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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling

A hierarchical solver is proposed for solving sparse ill-conditioned linear systems in parallel. The solver is based on a modification of the LoRaSp method, but employs a deferred-compression technique, which provably reduces the approximation error and significantly improves efficiency. Moreover, the deferred-compression technique introduces minimal overhead and does not affect parallelism. As a result, the new solver achieves linear computational complexity under mild assumptions and excellent parallel scalability. To demonstrate the performance of the new solver, we focus on applying it to solve sparse linear systems arising from ice sheet modeling. The strong anisotropic phenomena associated with the thin structure of ice sheets creates serious challenges for existing solvers. To address the anisotropy, we additionally developed a customized partitioning scheme for the solver, which captures the strong-coupling direction accurately. In general, the partitioning can be computed algebraically with existing software packages, and thus the new solver is generalizable for solving other sparse linear systems. Our results show that ice sheet problems of about 300 million degrees of freedom have been solved in just a few minutes using a thousand processors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Experimental and modeling analysis of detonation in circular arcs of the conventional high explosive PBX 9501

We examine the diffraction dynamics of a two-dimensional (2D) detonation in a circular arc of the conventional HMX-based, high performance, solid explosive PBX 9501, for which the detonation reaction zone length scale is estimated to be of the order of 100–150 µm. In this configuration, a steady propagating detonation will develop, sweeping around the arc with constant angular speed. We report on results from three PBX 9501 arc experiments, exploring the variation in linear speed on the inner and outer arc surfaces for the steady wave along with the structure of the curved detonation front, as a function of varying inner surface radius and arc thickness. Comparisons of the properties of the motion of the steady wave for each arc configuration are then made with a spatially-distributed PBX 9501 reactive burn model, calibrated to detonation performance properties in a 2D planar slab geometry. We show that geometry-induced curvature of the detonation near the inner arc surface has a significant effect on the detonation motion even for conventional high explosives. We also examine the detonation driving zone structure for each arc case, and thus the subsonic regions of the flow that determine the influence of the arc geometry on the detonation propagation. In addition, streamline paths and reaction progress isolines are calculated. Overall, we conclude that a common approximation for modeling conventional high explosive detonation, wherein the shock-normal detonation speed is assumed equal to the Chapman–Jouguet speed, can lead to significant errors in describing the speed at which the detonation propagates.

42 ENGINEERING↗
DOE OSTI2017

Investigation of a Quantum Monte Carlo Protocol To Achieve High Accuracy and High-Throughput Materials Formation Energies

High-throughput calculations based on density functional theory (DFT) methods have been widely implemented in the scientific community. However, depending on both the properties of interest as well as particular chemical/structural phase space, accuracy even for correct trends remains a key challenge for DFT. In this work, we evaluate the use of quantum Monte Carlo (QMC) to calculate material formation energies in a high-throughput environment. We test the performance of automated QMC calculations on 21 compounds with high quality reference data from the Committee on Data for Science and Technology (CODATA) thermodynamic database. We compare our approach to different DFT methods as well as different pseudopotentials, showing that errors in QMC calculations can be progressively improved especially when correct pseudopotentials are used. We determine a set of accurate pseudopotentials in QMC via a systematic investigation of multiple available pseudopotential libraries. We show that using this simple automated recipe, QMC calculations can outperform DFT calculations over a wide set of materials. Out of 21 compounds tested, chemical accuracy has been obtained in formation energies of 11 structures using our QMC recipe, compared to none using DFT calculations.

