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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Understanding the Role of 𝛼 Particles in Oblique Heliospheric Shock Oscillations

Recent observations by DSCOVR provide high temporal resolution (50 samples per second) magnetic vector field data that allows investigating the details of oblique heliospheric shock oscillations. It was found that some of these shocks exhibit magnetic oscillations, both downstream and upstream of the shock front. The DSCOVR/MAG magnetic field data are supplemented by an extensive database of low Mach number (M < 3) low‐β (<1) shock data observed by Wind albeit with lower temporal resolution. Motivated by the observations, we use the 2.5D hybrid model of the oblique shocks with α particles in addition to kinetic protons and electron fluid. We model the properties of the oblique shocks for a number of typical parameters found in observations and study the effects of the shock parameters and the relative α particle abundances on the properties of the shock magnetic field, density, and velocity oscillations. We find the α particles “surf” on the shock front and produce a wake of density oscillations. We examine the details of the phase space of the ions as well as the ion velocity distribution functions in various parts of the shock and study their nonthermal properties. We determine the effects of the α particle kinetic properties and abundances on the structure and dynamics of the shock downstream oscillations for a range of parameters relevant to low Mach number low‐β heliospheric shocks.

Ofman, L.↗
DOE OSTI2022

Physics-Informed Gaussian Process Regression for States Estimation and Forecasting in Power Grids

Real-time state estimation and forecasting are critical for the efficient operation of power grids. In this paper, a physics-informed Gaussian process regression (PhI-GPR) method is presented and used for forecasting and estimating the phase angle, angular speed, and wind mechanical power of a three-generator power grid system using sparse measurements. In standard data-driven Gaussian process regression (GPR), parameterized models for the prior statistics are fit by maximizing the marginal likelihood of observed data. In the PhI-GPR method, we propose to compute the prior statistics offline by solving stochastic differential equations (SDEs) governing the power grid dynamics. The short-term forecast of a power grid system dominated by wind generation is complicated by the stochastic nature of the wind and the resulting uncertainty in wind mechanical power. Here, we assume that the power grid dynamics are governed by swing equations, with the wind mechanical power fluctuating randomly in time. We solve these equations for the mean and covariances of the power grid states using the Monte Carlo simulation method. We demonstrate that the proposed PhI-GPR method can accurately forecast and estimate observed and unobserved states. For the considered problem, PhI-GPR has computational advantages over the ensemble Kalman filter (EnKF) method: In PhI-GPR, ensembles are computed offline and independently of the data acquisition process, whereas for EnFK, ensembles are computed online with data acquisition, rendering real-time forecast more challenging. We also demonstrate that the PhI-GPR forecast is more accurate than the EnKF forecast when the random mechanical wind power is non-Markovian. In contrast, the two methods produce similar forecasts for the Markovian mechanical wind power. For observed states, we show that PhI-GPR provides a forecast comparable to the standard data-driven GPR; both forecasts are significantly more accurate than the autoregressive integrated moving average (ARIMA) forecast. We also show that the ARIMA forecast is more sensitive to observation frequency and measurement errors than the PhI-GPR forecast.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1991

Determination of the coronal magnetic field from vector magnetograph data

A new algorithm was developed, tested, and applied to determine coronal magnetic fields above solar active regions. The coronal field above NOAA active region AR5747 was successfully estimated on 20 Oct. 1989 from data taken at the Mees Solar Observatory of the Univ. of Hawaii. It was shown that observational data can be used to obtain realistic estimates of coronal magnetic fields. The model has significantly extended the realism with which the coronal magnetic field can be inferred from observations. The understanding of coronal phenomena will be greatly advanced by a reliable technique, such as the one presented, for deducing the detailed spatial structure of the coronal field. The payoff from major current and proposed NASA observational efforts is heavily dependent on the success with which the coronal field can be inferred from vector magnetograms. In particular, the present inability to reliably obtain the coronal field has been a major obstacle to the theoretical advancement of solar flare theory and prediction. The results have shown that the evolutional algorithm can be used to estimate coronal magnetic fields.

