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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Challenges of Debris-Impact Risk Assessment for Robotic Spacecraft

This paper describes an orbital debris impact risk assessment performed on the command and data subsystem electronics box of QuikSCAT, a functioning spacecraft with approximately 18 years on orbit. Several aspects of the analysis are paid particular attention. First is the modeling of a thermal blanket at a small stand-off distance from the box chassis. The properties of the blanket are such that under some assumptions, it may be treated as an effective bumper shield, and under other assumptions, it may not. The assumptions and their effects on the results of the analysis are explored. Similarly, the configuration of the electronic components inside the chassis are such that several definitions of failure criteria appear plausible. The results of each treatment are presented together and compared with the status of the actual electronics box. The failure predictions vary widely between treatments, and the more conservative assumption sets predict incredulously high probabilities of failure. This is problematic because the conservative assumptions are the ones typically used in analyses for flight projects.

Ratliff, Martin↗
NASA NTRS2019

Midlatitude Lightning NOx Production Efficiency Inferred From OMI and WWLLN Data

Oxides of nitrogen are critical trace gases in the troposphere and are precursors for nitrate aerosol and ozone, which is an important pollutant and greenhouse gas. Lightning is the major source of NOx(NO + NO2) in the mid-to upper troposphere. We estimate the production efficiency (PE) of lightning NOx (LNOx) using satellite data from the Ozone Monitoring Instrument (OMI) and the ground-based WorldWide Lightning Location Network (WWLLN) in three northern midlatitude, primarily continental regions that include much of North America, Europe and East Asia. Data were obtained over 5 boreal summers, 2007 –2011 and comprise the largest number of midlatitude convective events to date for estimating the LNOx PE with satellite NO2and ground-based lightning measurements. In contrast to some previous studies, the algorithm assumes no minimum flash-rate threshold and estimates freshly produced LNOxby subtracting a background of aged NOx estimated from the OMI dataset itself. We infer an average value of 180 ± 100 moles LNOx produced per lightning flash. We also show evidence of a dependence of PE on lightning flash rate and find an approximate empirical power function relating moles LNOxto flashes. PE decreases by an order of magnitude for a 2-order of magnitude increase in flash rate. This phenomenon has not been reported in previous satellite LNOxstudies but is consistent with ground-based observations suggesting an inverse relationship between flash rate and size.

LNOx↗
NASA NTRS2021

Non-Causal Controller Approximation Methodology Augmented with Model Reference Control – Robust Design

This paper describes the development of a new control design methodology based on a non-causal controller structure and its approximation. The non-causal controller design is based on a loop shaping approach. Partial fraction decomposition is used, along with derivative approximations, to derive a proper transfer function design for a causal control structure. The premise for this non-causal control methodology is that the phase delay as a function of frequency ideally remains within approximately -90o, which tends to make the system robustly stable to uncertainties in the plant dynamics. To have a predictable control system response in lieu of the tolerance of this methodology to relatively large uncertainty in the plant dynamics, the approach is augmented with model reference control. The addition of model reference control can potentially further enhance the robustness of the design. A control system design example is presented in this paper, along with simulation results, to demonstrate the high degree of robustness of this non-causal methodology and its augmentation.

Control Systems↗
NASA NTRSDate not supplied

Automation of Geometric Accuracy Assessment Algorithm

When end-users are using multiple satellite images for a study the first step is often the assessment and rectification of geolocation offsets. We have developed an automated algorithm to calculate the geometric offsets between two satellite images. It splits both images into subset images (chips) and resamples them to a common resolution. Offsets are imposed on matching chips and the Pearson Cross Correlation (PCC) value calculated for each offset, where the best PCC gives the true offsets. With the true offsets corrected for, a quality of image registration is calculated, measurement uncertainty (MU). The MU threshold value is non-uniform across sensors because it depends on spectral characteristics of each sensor. Previously, the MU threshold was determined by manual inspection for each new sensor assessed. In this study, we automated MU threshold determination. 1/MU vs calculated offset approximates a Gaussian function in shape, see abstract image. A Gaussian function is fit to this dataset, and the root of the third derivative is calculated and applied as a quality threshold, removing the data of lower quality from the final assessment of image offsets. We apply this algorithm to commercial satellite data for proof of concept.

Alana Semple↗
DOE OSTI2017

Modular Expression Language for Ordinary Differential Equation Editing

MELODEEis a system for describing systems of initial value problem ordinary differential equations, and a compiler for the language that produces optimized code to integrate the differential equations. Features include rational polynomial approximation for expensive functions and automatic differentiation for symbolic jacobians

