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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

A Measure from Line-of-Sight Magnetograms for Prediction of Coronal Mass Ejections

From a sample of 17 vector magnetograms of 12 bipolar active regions we have recently found (1) that a measure of the overall nonpotentiality (the overall twist and shear in the magnetic field) of an active region is given by the strong shear length Lss, the length of the portion of the main neutral line on which the observed transverse fields is strong (greater than 150 Guass (G)) and strongly sheared (shear angle greater than 45 degrees), and (2) that L(sub ss) is well correlated with the coronal mass ejection (CME) productivity of the active regions during the plus or minus 2-day time window centered on the day of the magnetogram. In the present paper, from the same sample of 17 vector magnetograms, we show that there is a viable proxy for L(sub ss) that can be measured from a line-of-sight magnetogram. This proxy is the strong gradient length L(sub SG), the length of the portion of the main neutral line on which the potential transverse field is strong (greater than 150 G), and the gradient of the line-of-sight field is sufficiently steep (greater than approximately 50 G/Mm). In our sample of active regions, L(sub SG) is statistically significantly correlated with Lss (correlation confidence level greater than 95%), and L(sub SG) is as strongly correlated with active region CME productivity as is L(sub SS) (correlation confidence level approximately 99.7%). Because L(sub SG) can be measured from line-of-sight magnetograms obtained from conventional magnetographs, such as the magnetograph mode of the Michelson Doppler Imager (MDI) on board the Solar and Heliospheric Observatory, it is a dependable substitute for L(sub SS) for use in operational CME forecasting. In addition, via measurement of L(sub SG), the years-long, nearly continuous sequence of 1.5-hour cadence full disk line-of-sight magnetograms from MDI can be used to track the growth and decay of the large-scale nonpotentiality in active regions and to examine the role of this evolution in active region CME productivity.

Falconer, D. A.↗
NASA NTRS2012

Likelihood-Based Climate Model Evaluation

Climate models are deterministic, mathematical descriptions of the physics of climate. Confidence in predictions of future climate is increased if the physics are verifiably correct. A necessary, (but not sufficient) condition is that past and present climate be simulated well. Quantify the likelihood that a (summary statistic computed from a) set of observations arises from a physical system with the characteristics captured by a model generated time series. Given a prior on models, we can go further: posterior distribution of model given observations.

climate models↗
NASA NTRS2019

Prior biosphere model impact on global terrestrial CO2 fluxes estimated from OCO-2 retrievals

This study assesses the impact of different state of the art global biospheric CO2 flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC/yr). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.

Sajeev Philip↗
DOE OSTI2023

Detection of the significant impact of source clustering on higher order statistics with DES Year 3 weak gravitational lensing data

We measure the impact of source galaxy clustering on higher order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show that this effect can exceed measurement uncertainties for common higher order statistics for certain analysis choices. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey (DES) Year 3 (Y3) data, we construct null tests for the source-clustering-free case, finding a p-value of p = 4 × 10 −3 (2.6σ) using third-order map moments and p = 3 × 10 −11 (6.5σ) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either included in the model or minimized through ad hoc procedures (e.g. scale cuts). We verify that the procedures adopted in existing DES Y3 cosmological analyses were sufficient to render this effect negligible. Failing to account for source clustering can significantly impact cosmological inference from higher order gravitational lensing statistics, e.g. higher order N-point functions, wavelet-moment observables, and deep learning or field-level summary statistics of weak lensing maps.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

The Effects of Sensor Field-of-View on the Geometrical Characteristics of Sea Ice Leads and Implications for Large-Area Heat Flux Estimates

