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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Assessing Impacts on Pressure Stabilization and Leasing Acreage for CO 2 Storage Utilizing Oil Migration Concepts

Favorable geological storage for CO 2 has long been pictured as large anticlines with thick sandstones, similar to oil reservoirs in the petroleum system. Unlike oil, however, stored CO 2 does not need to be recoverable, which raises the possibility of using dissolution and residual trapping to augment the capacity of buoyant traps and tap more of the bulk rock volume. The work presented builds on that idea, asking the following question: If we inject CO 2 down to a syncline – analogous to the carrier bed in the petroleum system – how would this injection mechanism impact storage capacity and plume shape, migration, and stabilization? To address this question, we built a reservoir model, based on seismic interpretation of Middle Miocene strata, offshore Galveston, Texas. 3-D seismic and well logs were used to characterize key intervals. Reservoirs chosen for modeling are progradational-aggradational sands with mud intercalation. They have a higher degree of heterogeneity than the more conventional reservoirs commonly targeted for CO 2 storage. Modeling investigated how far the CO 2 plume would migrate under two scenarios: (1) injecting CO 2 at the base of the salt withdrawal basin (syncline scenario) and (2) injecting CO 2 at the base of the structural closure, similar to a common injection well location for EOR purposes (base scenario). For each scenario, we separately simulated injection of 30 MT of CO 2 and 60 MT of CO 2 continuously for 30 years and observe the plume and pressure evolution for 100 years after the injection stops. The simulation shows that injecting the CO 2 into a syncline limits the vertical migration of CO 2 , thus making synclinal injection more secure. In the syncline scenario, the geological layer around the injection point is more heterogeneous than the layer in the base scenario; thus, the CO 2 tends to migrate laterally. Additionally, in the syncline scenario, the plume does not even reach the upper part of the anticline, allowing us to safely store an additional amount of CO 2 into the reservoir. Furthermore, the simulation also shows that in the syncline scenario, the times needed for the reservoir to reach its stabilized pressure after the end of injections are faster. To summarize, CO 2 injection at the base of a syncline could provide additional storage, increase the safety of the project from the limited vertical plume migration, and expedite plume stabilization, which could result in the decrease of monitoring frequency as the project runs, thus lowering the operating cost of the project in the long run.

58 GEOSCIENCES↗
NASA NTRS1979

On the average configuration of the geomagnetic tail

A statistical study of the geomagnetic tail has revealed large scale variations in the field configuration both in N-S and E-W directions. The largest value of the B(z) component of the field was observed near the midplane of the tail. Results, such as the discovery of more depolar fields near the flanks of the tail can be incorporated into more realistic models, which should lead to a better understanding of tail behavior. The observed dependence of the tail on interplanetary sector structure may be interpreted in terms of models linking interplanetary field lines to those of the earth.

Fairfield, D. H.↗
DOE OSTI2024

Search for a light CP-odd Higgs boson decaying into a pair of τ -leptons in proton-proton collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

This paper reports a search for a light CP-odd scalar resonance with a mass of 20 GeV to 90 GeV in 13 TeV proton-proton collision data with an integrated luminosity of 140 fb -1 collected with the ATLAS detector at the Large Hadron Collider. The analysis assumes the resonance is produced via gluon-gluon fusion and decays into a $τ^+ τ^-$ pair which subsequently decays into a fully leptonic $µ^+ ν_µ \overline{ν}_τ e^- \overline{ν}_ e ν_τ$ or $e^+ ν_e \overline{ν}_τ µ^- \overline{ν}_µ ν_τ$ final state. No significant excess of events above the predicted Standard Model background is observed. The results are interpreted within a favour-aligned two-Higgs-doublet model, and a model independent cross-section interpretation is also given. Upper limits at 95% confidence level between 3.0 pb and 68 pb are set on the cross-section for producing a CP-odd Higgs boson that decays into a $τ^+ τ^-$ pair.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Search for supersymmetry in events with a photon, a lepton, and missing transverse momentum in proton-proton collisions at s = 13 TeV

Results of a search for supersymmetry are presented using events with a photon, an electron or muon, and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 35.9 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} =$ 13 TeV, produced by the LHC and collected with the CMS detector in 2016. Theoretical models with gauge-mediated supersymmetry breaking predict events with photons in the final state, as well as electroweak gauge bosons decaying to leptons. Searches for events with a photon, a lepton, and missing transverse momentum are sensitive probes of these models. No excess of events is observed beyond expectations from standard model processes. The results of the search are interpreted in the context of simplified models inspired by gauge-mediated supersymmetry breaking. These models are used to derive upper limits on the production cross sections and set lower bounds on masses of supersymmetric particles. Gaugino masses below 930 GeV are excluded at the 95% confidence level in a simplified model with electroweak production of a neutralino and chargino. For simplified models of gluino and squark pair production, gluino masses up to 1.75 TeV and squark masses up to 1.43 TeV are excluded at the 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1975