Blake, Robert C.↗
DOE OSTI2019

Monte Carlo Control Loops for Cosmic Shear Cosmology with DES Year 1

Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control of systematic errors. The Monte Carlo Control Loops (MCCL) is a forward modelling method designed to tackle this problem. It relies on the Ultra Fast Image Generator (UFig) to produce simulated images tuned to match the target data statistically, followed by calibrations and tolerance loops. We present the first end-to-end application of this method, on the Dark Energy Survey (DES) Year 1 wide field imaging data. We simultaneously measure the shear power spectrum $C_{\ell}$ and the redshift distribution $n(z)$ of the background galaxy sample. The method includes maps of the systematic sources, Point Spread Function (PSF), an Approximate Bayesian Computation (ABC) inference of the simulation model parameters, a shear calibration scheme, and the fast estimation of the covariance matrix. We find a close statistical agreement between the simulations and the DES Y1 data using an array of diagnostics. In a non-tomographic setting, we derive a set of $C_\ell$ and $n(z)$ curves that encode the cosmic shear measurement, as well as the systematic uncertainty. Following a blinding scheme, we measure the combination of $\Omega_m$, $\sigma_8$, and intrinsic alignment amplitude $A_{\rm{IA}}$, defined as $S_8D_{\rm{IA}} = \sigma_8(\Omega_m/0.3)^{0.5}D_{\rm{IA}}$, where $D_{\rm{IA}}=1-0.11(A_{\rm{IA}}-1)$. We find $S_8D_{\rm{IA}}=0.895^{+0.054}_{-0.039}$, where systematics are at the level of roughly 60\% of the statistical errors. We discuss these results in the context of earlier cosmic shear analyses of the DES Y1 data. Our findings indicate that this method and its fast runtime offer good prospects for cosmic shear measurements with future wide-field surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Toward Linear Stability Analysis of Upper Plenum Flows

Linear stability analysis is a tool used to help identify the sensitivity of a particular domain to perturbations and evaluate the system dynamics as a transition, if any, occurs. The development of a time invariant base flow for future use in a linear stability analysis is the focus of this investigation. A test case, with a Reynolds number of 100, was brought to a steady state using the spectral element code Nek5000 and the method of selective frequency damping. The convergence criteria for this method is the volume averaged value of the forcing function which, after approximately 80,000 time-steps, decreased to 3.6x10{sup -4}. Analysis shows that the case has yet to have reached the tolerance desired, 1x10{sup -6}. With the simulation in the process of converging a preliminary perturbation analysis was conducted. Due to the low Reynolds number of this case, 100, it was hypothesized that the flow would be linearly stable. This preliminary stability analysis only focused on the largest fundamental mode and the energy growth of that perturbation over time. Upon evaluation of the perturbation energy, which was shown to be monotonically decreasing in time, it was concluded that, despite not yet being converged, the system is in fact linearly stable. Future work includes evaluating the domain at higher Reynolds numbers, solving the eigenvalue problem created when the linearized Navier-Stokes are written in operator form and calculating the energy evolution of the optimal perturbation. (authors)

42 ENGINEERING↗
DOE OSTI2024

Constrained curve fitting for semi-parametric models with radial basis function networks

Common to many analysis pipelines in lattice gauge theory and the broader scientific discipline is the need to fit a semi-parametric model to data. We propose a fit method that utilizes a radial basis function network to approximate the non-parametric component of such models. The approximate parametric model is fit to data using the basin hopping global optimization algorithm. Parameter constraints are enforced through Gaussian priors. The viability of our method is tested by examining its use in a finite-size scaling analysis of the $q$-state Potts model and $p$-state clock model with $q=2,3$ and $p=4,\infty$.

Peterson, Curtis T.↗
DOE OSTI2019

Multiplicity dependence of light-flavor hadron production in p p collisions at s = 7 TeV

Comprehensive results on the production of unidentified charged particles, $π^±, K^±, K^0_S, K^*(892)^0, p,$ $\bar{p}$, $\phi$ (1020), Λ, $\bar{Λ}$, $\Xi^-$, $\bar{\Xi}^+$, $Ω^-$, and $\bar{Ω}^+$ hadrons in proton-proton ($pp$) collisions at $\sqrt{s}$ = 7 TeV at midrapidity ($|y|$ < 0.5) as a function of charged-particle multiplicity density are presented. In order to avoid autocorrelation biases, the actual transverse momentum ($p$ T ) spectra of the particles under study and the event activity are measured in different rapidity windows. In the highest multiplicity class, the charged-particle density reaches about 3.5 times the value measured in inelastic collisions. While the yield of protons normalized to pions remains approximately constant as a function of multiplicity, the corresponding ratios of strange hadrons to pions show a significant enhancement that increases with increasing strangeness content. Furthermore, all identified particle-to-pion ratios are shown to depend solely on charged-particle multiplicity density, regardless of system type and collision energy. The evolution of the spectral shapes with multiplicity and hadron mass shows patterns that are similar to those observed in $p$-Pb and Pb-Pb collisions at Large Hadron Collider energies. The obtained $p$ T distributions and yields are compared to expectations from QCD-based $pp$ event generators as well as to predictions from thermal and hydrodynamic models. These comparisons indicate that traces of a collective, equilibrated system are already present in high-multiplicity $pp$ collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1984

Multivariate spline methods in surface fitting

The use of spline functions in the development of classification algorithms is examined. In particular, a method is formulated for producing spline approximations to bivariate density functions where the density function is decribed by a histogram of measurements. The resulting approximations are then incorporated into a Bayesiaan classification procedure for which the Bayes decision regions and the probability of misclassification is readily computed. Some preliminary numerical results are presented to illustrate the method.

