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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

A three-dimensional dual potential procedure for inlets and indraft wind tunnels

A dual potential decomposition of the velocity field into a scalar and a vector potential function is extended to three dimensions and used in the finite-difference simulation of steady three-dimensional inviscid rotational flow through ducts and inlets. The procedure has been used to simulate the flow through the 80- by 120-Foot Wind Tunnel at NASA Ames Research Center. Vanes and screens located at the entrance of the inlet are modeled using actuator disk theory. The numerical predictions are in good agreement with experimental data.

Rao, K. V.↗
NASA NTRS2001

Scalar Measurements and Analysis of Helium Jets in Earth Gravity and Microgravity using Rainbow Schlieren Deflectometry

Recent experiments have shown that low-density gas jets injected into a high-density gas undergo an instability mode leading to highly periodic oscillations in the flow field. The transition from laminar to turbulent flow in these jets is abrupt, without a gradual change in scales. Although this type of instability at high Richardson numbers has been attributed to buoyancy, direct physical evidence was not acquired through experiments. In this study, several experiments were conducted in Earth gravity and microgravity to acquire qualitative data on near field flow structure of helium jets injected into air. Microgravity conditions were simulated in the 2.2-second drop tower at NASA Glenn Research Center. The operating parameters of this study included the tube inside diameter, the jet Reynolds number, and the jet Richardson number. Tubes with inside diameters of 19.05 mm and 31.75 mm were used in the experiments conducted in the drop tower. The jet flow was analyzed using quantitative rainbow schlieren deflectometry, a non-intrusive line of sight measurement technique for the whole field. The flow structure was characterized by distributions of angular deflection and the resulting helium mole fraction obtained from color schlieren images taken at 60 Hz. Three sets of experimental data with respect to three schlieren fields of view were acquired for each tube. Results show that the jet in microgravity was up to 70 percent wider than that in Earth gravity. The global jet flow oscillations observed in Earth gravity were absent in microgravity, providing direct experimental evidence that the flow instability in the low-density jet was buoyancy-induced. This study provides quantitative details of temporal flow evolution as the experiments undergo change in gravity in the drop tower.

Yep, Tze Wing↗
NASA NTRS1984

Long-wavelength Magnetic and Gravity Anomaly Correlations of Africa and Europe

Preliminary MAGSAT scalar magnetic anomaly data were compiled for comparison with long-wavelength-pass filtered free-air gravity anomalies and regional heat-flow and tectonic data. To facilitate the correlation analysis at satellite elevations over a spherical-Earth, equivalent point source inversion was used to differentially reduce the magnetic satellite anomalies to the radial pole at 350 km elevation, and to upward continue the first radial derivative of the free-air gravity anomalies. Correlation patterns between these regional geopotential anomaly fields are quantitatively established by moving window linear regression based on Poisson's theorem. Prominent correlations include direct correspondences for the Baltic Shield, where both anomalies are negative, and the central Mediterranean and Zaire Basin where both anomalies are positive. Inverse relationships are generally common over the Precambrian Shield in northwest Africa, the Basins and Shields in southern Africa, and the Alpine Orogenic Belt. Inverse correlations also presist over the North Sea Rifts, the Benue Rift, and more generally over the East African Rifts. The results of this quantitative correlation analysis support the general inverse relationships of gravity and magnetic anomalies observed for North American continental terrain which may be broadly related to magnetic crustal thickness variations.

Vonfrese, R. R. B.↗
NASA NTRS1985

Long-wavelength magnetic and gravity anomaly correlations on Africa and Europe

Preliminary MAGSAT scalar magnetic anomaly data were compiled for comparison with long-wavelength-pass filtered free-air gravity anomalies and regional heat-flow and tectonic data. To facilitate the correlation analysis at satellite elevations over a spherical-Earth, equivalent point source inversion was used to differentially reduce the magnetic satellite anomalies to the radial pole at 350 km elevation, and to upward continue the first radial derivative of the free-air gravity anomalies. Correlation patterns between these regional geopotential anomaly fields are quantitatively established by moving window linear regression based on Poisson's theorem. Prominent correlations include direct correspondences for the Baltic shield, where both anomalies are negative, and the central Mediterranean and Zaire Basin where both anomalies are positive. Inverse relationships are generally common over the Precambrian Shield in northwest Africa, the Basins and Shields in southern Africa, and the Alpine Orogenic Belt. Inverse correlations also presist over the North Sea Rifts, the Benue Rift, and more generally over the East African Rifts. The results of this quantitative correlation analysis support the general inverse relationships of gravity and magnetic anomalies observed for North American continental terrain which may be broadly related to magnetic crustal thickness variations.