Mikic, Zoran↗
DOE OSTI2014

Transit timing variations for planets co-orbiting in the horseshoe regime

Although not yet detected, pairs of exoplanets in 1:1 mean motion resonance probably exist. Low eccentricity, near-planar orbits, which in the comoving frame follow horseshoe trajectories, are one of the possible stable configurations. Here we study transit timing variations (TTVs) produced by mutual gravitational interaction of planets in this orbital architecture, with the goal to develop methods that can be used to recognize this case in observational data. In particular, we use a semi-analytic model to derive parametric constraints that should facilitate data analysis. We show that characteristic traits of the TTVs can directly constrain the (1) ratio of planetary masses and (2) their total mass (divided by that of the central star) as a function of the minimum angular separation as seen from the star. In an ideal case, when transits of both planets are observed and well characterized, the minimum angular separation can also be inferred from the data. As a result, parameters derived from the observed transit timing series alone can directly provide both planetary masses scaled to the central star mass.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2004

Regional Assimilation of NASA Atmospheric Infrared Sounder (AIRS) Data

The NASA Short-term Prediction Research and Transition (SPORT) Center seeks to accelerate the infusion of NASA Earth Science Enterprise (ESE) observations, data assimilation and modeling research into NW S forecast operations and decision-making. The Atmospheric Infrared Sounder (AIRS), is expected to advance climate research and weather prediction into the 21 st century. It is one of six instruments onboard Aqua, a satellite that is part of NASA s Earth Observing System. AIRS, along with two partner microwave sounding instruments, represents the most advanced atmospheric sounding system ever deployed in space. The system is capable of measuring the atmospheric temperature in the troposphere with radiosonde accuracies of 1 K over 1 km-thick layers under both clear and cloudy conditions, while the accuracy of the derived moisture profiles will exceed that obtained by radiosondes. It is imperative that the scientific community is prepared to take full advantage of next-generation satellite data that will become available within the next decade. The purpose of this paper is to describe a procedure designed to optimally assimilate AIRS data at high spatial resolution over both land and ocean. The assimilation system used in this study is the Local Analysis and Prediction System (LAPS) developed at the Forecast System Laboratory used extensively around the globe. Results will focus on quality control issues associated with AIRS, optimal assimilation strategies, and the impact of the AIRS data on subsequent numerical forecasts at 12 km produced by the next generation Weather Research and Forecast (WRF) model.

Chou, Shih-Hung↗
DOE OSTI2015

The Wind Forecast Improvement Project (WFIP): A Public–Private Partnership Addressing Wind Energy Forecast Needs

The Wind Forecast Improvement Project (WFIP) is a public–private research program, the goal of which is to improve the accuracy of short-term (0–6 h) wind power forecasts for the wind energy industry. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that included the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models and, second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the United States (the upper Great Plains and Texas) and included 12 wind profiling radars, 12 sodars, several lidars and surface flux stations, 184 instrumented tall towers, and over 400 nacelle anemometers. Results demonstrate that a substantial reduction (12%–5% for forecast hours 1–12) in power RMSE was achieved from the combination of improved numerical weather prediction models and assimilation of new observations, equivalent to the previous decade’s worth of improvements found for low-level winds in NOAA/National Weather Service (NWS) operational weather forecast models. Data-denial experiments run over select periods of time demonstrate that up to a 6% improvement came from the new observations. Ensemble forecasts developed by the private sector partners also produced significant improvements in power production and ramp prediction. Based on the success of WFIP, DOE is planning follow-on field programs.

17 WIND ENERGY↗
NASA NTRS1991

Retrieval of wind temperature and pressure from single Doppler radar and a numerical model

A 4D data assimilation algorithm to obtain 3D wind and thermodynamic fields from radial velocities and a numerical model is derived. It is a blend of the continuous updating technique of Charney et al. (1969) and a diagnostic pressure and temperature retrieval technique suggested by Gal-Chen (1978). This model is tested only against model-generated data which are viewed as 'data observed from a real atmosphere'. A thermal bubble developing in a dry, neutral environment is simulated. The thermal recovery technique is found to be a necessary procedure to obtain successful data assimilation results. The present assimilation method is found to be capable of reducing the 'observational error' and making the assimilation run converge toward the control run. Without data insertion, errors in the nonobserved wind component are large.