On the nature of the intercloud medium

Previous analyses of Copernicus observations of interstellar absorption in the spectra of unreddened stars are reviewed in the framework of steady-state ionization models for the intercloud (low-density) component of the interstellar medium. A simple homogeneous model is described which accounts for the H, C, N, S, and Si interstellar lines in the spectrum of lambda Sco in terms of an extensive low-density medium photoionized by Lyman continuum radiation from the II Sco OB association. Quantitative constraints are placed on the maximum permissible flux of diffuse soft X-rays, and the model is generalized to interpret the observed ion, electron, and hydrogen column densities in the low-density medium. Severe constraints are found to be imposed on ionization models by the ratios Si III/Si, Si IV/Si, and S IV/S. It is concluded that the observations may be explained if 10 to 30% of a representative line of sight passes through a photoionized medium of density 0.1 to 0.2/cu cm, if H I constitutes the bulk of the gas along the line of site, and if the gas is at a similar density or is in the form of shielded clumps or clouds.

Hill, J. K.↗
NASA NTRS1991

Theoretical description of spectral line profiles of parent molecules in cometary comae

The present overview of cometary spectral-line profiles obtainable through advancements in high-resolution spectroscopic studies, which allow the retrieval of coma kinematic properties from velocity-resolved spectral-line profiles, incorporates the most important gas dynamic processes into an outflow model which is tailored to the interpretation of spectroscopic observations of parent molecules. The model is then used to study the influence on parent-molecule spectral line profile formation of the field-of-view, the expansion velocity, the kinetic temperature, and the anisotropic outflow distributions.

Hu, Hong-Yao↗
NASA NTRS2017

Validation of Fatigue Modeling Predictions in Aviation Operations

Bio-mathematical fatigue models that predict levels of alertness and performance are one potential tool for use within integrated fatigue risk management approaches. A number of models have been developed that provide predictions based on acute and chronic sleep loss, circadian desynchronization, and sleep inertia. Some are publicly available and gaining traction in settings such as commercial aviation as a means of evaluating flight crew schedules for potential fatigue-related risks. Yet, most models have not been rigorously evaluated and independently validated for the operations to which they are being applied and many users are not fully aware of the limitations in which model results should be interpreted and applied.

operational safety↗
DOE OSTI2018

Search for B-L R -parity-violating top squarks in $\sqrt{s}$=13TeV pp collisions with the ATLAS experiment

A search for direct pair production of top squarks in final states with two tau leptons, b -jets, and missing transverse momentum is presented. The analysis is based on proton-proton collision data at √s = 13 TeV corresponding to an integrated luminosity of 36.1 fb -1 recorded with the ATLAS detector at the Large Hadron Collider in 2015 and 2016. Two exclusive channels with either two hadronically decaying tau leptons or one hadronically and one leptonically decaying tau lepton are considered. No significant deviation from the Standard Model predictions is observed in the data. The analysis results are interpreted in terms of model-independent limits and used to derive exclusion limits on the masses of the top squark $\tilde{t}_{1}$ and the tau slepton $\tilde{τ}_{1}$ in a simplified model of supersymmetry with a nearly massless gravitino. In this model, masses up to m ($\tilde{t}_{1}$) = 1.16 TeV and m ($\tilde{τ}_{1}$) = 1.00 TeV are excluded at 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2011

Strike-Slip Fault Patterns on Europa: Obliquity or Polar Wander?

Variations in diurnal tidal stress due to Europa's eccentric orbit have been considered as the driver of strike-slip motion along pre-existing faults, but obliquity and physical libration have not been taken into account. The first objective of this work is to examine the effects of obliquity on the predicted global pattern of fault slip directions based on a tidal-tectonic formation model. Our second objective is to test the hypothesis that incorporating obliquity can reconcile theory and observations without requiring polar wander, which was previously invoked to explain the mismatch found between the slip directions of 192 faults on Europa and the global pattern predicted using the eccentricity-only model. We compute predictions for individual, observed faults at their current latitude, longitude, and azimuth with four different tidal models: eccentricity only, eccentricity plus obliquity, eccentricity plus physical libration, and a combination of all three effects. We then determine whether longitude migration, presumably due to non-synchronous rotation, is indicated in observed faults by repeating the comparisons with and without obliquity, this time also allowing longitude translation. We find that a tidal model including an obliquity of 1.2?, along with longitude migration, can predict the slip directions of all observed features in the survey. However, all but four faults can be fit with only 1? of obliquity so the value we find may represent the maximum departure from a lower time-averaged obliquity value. Adding physical libration to the obliquity model improves the accuracy of predictions at the current locations of the faults, but fails to predict the slip directions of six faults and requires additional degrees of freedom. The obliquity model with longitude migration is therefore our preferred model. Although the polar wander interpretation cannot be ruled out from these results alone, the obliquity model accounts for all observations with a value consistent with theoretical expectations and cycloid modeling.

