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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Behaviour related flight speeds of Sandwich Terns and their implications for wind farm collision rate modelling and impact assessment

Highlights: • Flight speeds of Sandwich Terns vary with behavioural states. • Flight speed is a vital part of wind turbine collision rate models (CRM) for birds. • The variation in flight speed has major consequences for CRM output. • CRM output is vital for adequate Environmental Impact Assessments. - Abstract: Accurate quantification of flight speeds is a prerequisite to accurately predict the numbers of collision victims of proposed wind farms using collision rate models that are a vital part of Environmental Impact Assessments. We used GPS-loggers on Sandwich Terns to collect novel data on instantaneous flight speeds during foraging trips, separated for different behavioural stages, and applied these estimates in a widely used collision rate model. Average flight speed during a foraging trip corrected for individual variation and flight type was 36.9 ± 12.3 SD km h{sup −1} and flight speed was highest during inbound commuting (44.4 ± 12.0 km h{sup −1}) and lowest during foraging (29.9 ± 10.7 km h{sup −1}). Our results show significant differences in flight speeds of Sandwich Terns between behaviour stages during foraging trips, which resulted in divergent estimates of collision victims due to wind turbines depending on the function of the area in which wind farms are proposed. Since these conclusions are likely to hold for many other bird species, we conclude that behaviour of birds in a proposed wind farm is a factor to take into account when modelling collision rates as part of the Environmental Impact Assessment.

17 WIND ENERGY↗
DOE OSTI2022

Electronic structure of superconducting nickelates probed by resonant photoemission spectroscopy

We report the discovery of infinite-layer nickelate superconductors has spurred enormous interest. While the Ni 1+ cations possess nominally the same 3d 9 configuration as Cu 2+ in cuprates, the electronic structure variances remain elusive. Here, we present a soft X-ray photoemission spectroscopy study on parent and doped infinite-layer Pr-nickelate thin films with a doped perovskite reference. By identifying the Ni character with resonant photoemission and comparison with density functional theory + U (on-site Coulomb repulsion energy) calculations, we estimate U ~5 eV, smaller than the charge transfer energy Δ ~8 eV, confirming the Mott-Hubbard electronic structure in contrast to charge-transfer cuprates. Near the Fermi level (E F ), we observe a signature of occupied rare-earth states in the parent compound, which is consistent with a self-doping picture. Our results demonstrate a correlation between the superconducting transition temperature and the oxygen 2p hybridization near E F when comparing hole-doped nickelates and cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Investigation of a model based reconstruction technique for neutron tomography at the PULSTAR reactor

Herein, a model based neutron computed tomography (CT) reconstruction technique is developed and implemented to improve the spatial resolution of the reconstructed images. The spatial resolution of a scintillator and a charge-coupled device (CCD) based digital neutron imaging system is quantified and used as the system response function in the iterative reconstruction process. The response function is included in the forward projection model to provide better estimation of the actual projection, thus improving the spatial resolution of the reconstructed images. Experiments were performed at the neutron imaging facility of the PULSTAR research reactor to corroborate the performance of the developed algorithm with a 50 μm and 250 μa m 6 LiF:ZnS thick scintillator. The reconstruction results of the model based technique have shown an improvement of nearly 40% in achievable spatial resolution as compared to the standard filtered back projection (FBP) technique.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Turbulence-parameter estimation for current-energy converters using surrogate model optimization

Surrogate models maximize information utility by building predictive models in place of computational or experimentally expensive model runs. Marine hydrokinetic current energy converters require large-domain simulations to estimate array efficiencies and environmental impacts. Meso-scale models typically represent turbines as actuator discs that act as momentum sinks and sources of turbulence and its dissipation. An OpenFOAM model was developed where actuator disc k-ε turbulence was characterized using an approach developed for flows through vegetative canopies. Turbine-wake data from laboratory flume experiments collected at two influent turbulence intensities were used to calibrate parameters in the turbulence-source terms in the k-ε equations. Additionally, parameter influences on longitudinal wake profiles were estimated using Gaussian process regression with subsequent optimization minimizing the objective function within 3.1% of those obtained using the full model representation, but for 74% of the computational cost (far fewer model runs). This framework facilitates more efficient parameterization of the turbulence-source equations using turbine-wake data.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