Chemistry↗
DOE OSTI2013

TIME-AVERAGE-BASED METHODS FOR MULTI-ANGULAR SCALE ANALYSIS OF COSMIC-RAY DATA

Over the past decade, a number of experiments dealt with the problem of measuring the arrival direction distribution of cosmic rays, looking for information on the propagation mechanisms and the identification of their sources. Any deviation from the isotropy may be regarded to as a signature of unforeseen or unknown phenomena, mostly if well localized in the sky and occurring at low rigidity. It induced experimenters to search for excesses down to angular scales as narrow as 10 Degree-Sign , disclosing the issue of properly filtering contributions from wider structures. A solution commonly envisaged was based on time-average methods to determine the reference value of cosmic-ray flux. Such techniques are nearly insensitive to signals wider than the time window in use, thus allowing us to focus the analysis on medium- and small-scale signals. Nonetheless, the signal often cannot be excluded in the calculation of the reference value, which induces systematic errors. The use of time-average methods recently revealed important discoveries about the medium-scale cosmic-ray anisotropy, present both in the northern and southern hemispheres. It is known that the excess (or deficit) is observed as less intense than in reality and that fake deficit zones are rendered around true excesses because of the absolute lack of knowledge a priori of which signal is true and which is not. This work is an attempt to critically review the use of time-average-based methods for observing extended features in the cosmic-ray arrival distribution pattern.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Unified architecture for quantum lookup tables

Quantum access to arbitrary classical data encoded in unitary black-box oracles underlies interesting data-intensive quantum algorithms, such as machine learning or electronic structure simulation. The feasibility of these applications depends crucially on gate-efficient implementations of these oracles, which are commonly some reversible versions of the Boolean circuit for a classical lookup table. Here, we present a general parametrized architecture for quantum circuits implementing a lookup table that encompasses all prior work in realizing a continuum of optimal trade-offs between qubits, non-Clifford gates, and error resilience, up to logarithmic factors. Our architecture assumes only local 2D connectivity, yet recovers results, with the appropriate parameters, polylogarithmic error scaling. We also identify regimes, such as simultaneous sublinear scaling, in all parameters. These results enable tailoring implementations of the commonly used lookup table primitive to any given quantum device with constrained resources.

quantum circuits↗
DOE OSTI2023

Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions

Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Maitner, Brian S.↗
DOE OSTI2017

Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation

This paper presents methodology to enable path planning for an unmanned aerial vehicle that uses dynamic data-driven flight capability estimation. The main contribution of the work is a general mathematical approach that leverages offline high-fidelity physics-based modeling together with onboard sensor measurements to achieve dynamic path planning. The mathematical framework, expressed as a constrained partially observable Markov decision process, accounts for vehicle capability constraints and is robust to modeling error and disturbances in both the vehicle process and measurement models. Vehicle capability constraints are incorporated using probabilistic support vector machine surrogates of high-fidelity physics-based models that adequately capture the richness of the vehicle dynamics. Sensor measurements are treated in a general manner and can include combinations of multiple modalities such as that through global positioning system signals, inertial mass unit outputs, and structural strain data of the airframe. Results are presented for a simulated three-dimensional environment and point-mass airplane model. The vehicle can dynamically adjust its trajectory according to the observations it receives about its current state of health, thereby retaining a high probability of survival and mission success.

42 ENGINEERING↗
DOE OSTI2012

CONSTRAINING FUNDAMENTAL CONSTANT EVOLUTION WITH H I AND OH LINES

We report deep Green Bank Telescope spectroscopy in the redshifted H I 21 cm and OH 18 cm lines from the z = 0.765 absorption system toward PMN J0134-0931. A comparison between the 'satellite' OH 18 cm line redshifts, or between the redshifts of the H I 21 cm and 'main' OH 18 cm lines, is sensitive to changes in different combinations of three fundamental constants, the fine structure constant {alpha}, the proton-electron mass ratio {mu} {identical_to} m{sub p} /m{sub e} , and the proton g-factor g{sub p} . We find that the satellite OH 18 cm lines are not perfectly conjugate, with both different line shapes and stronger 1612 MHz absorption than 1720 MHz emission. This implies that the satellite lines of this absorber are not suitable to probe fundamental constant evolution. A comparison between the redshifts of the H I 21 cm and OH 18 cm lines, via a multi-Gaussian fit, yields the strong constraint [{Delta}F/F] = [ - 5.2 {+-} 4.3] Multiplication-Sign 10{sup -6}, where F {identical_to} g{sub p} [{mu}{alpha}{sup 2}]{sup 1.57} and the error budget includes contributions from both statistical and systematic errors. We thus find no evidence for a change in the constants between z = 0.765 and the present epoch. Incorporating the constraint [{Delta}{mu}/{mu}] < 3.6 Multiplication-Sign 10{sup -7} from another absorber at a similar redshift and assuming that fractional changes in g{sub p} are much smaller than those in {alpha}, we obtain [{Delta}{alpha}/{alpha}] = (- 1.7 {+-} 1.4) Multiplication-Sign 10{sup -6} over a look-back time of 6.7 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A More Accurate Measurement of the {sup 28}Si Lattice Parameter

