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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 235 records · Page 13
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NASA NTRS2002

Star Formation In the Galaxy and the Fluctuating UV Radiation Field

We examine the formation of massive stars in the Galaxy, the resultant fluctuating UV (ultraviolet) radiation field, and the effect of this field on the star-forming interstellar medium. There are substantial fluctuations of the UV radiation field in space (scales of 100's of parsecs) and time (time-scales of order 100 million years). The FUV (far ultraviolet) (6 eV less than hv less than 13.6 eV) field and the pressure determines whether the thermal balance of the neutral gas results in cold clouds or warm (T approx. 10(exp 4) K) neutral medium. We show how to calculate the average fractions of the gas in the cold and warm phases when the interstellar gas is subject to this fluctuating FUV field. The knowledge of how these fractions depend on the gas properties and on the FUV sources is a basic step in building a model of the large scale behavior of the ISM (interstellar medium) and the mutual relation between the ISM and the star formation rate.

Hollenbach, David↗
NASA NTRS2002

The LWS Geospace Storm Investigations Exploring the Extremes of Space Weather

The Geospace mission of the Living With a Star program is a family of investigations focusing on the compelling science questions that advance our ability to specify, understand, and predict the societal impact of solar variance. Two key areas have been identified as combining both importance to society and potential for scientific progress: 1) characterization and understanding of the acceleration, global distribution, and variability of energetic electrons and ions in the inner magnetosphere, and 2) characterization and understanding of the ionosphere and irregularities that affect communications, navigation and radar systems. Under these broad categories specific science questions have emerged as the priority science objectives for the first Geospace Investigations: How and why do relativistic electrons in the outer zone and slot region vary during geomagnetic storms? How does the long- and short-term variability of the Sun affect the global-scale behavior of the ionospheric electron density and irregularities, especially during magnetic storms and at mid-latitudes? The first Geospace mission will attempt to answer these questions.

Source record↗
NASA NTRS2003

Elastic Properties of Films of Water and Noble Gases Condensed at Low Temperatures

We have shown that there are extensive similarities between the quench-condensed noble gas films and those of amorphous water ice. In particular, both can be quite soft upon deposition and can stiffen considerably when annealed. Furthermore, this stiffening follows a logarithmic time dependence for all substances. The temperature dependence of these behaviors scales with the triple point. The results shown here show a strong thickness dependence, which has implications for any study of mechanical properties of films on substrates. The temperature dependence of the stiffening and the stiffening rate have now been characterized for the noble gases, and these observations provide a roadmap for new experiments on amorphous water ice.

Pohl, Robert O.↗
NASA NTRS1999

Turbulent Concentration of Chondrules: Size Distribution and Multifractal Scaling

Size-selective concentration of particles in 3D turbulence may be related to collection of chondrules and other constituents into primitive bodies in a weakly turbulent protoplanetary nebula. In the terrestrial planet region, both the characteristic size and narrow size distribution of chondrules are explained, whereas "fluffier" particles would be concentrated in lower density, or more intensely turbulent, regions of the nebula. The spatial distribution of concentrated particle density obeys multifractal scaling, suggesting a dose tie to the turbulent cascade process. This scaling behavior allows predictions of the concentration probabilities to be made in the protoplanetary nebula, which are so large (> 10(exp 3) - 10(exp 4)) that further studies must be made of the role of mass loading.