Atomic and Molecular Adsorption on Ag(111)

The adsorption of atomic (H, C, N, O, S) and molecular (OH, CH x , NH x , CO, NO, CN, N 2 , HNO, NOH, HCN, x = 1–3) species at 1/4 monolayer coverage on an extended Ag(111) surface was studied here using periodic density functional theory. Geometries and energies were calculated self-consistently using the PW91 functional; nonself-consistent energies using the RPBE functional are also provided. We analyze the binding energies, binding geometries, estimated diffusion barriers, harmonic vibrational frequencies, and energetic and geometric deformation parameters of these adsorbates, comparing them to experimental and theoretical results whenever possible. PW91 gives binding energies that match experimental binding energies more closely than RPBE, which consistently predicts weaker binding than PW91. The data were then used to construct and analyze thermochemistry-only potential energy pathways for the hydrocarbon-assisted and hydrogen-assisted selective catalytic reduction (SCR) of nitric oxide (NO). These analyses provide preliminary insights into the possible mechanistic paths of the SCR of NO on Ag(111). Specifically, we show that deep dehydrogenation leading to the formation of atomic intermediates is not favored on Ag(111).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Klinkenberg Effect and Effective Pressure for Gas Permeability of Tight Sandstones

Gas permeability k g of tight sandstones was measured while cycling pore pressure, Pf, and confining pressure, P c , using two different procedures. Firstly, we cycled the pore pressure from a minimum value close to atmospheric pressure to a maximum one slightly lower than P c , while keeping the Pc constant. Secondly, P f and P c were simultaneously varied so as to keep the difference, P c - P f , constant. Significant effects owing to slip flow were observed when the gas pressure was lower than about 5 MPa. Klinkenberg plots showed that, under constant P c , gas permeability kg decreased linearly for high values of 1/P f , reached a minimum and then sharply increased as 1/P f approached zero. Under constant P c - P f , k g again decreased linearly in the high limit of 1/P f and showed additional decrease in the low 1/P f limit. The linear segments in both procedures indicate that k g in tight sandstones was subject to slip flow at low values of P f , while the curved segments revealed the sensitivity of permeability to effective pressure when Pf became comparable in magnitude to confining pressure. The effective pressure coefficient α was estimated and generally appeared to be a well-defined decreasing function of the pressure difference P c - P f . We modified the Walsh permeability model for fissured rocks to include slip-flow effects and obtained satisfactory fits to the experimental data for the samples with lowest porosities and highest pressure-sensitivities. This observation suggests that the intrinsic permeability of these rocks was controlled by inter- and/or intra-granular crack-like pores.

58 GEOSCIENCES↗
DOE OSTI2018

Using both qualitative and quantitative data in parameter identification for systems biology models

Abstract In systems biology, qualitative data are often generated, but rarely used to parameterize models. We demonstrate an approach in which qualitative and quantitative data can be combined for parameter identification. In this approach, qualitative data are converted into inequality constraints imposed on the outputs of the model. These inequalities are used along with quantitative data points to construct a single scalar objective function that accounts for both datasets. To illustrate the approach, we estimate parameters for a simple model describing Raf activation. We then apply the technique to a more elaborate model characterizing cell cycle regulation in yeast. We incorporate both quantitative time courses (561 data points) and qualitative phenotypes of 119 mutant yeast strains (1647 inequalities) to perform automated identification of 153 model parameters. We quantify parameter uncertainty using a profile likelihood approach. Our results indicate the value of combining qualitative and quantitative data to parameterize systems biology models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Downfolding from ab initio to interacting model Hamiltonians: comprehensive analysis and benchmarking of the DFT+cRPA approach