Vonfrese, R. R. B.↗
NASA NTRS2014

Self-Calibration of BICEP1 Three-Year Data and Constraints on Astrophysical Polarization Rotation

Cosmic microwave background (CMB) polarimeters aspire to measure the faint B-mode signature predicted to arise from inflationary gravitational waves. They also have the potential to constrain cosmic birefringence, rotation of the polarization of the CMB arising from parity-violating physics, which would produce nonzero expectation values for the CMB's temperature to B-mode correlation (TB) and E-mode to B-mode correlation (EB) spectra. However, instrumental systematic effects can also cause these TB and EB correlations to be nonzero. In particular, an overall miscalibration of the polarization orientation of the detectors produces TB and EB spectra which are degenerate with isotropic cosmological birefringence, while also introducing a small but predictable bias on the BB spectrum. We find that BICEP1 three-year spectra, which use our standard calibration of detector polarization angles from a dielectric sheet, are consistent with a polarization rotation of alpha = −2.77deg +/- 0.86deg (statistical) +/- 1.3deg (systematic). We have revised the estimate of systematic error on the polarization rotation angle from the two-year analysis by comparing multiple calibration methods. We also account for the (negligible) impact of measured beam systematic effects. We investigate the polarization rotation for the BICEP1 100 GHz and 150 GHz bands separately to investigate theoretical models that produce frequency-dependent cosmic birefringence. We find no evidence in the data supporting either of these models or Faraday rotation of the CMB polarization by the Milky Way galaxy's magnetic field. If we assume that there is no cosmic birefringence, we can use the TB and EB spectra to calibrate detector polarization orientations, thus reducing bias of the cosmological B-mode spectrum from leaked E-modes due to possible polarization orientation miscalibration. After applying this "self-calibration" process, we find that the upper limit on the tensor-to-scalar ratio decreases slightly, from r < 0.70 to r < 0.65 at 95% confidence.

three-year↗
NASA NTRS1993

Pdf prediction of supersonic hydrogen flames

A hybrid method for the prediction of supersonic turbulent flows with combustion is developed consisting of a second order closure for the velocity field and a multi-scalar pdf method for the local thermodynamic state. It is shown that for non-premixed flames and chemical equilibrium mixture fraction, the logarithm of the (dimensionless) density, internal energy per unit mass and the divergence of the velocity have several advantages over other sets of scalars. The closure model is applied to a supersonic non-premixed flame burning hydrogen with air supplied by a supersonic coflow and the results are compared with a limited set of experimental data.

Eifler, P.↗
DOE OSTI2026

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗
DOE OSTI2023

Beyond the 3rd moment: a practical study of using lensing convergence CDFs for cosmology with DES Y3

ABSTRACT Widefield surveys probe clustered scalar fields – such as galaxy counts, lensing potential, etc. – which are sensitive to different cosmological and astrophysical processes. Constraining such processes depends on the statistics that summarize the field. We explore the cumulative distribution function (CDF) as a summary of the galaxy lensing convergence field. Using a suite of N-body light-cone simulations, we show the CDFs’ constraining power is modestly better than the second and third moments, as CDFs approximately capture information from all moments. We study the practical aspects of applying CDFs to data, using the Dark Energy Survey (DES Y3) data as an example, and compute the impact of different systematics on the CDFs. The contributions from the point spread function and reduced shear approximation are $\lesssim 1~{{\ \rm per\ cent}}$ of the total signal. Source clustering effects and baryon imprints contribute 1–10 per cent. Enforcing scale cuts to limit systematics-driven biases in parameter constraints degrade these constraints a noticeable amount, and this degradation is similar for the CDFs and the moments. We detect correlations between the observed convergence field and the shape noise field at 13σ. The non-Gaussian correlations in the noise field must be modelled accurately to use the CDFs, or other statistics sensitive to all moments, as a rigorous cosmology tool.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A Mountaintop View Requires Minimal Sorting: A Faster Contour Tree Algorithm