Rhoden, Alyssa Rose↗
DOE OSTI2024

Automatic Loss Factor Modeling and Attribution on Unlabeled PV Energy Data

We present a novel approach for modeling the loss factors of photovoltaic power generation systems (PV systems). This method is a white-box machine learning model built on convex optimization that is fast, interpretable, and auditable. It takes as an input the measured daily energy produced by the system, over a multi-year period, and returns a multiplicative decomposition model of the daily energy signal and full attribution of the total energy loss to each feature. The methods section of this paper has two major components: (1) the description of the signal decomposition (SD) model, expressed in the SD framework, and (2) the attribution of total energy losses via Shapley values. We validate the method on synthetic and open-source data sets and compare to similar methods from the literature.

artificial intelligence↗
DOE OSTI2018

Large proton cumulants from the superposition of ordinary multiplicity distributions

We construct here a multiplicity distribution characterized by large factorial cumulants (integrated correlation functions) from a simple combination of two ordinary multiplicity distributions characterized by small factorial cumulants. We find that such a model, which could be interpreted as representing two event classes, reproduces the preliminary data for the proton cumulants measured by the STAR collaboration at 7.7 GeV very well. This model then predicts very large values for the fifth and sixth order factorial cumulants, which can be tested in experiment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1980

Outer satellite atmospheres: Their extended nature and planetary interactions

Highly developed numerical models are applied to interpret extended-atmosphere data for the sodium cloud of Io and the hydrogen torus of Titan. Solar radiation pressure was identified and verified by model calculations as the mechanism to explain two different east-west asymmetries observed in the sodium cloud. Analysis of sodium line profile data, suggesting that a Jupiter magnetospheric wind may be responsible for high speed sodium atoms emitted from Io, and preliminary modeling of the interaction of the Io plasma torus and Io's sodium cloud are also reported. Models presented for Titan's hydrogen torus are consistent both with the recent Pioneer 11 measurements and earlier Earth-orbiting observations by the Copernicus satellite. Progress is reported on developing models for extended gas and dust atmospheres of comets.

Smyth, W. H.↗
NASA NTRS2011

Fermi/GBM Observations of SGRJ0501 + 4516 Bursts

We present our temporal and spectral analyses of 29 bursts from SGRJ0501+4516, detected with the Gamma-ray Burst Monitor onboard the Fermi Gamma-ray Space Telescope during the 13 days of the source activation in 2008 (August 22 to September 3). We find that the T(sub 90) durations of the bursts can be fit with a log-normal distribution with a mean value of approx. 123 ms. We also estimate for the first time event durations of Soft Gamma Repeater (SGR) bursts in photon space (i.e., using their deconvolved spectra) and find that these are very similar to the T(sub 90)s estimated in count space (following a log-normal distribution with a mean value of approx. 124 ms). We fit the time-integrated spectra for each burst and the time-resolved spectra of the five brightest bursts with several models. We find that a single power law with an exponential cutoff model fits all 29 bursts well, while 18 of the events can also be fit with two black body functions. We expand on the physical interpretation of these two models and we compare their parameters and discuss their evolution. We show that the time-integrated and time-resolved spectra reveal that E(sub peak) decreases with energy flux (and fluence) to a minimum of approx. 30 keV at F = 8.7 x 10(exp -6)erg/sq cm/s, increasing steadily afterwards. Two more sources exhibit a similar trend: SGRs J1550 - 5418 and 1806 - 20. The isotropic luminosity, L(sub iso), corresponding to these flux values is roughly similar for all sources (0.4 - l.5 x 10(exp 40) erg/s.