Abstract Model Hamiltonians are regularly derived from first principles to describe correlated matter. However, the standard methods for this contain a number of largely unexplored approximations. For a strongly correlated impurity model system, here we carefully compare a standard downfolding technique with the best possible ground-truth estimates for charge-neutral excited-state energies and wave functions using state-of-the-art first-principles many-body wave function approaches. To this end, we use the vanadocene molecule and analyze all downfolding aspects, including the Hamiltonian form, target basis, double-counting correction, and Coulomb interaction screening models. We find that the choice of target-space basis functions emerges as a key factor for the quality of the downfolded results, while orbital-dependent double-counting corrections diminish the quality. Background screening of the Coulomb interaction matrix elements primarily affects crystal-field excitations. Our benchmark uncovers the relative importance of each downfolding step and offers insights into the potential accuracy of minimal downfolded model Hamiltonians.

Chemistry↗
DOE OSTI2022

Early-Stage Evaluation of Catalyst Manufacturing Cost and Environmental Impact Using CatCost

The costs and environmental impacts of catalyst manufacture are often neglected during early-stage research because of a lack of accessible, standardized tools to assess them. Here we report the key features of CatCost, a free and public estimation tool for the evaluation of catalyst cost. We demonstrate its functionality with a case study of diverse catalysts (ZSM-5, Pt/TiO2 and Mo2C) for the catalytic fast pyrolysis of biomass. We quantified the economic and environmental improvements made by replacing circulating-bed ZSM-5 with more stable, fixed-bed Pt/TiO2 and Mo2C catalysts, while revealing the effects of synthesis methods and production scale on catalyst costs. The manufacture of ZSM-5 had a large processing cost contribution that was strongly scale dependent, whereas the costs of the other catalysts were dominated by raw materials at all scales. Furthermore, while ZSM-5 costs the least per kilogram, the more stable catalysts cost half as much per gallon of fuel.

BIOMASS FUELS,ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Gaussian approximation potentials for accurate thermal properties of two-dimensional materials

Two-dimensional materials (2DMs) continue to attract a lot of attention, particularly for their extreme flexibility and superior thermal properties. Molecular dynamics simulations are among the most powerful methods for computing these properties, but their reliability depends on the accuracy of interatomic interactions. While first principles approaches provide the most accurate description of interatomic forces, they are computationally expensive. In contrast, classical force fields are computationally efficient, but have limited accuracy in interatomic force description. Machine learning interatomic potentials, such as Gaussian Approximation Potentials, trained on density functional theory (DFT) calculations offer a compromise by providing both accurate estimation and computational efficiency. Here, in this work, we present a systematic procedure to develop Gaussian approximation potentials for selected 2DMs, graphene, buckled silicene, and h-XN (X = B, Al, and Ga, as binary compounds) structures. We validate our approach through calculations that require various levels of accuracy in interatomic interactions. The calculated phonon dispersion curves and lattice thermal conductivity, obtained through harmonic and anharmonic force constants (including fourth order) are in excellent agreement with DFT results. HIPHIVE calculations, in which the generated GAP potentials were used to compute higher-order force constants instead of DFT, demonstrated the first-principles level accuracy of the potentials for interatomic force description. Molecular dynamics simulations based on phonon density of states calculations, which agree closely with DFT-based calculations, also show the success of the generated potentials in high-temperature simulations.

