SEARCH · Search NASA

Results for “distributed”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,459 records · Page 81

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Comparison of nanocomposite dispersion and distribution for several melt mixers

Breakup (dispersion) and distribution of nanoparticles are the chief hurdles towards taking advantage of nanoparticles in polymer nanocomposites for reinforcement, flame retardancy, conductivity, chromaticity, and other properties. Microscopy is often used to quantify mixing, but it has a limited field of view, does not average over bulk samples, and fails to address nano-particle hierarchical structures. Ultra-small-angle X-ray scattering (USAXS) can provide a macroscopic statistical average of nanoscale dispersion (breakup) and emergent hierarchical structure, as well as the distribution on the nanoscale. Here, this work compares several common mixer geometries for carbon black-polystyrene nanocomposites. Two twin-screw extruder geometries, typical for industrial processing of melt blends, are compared with a laboratory-scale single screw extruder and a Banbury mixer. It is found that for a given mixer, nanoscale distribution increases following a van der Waals function using accumulated strain as an analogue for temperature while macroscopic distribution/dispersion, using microscopy, does not follow this dependency. Breakup and aggregation in dispersive mixing follow expected behavior on the nanoscale. Across these drastically different mixing geometries an unexpected dependency is observed for nanoscale distributive mixing (both nano and macroscopic) as a function of accumulated strain that may reflect a transition from distributive turbulent to dispersive laminar mixing as the mixing gap is reduced.

36 MATERIALS SCIENCE↗

DOE OSTI2016

The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operate the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.

14 SOLAR ENERGY↗

DOE OSTI2017

A two-stage stochastic optimization model for scheduling electric vehicle charging loads to relieve distribution-system constraints

Electric vehicles (EVs) hold promise to improve the energy efficiency and environmental impacts of transportation. However, widespread EV use can impose significant stress on electricity-distribution systems due to their added charging loads. This paper proposes a centralized EV charging-control model, which schedules the charging of EVs that have flexibility. This flexibility stems from EVs that are parked at the charging station for a longer duration of time than is needed to fully recharge the battery. The model is formulated as a two-stage stochastic optimization problem. The model captures the use of distributed energy resources and uncertainties around EV arrival times and charging demands upon arrival, non-EV loads on the distribution system, energy prices, and availability of energy from the distributed energy resources. We use a Monte Carlo-based sample-average approximation technique and an L-shaped method to solve the resulting optimization problem efficiently. We also apply a sequential sampling technique to dynamically determine the optimal size of the randomly sampled scenario tree to give a solution with a desired quality at minimal computational cost. Here, we demonstrate the use of our model on a Central-Ohio-based case study. We show the benefits of the model in reducing charging costs, negative impacts on the distribution system, and unserved EV-charging demand compared to simpler heuristics. Lastly, we also conduct sensitivity analyses, to show how the model performs and the resulting costs and load profiles when the design of the station or EV-usage parameters are changed.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Large gyro-orbit model of ion velocity distribution in plasma near a wall in a grazing-angle magnetic field

A model is presented for the ion distribution function in a plasma at a solid target with a magnetic field $\boldsymbol {B}$ inclined at a small angle, $\alpha \ll 1$ (in radians), to the target. Adiabatic electrons are assumed, requiring $\alpha \gg \sqrt {Zm_{e}/m_{i}}$ , where $m_{e}$ and $m_{i}$ are the electron and ion mass, respectively, and $Z$ is the charge state of the ion. An electric field $\boldsymbol {E}$ is present to repel electrons, and so the characteristic size of the electrostatic potential $\phi$ is set by the electron temperature $T_{e}$ , $e\phi \sim T_{e}$ , where $e$ is the proton charge. An asymptotic scale separation between the Debye length $\lambda _{D} = \sqrt {\epsilon _0 T_{{e}} / e^{2} n_{{e}} }$ , the ion sound gyro-radius $\rho _{s} = \sqrt { m_{i} ( ZT_{e} + T_{i} ) } / (ZeB)$ and the size of the collisional region $d_{c} = \alpha \lambda _{\textrm {mfp}}$ is assumed, $\lambda _{D} \ll \rho _{s} \ll d_{c}$ . Here $\epsilon _0$ is the permittivity of free space, $n_{e}$ is the electron density, $T_{i}$ is the ion temperature, $B= |\boldsymbol {B}|$ and $\lambda _{\textrm {mfp}}$ is the collisional mean free path of an ion. The form of the ion distribution function is assumed at distances $x$ from the wall such that $\rho _{s} \ll x \ll d_{c}$ , that is, collisions are not treated. A self-consistent solution of the electrostatic potential for $x \sim \rho _{s}$ is required to solve for the quasi-periodic ion trajectories and for the ion distribution function at the target. The large gyro-orbit model presented here allows to bypass the numerical solution of $\phi (x)$ and results in an analytical expression for the ion distribution function at the target. It assumes that $\tau =T_{i}/(ZT_{e})\gg 1$ , and ignores the electric force on the quasi-periodic ion trajectory until close to the target. For $\tau \gtrsim 1$ , the model provides an extremely fast approximation to energy–angle distributions of ions at the target. These can be used to make sputtering predictions.