The release of heat from sea ice fractures ('leads') is an important component of the heat budget in the Arctic, but their impact on regional scale climate is difficult to assess without more information on their distribution in both space and time. Remote sensing of leads using satellite data, specifically AVHRR thermal and Landsat visible-band imagery, is examined empirically with respect to lead width, orientation, and area fraction. The geometrical aspects of the sensor are simulated so that the effect of sensor field-of-view on retrieved lead width statistics can be assessed. This is done using Landsat data and simulated lead networks degraded to AVHRR pixel sizes. The analyses illustrate how leads of sufficiently high contrast tend to 'grow' with increasing pixel size and how small or low contrast leads disappear. The relationship between lead contrast and the width/field-of-view ratio is also examined in order to determine the limits of lead detectability, and illustrates the multivalued nature of the problem of lead width retrieval. To help quantify the importance of changes in lead statistics, turbulent heat flux is calculated as a function of lead width and lead fraction. It is shown that pixel size has a substantial effect on estimates of turbulent heat transfer from leads to the atmosphere.

Key, J.↗
DOE OSTI2021

Scattering amplitudes for all masses and spins

We introduce a formalism for describing four-dimensional scattering amplitudes for particles of any mass and spin. This naturally extends the familiar spinor-helicity formalism for massless particles to one where these variables carry an extra SU(2) little group index for massive particles, with the amplitudes for spin Sparticles transforming as symmetric rank 2S tensors. We systematically characterise all possible three particle amplitudes compatible with Poincare symmetry. Unitarity, in the form of consistent factorization, imposes algebraic conditions that can be used to construct all possible four-particle tree amplitudes. This also gives us a convenient basis in which to expand all possible four-particle amplitudes in terms of what can be called “spinning polynomials”. Many general results of quantum field theory follow the analysis of four-particle scattering, ranging from the set of all possible consistent theories for massless particles, to spin-statistics, and the Weinberg-Witten theorem. We also find a transparent understanding for why massive particles of sufficiently high spin cannot be “elementary”. The Higgs and Super-Higgs mechanisms are naturally discovered as an infrared unification of many disparate helicity amplitudes into a smaller number of massive amplitudes, with a simple understanding for why this can’t be extended to Higgsing for gravitons. We illustrate a number of applications of the formalism at one-loop, giving few-line computations of the electron (g - 2) as well as the beta function and rational terms in QCD. “Off-shell” observables like correlation functions and form-factors can be thought of as scattering amplitudes with external “probe” particles of general mass and spin, so all these objects — amplitudes, form factors and correlators, can be studied from a common on-shell perspective.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Quantitative and interpretable order parameters for phase transitions from persistent homology

Here, we apply modern methods in computational topology to the task of discovering and characterizing phase transitions. As illustrations, we apply our method to four two-dimensional lattice spin models: the Ising, square ice, XY, and fully frustrated XY models. In particular, we use persistent homology, which computes the births and deaths of individual topological features as a coarse-graining scale or sublevel threshold is increased, to summarize multiscale and high-point correlations in a spin configuration. We employ vector representations of this information called persistence images to formulate and perform the statistical task of distinguishing phases. For the models we consider, a simple logistic regression on these images is sufficient to identify the phase transition. Interpretable order parameters are then read from the weights of the regression. This method suffices to identify magnetization, frustration, and vortex-antivortex structure as relevant features for phase transitions in our models. We also define “persistence” critical exponents and study how they are related to those critical exponents usually considered.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mass Detection for Heavy-Duty Vehicles using Gaussian Belief Propagation

Predicting vehicle mass is critical to accurately estimate energy use and emissions of commercial trucks. However, data from vehicle telematics is often not at sufficient temporal resolution or accuracy for use in model-based detection methods. In this work, a new statistical mass prediction technique is described for heavy-duty vehicles that incorporates the use Gaussian Belief Propagation (GBP) for probabilistic inference. Similar to Bayesian inference models, the GBP model typically requires less labeled training data than other contemporary machine learning techniques. First, a factor graph is constructed, and a set of Gaussian belief nodes with associated means and variances are fitted to the training data. To better handle noisy input data, the GBP mass prediction model utilizes a k-nearest factors (kNF) algorithm for probabilistic inference on unseen testing data. The proposed method is compared with a classical weighted k-nearest neighbors (kNN) regressor. This statistical kNF-GBP model works even with low-quantity, low-quality initial training data, while being capable of realtime mass estimation. Unlike the kNN regressor, the GBP model produces a measure of uncertainty with its predictions. The proposed method is validated using curve-sampled driving data collected from multiple cloud-connected Class 8 regional haul diesel trucks. Both the kNN regressor and the kNF-GBP mass prediction model were able to predict payload mass with coefficients of determination above 0.97 with minimal data preprocessing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1979

