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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Large-scale effects on the regulation of tropical sea surface temperature

The dominant terms in the surface energy budget of the tropical oceans are absorption of solar radiation and evaporative cooling. If it is assumed that relative humidity in the boundary layer remains constant, evaporative cooling will increase rapidly with sea surface temperature (SST) because of the strong temperature dependence of saturation water vapor pressure. The resulting stabilization of SST provided by evaporative cooling is sufficient to overcome positive feedback contributed by the decrease of surface net longwave cooling with increasing SST. Evaporative cooling is sensitive to small changes in boundary-layer relative humidity. Large and negative shortwave cloud forcing in the regions of highest SST are supported by the moisture convergence associated with largescale circulations. In the descending portions of these circulations the shortwave cloud forcing is suppressed. When the effect of these circulations is taken into account by spatial averaging, the area-averaged cloud forcing shows no sensitivity to area-averaged SST changes associated with the 1987 warming event in the tropical Pacific. While the shortwave cloud forcing is large and important in the convective regions, the importance of its role in regulating the average temperature of the tropics and in modulating temperature gradients within the tropics is less clear. A heuristic model of SST is used to illustrate the possible role of large-scale atmospheric circulations on SST in the tropics and the coupling between SST gradients and mean tropical SST. The intensity of large-scale circulations responds sensitivity to SST gradients and affects the mean tropical SST by supplying dry air to the planetary boundary layer. Large SST gradients generate vigorous circulations that increase evaporation and reduce the mean SST.

Hartmann, Dennis L.↗
NASA NTRS1994

Large-scale processes in the solar nebula

Theoretical models of the structure of a minimum mass solar nebula should be able to provide the physical context to help evaluate the efficacy of any mechanism proposed for the formation of chondrules or Ca, Al-rich inclusions (CAI's). These models generally attempt to use the equations of radiative hydrodynamics to calculate the large-scale structure of the solar nebula throughout the planet-forming region. In addition, it has been suggested that chondrules and CAI's (=Ch&CAI's) may have been formed as a direct result of large-scale nebula processing such as passage of material through high-temperature regions associated with the global structure of the nebula. In this report we assess the status of global models of solar nebula structure and of various related mechanisms that have been suggested for Ch and CAI formation.

Boss, A. P.↗
NASA NTRS1986

Small-scale motions observed by aircraft in the tropical lower stratosphere - Evidence for mixing and its relationship to large-scale flows

Measurements of temperature and ozone from instrumented aircraft in the tropical lower stratosphere show the presence of small-scale disturbances generated by underlying cumulus convection and Kelvin-Helmholtz instability. The disturbances associated with underlying convection have peak-to-peak vertical parcel excursions of about 300 m. Flying conditions were smooth, suggesting an ensemble of gravity waves and little or no turbulent mixing. It is nevertheless possible that these waves break at other altitudes, leading to turbulent mixing and net fluxes of vertically stratified tracers. Disturbances attributed to KH instability implied vertical parcel excursions of 300-400 m. The disturbances coincided with rough flying conditions, suggesting turbulent mixing. A linear stability analysis of the atmospheric basic state defined by high-resolution radiosondes shows fastest growing waves with horizontal wavelengths of 1.4-1.8 km, consistent with the aircraft observations. The strong shears responsible for the KH instability are due to large-scale waves propagating into a region of small intrinsic frequency. Radiosonde observations show that the zonal length scale of these waves is about 1000 km.

Pfister, Leonhard↗
NASA NTRS2016

Ice Accretion Test Results for Three Large-Scale Swept-Wing Models in the NASA Icing Research Tunnel

The design and certification of modern transport airplanes for flight in icing conditions increasing relies on three-dimensional numerical simulation tools for ice accretion prediction. There is currently no publically available, high-quality, ice accretion database upon which to evaluate the performance of icing simulation tools for large-scale swept wings that are representative of modern commercial transport airplanes. The purpose of this presentation is to present the results of a series of icing wind tunnel test campaigns whose aim was to provide an ice accretion database for large-scale, swept wings.