Physics↗

DOE OSTI2018

Atomistic Investigations of the Effects of Si/Al Ratio and Al Distribution on the Adsorption Selectivity of n -Alkanes in Brønsted-Acid Zeolites

The adsorption of n -alkanes onto Brønsted-acid sites is a key step in the catalytic cracking of alkanes. Employing configurational-bias Monte Carlo simulations, we have investigated how the ratio of equilibrium adsorption constants for central C-C bonds relative to terminal bonds of n -alkanes (i.e., the adsorption selectivity ratio) in Brønsted-acid zeolites is influenced by the Si/Al ratio and the Al distribution. A new computational approach was implemented, and the developed force field was validated by a comprehensive comparison between simulation results and experimental data for a number of Brønsted-acid zeolites. While the adsorption selectivity seems to be relatively insensitive to the Si/Al ratio, our results reveal that the Al distribution plays a crucial role in determining the adsorption selectivity. Changes in the Al distribution result in a change of as much as 2-fold in the adsorption selectivity ratio for n -hexane. The selectivity generally shows larger variations with respect to Al distribution in zeolites with a larger Si/Al ratio. The two factors identified by this work that substantially influence the selectivity ratio are the siting of Al atoms among T-sites and their spatial proximity, and an atomic-level understanding of each of these effects was achieved. The siting of Al atoms at more or less selective T-sites significantly influences the overall selectivity ratio, and Al atoms in close proximity can synergistically enhance the adsorption of central C-C bonds, leading to a higher selectivity ratio relative to isolated Al atoms. Finally, we anticipate that these results will have important implications for future large-scale computational screenings and the development of advanced synthesis approaches to target certain Al distributions in zeolites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Structure, Dynamics, and Hydrogen Transport in Amorphous Polymers: An Analysis of the Interplay between Free Volume Element Distribution and Local Segmental Dynamics from Molecular Dynamics Simulations

Polymers are attractive membrane materials owing to their mechanical robustness and relatively inexpensive fabrication. An important indicator of membrane performance are free volume elements (FVE): microporous void spaces created by the inefficient packing of bulky groups along the polymer chain. FVEs tend to degrade over time, as polymer chains reorganize irreversibly. While it is widely accepted that polymer flexibility has an impact on membrane transport properties, the molecular nature of this impact is still not well understood. By the establishment of a correlation between local chain dynamics and the distribution of free volume elements (FVEs), penetrant transport can be regulated more efficiently in amorphous polymer membranes. In this work, we implement all-atom molecular dynamics (MD) simulations to explore the relationship between chain dynamics and free volume in three polymers with different levels of backbone flexibility: polymethylpentene (PMP), polystyrene (PS), and HAB-6FDA thermally rearranged polymer (TRP). We construct these polymers at different temperatures and examine how temperature impacts the FVE distribution and segmental mobility. Our analysis shows that chain segments near FVEs have higher mobility compared with the atoms in the bulk; the extent of this difference increases with chain flexibility. Increasing the chain flexibility by increasing the temperature results in a broader FVE distribution. Rigid polymers such as TRP show the most robust FVE distribution and are not significantly affected by the temperature change. To capture penetrant diffusion through the polymer matrix, hydrogen is inserted and the diffusion is measured at different temperatures; hydrogen mobility is influenced by the FVE structure and overall mobility of polymer chains. Lastly, at low temperatures, hydrogen mobility is influenced by void distribution, while at high temperatures, polymer dynamics dictate hydrogen transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Spatial distribution of melt-season cloud radiative effects over Greenland: Evaluating satellite observations, reanalyses, and model simulations against in situ measurements