Cuzzi, Jeffrey N.↗
NASA NTRS2009

A Comparative Study of a 1/4-Scale Gulfstream G550 Aircraft Nose Gear Model

A series of fluid dynamic and aeroacoustic wind tunnel experiments are performed at the University of Florida Aeroacoustic Flow Facility and the NASA-Langley Basic Aerodynamic Research Tunnel Facility on a high-fidelity -scale model of Gulfstream G550 aircraft nose gear. The primary objectives of this study are to obtain a comprehensive aeroacoustic dataset for a nose landing gear and to provide a clearer understanding of landing gear contributions to overall airframe noise of commercial aircraft during landing configurations. Data measurement and analysis consist of mean and fluctuating model surface pressure, noise source localization maps using a large-aperture microphone directional array, and the determination of far field noise level spectra using a linear array of free field microphones. A total of 24 test runs are performed, consisting of four model assembly configurations, each of which is subjected to three test section speeds, in two different test section orientations. The different model assembly configurations vary in complexity from a fully-dressed to a partially-dressed geometry. The two model orientations provide flyover and sideline views from the perspective of a phased acoustic array for noise source localization via beamforming. Results show that the torque arm section of the model exhibits the highest rms pressures for all model configurations, which is also evidenced in the sideline view noise source maps for the partially-dressed model geometries. Analysis of acoustic spectra data from the linear array microphones shows a slight decrease in sound pressure levels at mid to high frequencies for the partially-dressed cavity open model configuration. In addition, far field sound pressure level spectra scale approximately with the 6th power of velocity and do not exhibit traditional Strouhal number scaling behavior.

Khorrami, Mehdi R.↗
NASA NTRS2009

Understanding the Scalability of Bayesian Network Inference using Clique Tree Growth Curves

Bayesian networks (BNs) are used to represent and efficiently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to perform computation in BNs is clique tree clustering and propagation. In this approach, BN computation consists of propagation in a clique tree compiled from a Bayesian network. There is a lack of understanding of how clique tree computation time, and BN computation time in more general, depends on variations in BN size and structure. On the one hand, complexity results tell us that many interesting BN queries are NP-hard or worse to answer, and it is not hard to find application BNs where the clique tree approach in practice cannot be used. On the other hand, it is well-known that tree-structured BNs can be used to answer probabilistic queries in polynomial time. In this article, we develop an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN's non-root nodes to the number of root nodes, or (ii) the expected number of moral edges in their moral graphs. Our approach is based on combining analytical and experimental results. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for each set. For the special case of bipartite BNs, we consequently have two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, we systematically increase the degree of the root nodes in bipartite Bayesian networks, and find that root clique growth is well-approximated by Gompertz growth curves. It is believed that this research improves the understanding of the scaling behavior of clique tree clustering, provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms, and presents an aid for analytical trade-off studies of clique tree clustering using growth curves.

Mengshoel, Ole Jakob↗
NASA NTRS2010

DEM Solutions Develops Answers to Modeling Lunar Dust and Regolith

With the proposed return to the Moon, scientists like NASA-KSC's Dr. Calle are concerned for a number of reasons. We will be staying longer on the planet's surface, future missions may include dust-raising activities, such as excavation and handling of lunar soil and rock, and we will be sending robotic instruments to do much of the work for us. Understanding more about the chemical and physical properties of lunar dust, how dust particles interact with each other and with equipment surfaces and the role of static electricity build-up on dust particles in the low-humidity lunar environment is imperative to the development of technologies for removing and preventing dust accumulation, and successfully handling lunar regolith. Dr. Calle is currently working on the problems of the electrostatic phenomena of granular and bulk materials as they apply to planetary surfaces, particularly to those of Mars and the Moon, and is heavily involved in developing instrumentation for future planetary missions. With this end in view, the NASA Kennedy Space Center's Innovative Partnerships Program Office partnered with OEM Solutions, Inc. OEM Solutions is a global leader in particle dynamics simulation software, providing custom solutions for use in tackling tough design and process problems related to bulk solids handling. Customers in industries such as pharmaceutical, chemical, mineral, and materials processing as well as oil and gas production, agricultural and construction, and geo-technical engineering use OEM Solutions' EDEM(TradeMark) software to improve the design and operation of their equipment while reducing development costs, time-to-market and operational risk. EDEM is the world's first general-purpose computer-aided engineering (CAE) tool to use state-of-the-art discrete element modeling technology for the simulation and analysis of particle handling and manufacturing operations. With EDEM you'can quickly and easily create a parameterized model of your granular solids system. Computer-aided design (CAD) models of real particles can be imported to obtain an accurate representation of their shape. EDEM(TradeMark) uses particle-scale behavior models to simulate bulk solids behavior. In addition to particle size and shape, the models can account for physical properties of particles along with interaction between particles and with equipment surfaces and surrounding media, as needed to define the physics of a particular process.