Liou, Yu-Chieng↗
NASA NTRS2017

NASA's Big Earth Data Initiative Accomplishments

The goal of NASA's effort for BEDI is to improve the usability, discoverability, and accessibility of Earth Observation data in support of societal benefit areas. Accomplishments: In support of BEDI goals, datasets have been entered into Common Metadata Repository(CMR), made available via the Open-source Project for a Network Data Access Protocol (OPeNDAP), have a Digital Object Identifier (DOI) registered for the dataset, and to support fast visualization many layers have been added in to the Global Imagery Browse Services (GIBS).

CMR↗
NASA NTRS1998

Prototype Local Data Integration System and Central Florida Data Deficiency

This report describes the Applied Meteorology Unit's (AMU) task on the Local Data Integration System (LDIS) and central Florida data deficiency. The objectives of the task are to identify all existing meteorological data sources within 250 km of the Kennedy Space Center (KSC) and the Eastern Range at Cape Canaveral Air Station (CCAS), identify and configure an appropriate LDIS to integrate these data, and implement a working prototype to be used for limited case studies and data non-incorporation (DNI) experiments. The ultimate goal for running LDIS is to generate products that may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of the 45th Weather Squadron (45 WS), Spaceflight Meteorology Group (SMG), and the Melbourne National Weather Service (NWS MLB) operational requirements. The LDIS has the potential to provide added value for nowcasts and short term forecasts for two reasons. First, it incorporates all data operationally available in east central Florida. Second, it is run at finer spatial and temporal resolutions than current national-scale operational models. In combination with a suitable visualization tool, LDIS may provide users with a more complete and comprehensive understanding of evolving fine-scale weather features than could be developed by individually examining the disparate data sets over the same area and time. The utility of LDIS depends largely on the reliability and availability of observational data. Therefore, it is important to document all existing meteorological data sources around central Florida that can be incorporated by it. Several factors contribute to the data density and coverage over east central Florida including the level in the atmosphere, distance from KSC/CCAS, time, and prevailing weather. The central Florida mesonet consists of existing surface meteorological and hydrological data available from the Tampa NWS and data servers at Miami and Jacksonville. However the utility of these data for operational use is limited, mainly because there are relatively few additional meteorological observations within 50 km of KSC/CCAS to supplement existing METAR and KSC/CCAS tower reports.

Manobianco, John↗
DOE OSTI2019

Discussion of “Is reliability a new science?”

I would like to thank the participants of the panel at the 10th International Conference on Mathematical Methods in Reliability (MMR 2017) for their thoughtful and thorough discussion on this topic. In considering the fundamentals of a discipline, it is often possible to gain additional understanding about its strengths, weaknesses, and potential gaps. I confess that my perspective on the topic most closely matches thoughts expressed by William Meeker about the crux of the matter being tied to the choice of definitions. There are a multitude of candidate definitions, and each of the panelists chose to focus on different aspects from different sources. I opted for the Oxford English Dictionary definition of “The intellectual and practical activity encompassing the systematic study of the structure and behaviour of the physical and natural world through observation and experiment.” Based on this definition, I would conclude that reliability can qualify as a science because (1) it shares elements of intellectual and practical activity through the development of methodologies to characterize observed patterns, (2) it considers both the structure and behavior of the systems that it seeks to characterize, and (3) it involves notions of obtaining data (observation) and prioritizes the collection of high-quality data with known pedigree through experimentation. More broadly, however, I think that it has elements that expand beyond just a science and contain elements of engineering. To illustrate this, I present some of the thinking that has recently been occurring related to the distinction between statistical science and statistical engineering.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