Arctic clouds can profoundly influence surface radiation and thus surface melt. Over Greenland, these cloud radiative effects (CRE) vary greatly with the diverse topography. To investigate the ability of assorted platforms to reproduce heterogeneous CRE, we evaluate CRE spatial distributions from a satellite product, reanalyses, and a global climate model against estimates from 21 automatic weather stations (AWS). Net CRE estimated from AWS generally decreases with elevation, forming a “warm center” distribution. CRE areal averages from the five large–scale data sets we analyze are all around 10 W/m 2 . Modern–Era Retrospective Analysis for Research and Applications version 2 (MERRA–2), ERA–Interim, and Clouds and the Earth's Radiant Energy System (CERES) CRE estimates agree with AWS and reproduce the warm center distribution. However, the National Center for Atmospheric Research Arctic System Reanalysis (ASR) and the Community Earth System Model Large ENSemble Community Project (LENS) show strong warming in the south and northwest, forming a warm L–shape distribution. Discrepancies are mainly caused by longwave CRE in the accumulation zone. MERRA–2, ERA–Interim, and CERES successfully reproduce cloud fraction and its dominant positive influence on longwave CRE in this region. On the other hand, longwave CRE from ASR and LENS correlates strongly with ice water path instead of with cloud fraction or liquid water path. Moreover, ASR overestimates cloud fraction and LENS underestimates liquid water path substantially, both with limited spatial variability. MERRA–2 best captures the observed interstation changes, captures most of the observed cloud–radiation physics, and largely reproduces both albedo and cloud properties. Furthermore, the warm center CRE spatial distribution indicates that clouds enhance surface melt in the higher accumulation zone and reduce surface melt in the lower ablation zone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Wave-driven butterfly distribution of Van Allen belt relativistic electrons

Van Allen radiation belts consist of relativistic electrons trapped by Earth's magnetic field. Trapped electrons often drift azimuthally around Earth and display a butterfly pitch angle distribution of a minimum at 90° further out than geostationary orbit. This is usually attributed to drift shell splitting resulting from day–night asymmetry in Earth’s magnetic field. However, direct observation of a butterfly distribution well inside of geostationary orbit and the origin of this phenomenon have not been provided so far. Here we report high-resolution observation that a unusual butterfly pitch angle distribution of relativistic electrons occurred within 5 Earth radii during the 28 June 2013 geomagnetic storm. In conclusion, simulation results show that combined acceleration by chorus and magnetosonic waves can successfully explain the electron flux evolution both in the energy and butterfly pitch angle distribution. Finally, the current provides a great support for the mechanism of wave-driven butterfly distribution of relativistic electrons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

Neutron and weak-charge distributions of the 48 Ca nucleus

What is the size of the atomic nucleus? This deceivably simple question is difficult to answer. Although the electric charge distributions in atomic nuclei were measured accurately already half a century ago, our knowledge of the distribution of neutrons is still deficient. In addition to constraining the size of atomic nuclei, the neutron distribution also impacts the number of nuclei that can exist and the size of neutron stars. We present an ab initio calculation of the neutron distribution of the neutron-rich nucleus 48 Ca. We show that the neutron skin (difference between the radii of the neutron and proton distributions) is significantly smaller than previously thought. We also make predictions for the electric dipole polarizability and the weak form factor; both quantities that are at present targeted by precision measurements. Here, based on ab initio results for 48 Ca, we provide a constraint on the size of a neutron star.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Distributed quantum sensing of multiple phases with fewer photons

Abstract Distributed quantum metrology has drawn intense interest as it outperforms the optimal classical counterparts in estimating multiple distributed parameters. However, most schemes so far have required entangled resources consisting of photon numbers equal to or more than the parameter numbers, which is a fairly demanding requirement as the number of nodes increases. Here, we present a distributed quantum sensing scenario in which quantum-enhanced sensitivity can be achieved with fewer photons than the number of parameters. As an experimental demonstration, using a two-photon entangled state, we estimate four phases distributed 3 km away from the central node, resulting in a 2.2 dB sensitivity enhancement from the standard quantum limit. Our results show that the Heisenberg scaling can be achieved even when using fewer photons than the number of parameters. We believe our scheme will open a pathway to perform large-scale distributed quantum sensing with currently available entangled sources.