2D Materials↗
DOE OSTI2016

Bayesian calibration of coarse-grained forces: Efficiently addressing transferability

Generating and calibrating forces that are transferable across a range of state-points remains a challenging task in coarse-grained (CG) molecular dynamics. In this work, we present a coarse-graining workflow, inspired by ideas from uncertainty quantification and numerical analysis, to address this problem. The key idea behind our approach is to introduce a Bayesian correction algorithm that uses functional derivatives of CG simulations to rapidly and inexpensively recalibrate initial estimates f{sub 0} of forces anchored by standard methods such as force-matching. Taking density-temperature relationships as a running example, we demonstrate that this algorithm, in concert with various interpolation schemes, can be used to efficiently compute physically reasonable force curves on a fine grid of state-points. Importantly, we show that our workflow is robust to several choices available to the modeler, including the interpolation schemes and tools used to construct f{sub 0}. In a related vein, we also demonstrate that our approach can speed up coarse-graining by reducing the number of atomistic simulations needed as inputs to standard methods for generating CG forces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Effects of annealed temperature on the properties of TiO{sub 2} thin films

In this work, the structural, morphological and electrical properties of TiO{sub 2} thin films are studied. The phase transformation of TiO{sub 2} from anatase to rutile is occurred at a certain temperature. This transformation increases defects concentration onthe surface of the film which acts as trapping sites for carriers, thereby affecting the Fermi level of TiO{sub 2} film.Quantitative estimation of Fermi level shifting is measured in terms of work function measurement using scanning Kelvin probe measurement. Work function of TiO{sub 2} was found to decrease with increasing annealed temperature indicating shifting of Fermi level towards conduction band. Position of Fermi level plays an important role in phase transformation and electronic properties of TiO{sub 2}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Novel 2D velocity estimation method for large transient events in plasmas

Dynamics of fast transient events are challenging to be analyzed with high time resolution. Such events can occur in fusion plasmas such as the filaments during edge-localized modes (ELMs). Here, we present a robust method—the spatial displacement estimation—for estimating the displacements of structures with fast dynamics from high spatial and time resolution imaging diagnostics [e.g., gas-puff imaging (GPI)] with sampling time temporal resolution. First, a background suppression method is shown, which suppresses the slowly time-evolving and spatially non-uniform background in the signal. In the second step, a two-dimensional polynomial trend subtraction method is presented to tackle the remaining polynomial order trend in the signal. After performing these pre-processing steps, the spatial displacement of the propagating structure is estimated from the two-dimensional spatial cross-correlation coefficient function calculated between consecutive frames. The method is tested for its robustness and accuracy by simulated Gaussian events and spatially displaced random noise. An example application of the method is presented on propagating ELM filaments measured by the GPI system on the National Spherical Torus Experiment spherical tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Anomalies of cosmic anisotropy from holographic universality of great-circle variance

We examine all-sky cosmic microwave background temperature maps on large angular scales to compare their consistency with two scenarios: the standard inflationary quantum picture, and a distribution constrained to have a universal variance of primordial curvature perturbations on great circles. The latter symmetry is not a property of standard quantum inflation, but may be a symmetry of holographic models with causal quantum coherence on null surfaces. Since the variation of great-circle variance is dominated by the largest angular scale modes, in the latter case the amplitude and direction of the unobserved intrinsic dipole (that is, the ℓ = 1 harmonics) can be estimated from measured ℓ = 2, 3 harmonics by minimizing the variance of great-circle variances including only ℓ = 1, 2, 3 modes. It is found that including the estimated intrinsic dipole leads to a nearly-null angular correlation function over a wide range of angles, in agreement with a null anti-hemispherical symmetry independently motivated by holographic causal arguments, but highly anomalous in standard cosmology. Simulations are used here to show that simultaneously imposing the constraints of universal great-circle variance and the vanishing of the angular correlation function over a wide range of angles tends to require patterns that are unusual in the standard picture, such as anomalously high sectorality of the ℓ = 3 components, and a close alignment of principal axes of ℓ = 2 and ℓ = 3 components, that have been previously noted on the actual sky. The precision of these results appears to be primarily limited by errors introduced by models of Galactic foregrounds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Normalizing flows for likelihood-free inference with fusion simulations