Assessment of economic factors affecting the satellite power system. Volume 2: The systems implications of rectenna siting issues

The feasibility was evaluated of finding potential sites for Solar Power Satellite (SPS) receiving antennas (rectennas) in the continental United States, in sufficient numbers to permit the SPS to make a major contribution to U.S. generating facilities, and to give statistical validity to an assessment of the characteristics of such sites and their implications for the design of the SPS system. It is found that the cost-optimum power output of the SPS does not depend on the particular value assigned to the cost per unit area of a rectenna and its site, as long as it is independent of rectenna area. Many characteristics of the sites chosen affect the optimum design of the rectenna itself.

Chapman, P. K.↗
NASA NTRS1981

Alterations of the climate of a primitive equation model produced by filtering approximations and subsequent tuning and stochastic forcing

A comparison is made of the simulated climates of nonlinear models based on the primitive equations (PE), balance equations (BE), and quasi-geostrophic (QG) equations. The models and numerical procedures are identical in all possible respects. The models are highly truncated spectral forms of Lorenz's (1960) energy preserving two-layer model. Two means of making use of the information contained in the (presumed known) short-term prediction error statistics are investigated. An unrealistically high level of thermal forcing is used so that the model climates are sufficiently different to allow any improvements due to the empirical methods to be observed. The general tuning problem is outlined and the QG model is tuned, using data obtained from a PE model run, to minimize the mean squared short term prediction error.

Hoffman, R. N.↗
NASA NTRS2003

A Measure from Line-of-Sight Magnetograms for Prediction of Coronal Mass Ejections

From a sample of 17 vector magnetograms of 12 bipolar active regions, we have recently found (1) that a measure of the overall nonpotentiality (the overall twist and shear in the magnetic field) of an active region is given by the strong-shear length L(sub SS), the length of the portion of the main neutral line on which the observed transverse fields is strong (greater than 150 G) and strongly sheared (shear angle greater than 45 deg), and (2) that L(sub SS) is well correlated with the CME productivity of the active regions during the +/- 2-day time window centered on the day of the magnetogram. In the present paper, from the same sample of 17 vector magnetograms, we show that there is a viable proxy for L(sub SS) that can be measured from a line-of-sight magnetogram. This proxy is the strong-gradient length L(sub SG), the length of the portion of the main neutral line on which the potential transverse field is strong (greater than 150 G) and the gradient of the line-of-sight field is sufficiently steep (greater than or approximately 50 G/Mm). In our sample of active regions, L(sub SG) is statistically significantly correlated with L(sub SS) (correlation confidence level greater than 95%), and L(sub SG) is as strongly correlated with active-region CME productivity as is L(sub SS)(correlation confidence level approximately 99.7%). Because L(sub SG) can be measured from line-of-sight magnetograms obtained from conventional magnetographs, such as the magnetograph mode of the Michelson Doppler Imager (MDI) on board the Solar and Heliospheric Observatory (SOHO), it is a dependable substitute for L(sub SS) for use in operational CME forecasting. In addition, via measurement of L(sub SG), the years-long, nearly continuous sequence of 1.5-hour-cadence full-disk line-of-sight magnetograms from MDI can be used to track the growth and decay of the large-scale nonpotentiality in active regions and to examine the role of this evolution in active-region CME productivity.