Science & Technology - Other Topics↗

DOE OSTI2017

Crop yield response to climate change varies with crop spatial distribution pattern

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40% by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Understanding the hydrological response of a headwater-dominated catchment by analysis of distributed surface–subsurface interactions

Abstract We computationally explore the relationship between surface–subsurface exchange and hydrological response in a headwater-dominated high elevation, mountainous catchment in East River Watershed, Colorado, USA. In order to isolate the effect of surface–subsurface exchange on the hydrological response, we compare three model variations that differ only in soil permeability. Traditional methods of hydrograph analysis that have been developed for headwater catchments may fail to properly characterize catchments, where catchment response is tightly coupled to headwater inflow. Analyzing the spatially distributed hydrological response of such catchments gives additional information on the catchment functioning. Thus, we compute hydrographs, hydrological indices, and spatio-temporal distributions of hydrological variables. The indices and distributions are then linked to the hydrograph at the outlet of the catchment. Our results show that changes in the surface–subsurface exchange fluxes trigger different flow regimes, connectivity dynamics, and runoff generation mechanisms inside the catchment, and hence, affect the distributed hydrological response. Further, changes in surface–subsurface exchange rates lead to a nonlinear change in the degree of connectivity—quantified through the number of disconnected clusters of ponding water—in the catchment. Although the runoff formation in the catchment changes significantly, these changes do not significantly alter the aggregated streamflow hydrograph. This hints at a crucial gap in our ability to infer catchment function from aggregated signatures. We show that while these changes in distributed hydrological response may not always be observable through aggregated hydrological signatures, they can be quantified through the use of indices of connectivity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Analysis of multipacting threshold sensitivity to the random distributions of the secondary electron yield parameters

The way multipacting develops, depends strongly on the secondary emission property of the surface material. The knowledge of secondary electron yield is crucial for accurate prediction of the multipacting threshold. Variations in secondary electron yield parameters from experimental measurements create uncertainty, stemming from handling and surface preparation, and these uncertainties significantly affect multipacting threshold predictions. Despite their significance, the previous studies on the multipacting phenomenon did not adequately address the effect of an assumed random distribution of the secondary emission parameters on the multipacting threshold. Therefore, this paper aims to provide a comprehensive statistical study on how the different random distributions of the secondary emission parameters and, as a result, the uncertainty in the secondary electron yield affect multipacting thresholds. We focus on three commonly used distributions, namely uniform, normal, and truncated normal distributions, to define the uncertainty of random inputs. We use the chaos polynomial expansion method to determine how much each of the random parameters contributes to the multipacting threshold uncertainty. Additionally, we calculate Sobol sensitivity indices to evaluate the impact of the individual parameters or groups of parameters on the model outputs and study how different random distributions of these parameters affected the Sobol index results.

physics↗

DOE OSTI2024

Bimodality in simulated precipitation frequency distributions and its relationship with convective parameterizations

Abstract Bimodality in precipitation frequency distributions is often evident in atmospheric models, but rarely in observations. This study i) proposes a metric to objectively quantify the bimodality in precipitation distributions, ii) evaluates model simulations contributed to the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5), phase 6 (CMIP6), and the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project by comparing them to satellite-based and reanalysis precipitation products, and iii) investigates possible origins of bimodal precipitation distributions. Our results reveal that about 83% (20 out of 24) of CMIP5 and 70% (21 out of 30) of CMIP6 models used in this study exhibit bimodal distributions. The few DYAMOND models that use a deep convective parameterization also show bimodal distributions, while most DYAMOND models do not. Predictably, the bimodality originates from the separation of precipitation process between resolved grid-scale and parameterized subgrid-scale. However, in a larger number of models bimodality arises from the parameterized subgrid-scale convective precipitation alone.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Equity‐aware power distribution system restoration