Fluid-based scrape-off layer transport codes, such as UEDGE, are heavily utilized in tokamak analysis and design, but typically require user-specified anomalous transport coefficients to match experiments. Determining the uniqueness of these parameters and the uncertainties in them to match experiments can provide valuable insights to fusion scientists. Here, we leverage recent work in the area of likelihood-free inference (‘simulation-based inference’) to train a neural network, which enables accurate statistical inference of the anomalous transport coefficients given experimental plasma profile input. UEDGE is treated as a black-box simulator and runs multiple times with anomalous transport coefficients sampled from priors, and the neural network is trained on these simulations to emulate the posterior. The neural network is trained as a normalizing flow model for density estimation, allowing it to accurately represent complicated, high-dimensional distribution functions. With a fixed simulation budget, we compare a single-round procedure to a multi-round approach that guides the training simulations toward a specific target observation. Finally, we discuss the future possibilities for use of amortized models, which train on a wide range of simulations and enable fast statistical inference for results during experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

The binned bispectrum estimator: template-based and non-parametric CMB non-Gaussianity searches

We describe the details of the binned bispectrum estimator as used for the official 2013 and 2015 analyses of the temperature and polarization CMB maps from the ESA Planck satellite. The defining aspect of this estimator is the determination of a map bispectrum (3-point correlation function) that has been binned in harmonic space. For a parametric determination of the non-Gaussianity in the map (the so-called f NL parameters), one takes the inner product of this binned bispectrum with theoretically motivated templates. However, as a complementary approach one can also smooth the binned bispectrum using a variable smoothing scale in order to suppress noise and make coherent features stand out above the noise. This allows one to look in a model-independent way for any statistically significant bispectral signal. This approach is useful for characterizing the bispectral shape of the galactic foreground emission, for which a theoretical prediction of the bispectral anisotropy is lacking, and for detecting a serendipitous primordial signal, for which a theoretical template has not yet been put forth. Both the template-based and the non-parametric approaches are described in this paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Determination of nuclear PDFs using Markov chain Monte Carlo methods

Global QCD analyses of nuclear parton distribution functions (nPDFs) have traditionally relied on the Hessian method for uncertainty estimation. However, the inherent Gaussian approximation and reliance on local curvature often prove insufficient for nPDF fits, which are frequently characterized by limited data constraints and non-Gaussian likelihoods. In this paper, we present the first nPDF determination based on Markov Chain Monte Carlo (MCMC) techniques, implemented within the nCTEQ framework using an adaptive Metropolis-Hastings algorithm. The MCMC approach enables a direct mapping of the posterior distribution and reveals a highly nontrivial parameter-space structure, including multiple modes and pronounced non-Gaussian behavior, particularly for the valence PDFs. We perform the first single-nucleus global analysis of lead PDFs using exclusively lead data and compare it to a multi-nuclei fit employing a standard analytic A dependence. The inclusion of lighter nuclei reduces quark uncertainties and modifies the shape of the lead PDFs, while leaving the gluon distribution largely unaffected. A complementary Hessian analysis exposes systematic limitations of the Gaussian approximation. Our results demonstrate that MCMC methods provide a more reliable framework for uncertainty quantification in nPDF determinations.

Derakhshanian, N. [Institute of Nuclear Physics Po↗
DOE OSTI2025

Current-based metrology with two-terminal mesoscopic conductors

The traditional approach to quantum parameter estimation focuses on the quantum state, deriving fundamental bounds on precision through the quantum Fisher information. In most experimental settings, however, performing arbitrary quantum measurements is highly unfeasible. In open quantum systems, an alternative approach to metrology involves the measurement of stochastic currents flowing from the system to its environment. However, the present understanding of current-based metrology is mostly limited to Markovian master equations. Considering a parameter estimation problem in a two-terminal mesoscopic conductor, we identify the key elements that determine estimation precision within the Landauer-Büttiker formalism. Crucially, this approach allows us to address arbitrary coupling and temperature regimes. Furthermore, we obtain analytical results for the precision in linear-response and zero-temperature regimes. For the specific parameter estimation task that we consider, we demonstrate that the boxcar transmission function is optimal for current-based metrology in all parameter regimes.

Landauer formula↗