Dunn, Carol Anne↗
NASA NTRS2010

Understanding the Scalability of Bayesian Network Inference Using Clique Tree Growth Curves

One of the main approaches to performing computation in Bayesian networks (BNs) is clique tree clustering and propagation. The clique tree approach consists of propagation in a clique tree compiled from a Bayesian network, and while it was introduced in the 1980s, there is still a lack of understanding of how clique tree computation time depends on variations in BN size and structure. In this article, we improve this understanding by developing an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN s non-root nodes to the number of root nodes, and (ii) the expected number of moral edges in their moral graphs. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for the total size of each set. For the special case of bipartite BNs, there are two sets and two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, where random bipartite BNs generated using the BPART algorithm are studied, we systematically increase the out-degree of the root nodes in bipartite Bayesian networks, by increasing the number of leaf nodes. Surprisingly, root clique growth is well-approximated by Gompertz growth curves, an S-shaped family of curves that has previously been used to describe growth processes in biology, medicine, and neuroscience. We believe that this research improves the understanding of the scaling behavior of clique tree clustering for a certain class of Bayesian networks; presents an aid for trade-off studies of clique tree clustering using growth curves; and ultimately provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms.

Mengshoel, Ole J.↗
NASA NTRS2016

A Comparison of the Noise Characteristics of a Conventional Slat and Krueger Flap

An aeroacoustic test of two types of leading-edge high-lift devices has been conducted in the NASA Langley Quiet Flow Facility. The test compares a conventional slat with a notional equivalent-mission Krueger flap. The test matrix includes points that allow for direct comparison of the conventional and Krueger devices for equivalent-mission configurations, where the two high-lift devices satisfy the same lift requirements for a free air flight path at the same cruise airfoil angle of attack. Measurements are made for multiple Mach numbers and directivity angles. Results indicate that the Krueger flap shows similar agreement to the expected power law scaling of a conventional flap, both in terms of Strouhal number and fixed frequency (as a surrogate for Helmholtz number). Directivity patterns vary depending on the specific slat and Krueger orientations. Varying the slat gap while holding overlap constant has the same influence on both the conventional slat and Krueger flap acoustic signature. Closing the gap shows dramatic reduction in levels for both devices. Varying the Krueger overlap has a different effect on the data when compared to varying the slat overlap, but analysis is limited by acoustic sources that regularly present themselves in model-scale wind tunnel testing but are not present for full-scale vehicles. The Krueger cavity is found to have some influence on level and directivity, though not as much as the other considered parameter variations. Overall, while the spectra of the two devices are different in detail, their scaling behavior for varying parameters is extremely similar.

Bahr, Christopher J.↗
NASA NTRS2019

The Southern Ocean Sea Surface Temperature Response to Ozone Depletion: A Multi-Model Comparison

The effect of the Antarctic ozone hole extends downwards from the stratosphere, with clear signatures in surface weather patterns including a positive trend in the Southern Annular Mode (SAM). Several recent studies have used coupled climate models to investigate the impact of these changes on Southern Ocean sea surface temperature (SST), notably motivated by the observed cooling from the late 1970s. Here we examine the robustness of these model results through comparison of both previously published and new simulations. We focus on the calculation of ‘climate response functions' (CRFs), transient responses to an instantaneous step-change in ozone concentrations. The CRF for most models consists of a rapid cooling of SST, followed by a slower warming trend. However, inter-model comparison reveals large uncertainties, such that even the sign of the impact of ozone depletion on historical SST, when reconstructed from the CRF, remains unconstrained. Comparison of these CRFs with SST responses to a hypothetical step-change in the SAM, inferred through lagged linear regression, shows broadly similar results. Causes of uncertainty are explored by examining relationships between model climatologies and their CRFs. The inter-model spread in CRFs can be reproduced by varying a single subgrid-scale mixing parameter within a single model. Antarctic sea-ice CRFs are also calculated: these do not generally exhibit the two-time-scale behavior of SST, suggesting a complex relationship between the two. Finally, by constraining model climatology-response relationships with observational values, we conclude that ozone depletion in unlikely to have been the primary driver of the observed SST cooling trend.