Abstract The efficient, reliable, and resilient supply of electricity has become essential for social and economic well‐being of the modern society. However, more frequent occurrence of extreme weather events has exposed inequity in the planning and operation practices of power distribution systems, evidenced in higher vulnerability and longer power interruptions for some parts of the grid as compared to others. This paper proposes an equity‐aware power distribution system restoration model in an effort to ensure a more equitable yet resilient power distribution operation after outages. To this end, the proposed equity‐aware distribution system restoration model balances the efficiency of the restoration operation and the equitable allocation of distributed energy resources among affected customers after an outage, while prioritizing the critical infrastructure (e.g. hospitals). The results demonstrate the effectiveness of the proposed framework to ensure a more equitable restoration process as measured by the proposed fairness and restoration performance indices.

Engineering↗

DOE OSTI2021

Redshift evolution of the underlying type Ia supernova stretch distribution

The detailed nature of type Ia supernovae (SNe Ia) remains uncertain, and as survey statistics increase, the question of astrophysical systematic uncertainties arises, notably that of the evolution of SN Ia populations. We study the dependence on redshift of the SN Ia SALT2.4 light-curve stretch, which is a purely intrinsic SN property, to probe its potential redshift drift. The SN stretch has been shown to be strongly correlated with the SN environment, notably with stellar age tracers. We modeled the underlying stretch distribution as a function of redshift, using the evolution of the fraction of young and old SNe Ia as predicted using the SNfactory dataset, and assuming a constant underlying stretch distribution for each age population consisting of Gaussian mixtures. We tested our prediction against published samples that were cut to have marginal magnitude selection effects, so that any observed change is indeed astrophysical and not observational in origin. In this first study, there are indications that the underlying SN Ia stretch distribution evolves as a function of redshift, and that the age drifting model is a better description of the data than any time-constant model, including the sample-based asymmetric distributions that are often used to correct Malmquist bias at a significance higher than 5σ. The favored underlying stretch model is a bimodal one, composed of a high-stretch mode shared by both young and old environments, and a low-stretch mode that is exclusive to old environments. The precise effect of the redshift evolution of the intrinsic properties of a SN Ia population on cosmology remains to be studied. The astrophysical drift of the SN stretch distribution does affect current Malmquist bias corrections, however, and thereby the distances that are derived based on SN that are affected by observational selection effects. We highlight that this bias will increase with surveys covering increasingly larger redshift ranges, which is particularly important for the Large Synoptic Survey Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Impact of non-Maxwellian electron velocity distribution functions on inferred plasma parameters in collective Thomson scattering

Optical collective Thomson scattering provides precise density and temperature measurements in numerous plasma-physics experiments. The accuracy of such measurements depends on the core assumption that the underlying electron distribution functions in under-dense laser-produced plasmas are Maxwellian. A statistically based, quantitative analysis of the errors in the measured electron density and temperature is presented when synthetic data calculated using a non-Maxwellian electron distribution function is fit assuming a Maxwellian electron distribution. Such analysis can lead to errors of up to 50% in temperature and 30% in density, in the specific case of super-Gaussian distributions characteristic of inverse bremsstrahlung heating. Furthermore including the proper family of non-Maxwellian electron distribution functions, as a fitting parameter, in Thomson-scattering analysis removes the model-dependent errors in the inferred parameters at a minimal cost to the statistical uncertainty.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Edge termination in vertical GaN diodes: Electric field distribution probed by second harmonic generation

We characterized the electric field distribution of GaN-on-GaN p–n diodes with partially compensated ion-implanted edge termination (ET) using an electric field induced second harmonic generation technique (EFISHG). The distributed electric field from the anode to the outer edge of the ET demonstrates the effectiveness of the ET structure. However, EFISHG also shows that its effectiveness is strongly dependent on the acceptor charge distribution in the ET's partially compensated layer (PC). A generally lower amount of acceptor charge can be inferred from the measured electric field distribution resulting from excessive ion implantation energy or dose during ET fabrication and causing lower than optimal breakdown voltage. Localized field crowding can be observed when the remaining acceptors uncompensated by the implant in the PC layer are nonuniformly distributed around the periphery of the devices. Important information can be obtained from these direct electric field measurements and used for optimizing the device design and fabrication process.

Cao, Yuke↗