Micro-meteoroid and orbital debris radar from Goldstone Radar observations

Micro-meteoroid and orbital debris (MMOD) refers to millions of micrometeoroids and orbital debris orbiting the Earth, which can come from remaining parts of spacecraft from previous missions. These debris objects keep colliding and creating new pieces of debris, with very different sizes ranging from millimeters to meters. About 99.3% of the debris objects have a size < 1 cm. These debris objects, traveling at speeds of 10 km/s, can cause significant damage to spacecraft, satellites, and astronauts. Despite the historic use of shielding to protect vital spacecraft components, MMOD still present a potential hazard for future missions and operations involving humans in space. Goldstone’s orbital debris radar (ODR) enhances the NASA orbital debris model with radar observation data, providing vital information on orbital debris detections: size, Doppler, range, and orbit inclination angle. These observations currently provide the only access to information about this size class (2 mm to 10 mm) of orbital debris. Goldstone’s ODR experiments operate as a bistatic radar, with overlapping beams providing a wide distribution of ranges. From 2004 to early 2018, Goldstone’s ODR has been collecting orbital debris data from altitudes covering 280 km to 3000 km. Since the decommissioning of the receive antenna in early 2018, Goldstone’s range coverage is reduced to a 300 km window within a 600 km to 1000 km potential range coverage, depending on the pointing geometry and antenna station used. We are investigating alternative transmit receive configurations at Goldstone to recover our previous wide range coverage.

Rodriguez-Alvarez, Nereida↗
NASA NTRS2010

The Software Correlator of the Chinese VLBI Network

The software correlator of the Chinese VLBI Network (CVN) has played an irreplaceable role in the CVN routine data processing, e.g., in the Chinese lunar exploration project. This correlator will be upgraded to process geodetic and astronomical observation data. In the future, with several new stations joining the network, CVN will carry out crustal movement observations, quick UT1 measurements, astrophysical observations, and deep space exploration activities. For the geodetic or astronomical observations, we need a wide-band 10-station correlator. For spacecraft tracking, a realtime and highly reliable correlator is essential. To meet the scientific and navigation requirements of CVN, two parallel software correlators in the multiprocessor environments are under development. A high speed, 10-station prototype correlator using the mixed Pthreads and MPI (Massage Passing Interface) parallel algorithm on a computer cluster platform is being developed. Another real-time software correlator for spacecraft tracking adopts the thread-parallel technology, and it runs on the SMP (Symmetric Multiple Processor) servers. Both correlators have the characteristic of flexible structure and scalability.

Zheng, Weimin↗
DOE OSTI2018

Distinct Contributions of Ice Nucleation, Large-Scale Environment, and Shallow Cumulus Detrainment to Cloud Phase Partitioning With NCAR CAM5

Mixed-phase clouds containing both liquid droplets and ice particles occur frequently at high latitudes and in the midlatitude storm track regions. Simulations of the cloud phase partitioning between liquid and ice hydrometeors in state-of-the-art global climate models are still associated with large biases. For this study, the phase partitioning in terms of liquid mass phase ratio (MPR liq , defined as the ratio of liquid mass to total condensed water mass) simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against the observational data from A-Train satellite remote sensors. Modeled MPR liq is significantly lower than observations on the global scale, especially in the Southern Hemisphere (e.g., Southern Ocean and the Antarctic). Sensitivity tests with CAM5 are conducted to investigate the distinct contributions of heterogeneous ice nucleation, shallow cumulus detrainment, and large-scale environment (e.g., winds, temperature, and water vapor) to the low MPR liq biases. Our results show that an aerosol-aware ice nucleation parameterization increases the MPR liq especially at temperatures colder than -20°C and significantly improves the model agreements with observations in the Polar regions in summer. The decrease of threshold temperature over which all detrained cloud water is liquid from 268 to 253 K enhances the MPR liq and improves the MPR liq mostly over the Southern Ocean. By constraining water vapor in CAM5 toward reanalysis, modeled low biases in many geographical regions are largely reduced through a significant decrease of cloud ice mass mixing ratio.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Spatial representation of organic carbon and active-layer thickness of high latitude soils in CMIP5 earth system models

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (F.SMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for redudng existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Modellntercomparison Project Phase 5 { CMIP5) ESMs with those predicted from geospatial predictions, based on observation data for the state of Alaska, USA. For the geospatial modeling. we used soil profile observations {585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m-2) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors. when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primaly factors leading to observed differences were ( 1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in F.SMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks.