In 2011, a discrepancy between the values of the Planck constant measured by counting Si atoms and by comparing mechanical and electrical powers prompted a review, among others, of the measurement of the spacing of {sup 28}Si (220) lattice planes, either to confirm the measured value and its uncertainty or to identify errors. This exercise confirmed the result of the previous measurement and yields the additional value d{sub 220} = 192 014 711.98(34) am having a reduced uncertainty.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Analytic gradients for the single-reference driven similarity renormalization group second-order perturbation theory

Herein we derive and implement analytic energy gradients for the single-reference driven similarity renormalization group second-order perturbation theory (DSRG-PT2). The resulting equations possess an asymptotic scaling that is identical to that of the second-order Møller–Plesset perturbation theory (MP2), indicating that the exponential regularizer in the DSRG equations does not introduce formal difficulties in the gradient theory. We apply the DSRG-PT2 method to optimizing the geometries of 15 small molecules. The equilibrium bond lengths computed with DSRG-PT2 are found similar to those of MP2, yielding a mean absolute error of 0.0033 Å and a standard deviation of 0.0045 Å when compared with coupled cluster with singles, doubles, and perturbative triples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Estimation of Forest Aboveground Biomass from Derivatives of Vegetation-Structure Profiles

Several studies have found that the vertical Fourier transform of lidar, interferometric Synthetic Aperture Radar (SAR), and stereo photogrammetric profiles at empirically-determined spatial frequencies enables high-performance forest aboveground biomass (AGB) estimation. Linear combinations of real and imaginary parts of Fourier transforms of Tomographic (multi-baseline) SAR (TomoSAR) profiles, from Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) airborne data, generate ~20%-precision estimates of AGB in the Saskatchewan area of Canada. We found that this 20% precision can be improved to ~15%, a factor of 30% improvement in root mean square error (RMSE) if, in addition to using Fourier transforms of the profile itself, we use Fourier transforms of the spatial, vertical derivative of the profile. The formulation of this "derivative" algorithm is the subject of this paper.

Treuhaft, Robert↗
DOE OSTI2024

Effect of XC functionals and dispersion corrections on the DFT‐computed structural and vibrational properties of SrCl 2 –NaCl and ZrF 4 –LiF

Density functional theory (DFT) calculations were performed to examine the impact of exchange–correlation (XC) functionals and van der Waals corrections (specifically the D3 method) on the structural and vibrational properties of the SrCl 2 –NaCl and ZrF 4 –LiF salt systems. Multiple XC functionals, including the local density approximation (LDA), the generalized gradient approximation using the Perdew–Burke–Ernzerhof (PBE) model, and its modified form suitable for solids (PBEsol), the dispersion-corrected PBE-D3 and PBEsol-D3, were considered. Of these functionals, LDA was found to exhibit the highest degree of error, while PBEsol and PBE-D3 displayed the least error. Underestimated lattice parameters compared with experimental values were observed to result in higher force constants, leading to an overprediction of vibrational frequencies. Conversely, an overestimation of lattice parameters was associated with lower vibrational frequencies. The methodology presented in this study yielded results that are in good agreement with experiment, irrespective of the method (finite differences vs. density functional perturbation theory) employed for calculating infrared and Raman spectra. It was further demonstrated that for alkali halides with weak Raman scattering, utilizing a supercell constructed from primitive cells better predicts Raman features than does the use of conventional cells.