Wind-Tunnel Tests↗
DOE OSTI2021

Galaxy assembly bias and large-scale distribution: a comparison between IllustrisTNG and a semi-analytic model

In this work, we compare large scale structure observables for stellar mass selected samples at z = 0, as predicted by two galaxy models, the hydrodynamical simulation IllustrisTNG and the Santa-Cruz semi-analytic model (SC-SAM). Although both models have been independently calibrated to match observations, rather than each other, we find good agreement between the two models for two-point clustering and galaxy assembly bias signatures. The models also show a qualitatively similar response of occupancy and clustering to secondary halo parameters other than mass, such as formation history and concentration, although with some quantitative differences. Thus, our results demonstrate that the galaxy–halo relationships in SC-SAM and TNG are quite similar to first order. However, we also find areas in which the models differ. For example, we note a strong correlation between halo gas content and environment in TNG, which is lacking in the SC-SAM, as well as differences in the occupancy predictions for low-mass haloes. Moreover, we show that higher order statistics, such as cumulants of the density field, help us to accurately describe the galaxy distribution and discriminate between models that show degenerate behaviour for two-point statistics. Our results suggest that SAMs are a promising cost-effective and intuitive method for generating mock catalogues for next generation cosmological surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Framework for Large-scale Implementation of Wholesale-Retail Transactive Control Mechanism

Transactive energy is a control technique that uses market mechanisms to achieve desired control objectives. Several simulation studies and field demonstrations were carried out in recent years, but all focused on small scale systems and purpose-built simplified models which are not always capable of pointing out all the advantages and shortcomings of transac- tive energy methods. This work describes a co-simulation framework built on a hierarchical control architecture that allows for conducting studies of the impacts of a very large-scale deployment of transactive energy. The hierarchical transactive control architecture adopted in this work helps with alleviating computation and communication burden to facilitate a more effective large scale real-time market operation among device level resources and the system level operators. The co-simulation framework is evaluated an integrated power sys- tem model of unprecedented scale composed of the Western Electricity Coordination Council (WECC) transmission system with tens of thousands of distribution systems deployed with flexible device-level distributed energy resources (DERs) using off-the-shelf simulators.

Transactive energy, market-based controls, DER int↗
DOE OSTI2020

Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data

Nationwide population-based cohort provides a new opportunity to build an automated risk prediction model based on individuals’ history of health and healthcare beyond existing risk prediction models. We tested the possibility of machine learning models to predict future incidence of Alzheimer’s disease (AD) using large-scale administrative health data. From the Korean National Health Insurance Service database between 2002 and 2010, we obtained de-identified health data in elders above 65 years (N = 40,736) containing 4,894 unique clinical features including ICD-10 codes, medication codes, laboratory values, history of personal and family illness and socio-demographics. To define incident AD we considered two operational definitions: “definite AD” with diagnostic codes and dementia medication (n = 614) and “probable AD” with only diagnosis (n = 2026). We trained and validated random forest, support vector machine and logistic regression to predict incident AD in 1, 2, 3, and 4 subsequent years. For predicting future incidence of AD in balanced samples (bootstrapping), the machine learning models showed reasonable performance in 1-year prediction with AUC of 0.775 and 0.759, based on “definite AD” and “probable AD” outcomes, respectively; in 2-year, 0.730 and 0.693; in 3-year, 0.677 and 0.644; in 4-year, 0.725 and 0.683. The results were similar when the entire (unbalanced) samples were used. Important clinical features selected in logistic regression included hemoglobin level, age and urine protein level. This study may shed a light on the utility of the data-driven machine learning model based on large-scale administrative health data in AD risk prediction, which may enable better selection of individuals at risk for AD in clinical trials or early detection in clinical settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Local and large-scale effects on the astrophysics of void galaxies