Falconer, D. A.↗
NASA NTRS1994

Statistical Analysis of NAS Parallel Benchmarks and LINPACK Results

In the last three years extensive performance data have been reported for parallel machines both based on the NAS Parallel Benchmarks, and on LINPACK. In this study we have used the reported benchmark results and performed a number of statistical experiments using factor, cluster, and regression analyses. In addition to the performance results of LINPACK and the eight NAS parallel benchmarks, we have also included peak performance of the machine, and the LINPACK n and n(sub 1/2) values. Some of the results and observations can be summarized as follows: 1) All benchmarks are strongly correlated with peak performance. 2) LINPACK and EP have each a unique signature. 3) The remaining NPB can grouped into three groups as follows: (CG and IS), (LU and SP), and (MG, FT, and BT). Hence three (or four with EP) benchmarks are sufficient to characterize the overall NPB performance. Our poster presentation will follow a standard poster format, and will present the data of our statistical analysis in detail.

Meuer, Hans-Werner↗
DOE OSTI2025

Suppressing the sample variance of DESI-like galaxy clustering with fast simulations

Ongoing and upcoming galaxy redshift surveys, such as the Dark Energy Spectroscopic Instrument (DESI) survey, will observe vast regions of sky and a wide range of redshifts. In order to model the observations and address various systematic uncertainties, N-body simulations are routinely adopted, however, the number of large simulations with sufficiently high mass resolution is usually limited by available computing time. Therefore, achieving a simulation volume with the effective statistical errors significantly smaller than those of the observations becomes prohibitively expensive. In this study, we apply the Convergence Acceleration by Regression and Pooling (CARPool) method to mitigate the sample variance of the DESI-like galaxy clustering in the AbacusSummit simulations, with the assistance of the quasi-N-body simulations FastPM. Based on the halo occupation distribution (HOD) models, we construct different FastPM galaxy catalogs, including the luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars, with their number densities and two-point clustering statistics well matched to those of AbacusSummit. We also employ the same initial conditions between AbacusSummit and FastPM to achieve high cross-correlation, as it is useful in effectively suppressing the variance. Our method of reducing noise in clustering is equivalent to performing a simulation with volume larger by a factor of 5 and 4 for LRGs and ELGs, respectively. We also mitigate the standard deviation of the LRG bispectrum with the triangular configurations k 2 = 2k 1 = 0.2 h Mpc -1 by a factor of 1.6. With smaller sample variance on galaxy clustering, we are able to constrain the baryon acoustic oscillations (BAO) scale parameters to higher precision. The CARPool method will be beneficial to better constrain the theoretical systematics of BAO, redshift space distortions (RSD) and primordial non-Gaussianity (NG).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Dark energy survey year 1 results: Constraining baryonic physics in the Universe

ABSTRACT Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3 × 2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modelling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude (Q1) generally reflects the strength of baryon feedback. With the upper limit of Q1 prior being bound by the Illustris feedback scenarios, we reach $\sim 20{{\ \rm per\ cent}}$ improvement in the constraint of $S_8=\sigma _8(\Omega _{\rm m}/0.3)^{0.5}=0.788^{+0.018}_{-0.021}$ compared to the original DES 3 × 2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 arcmin, which was excluded in previous DES analyses that did not model baryonic physics. We obtain $S_8=0.781^{+0.014}_{-0.015}$ for the combined DES Y1+Planck EE+BAO analysis with a non-informative Q1 prior. In terms of the baryon constraints, we measure $Q_1=1.14^{+2.20}_{-2.80}$ for DES Y1 only and $Q_1=1.42^{+1.63}_{-1.48}$ for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than 2σ.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Thermal transport in compensated semimetals: Effect of electron-electron scattering on Lorenz ratio