Raman↗
DOE OSTI2021

Comprehensive review of photophysical parameters (ε, Φ f , τ s ) of tetraphenylporphyrin (H 2 TPP) and zinc tetraphenylporphyrin (ZnTPP) – Critical benchmark molecules in photochemistry and photosynthesis

Tetraphenylporphyrin (H 2 TPP) and zinc tetraphenylporphyrin (ZnTPP) are widely used benchmark molecules in diverse photochemical studies given facile synthetic access, rich visible-region spectra, and broad structural analogy to chlorophylls. Yet the literature values for each key photophysical parameter – the molar absorption coefficient (ε), fluorescence quantum yield (Φ f ), and also singlet excited-state lifetime (τ S ) – vary over an astonishing range. Here, a comprehensive literature review (~1940–September 2020) encompassing 871 publications is reported for these essential parameters. Each parameter is determined by measurement with distinct instrumentation and suffers idiosyncratic sources of error. The best values for H 2 TPP are ε = 460,000 cm -1 ·M -1 , Φ f = 0.090, and τ S = 12.8 ns in Ar- purged toluene (Φf = 0.070, τS = 9.9 ns in toluene in air); the best values for ZnTPP are ε = 560,000 cm -1 ·M -1 , Φf = 0.030, and τ S = 2.1 ns in Ar-purged toluene (Φ f = 0.029, τ S = 2.0 ns in toluene in air). The choice of values for such parameters has far-reaching consequences in photochemistry ranging from fluorescence (or Förster) resonance energy transfer (FRET) processes to assessments of molecular brightness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Revealing the Formation Energy–Exfoliation Energy–Structure Correlation of MAB Phases Using Machine Learning and DFT

MAB phases are popular as high-temperature materials with high damage tolerance and excellent electrical conductivity that are used to exfoliate two-dimensional (2D) transition metal borides (MBenes); a promising material for developing next- generation nanodevices. In this report, we explore the correlation between the formation energy, exfoliation energy and structural factors of MAB phases using DFT and machine learning. In order to do so, we developed three different machine learning models based on the support vector machine, deep neural network, and random forest regressor to study the stability of the MAB phases by calculating their formation energies. Furthermore, our support vector machine and deep neural network models are capable of predicting the formation energies with mean absolute errors less than 0.1 eV/atom. We demonstrated that the stability of a MAB phase for a given transition metal decreases when the A element changes from Al to Tl. The density functional theory (DFT) re- vealed that M-A and M-B bond strength strongly correlates with the stability of MAB phases. In addition, the exfoliation possibility of 2D MBenes becomes higher when the A element changes from Al to Tl due to weakening of M-A and M-B bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Measuring the thermal Sunyaev-Zel'dovich effect through the cross correlation of Planck and WMAP maps with ROSAT galaxy cluster catalogs

We measure a significant correlation between the thermal Sunyaev-Zel'dovich effect in the Planck and WMAP maps and an X-ray cluster map based on ROSAT. We use the 100, 143 and 343 GHz Planck maps and the WMAP 94 GHz map to obtain this cluster cross spectrum. We check our measurements for contamination from dusty galaxies using the cross correlations with the 217, 545 and 857 GHz maps from Planck. Our measurement yields a direct characterization of the cluster power spectrum over a wide range of angular scales that is consistent with large cosmological simulations. The amplitude of this signal depends on cosmological parameters that determine the growth of structure (σ{sub 8} and Ω M) and scales as σ{sub 8}{sup 7.4} and Ω M{sup 1.9} around the multipole (ℓ) ∼ 1000. We constrain σ{sub 8} and Ω M from the cross-power spectrum to be σ{sub 8}(Ω M/0.30){sup 0.26} = 0.8±0.02. Since this cross spectrum produces a tight constraint in the σ{sub 8} and Ω M plane the errors on a σ{sub 8} constraint will be mostly limited by the uncertainties from external constraints. Future cluster catalogs, like those from eRosita and LSST, and pointed multi-wavelength observations of clusters will improve the constraining power of this cross spectrum measurement. In principle this analysis can be extended beyond σ{sub 8} and Ω M to constrain dark energy or the sum of the neutrino masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Modeling phonon-mediated quasiparticle poisoning in superconducting qubit arrays