Climate response functions (CRF)↗
NASA NTRS2021

The NANOGrav 12.5 Year Data Set: Monitoring Interstellar Scattering Delays

We extract interstellar scintillation parameters for pulsars observed by the NANOGrav radio pulsar timing program. Dynamic spectra for the observing epochs of each pulsar were used to obtain estimates of scintillation timescales, scintillation bandwidths, and the corresponding scattering delays using a stretching algorithm to account for frequency-dependent scaling. We were able to measure scintillation bandwidths for 28 pulsars at1500 MHz and 15 pulsars at 820 MHz. We examine scaling behavior for 17 pulsars and find power-law indices ranging from−0.7 to−3.6, though these may be biased shallow due to insufficient frequency resolution at lower frequencies. We were also able to measure scintillation timescales for six pulsars at 1500 MHz and seven pulsars at820 MHz. There is fair agreement between our scattering delay measurements and electron-density model predictions for most pulsars. We derive interstellar scattering-based transverse velocities assuming isotropic scattering and a scattering screen halfway between the pulsar and Earth. We also estimate the location of the scattering screens assuming proper motion and interstellar scattering-derived transverse velocities are equal. We find no correlations between variations in scattering delay and either variations in dispersion measure or flux density. For most pulsars for which scattering delays are measurable, we find that time-of-arrival uncertainties for a given epoch are larger than our scattering delay measurements, indicating that variable scattering delays are currently subdominant in our overall noise budget but are important for achieving precisions of tens of nanoseconds or less.

Jacob E Turner↗
DOE OSTI2026

Neural Scaling Laws for Jet Generation

Recently observed empirical scaling laws describe the performance of foundation-type models as three independent key quantities -- dataset size, compute, and model parameters -- are modified. Extracting these scaling laws informs the training of large complex models for which the tuning of hyperparameters in traditional ways is not feasible. This work for the first time explores if scaling laws can also be observed for the task of particle jet generation -- both relevant as a pre-training objective for foundation models and as in-situ simulation by itself. We indeed replicate the key logarithmic scaling law behavior for model-size scaling. Beyond studying the next token prediction validation loss of the generative model, we also study the sliced Wasserstein distance of five physical quantities that are not immediately available to the model during training. Our study shows that this quantity is monotonically related to the next token prediction validation loss, meaning that this loss is indeed a good proxy for the physics performance. For the scaling with dataset size and compute, we observe substantially weaker scaling behavior of both the loss and the sliced Wasserstein distance. We analyze this behavior by introducing the concept of a learnable window, and argue that autoregressive next token prediction on jet constituents exhibits comparatively rapid saturation relative to language-model studies. We discuss possible origins of this behavior, including the stochastic nature of QCD radiation and differences between generative and supervised learning tasks in collider physics.

Amram, Oz [Fermilab]↗
NASA NTRS2001

Cloud Structure and Cloud-Radiation Interaction: From Smallest Observable Scales (Less than 10 m) to GCM Grid Scales (More than 100 km)

In this presentation we review the fractal nature of internal cloud structure from cm- to km-scales as captured by in-situ probes during long horizontal penetrations by aircraft. We uncover the non-Poissonian spatial distribution of cloud droplets at submeter scales and confirm scale-invariant behavior for large scales. Based on these structural characteristics, we generate simple fractal cloud models that reproduce statistical scaling properties of real clouds. These stochastic models represent a link between nonlinear science, in general, and cloud-radiation interaction, in particular. Next we run three-dimensional radiative transfer computations on these synthetic fractal clouds and compare the structure of the resulting radiation fields with the known structure of the cloud model and with satellite images of real clouds. The different behaviors observed for small and large-scale variabilities will be discussed in detail. We find that while the large-scale fluctuations of the resulting radiation fields resemble those in the original scale-invariant cloud structure, the radiation at small scales is much smoother than its cloud liquid water counterpart. This violates scale-invariance and produces a scale-break at 0.2-0.5 km that is clearly observed in high-resolution satellite data such as from Landsat. Finally, we show how radiative transfer Green function theory in the photon diffusion limit explains (and predicts) the above phenomena of "radiative smoothing."