It is well known that the electronic thermal conductivity of clean compensated semimetals can be greatly enhanced over the electric conductivity by the availability of an ambipolar mechanism of conduction, whereby electrons and holes flow in the same direction experiencing negligible Coulomb scattering as well as negligible impurity scattering. This enhancement—resulting in a breakdown of the Wiedemann-Franz law with an anomalously large Lorenz ratio—has been recently observed in two-dimensional monolayer and bilayer graphene near the charge neutrality point. In contrast to this, three-dimensional compensated semimetals such as WP 2 and Sb are typically found to show a reduced Lorenz ratio. Here, we investigate the reasons for this difference, focusing on the low-temperature regime where the electron-electron scattering is expected to dominate over other scattering mechanisms. We show that the different regimes of Fermi statistics (nondegenerate electron-hole liquid in graphene versus degenerate electron-hole liquid in compensated semimetals) are not sufficient to explain the reduction of the Lorenz ratio in the latter. We propose that the solution of the puzzle lies in the large separation of electron and hole pockets in momentum space, which allows compensated semimetals to sustain sizable regions of electron-hole accumulation near the contacts. These accumulations suppress the ambipolar conduction mechanism and effectively split the system into two independent electron and hole conductors. We present a quantitative theory of the crossover from ambipolar to unipolar conduction as a function of the size of the electron-hole accumulation regions, and show that it naturally leads to a sample-size-dependent thermal conductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1987

Program for Analysis and Enhancement of Images

Land Analysis System (LAS) is collection of image-analysis computer programs designed to manipulate and analyze multispectral image data. Provides user with functions ingesting various sensor data, radiometric and geometric corrections, image registration, training site selection, supervised and unsupervised classification, Fourier domain filtering, and image enhancement. Sufficiently modular and includes extensive library of subroutines to permit inclusion of new algorithmic programs. Commercial package International Mathematical & Statistical Library (IMSL) required for full implementation of LAS. Written in VAX FORTRAN 77, C, and Macro assembler for DEC VAX operating under VMS 4.0.

Lu, Yun-Chi↗
DOE OSTI2025

Dark Energy Survey: Modeling strategy for multiprobe cluster cosmology and validation for the Full Six-year Dataset

We introduce an updated To&Krause2021 model for joint analyses of cluster abundances and large-scale two-point correlations of weak lensing and galaxy and cluster clustering (termed CL+3x2pt analysis) and validate that this model meets the systematic accuracy requirements of analyses with the statistical precision of the final Dark Energy Survey (DES) Year 6 (Y6) dataset. The validation program consists of two distinct approaches, (1) identification of modeling and parameterization choices and impact studies using simulated analyses with each possible model misspecification (2) end-to-end validation using mock catalogs from customized Cardinal simulations that incorporate realistic galaxy populations and DES-Y6-specific galaxy and cluster selection and photometric redshift modeling, which are the key observational systematics. In combination, these validation tests indicate that the model presented here meets the accuracy requirements of DES-Y6 for CL+3x2pt based on a large list of tests for known systematics. In addition, we also validate that the model is sufficient for several other data combinations: the CL+GC subset of this data vector (excluding galaxy--galaxy lensing and cosmic shear two-point statistics) and the CL+3x2pt+BAO+SN (combination of CL+3x2pt with the previously published Y6 DES baryonic acoustic oscillation and Y5 supernovae data).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Dark energy survey: Modeling strategy for multiprobe cluster cosmology and validation for the full six-year dataset

Here, we introduce an updated To&Krause2021 model for joint analyses of cluster abundances and large-scale two-point correlations of weak lensing and galaxy and cluster clustering (termed CL+3×2 pt analysis) and validate that this model meets the systematic accuracy requirements of analyses with the statistical precision of the final Dark Energy Survey (DES) Year 6 (Y6) dataset. The validation program consists of two distinct approaches, (i) identification of modeling and parametrization choices and impact studies using simulated analyses with each possible model misspecification and (ii) end-to-end validation using mock catalogs from customized Cardinal simulations that incorporate realistic galaxy populations and DES-Y6-specific galaxy and cluster selection and photometric redshift modeling, which are the key observational systematics. In combination, these validation tests indicate that the model presented here meets the accuracy requirements of DES-Y6 for CL+3×2 pt based on a large list of tests for known systematics. In addition, we also validate that the model is sufficient for several other data combinations: the CL+GC subset of this data vector (excluding galaxy–galaxy lensing and cosmic shear two-point statistics) and the CL+3×2 pt+BAO+SN (combination of CL+3×2 pt with the previously published Y6 DES baryonic acoustic oscillation and Y5 supernovae data).

79 ASTRONOMY AND ASTROPHYSICS↗