Correlated errors caused by ionizing radiation impacting superconducting qubit chips are problematic for quantum error correction. Such impacts generate quasiparticle (QP) excitations in the qubit electrodes, which temporarily reduce qubit coherence significantly. The many energetic phonons produced by a particle impact travel efficiently throughout the device substrate and generate quasiparticles with high probability, thus causing errors on a large fraction of the qubits in an array simultaneously. Here, we describe a comprehensive strategy for the numerical simulation of the phonon and quasiparticle dynamics in the aftermath of an impact. We compare the simulations with experimental measurements of phonon-mediated QP poisoning and demonstrate that our modeling captures the spatial and temporal footprint of the QP poisoning for various configurations of phonon downconversion structures. We thus present a path forward for the operation of superconducting quantum processors in the presence of ionizing radiation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Evaluation of the WRF lake module (v1.0) and its improvements at a deep reservoir

Large lakes and reservoirs play important roles in modulating regional hydrological cycles and climate; however, their representations in coupled models remain uncertain. The existing lake module in the Weather Research and Forecasting (WRF) system (hereafter WRF-Lake), although widely used, did not accurately predict temperature profiles in deep lakes mainly due to its poor lake surface property parameterizations and underestimation of heat transfer between lake layers. We therefore revised WRF-Lake by improving its (1) numerical discretization scheme; (2) surface property parameterization; (3) diffusivity parameterization for deep lakes; and (4) convection scheme, the outcome of which became WRF-rLake (i.e., revised lake model). We evaluated the off-line WRF-rLake by comparing simulated and measured water temperature at the Nuozhadu Reservoir, a deep reservoir in southwestern China. WRF-rLake performs better than its predecessor by reducing the root-mean-square error (RMSE) against observed lake surface temperatures (LSTs) from 1.4 to 1.1°C and consistently improving simulated vertical temperature profiles. We also evaluated the sensitivity of simulated water temperature and surface energy fluxes to various modeled lake processes. We found (1) large changes in surface energy balance fluxes (up to 60 W m -2 ) associated with the improved surface property parameterization and (2) that the simulated lake thermal structure depends strongly on the light extinction coefficient and vertical diffusivity. Although currently only evaluated at the Nuozhadu Reservoir, we expect that these model parameterization and structural improvements could be general and therefore recommend further testing at other deep lakes and reservoirs.

58 GEOSCIENCES↗
DOE OSTI2026

Virtual refrigerant charge sensor for variable-speed heat pumps based on feature selection

The refrigerant charge level in heat pump systems significantly impacts their energy efficiency. Virtual refrigerant charge (VRC) sensing technology has been comprehensively investigated and well-established due to its lower cost compared to physical sensors. However, the previous VRC research often relied on expert judgment and physical reasoning for their variable selection, which can potentially select redundant (or highly correlated) or insignificant features, and it is also primarily focused on single-speed systems. To address these challenges, this study proposes a VRC algorithm for variable-speed heat pumps that selects features through a rigorous feature selection method in combination with physical insights. We also propose a piecewise linear model structure segmented by subcooling temperature to accurately predict charge levels, particularly when subcooling temperatures are substantially low. The proposed algorithm was evaluated using experimental data of a residential R410A heat pump, and the performance was compared with two baseline VRC algorithms. The results are: (1) The proposed algorithm outperforms for the case with subcooling temperature less than 1 °C. (2) The proposed algorithm achieves a tested mean absolute percentage error (MAPE) of 4.23%, and improves the overall accuracy for cooling conditions by approximately 60%, compared with the two baseline algorithms. (3) The proposed algorithm uses two fewer features and improves the accuracy for undercharge cooling conditions by 68.0%, compared with baseline algorithm 2. These improvements enhance prediction accuracy and prevent overfitting, providing a more reliable refrigerant charge level prediction and helping improve the heat pump energy efficiency.

Liang, Chenjiyu↗