Marshak, Alexander↗
DOE OSTI2022

Role of α → ε → α phase transformation on the spall behavior of iron at atomic scales

Shock compression of iron microstructures above a threshold stress results in a α (BCC) → ε (HCP) transformation and the propagation of the release wave brings the metal back to the α phase following the ε→α transformation. Predicting failure behavior under shock loading conditions (spallation) relies on understanding the evolution of defects in the microstructure as it undergoes the α→ε→α phase transformation. This study uses molecular dynamics (MD) simulations to investigate the role of defect evolution during α→ε→α phase transformation on the spall strength values of single-crystal (sc) Fe microstructures. The MD simulations aim to characterize the ε phase fraction formed during shock compression and the defects during shock release for variations in loading orientations and shock stresses. The simulations are carried out for loading along the [100], [110], [111], and [112] orientations and for impact velocities ranging from 600 m/s to 1 km/s. The ε phase fractions during compression and defects (dislocations, twins) characterized during spall failure show an orientation dependence that affects the spall strength values. Here, the lowest value for spall strength is observed for the <110> loading orientation that shows a high density of twinning at the spall plane, whereas the highest value is observed for the <100> orientation and is associated with a α (BCC) → γ (FCC) transformation at the spall plane. The correlations of the spall strength values with the strain rates and with the ε phase fractions are discussed.

36 MATERIALS SCIENCE↗
NASA NTRS2013

Predicting Pilot Behavior in Medium Scale Scenarios Using Game Theory and Reinforcement Learning

Effective automation is critical in achieving the capacity and safety goals of the Next Generation Air Traffic System. Unfortunately creating integration and validation tools for such automation is difficult as the interactions between automation and their human counterparts is complex and unpredictable. This validation becomes even more difficult as we integrate wide-reaching technologies that affect the behavior of different decision makers in the system such as pilots, controllers and airlines. While overt short-term behavior changes can be explicitly modeled with traditional agent modeling systems, subtle behavior changes caused by the integration of new technologies may snowball into larger problems and be very hard to detect. To overcome these obstacles, we show how integration of new technologies can be validated by learning behavior models based on goals. In this framework, human participants are not modeled explicitly. Instead, their goals are modeled and through reinforcement learning their actions are predicted. The main advantage to this approach is that modeling is done within the context of the entire system allowing for accurate modeling of all participants as they interact as a whole. In addition such an approach allows for efficient trade studies and feasibility testing on a wide range of automation scenarios. The goal of this paper is to test that such an approach is feasible. To do this we implement this approach using a simple discrete-state learning system on a scenario where 50 aircraft need to self-navigate using Automatic Dependent Surveillance-Broadcast (ADS-B) information. In this scenario, we show how the approach can be used to predict the ability of pilots to adequately balance aircraft separation and fly efficient paths. We present results with several levels of complexity and airspace congestion.

Game Theory↗
NASA NTRS1983

Simulation of turbulent shear flows at Stanford and NASA-Ames - What can we do and what have we learned?

The capabilities and limitations of large eddy simulation (LES) and full turbulence simulation (FTS) are outlined. It is pointed out that LES, although limited at the present time by the need for periodic boundary conditions, produces large-scale flow behavior in general agreement with experiments. What is more, FTS computations produce small-scale behavior that is consistent with available experiments. The importance of the development work being done on the National Aerodynamic Simulator is emphasized. Studies at present are limited to situations in which periodic boundary conditions can be applied on boundaries of the computational domain where the flow is turbulent.

Reynolds, W. C.↗