant radius discrepancy between our sample and the handful of M dwarfs with interferometric radii. We conclude that neither rotation nor binarity are responsible for the inflated radii of fully convective M dwarfs, and that all fully convective M dwarfs are larger than models predict.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

A model for predicting aortic dynamic response to -G sub z impact acceleration.

A steady state dynamic response model for the radial motion of the aorta is developed from in vivo pressure-displacement and nerve stimulation experiments on canines. The model represented by a modified Van der Pol wave motion oscillator closely predicts steady state and perturbed response results. The applicability of the steady state canine aortic model to tailward acting impact forces is studied by means of the perturbed phase plane of the oscillator. The backflow through the aortic arch resulting from a specified acceleration-time profile is computed and an analysis for predicting the forced motion aortic response is presented.

Advani, S. H.↗
NASA NTRS2018

Semi-Empirical Modeling and Prediction of Direct Combustor Noise

Due to turbofan design trends, advances in fan-noise-mitigation techniques, and expected aircraft configuration changes, the impact on overall airport community noise from certain aircraft-propulsion noise sources, such as fan and jet noise, will be reduced at all certification points in the future. The situation with regard to turbofan-core noise is less clear however. Combustor noise in particular—which presently is an important core-noise component, but not dominant from an overall noise perspective—could become more prominent in upcoming high-power-density core designs. Its detailed source structure in the combustor, including the indirect combustor-noise mechanism, and the effects of the propagation path through the engine and exhaust nozzle need to be better understood. This report reviews the current status of modeling and prediction of direct combustor noise. This work is carried out under the NASA Advanced Air Vehicles Program, Advanced Air Transport Technology Project, Aircraft Noise Reduction Subproject.

Turbomachinery Noise↗
DOE OSTI2018

A Two-Stage Physical-Based Model for Predicting Flow Stress of As-cast TiAl Alloy Under Hot Deformation Conditions

The hot deformation behavior of Ti-30Al-4.2Mn-4.5Nb-0.2B alloy was investigated using the isothermal compression experiment at temperatures of 1020-1200 °C and strain rates of 0.001-1 s{sup −1}. The flow stress was sensitive to the deformation parameters like temperature and strain rate, which decreases with the increase in temperature and decrease in strain rates. Based on the true stress-true strain data, a two-stage physical-based model was proposed to describe the flow stress curve of as-cast TiAl alloy during hot deformation process. For establishing the model, at first, the flow curves of dynamic recovery (DRV) were modeled by employing stress-dislocation relation and adjusting dislocation annihilation coefficient Ω. Then, the flow curves of dynamic recrystallization (DRX) were modeled by considering the dynamic softening behavior into Avrami equation. Finally, the flow curves in the entire deformation stages could be described by embedding the predicted data of DRV model (i.e., flow stress before the critical strain) into the predicted data by DRX model (i.e., flow stress after the critical strain). The critical strain for initiation of DRX was determined by the double-differentiation method. To evaluate the applicability and effectiveness of DRX kinetics equation, the DRX curves were calculated and were consistent with the microstructure observation. Comparison between the experimental and predicted data shows that the proposed physical-based model can well forecast the flow stress under a wide working domain.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Modeling the two-point correlation of the vector stream function

A new model for the two-point vector stream function correlation has been developed using tensor invariant arguments and evaluated by the comparison of model predictions with DNS data for incompressible homogeneous turbulent shear flow. This two-point vector stream function model correlation can then be used to calculate the two-point velocity correlation function and other quantities useful in turbulence modeling. The model assumes that the two-point vector stream function correlation can be written in terms of the separation vector and a new tensor function that depends only on the magnitude of the separation vector. The model has a single free model coefficient, which has been chosen by comparison with the DNS data. The relative error of the model predictions of the two-point vector stream function correlation is only a few percent for a broad range of the model coefficient. Predictions of the derivatives of this correlation, which are of interest in turbulence modeling, may not be this accurate.