Guseman, L. F., Jr.↗
NASA NTRS1980

Convolution of a Doppler line by a Gaussian instrument function

A simple and direct method is obtained for assessing the distortion of a Doppler line by a Gaussian instrument function. It is suggested that a close approximation to the width of a Gaussian instrument function, or an almost Gaussian function, may be obtained by measuring a line with a Doppler absorption coefficient. The method is applicable to diode laser measurements, and may be used whenever a Gaussian instrument function is a reasonable approximation to real conditions

Fridovich, B.↗
DOE OSTI2017

The effect of Limber and flat-sky approximations on galaxy weak lensing

We review the effect of the commonly-used Limber and flat-sky approximations on the calculation of shear power spectra and correlation functions for galaxy weak lensing. These approximations are accurate at small scales, but it has been claimed recently that their impact on low multipoles could lead to an increase in the amplitude of the mass fluctuations inferred from surveys such as CFHTLenS, reducing the tension between galaxy weak lensing and the amplitude determined by Planck from observations of the cosmic microwave background. Here, we explore the impact of these approximations on cosmological parameters derived from weak lensing surveys, using the CFHTLenS data as a test case. We conclude that the use of small-angle approximations for cosmological parameter estimation is negligible for current data, and does not contribute to the tension between current weak lensing surveys and Planck.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

LTAU (Loss Trajectory Analysis for Uncertainty) is a technique for estimating the uncertainty in a model's predictions for any regression task by approximating the cumulative distribution function (CDF) of the model's errors over the course of training. The approximated CDF, combined with a similarity search algorithm in the model's descriptor space, can then be used to estimate the likelihood that the model's predictions on any given test point will fall below a chosen threshold. LTAU-FF (LTAU in atomistic Force Fields) is the application of LTAU specifically for use with atomistic force fields.

Vita, JoshuaA↗
DOE OSTI2017

Ab initio molecular dynamics simulations of liquid water using high quality meta-GGA functionals

We have used ab initio molecular dynamics (AIMD) to characterize water properties using two meta-generalized gradient approximation (meta-GGA) functionals, M06-L-D3 and B97M-rV, and compared their performance against a standard GGA corrected for dispersion, revPBE-D3, at ambient conditions (298 K, and 1 g cm –3 or 1 atm). Simulations of the equilibrium density, radial distribution functions, self-diffusivity, the infrared spectrum, liquid dipole moments, and characterizations of the hydrogen bond network show that all three functionals have overcome the problem of the early AIMD simulations that erroneously found ambient water to be highly structured, but they differ substantially among themselves in agreement with experiment on this range of water properties. We show directly using water cluster data up through the pentamer that revPBE-D3 benefits from a cancellation of its intrinsic functional error by running classical trajectories, whereas the meta-GGA functionals are demonstrably more accurate and would require the simulation of nuclear quantum effects to realize better agreement with all cluster and condensed phase properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

Properties of the Io plasma torus inferred from Voyager EUV data

A physical model for the Io plasma torus is constructed to explain the EUV radiative emission observed by the Voyager UV spectrometer. Electron impact excitation rate coefficients for electronic transitions of S III, S IV, O II and O III are calculated by the method of distorted waves (Davis, Kepple, and Blaha, 1976); these coefficients account for the asymmetric shape of the 686 A feature. It is concluded that the electron gas must have a distribution function with a non-Maxwellian tail. An approximate representation of the distribution function as two temperature components requires a cold component of 3.5-4 eV and density of 2000 per cu cm and a hot component of about 100 eV and density of 50-100 per cu cm to satisfy observational constraints.

Strobel, D. F.↗
NASA NTRS1986

An adaptive characteristic Petrov-Galerkin finite element method for convection-dominated linear and nonlinear parabolic problems in one space variable

The present adaptive FEM technique for convection-dominated problems is based on a Petrov-Galerkin scheme for spatial approximation, whose typical time-step employs test functions chosen to yield an approximate solution coinciding with the exact solutions at the finite element grid nodes. The derivation of truly local a posteriori error estimates is made possible by this procedure, which is also shown to be a very effective solver by the numerical examples presented.

Demkowicz, L.↗
NASA NTRS1993

Parameter estimation techniques based on optimizing goodness-of-fit statistics for structural reliability

New methods are presented that utilize the optimization of goodness-of-fit statistics in order to estimate Weibull parameters from failure data. It is assumed that the underlying population is characterized by a three-parameter Weibull distribution. Goodness-of-fit tests are based on the empirical distribution function (EDF). The EDF is a step function, calculated using failure data, and represents an approximation of the cumulative distribution function for the underlying population. Statistics (such as the Kolmogorov-Smirnov statistic and the Anderson-Darling statistic) measure the discrepancy between the EDF and the cumulative distribution function (CDF). These statistics are minimized with respect to the three Weibull parameters. Due to nonlinearities encountered in the minimization process, Powell's numerical optimization procedure is applied to obtain the optimum value of the EDF. Numerical examples show the applicability of these new estimation methods. The results are compared to the estimates obtained with Cooper's nonlinear regression algorithm.

Starlinger, Alois↗