Consider a scalar field f : M → R, where M is a triangulated simplicial mesh in R d . A level set, or contour, at value v is a connected component of f –1 (v). As v is changed, these contours change topology, merge into each other, or split. Contour trees are concise representations of f that track this contour behavior. The vertices of these trees are the critical points of f, where the gradient is zero. The edges represent changes in the topology of contours. It is a fundamental data structure in data analysis and visualization, and there is significant previous work (both theoretical and practical) on algorithms for constructing contour trees. Suppose M has n vertices, N facets, and t critical points. A classic result of Carr, Snoeyink, and Axen (2000) gives an algorithm that takes O(n log n+Nα(N)) time (where α(·) is the inverse Ackermann function). A further improvement to O(t log t + N) time was given by Chiang et al. All these algorithms involve a global sort of the critical points, a significant computational bottleneck. Unfortunately, lower bounds of Ω(t log t) also exist. We present the first algorithm that can avoid the global sort and has a refined time complexity that depends on the contour tree structure. Intuitively, if the tree is short and fat, we get significant improvements in running time. For a partition of the contour tree into a set of descending paths, P, our algorithm runs in O($\Sigma$ pϵP |p| log |p| + tα(t) + N). This is at most O(t log D + N), where D is the diameter of the contour tree. Moreover, it is O(tα(t) + N) for balanced trees, a significant improvement over the previous complexity. Our algorithm requires numerous ideas: partitioning the contour tree into join and split trees, a local growing procedure to iteratively build contour trees, and the use of heavy path decompositions for the time complexity analysis. There is a crucial use of a family of binomial heaps to maintain priorities, ensuring that any comparison made is between comparable nodes of the contour tree. We also prove lower bounds showing that the $\Sigma$ pϵP |p| log |p| complexity is inherent to computing contour trees.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dependence of Aerosol-Droplet Partitioning on Turbulence in a Laboratory Cloud

Activation is the first step in aerosol-cloud interactions, which have been identified as one of the principal uncertainties in Earth's climate system. Aerosol particles become cloud droplets, or activate, when the ambient saturation ratio exceeds a threshold, which depends on the particle's size and hygroscopicity. In the traditional formulation of the process, only average, uniform saturation ratios are considered. Furthermore, turbulent environments like clouds intrinsically have fluctuations around mean values in the scalar fields of temperature and water vapor concentration, which determine the saturation ratio. Through laboratory measurements, we show that these fluctuations are an important parameter that needs to be addressed to fully describe activation. Our results show, even for single-sized, chemically homogeneous aerosols, that fluctuations blur the correspondence between activation and a particle's size and chemical composition, that turbulence can increase the fraction of aerosol particles which activate, and that the activated fraction decreases monotonically as the concentration of aerosol increases. Taken together, our data demonstrate that fluctuations can have effects equivalent to the aerosol limited and updraft limited regimes, known from adiabatic parcel theory.

58 GEOSCIENCES↗
NASA NTRS1994

Progress in navigation filter estimate fusion and its application to spacecraft rendezvous

A new derivation of an algorithm which fuses the outputs of two Kalman filters is presented within the context of previous research in this field. Unlike other works, this derivation clearly shows the combination of estimates to be optimal, minimizing the trace of the fused covariance matrix. The algorithm assumes that the filters use identical models, and are stable and operating optimally with respect to their own local measurements. Evidence is presented which indicates that the error ellipsoid derived from the covariance of the optimally fused estimate is contained within the intersections of the error ellipsoids of the two filters being fused. Modifications which reduce the algorithm's data transmission requirements are also presented, including a scalar gain approximation, a cross-covariance update formula which employs only the two contributing filters' autocovariances, and a form of the algorithm which can be used to reinitialize the two Kalman filters. A sufficient condition for using the optimally fused estimates to periodically reinitialize the Kalman filters in this fashion is presented and proved as a theorem. When these results are applied to an optimal spacecraft rendezvous problem, simulated performance results indicate that the use of optimally fused data leads to significantly improved robustness to initial target vehicle state errors. The following applications of estimate fusion methods to spacecraft rendezvous are also described: state vector differencing, and redundancy management.