Oberlack, M.↗
NASA NTRS2019

Understanding Heating in Active Region Cores through Machine Learning. I. Numerical Modeling and Predicted Observables

To adequately constrain the frequency of energy deposition in active region cores in the solar corona, systematic comparisons between detailed models and observational data are needed. In this paper, we describe a pipeline for forward modeling active region emission using magnetic field extrapolations and field-aligned hydrodynamic models. We use this pipeline to predict time-dependent emission from active region NOAA 1158 for low-, intermediate-, and high-frequency nanoflares. In each pixel of our predicted multi-wavelength, time-dependent images, we compute two commonly used diagnostics: the emission measure slope and the time lag. We find that signatures of the heating frequency persist in both of these diagnostics. In particular, our results show that the distribution of emission measure slopes narrows and the mean decreases with decreasing heating frequency and that the range of emission measure slopes is consistent with past observational and modeling work. Furthermore, we find that the time lag becomes increasingly spatially coherent with decreasing heating frequency while the distribution of time lags across the whole active region becomes more broad with increasing heating frequency. In a follow-up paper, we train a random forest classifier on these predicted diagnostics and use this model to classify real observations of NOAA 1158 in terms of the underlying heating frequency.

UV radiation↗
DOE OSTI2015

SPATIALLY RESOLVED l-C{sub 3}H{sup +} EMISSION IN THE HORSEHEAD PHOTODISSOCIATION REGION: FURTHER EVIDENCE FOR A TOP-DOWN HYDROCARBON CHEMISTRY

Small hydrocarbons, such as C{sub 2}H, C{sub 3}H, and C{sub 3}H{sub 2} are more abundant in photo-dissociation regions (PDRs) than expected based on gas-phase chemical models. To explore the hydrocarbon chemistry further, we observed a key intermediate species, the hydrocarbon ion l-C{sub 3}H{sup +}, in the Horsehead PDR with the Plateau de Bure Interferometer at high-angular resolution (6″). We compare with previous observations of C{sub 2}H and c-C{sub 3}H{sub 2} at similar angular resolution and new gas-phase chemical model predictions to constrain the dominant formation mechanisms of small hydrocarbons in low-UV flux PDRs. We find that at the peak of the HCO emission (PDR position), the measured l-C{sub 3}H{sup +}, C{sub 2}H, and c-C{sub 3}H{sub 2} abundances are consistent with current gas-phase model predictions. However, in the first PDR layers, at the 7.7 μm polycyclic aromatic hydrocarbon band emission peak, which are more exposed to the radiation field and where the density is lower, the C{sub 2}H and c-C{sub 3}H{sub 2} abundances are underestimated by an order of magnitude. At this position, the l-C{sub 3}H{sup +} abundance is also underpredicted by the model but only by a factor of a few. In addition, contrary to the model predictions, l-C{sub 3}H{sup +} peaks further out in the PDR than the other hydrocarbons, C{sub 2}H and c-C{sub 3}H{sub 2}. This cannot be explained by an excitation effect. Current gas-phase photochemical models thus cannot explain the observed abundances of hydrocarbons, in particular, in the first PDR layers. Our observations are consistent with a top-down hydrocarbon chemistry, in which large polyatomic molecules or small carbonaceous grains are photo-destroyed into smaller hydrocarbon molecules/precursors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Measurement of the properties of Higgs boson production at $\sqrt{s}$ = 13 TeV in the H → γγ channel using 139 fb -1 of pp collision data with the ATLAS experiment

Measurements of Higgs boson production cross-sections are carried out in the diphoton decay channel using 139 fb -1 of pp collision data at $\sqrt{s}$ = 13 TeV collected by the ATLAS experiment at the LHC. The analysis is based on the definition of 101 distinct signal regions using machine-learning techniques. The inclusive Higgs boson signal strength in the diphoton channel is measured to be $1.04^{+0.10}_{-0.09}$. Cross-sections for gluon-gluon fusion, vector-boson fusion, associated production with a W or Z boson, and top associated production processes are reported. An upper limit of 10 times the Standard Model prediction is set for the associated production process of a Higgs boson with a single top quark, which has a unique sensitivity to the sign of the top quark Yukawa coupling. Higgs boson production is further characterized through measurements of Simplified Template Cross-Sections (STXS). In total, cross-sections of 28 STXS regions are measured. The measured STXS cross-sections are compatible with their Standard Model predictions, with a p-value of 93%. The measurements are also used to set constraints on Higgs boson coupling strengths, as well as on new interactions beyond the Standard Model in an effective field theory approach. No significant deviations from the Standard Model predictions are observed in these measurements, which provide significant sensitivity improvements compared to the previous ATLAS results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Galaxies in X-Ray Selected Clusters and Groups in Dark Energy Survey Data. I. Stellar Mass Growth of Bright Central Galaxies Since z ~ 1.2