Active-layer thickness↗
DOE OSTI2014

Diversity of extrasolar planets and diversity of molecular cloud cores. I. Semimajor axes

We show that the diversity of extrasolar planetary systems may be related to the diversity of molecular cloud cores. In previous studies of planet formation, artificial initial conditions of protoplanetary disks or steady state disks, such as the minimum mass nebula model, have often been used so that the influence of cloud core properties on planet formation is not realized. To specifically and quantitatively demonstrate our point, we calculate the dependence of disk properties on cloud core properties and show that the boundary of the giant planet formation region in a disk is a function of cloud core properties with the conventional core accretion model of giant planet formation. The gravitational stability of a disk depends on the properties of its progenitor cloud core. We also compare our calculations with observations of extrasolar planets. From the observational data of cloud cores, our model could infer the range and most frequent values of observed semimajor axes of extrasolar planets. Our calculations suggest that planet formation at the snowline alone could not completely explain the semimajor axis distribution. If the current observations are not biased, our calculations indicate that the planet formation at the snowline is inefficient. We suggest that there will be more observed planets with semimajor axis <9 AU than >9 AU, even with a longer duration of observations, if the planet formation at the snowline is inefficient.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Testing the Bose-Einstein Condensate dark matter model at galactic cluster scale

The possibility that dark matter may be in the form of a Bose-Einstein Condensate (BEC) has been extensively explored at galactic scale. In particular, good fits for the galactic rotations curves have been obtained, and upper limits for the dark matter particle mass and scattering length have been estimated. In the present paper we extend the investigation of the properties of the BEC dark matter to the galactic cluster scale, involving dark matter dominated astrophysical systems formed of thousands of galaxies each. By considering that one of the major components of a galactic cluster, the intra-cluster hot gas, is described by King's β-model, and that both intra-cluster gas and dark matter are in hydrostatic equilibrium, bound by the same total mass profile, we derive the mass and density profiles of the BEC dark matter. In our analysis we consider several theoretical models, corresponding to isothermal hot gas and zero temperature BEC dark matter, non-isothermal gas and zero temperature dark matter, and isothermal gas and finite temperature BEC, respectively. The properties of the finite temperature BEC dark matter cluster are investigated in detail numerically. We compare our theoretical results with the observational data of 106 galactic clusters. Using a least-squares fitting, as well as the observational results for the dark matter self-interaction cross section, we obtain some upper bounds for the mass and scattering length of the dark matter particle. Our results suggest that the mass of the dark matter particle is of the order of μ eV, while the scattering length has values in the range of 10{sup −7} fm.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Search for dark matter produced in association with a Higgs boson decaying to bottom quarks in proton-proton collisions at $\sqrt{s}=13$ TeV

A search for dark matter particles produced in association with a Higgs boson decaying to a bottom quark-antiquark pair in proton-proton collisions at $\sqrt{s}=13$ TeV is presented. The data, collected with the CMS detector at the LHC, correspond to an integrated luminosity of 101 fb −1 . The analysis is performed in exclusive categories targeting both Lorentz-boosted (merged) and resolved 𝑏 jet pair topologies, covering a wide range of Higgs boson transverse momentum. A statistical combination is made with a previous search using data collected in 2016 and corresponding to an integrated luminosity of 35.9 fb −1 . The observed data agree with the standard model background predictions. Constraints are placed on models predicting new particles or interactions, such as those in the simplified frameworks of baryonic-𝑍′ and 2⁢HDM + 𝑎, where the latter is a type-II two-Higgs-doublet model featuring a heavy pseudoscalar with an additional light pseudoscalar. Upper limits at 95% confidence level are set on the production cross section for these models. For the baryonic-𝑍′ model, 𝑍′ boson masses below 2.25 TeV are excluded for a dark matter particle candidate mass of 1 GeV. In the 2⁢HDM + 𝑎 model, heavy pseudoscalar masses between 850 and 1300 GeV are excluded for a light pseudoscalar mass of 350 GeV.

Hayrapetyan, A. [Yerevan Physics Institute]↗