Carpenter, J. Russell↗
DOE OSTI2023

CMS Physics Results in the LHC Runs 2,3

The Large hadron Collider at CERN and four scientific collaborations: Alice, ATLAS, CMS, LHCb are in operation since September 2008. The accelerator delivered and the experiments processed trillions of events of proton-proton and heavy ions collisions and provided useful data for thousands of physics analyses and publications. The jewel of the published data is a discovery in 2012 of the long anticipated Higgs boson. During the operation time the regular acquisition of data was interleaved with two periods of maintenance, Long-shutdown-1 (2013-2015) and Long-shutdown-2 (2018-2022), which resulted in several improvements to the machine and the experiments. The CMS collaboration recorded to date two large physics datasets of pp collision data. The first dataset, called Run 2, was recorded between 2015 and 2018 with 140fb-1 of integrated luminosity taken at 13TeV of center of mass energy. The second dataset, called Run 3, has just started in 2022 and it has been recording pp collision data at 13.6 TeV of center of mass energy, with 80 fb-1 of data collected till the end of July 2023.For my presentation I selected the most recent results produced by CMS from Run2 and Run 3 which are covering the topics of Higgs boson properties, searches for new particles and additional scalars, top quark production and properties, and I am discussing other interesting models e.g. using SM particles as portals to the Dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Experimental discovery of structure–property relationships in ferroelectric materials via active learning

Emergent functionalities of structural and topological defects in ferroelectric materials underpin an extremely broad spectrum of applications ranging from domain wall electronics to high dielectric and electromechanical responses. Many of these functionalities have been discovered and quantified via local scanning probe microscopy methods. However, the search has until now been based on either trial and error, or using auxiliary information such as the topography or domain wall structure to identify potential objects of interest on the basis of the intuition of operator or pre-existing hypotheses, with subsequent manual exploration. Here we report the development and implementation of a machine learning framework that actively discovers relationships between local domain structure and polarization-switching characteristics in ferroelectric materials encoded in the hysteresis loop. The hysteresis loops and their scalar descriptors such as nucleation bias, coercive bias and the hysteresis loop area (or more complex functionals of hysteresis loop shape) and corresponding uncertainties are used to guide the discovery of these relationships via automated piezoresponse force microscopy and spectroscopy experiments. As such, this approach combines the power of machine learning methods to learn the correlative relationships between high-dimensional data, as well as human-based physics insights encoded into the acquisition function. For ferroelectric materials, this automated workflow demonstrates that the discovery path and sampling points of on- and off-field hysteresis loops are largely different, indicating that on- and off-field hysteresis loops are dominated by different mechanisms. Here, the proposed approach is universal and can be applied to a broad range of modern imaging and spectroscopy methods ranging from other scanning probe microscopy modalities to electron microscopy and chemical imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantitative radiography for determining density fluctuations in HED experiments

We have developed a method to extract density fluctuation measurements from x-ray radiographs of high-energy density (HED) instability growth and turbulence experiments. We use this information to calculate density fluctuation statistics for constraining the performance of turbulent mix models in HED systems. The density calculation combines image filtering, removal of systemic effects such as backlighter variation, calculation of transmission across multiple materials, and use of tracer materials to generate an approximate single-material density field. From the density map, we calculate both average density and a variance-like moment b (density-specific-volume covariance), which we compare to our models. We infer both quantities from a single image, which is significantly more information than the historic single scalar mix width measurements. We also develop a method of analyzing simulation outputs that incorporate both the density fluctuation metric from a turbulence model and the bulk material maps from the hydrodynamic code. This analysis helps address the question of how to initialize the simulations for best comparison to data from systems with large separations of scale in the mixing perturbation initial condition. We find that our data analysis method yields 1D average density and b curves with similar morphology and amplitudes as those from preliminary simulation comparisons.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

hi_class background evolution, initial conditions and approximation schemes

Cosmological datasets have great potential to elucidate the nature of dark energy and test gravity on the largest scales available to observation. Theoretical predictions can be computed with hi_class (www.hiclass-code.net), an accurate, fast and flexible code for linear cosmology, incorporating a wide range of dark energy theories and modifications to general relativity. We introduce three new functionalities into hi_class: (1) Support for models based on covariant Lagrangians, including a constraint-preserving integration scheme for the background evolution and a series of worked-out examples: Galileon, nKGB, quintessence (monomial, tracker) and Brans-Dicke. (2) Consistent initial conditions for the scalar-field perturbations in the deep radiation era, identifying the conditions under which modified-gravity isocurvature perturbations may grow faster than adiabatic modes leading to a loss of predictivity. (3) An automated quasistatic approximation scheme allowing order-of-magnitude improvement in computing performance without sacrificing accuracy for wide classes of models. These enhancements bring the treatment of dark energy and modified gravity models to the level of detail comparable to software tools restricted to standard $\Lambda$CDM cosmologies. Finally, the hi_class code is publicly available (https://github.com/miguelzuma/hi_class_public), ready to explore current data and prepare for next-generation experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Lanczos algorithm for lattice QCD matrix elements