ABSTRACT Galaxies in cosmic voids have been reported with properties related to a delayed evolution compared to the rest of the Universe. These characteristics reflect the interaction of galaxies with the environment. However, it is not clear the degree of influence of the large-scale structure on the properties of void galaxies or if these are only influenced by the low local density around them typical of these regions. In this article, we identified cosmic voids in the SDSS-DR16 and studied the g–r colour, star formation rate, and concentration of galaxies. We identified galaxy groups to characterize the local environment and studied the properties of galaxies as a function of total and stellar masses, separately analysing those in voids and the general sample. Our results show that galaxies that inhabit haloes of a given mass (below ${\sim}10^{13.5}{\rm M}_{\odot }$), are bluer, have a higher star formation rate and are less concentrated when the host halo is inside voids compared to other regions. For larger halo masses, the trend disappears. We also analyse whether the properties of galaxies are sensitive to the type of voids that inhabit. This is done by separating voids embedded in overdense regions (S-type) from those that asymptotically converge to the average density of the Universe (R-type). We found that galaxies in R-type voids are bluer, with higher SFR and less concentration than in S-type voids. Our results indicate some degree of correlation of galaxy properties with the large-scale environment provided by voids, suggesting possible second-order mechanisms in galaxy evolution.

Astronomy & Astrophysics↗
DOE OSTI2022

Improving deep learning performance for predicting large-scale geological ${{CO}_{2}}$ sequestration modeling through feature coarsening

Physics-based reservoir simulation for fluid flow in porous media is a numerical simulation method to predict the temporal-spatial patterns of state variables (e.g. pressure p) in porous media, and usually requires prohibitively high computational expense due to its non-linearity and the large number of degrees of freedom (DoF). This work describes a deep learning (DL) workflow to predict the pressure evolution as fluid flows in large-scale 3-dimensional(3D) heterogeneous porous media. In particular, we develop an efficient feature coarsening technique to extract the most representative information and perform the training and prediction of DL at the coarse scale, and further recover the resolution at the fine scale by spatial interpolation. We validate the DL approach to predict pressure field against physics-based simulation data for a field-scale 3D geologic CO 2 sequestration reservoir model. We evaluate the impact of feature coarsening on DL performance, and observe that the feature coarsening not only decreases the training time by >74% and reduces the memory consumption by >75%, but also maintains temporal error 0.63% on average. Besides, the DL workflow provides predictive efficiency with 1406 times speedup compared to physics-based numerical simulation. The key findings from this research significantly improve the training and prediction efficiency of deep learning model to deal with large-scale heterogeneous reservoir models, and thus it can also be further applied to accelerate workflows of history matching and reservoir optimization for close-loop reservoir management.

58 GEOSCIENCES↗
DOE OSTI2025

Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures

The use of active wake mixing (AWM) to mitigate downstream turbine wakes has created new opportunities for reducing power losses in wind farms. However, many current analytical or semi-empirical wake models do not capture the flow instabilities that are excited through the blade pitch actuation. In this work, we develop a framework, which accounts for the impacts of the large-scale coherent structures and turbulence on the mean flow, for modeling AWM. The framework uses a triple-decomposition approach for the unsteady flow field and models the mean flow and fine-scale turbulence with a parabolized Reynolds-averaged Navier–Stokes (RANS) system. The wave components are modeled using a simplified spatial linear stability formulation that captures the growth and evolution of the coherent structures. Comparisons with high-fidelity large eddy simulations (LESs) of the turbine wakes showed that this framework was able to capture the additional wake mixing and faster wake recovery in the far-wake regions for both the pulse and helix AWM strategies with minimal computational expense. In the near-wake region, some differences are observed in both the RANS velocity profiles and initial growth of the large-scale structures, which may be due to some simplifying assumptions used in the model.