Using the science verification data of the Dark Energy Survey for a new sample of 106 X-ray selected clusters and groups, we study the stellar mass growth of bright central galaxies (BCGs) since redshift z ~ 1.2. Compared with the expectation in a semi-analytical model applied to the Millennium Simulation, the observed BCGs become under-massive/under-luminous with decreasing redshift. Here, we incorporate the uncertainties associated with cluster mass, redshift, and BCG stellar mass measurements into an analysis of a redshift-dependent BCG-cluster mass relation, $m_*$ $∝ \huge{(}$$\frac{M_{200}}{1.5x10^{14}M_⊙}\huge{)}$$^{0.24±0.08}$ $(1 + z)$$^{-0.19±0.34}$, and compare the observed relation to the model prediction. We estimate the average growth rate since z = 1.0 for BCGs hosted by clusters of M 200,z = 10 13.8 M ⊙ ; at z = 1.0: m * , BCG appears to have grown by 0.13 ± 0.11 dex, in tension at the ~2.5σ significance level with the 0.40 dex growth rate expected from the semi-analytic model. We show that the build-up of extended intracluster light after z = 1.0 may alleviate this tension in BCG growth rates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Bottom-up coarse-grained models with predictive accuracy and transferability for both structural and thermodynamic properties of heptane-toluene mixtures

This work investigates the promise of a “bottom-up” extended ensemble framework for developing coarse-grained (CG) models that provide predictive accuracy and transferability for describing both structural and thermodynamic properties. We employ a force-matching variational principle to determine system-independent, i.e., transferable, interaction potentials that optimally model the interactions in five distinct heptane-toluene mixtures. Similarly, we employ a self-consistent pressure-matching approach to determine a system-specific pressure correction for each mixture. The resulting CG potentials accurately reproduce the site-site rdfs, the volume fluctuations, and the pressure equations of state that are determined by all-atom (AA) models for the five mixtures. Furthermore, we demonstrate that these CG potentials provide similar accuracy for additional heptane-toluene mixtures that were not included their parameterization. Surprisingly, the extended ensemble approach improves not only the transferability but also the accuracy of the calculated potentials. Additionally, we observe that the required pressure corrections strongly correlate with the intermolecular cohesion of the system-specific CG potentials. Moreover, this cohesion correlates with the relative “structure” within the corresponding mapped AA ensemble. Finally, the appendix demonstrates that the self-consistent pressure-matching approach corresponds to minimizing an appropriate relative entropy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

The EST Model for Predicting Progressive Damage and Failure of Open Hole Bending Specimens

Progressive damage and failure in open hole composite laminate coupons subjected to flexural loading is modeled using Enhanced Schapery Theory (EST). Previous studies have demonstrated that EST can accurately predict the strength of open hole coupons under remote tensile and compressive loading states. This homogenized modeling approach uses single composite shell elements to represent the entire laminate in the thickness direction and significantly reduces computational cost. Therefore, when delaminations are not of concern or are active in the post-peak regime, the version of EST presented here is a good engineering tool for predicting deformation response. Standard coupon level tests provides all the input data needed for the model and they are interpreted in conjunction with finite element (FE) based simulations. Open hole bending test results of three different IM7/8552 carbon fiber composite layups agree well with EST predictions. The model is able to accurately capture the curvature change and deformation localization in the specimen at and during the post catastrophic load drop event.

damage↗