Recent work [M. L. Wagman, Lanczos, the transfer matrix, and the signal-to-noise problem, .] found that an analysis formalism based on the Lanczos algorithm allows energy levels to be extracted from Euclidean correlation functions with faster ground-state convergence than effective masses, convergent estimators for multiple states from a single correlator, and two-sided error bounds. After filtering out spurious eigenvalues and using outlier-robust estimators within a nested bootstrap framework, Lanczos estimators behave more like multistate fit results than effective masses—but without involving statistical fitting. We extend this formalism to the determination of matrix elements from three-point correlation functions and provide a physical picture of “spurious-state filtering” involving restriction to a Hermitian subspace. We demonstrate similar advantages for matrix elements as for spectroscopy through example applications to noiseless mock-data and (bare) forward matrix elements of the strange scalar current between both ground and excited states with the quantum numbers of the nucleon.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Evolving Dark Sector and the Dark Dimension Scenario

String theory naturally leads to the expectation that dark energy is not stable, and may be evolving as captured by the Swampland de Sitter conjectures. Moreover, motivated by the distance conjecture, a unification of dark sector has been proposed, where the smallness of dark energy leads to one extra dimension of micron size with dark matter being the Kaluza--Klein graviton excitations in this extra dimension. We consider the natural possibility that the radius of the dark dimension varies as the dark energy decreases, leading to the variation of the dark matter mass. This correlates the decrease of the dark energy with the variation of the dark matter mass as they depend on the variations of a scalar field $ϕ$ controlling the radius of the extra dimension. A simple realization of this idea for small range of $ϕ$ is adequately captured by choosing a potential which is locally of the form $V=V_0\ {\rm exp}(-cϕ)$ and dark matter mass $m_{\rm DM}=m_0\ {\rm exp}(-c' ϕ)$ where the sign of $ϕ$ is chosen such that $c'\geq 0$ while we have two choices for the sign of $c$ depending on whether the dark dimension expands or shrinks when the dark energy dominates. We find excellent agreement with recent experimental data from DESI DR2 combined with SN measurements (from DES, Union3 or Pantheon+) and reproduces the same significance as CPL parametrization with the added benefit of providing a natural explanation for the apparent phantom behavior ($w<-1$) reported by DESI and DES based on a physical model. DESI and SN datasets independently favor non-zero values of $c'$ and $c$, respectively, both lying within the expected $\mathcal{O}(1)$ range suggested by the Swampland criteria. Moreover, our best fit value $c'\simeq 0.05 \pm 0.01$ is remarkably consistent with the experimental upper bound of $c'\lesssim 0.2$ demanded by the lack of detection of fifth force in the dark sector.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗
NASA NTRS2012

Simulations of Spray Reacting Flows in a Single Element LDI Injector With and Without Invoking an Eulerian Scalar PDF Method

This paper presents the numerical simulations of the Jet-A spray reacting flow in a single element lean direct injection (LDI) injector by using the National Combustion Code (NCC) with and without invoking the Eulerian scalar probability density function (PDF) method. The flow field is calculated by using the Reynolds averaged Navier-Stokes equations (RANS and URANS) with nonlinear turbulence models, and when the scalar PDF method is invoked, the energy and compositions or species mass fractions are calculated by solving the equation of an ensemble averaged density-weighted fine-grained probability density function that is referred to here as the averaged probability density function (APDF). A nonlinear model for closing the convection term of the scalar APDF equation is used in the presented simulations and will be briefly described. Detailed comparisons between the results and available experimental data are carried out. Some positive findings of invoking the Eulerian scalar PDF method in both improving the simulation quality and reducing the computing cost are observed.

Shih, Tsan-Hsing↗