17 WIND ENERGY↗
NASA NTRS1994

Latitudinal variability of large-scale coronal temperature and its association with the density and the global magnetic field

In this paper we utilize the latitiude distribution of the coronal temperature during the period 1984-1992 that was derived in a paper by Guhathakurta et al, 1993, utilizing ground-based intensity observations of the green (5303 A Fe XIV) and red (6374 A Fe X) coronal forbidden lines from the National Solar Observatory at Sacramento Peak, and establish it association with the global magnetic field and the density distributions in the corona. A determination of plasma temperature, T, was estimated from the intensity ratio Fe X/Fe XIV (where T is inversely proportional to the ratio), since both emission lines come from ionized states of Fe, and the ratio is only weakly dependent on density. We observe that there is a large-scale organization of the inferred coronal temperature distribution that is associated with the large-scale, weak magnetic field structures and bright coronal features; this organization tends to persist through most of the magnetic activity cycle. These high-temperature structures exhibit time-space characteristics which are similar to those of the polar crown filaments. This distribution differs in spatial and temporal characterization from the traditional picture of sunspot and active region evolution over the range of the sunspot cycle, which are manifestations of the small-scale, strong magnetic field regions.

Guhathakurta, M.↗
DOE OSTI2025

Complexity Reduction Methods for Large-Scale Spatially Explicit Biofuels Network Design

The size and complexity of energy system optimization models have increased significantly in recent years, driven by the availability of high-resolution spatial data. We present complexity reduction and solution methods that enable us to efficiently represent high-resolution spatial data in the network design of large-scale energy systems. We aim to reduce the size and enhance the computational efficiency of network design models without sacrificing solution accuracy. Specifically, we first present how to aggregate highly granular data into larger resolutions without averaging out their specific properties through a composite-curve-based approach and then develop a method to linearly represent these curves. Second, we utilize a general clustering method to determine groups of geographically proximate biomass fields and establish a single transportation arc for all of them, reducing the number of transportation-related variables while maintaining an accurate representation of the system. Finally, we introduce a two-step algorithm that decomposes large-scale network design problems into two smaller, more manageable subproblems. We demonstrate the application of our methods using a case study of switchgrass-to-biofuels network design in the eight states of the U.S. Midwest, using realistic and highly explicit spatial data.

09 BIOMASS FUELS↗
NASA NTRS1984

The concentration of the large-scale solar magnetic field by a meridional surface flow

Analytical and numerical solutions to the magnetic flux transport equation in the absence of new bipolar sources of flux are calculated for several meridional flow profiles and a range of peak flow speeds. It is found that a poleward flow with a broad profile and a nominal 10 m/s maximum speed concentrates the large-scale field into very small caps of less than 15 deg half-angle, with average field strengths of several tens of gauss, contrary to observations. A flow which reaches its peak speed at a relatively low latitude and then decreases rapidly to zero at higher latitudes leads to a large-scale field pattern which is consistent with observations. For such a flow, only lower latitude sunspot groups can contribute to interhemispheric flux annihilation and the resulting decay and reversal of the polar magnetic fields.

Devore, C. R.↗
NASA NTRS1981

Ground test of a large scale 'D' vented thrust deflecting nozzle

Future V/STOL aircraft will require efficient techniques for changing the thrust vector from the vertical direction for VTOL operation to the horizontal direction for conventional flight. Most V/STOL concepts utilize thrust vectoring nozzles to provide this variation in the thrust vector direction. An experimental test program was initiated to demonstrate the capabilities of a large scale 'D' vented thrust deflecting system coupled with a high bypass ratio turbofan engine. Data were obtained for a 'D' vented nozzle mounted behind a YTF-34-F5 turbofan engine. Preliminary data are presented for a variety of test conditions. Attention is given to aspects of 'D' vented nozzle design, the test apparatus, engine-nozzle compatibility, exit area variation, longitudinal vectoring performance, nozzle temperature distribution, and large scale - small scale comparisons.