Lin, Lin↗
DOE OSTI2022

Survival analysis of localized prostate cancer with deep learning

In recent years, data-driven, deep-learning-based models have shown great promise in medical risk prediction. By utilizing the large-scale Electronic Health Record data found in the U.S. Department of Veterans Affairs, the largest integrated healthcare system in the United States, we have developed an automated, personalized risk prediction model to support the clinical decision-making process for localized prostate cancer patients. This method combines the representative power of deep learning and the analytical interpretability of parametric regression models and can implement both time-dependent and static input data. To collect a comprehensive evaluation of model performances, we calculate time-dependent C-statistics C td over 2-, 5-, and 10-year time horizons using either a composite outcome or prostate cancer mortality as the target event. The composite outcome combines the Prostate-Specific Antigen (PSA) test, metastasis, and prostate cancer mortality. Our longitudinal model Recurrent Deep Survival Machine (RDSM) achieved C td 0.85 (0.83), 0.80 (0.83), and 0.76 (0.81), while the cross-sectional model Deep Survival Machine (DSM) attained C td 0.85 (0.82), 0.80 (0.82), and 0.76 (0.79) for the 2-, 5-, and 10-year composite (mortality) outcomes, respectively. In addition to estimating the survival probability, our method can quantify the uncertainty associated with the prediction. The uncertainty scores show a consistent correlation with the prediction accuracy. We find PSA and prostate cancer stage information are the most important indicators in risk prediction. Our work demonstrates the utility of the data-driven machine learning model in prostate cancer risk prediction, which can play a critical role in the clinical decision system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Revisiting Reentry Roll Resonance

Here, this paper revisits the subject of reentry roll resonance, which occurs when the roll rate and pitch frequency become equal in a spinning reentry vehicle. A first-principles model is developed and analyzed numerically and by using a reduced-order pendulum model for the relative phase of the roll and pitch/yaw axes. The results show good qualitative agreement with recent flight data and provide a natural physical interpretation. Based on the model it is suggested that sustained roll resonance depends primarily on the initial phase relationship between the pitch and roll axes, in addition to the vehicle moments of inertia and the vehicle symmetry. Finally the model is used to propose a mechanism for sustained resonance in vehicles spinning about a major axis, a condition previously thought to be forbidden.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the field of fluid mechanics. Although these methods are proven successful for many applications, there is a grand challenge of improving their generalizability. This is particularly essential when data-driven models are employed within outer-loop applications like optimization. In this work, we put forth a physics-guided machine learning (PGML) framework that leverages the interpretable physics-based model with a deep learning model. Leveraging a concatenated neural network design from multi-modal data sources, the PGML framework is capable of enhancing the generalizability of data-driven models and effectively protects against or inform about the inaccurate predictions resulting from extrapolation. We apply the PGML framework as a novel model fusion approach combining the physics-based Galerkin projection model and long- to short-term memory (LSTM) network for parametric model order reduction of fluid flows. We demonstrate the improved generalizability of the PGML framework against a purely data-driven approach through the injection of physics features into intermediate LSTM layers. Our quantitative analysis shows that the overall model uncertainty can be reduced through the PGML approach, especially for test data coming from a distribution different than the training data. Moreover, we demonstrate that our approach can be used as an inverse diagnostic tool providing a confidence score associated with models and observations. The proposed framework also allows for multi-fidelity computing by making use of low-fidelity models in the online deployment of quantified data-driven models.

42 ENGINEERING↗
NASA NTRS2021

Variation of Ice Microphysical Properties With Temperature and Humidity at Tops of Convective Clouds

A better understanding of the many interacting processes governing the evaluation of ice in natural clouds is required to improve the representation of ice clouds in global circulation models. Recent studies suggest a dominant role of vapor growth processes in determining the temperature dependence of cloud top ice sizes and shapes. Using airborne cloud remote sensing along with reanalysis data, here we show that observed cloud top ice effective radii and estimated normalized growth rates at cloud top highly correlate with an approximately linear relationship, which is consistent with a conceptual model also presented. Furthermore, significant differences in crystal shape characteristics and scattering asymmetry parameters are found between sub- and super-saturated cloud tops over ocean, although not over land. These results provide valuable observational targets for studying ice formation and evolution processes using models, while also helping interpretation of satellite observations of ice microphysical properties at cloud tops.

ice↗
NASA NTRSDate not supplied

Parahydrogen Properties Version 05 Database Release for Nuclear Thermal Propulsion Applications

Consistent modeling assumptions across any large project are crucial to minimize errors between different approaches. Use of consistent material and fluid properties across a large project supports consistent interpretation and application within modeling and simulation results as well as their relevancy to operational systems. NASA’s Space Nuclear Propulsion program dedicates extensive resources towards establishing consistent and, to the extent possible, accurate property databases for its internal staff and all external partners. This work highlights the extensive research performed to modernize the fluid property database of hydrogen which is the leading propellant option for in-space nuclear propelled spacecraft. Specifically, the parahydrogen spin state is of interest since the propellant is stored in a near normal boiling point liquid state which results in it consisting almost entirely of the parahydrogen spin isomer. This database tool has taken recent NASA work and modernized it into a python-based package for easy usage across all modeling entities. The package allows users to provide temperature and pressure pairs along with their desired output properties to yield results accounting for both real-gas and equilibrium dissociation effects while also sharing the default thermodynamic reference state provided by the National Institute of Standards and Technology (NIST) Standard Database 23. The suite also includes advanced capabilities to increase usability, such as on-the-fly interpolation and multidimensional plotting.

Nuclear Thermal Propulsion↗