Rosenberg, E. W.↗
DOE OSTI2020

Modeling of Grid-Forming and Grid-Following Inverters for Dynamic Simulation of Large-Scale Distribution Systems

Historically, distribution system planning studies mainly focused on steady state and quasi-steady state analysis, with limited attention paid to dynamic analysis. This paper develops three-phase, electromechanical models for both grid-forming and grid-following inverters, and integrates them into an open source, three-phase distribution network solver, thereby enabling dynamic simulation of large-scale, three-phase unbalanced distribution systems with high penetration of inverter-based DERs. The proposed inverter models are validated against electromagnetic simulation and field test data from the CERTS/AEP microgrid testbed, and simulated in an islanded 5252 node distribution system in the GridLAB-D simulation environment. Simulation verifies the effectiveness of the proposed inverter models for large-scale distribution system analysis. Finally, study results show that compared to traditional grid-following inverters, the high penetration of grid-forming inverters can improve the voltage and frequency stability of islanded distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Large-scale 2D heterostructures from hydrogen-bonded organic frameworks and graphene with distinct Dirac and flat bands

The current strategies for building 2D organic-inorganic heterojunctions involve mostly wet-chemistry processes or exfoliation and transfer, leading to interface contaminations, poor crystallizing, or limited size. Here we show a bottom-up procedure to fabricate 2D large-scale heterostructure with clean interface and highly-crystalline sheets. As a prototypical example, a well-ordered hydrogen-bonded organic framework is self-assembled on the highly-oriented-pyrolytic-graphite substrate. The organic framework adopts a honeycomb lattice with faulted/unfaulted halves in a unit cell, resemble to molecular “graphene”. Interestingly, the topmost layer of substrate is self-lifted by organic framework via strong interlayer coupling, to form effectively a floating organic framework/graphene heterostructure. The individual layer of heterostructure inherits its intrinsic property, exhibiting distinct Dirac bands of graphene and narrow bands of organic framework. Our results demonstrate a promising approach to fabricate 2D organic-inorganic heterostructure with large-scale uniformity and highly-crystalline via the self-lifting effect, which is generally applicable to most of van der Waals materials.

36 MATERIALS SCIENCE↗
NASA NTRS1976

Evidence of a large-scale gradient in the solar wind velocity

Measurements of the solar wind velocity are compared at two widely separated locations, using plasma data obtained by Mariner 5, en route to Venus, and with the near-earth satellites Explorer 33, 34, and 35. A previous study of the propagation of interplanetary sector boundaries between Mariner and the earth had implied the existence of large scale velocity gradient which was interpreted as a latitude gradient of approximately 13 km/sec per degree of latitude. The results of the present investigation in which the earlier results were extended to the overall solar wind, without regard to the presence of sector boundaries, suggests that a latitude dependence of the solar wind velocity is the most plausible interpretation of the large-scale velocity gradient.

Rhodes, E. J., Jr.↗
DOE OSTI2021

A Framework for International Collaboration on ITER Using Large-Scale Data Transfer to Enable Near-Real-Time Analysis

The global nature of the ITER project along with its projected ~ petabyte per day data generation presents a unique challenge, but also an opportunity for the fusion community to rethink, optimize, and enhance our scientific discovery process. Recognizing this, collaborative research with computational scientists was undertaken over the past several years to create a framework for large-scale data movement across wide-area networks (WANs), to enable global near-real time analysis of fusion data. This would broaden the available computational resources for analysis/simulation, and increase the number of researchers actively participating in experiments. An official demonstration of this framework for fast, large data transfer and real-time analysis was carried out between the KSTAR tokamak in Daejeon, Korea and PPPL in Princeton, USA. Streaming large data transfer, with near real-time movie creation and analysis of the KSTAR Electron Cyclotron Emission imaging (ECEI) data, was performed using the I/O framework ADIOS, and comparisons made at PPPL with simulation results from the XGC1 code. These demonstrations were made possible utilizing an optimized network configuration at PPPL, which achieved over 8.8 Gbps (88% utilization) in throughput tests from NFRI to PPPL. This demonstration showed the feasibility for large-scale data analysis of KSTAR data, and provides a nascent framework to enable use of globally distributed computational and personnel resources in pursuit of scientific knowledge from the ITER experiment.

43 PARTICLE ACCELERATORS↗