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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Scramjet Engine Flowpath Development for the Hyper-X Mach 10 Flight Test

The third flight of the Hyper-X Research Vehicle at nearly Mach 10 in November 2004 demonstrated the potential for airbreathing propulsion at hypersonic speeds. The flowpath of the scramjet engine used in the Hyper-X Research Vehicle was developed using computational fluid dynamic based design method in combination with a systematic series of ground tests in the NASA HyPulse Shock Tunnel at conditions duplicating Mach 10 flight. The test model was a true scale height and length of the internal flight engine flowpath that was partial width and truncated fore and aft. Tests were conducted using a mixture of hydrogen augmented with two-percent silane. Silane gas served as an ignition aid during the short duration of the pulse facility tests. The engine inflow values of pressure, temperature, and Mach number were parametrically varied during the ground test entries to broaden the database over the expected uncertainty in the flight conditions. A review of the ground test technique and comparisons of the ground test pressures along with selected data from the third flight are presented.

Rogers, R. C.↗
NASA NTRS2010

Details of Side Load Test Data and Analysis for a Truncated Ideal Contour Nozzle and a Parabolic Contour Nozzle

Two cold flow subscale nozzles were tested for side load characteristics during simulated nozzle start transients. The two test article contours were a truncated ideal and a parabolic. The current paper is an extension of a 2009 AIAA JPC paper on the test results for the same two nozzle test articles. The side load moments were measured with the strain tube approach in MSFC s Nozzle Test Facility. The processing techniques implemented to convert the strain gage signals into side load moment data are explained. Nozzle wall pressure profiles for separated nozzle flow at many NPRs are presented and discussed in detail. The effect of the test cell diffuser inlet on the parabolic nozzle s wall pressure profiles for separated flow is shown. The maximum measured side load moments for the two contours are compared. The truncated ideal contour s peak side load moment was 45% of that of the parabolic contour. The calculated side load moments, via mean-plus-three-standard-deviations at each nozzle pressure ratio, reproduced the characteristics and absolute values of measured maximums for both contours. The effect of facility vibration on the measured side load moments is quantified and the effect on uncertainty is calculated. The nozzle contour designs are discussed and the impact of a minor fabrication flaw in the nozzle contours is explained.

Ruf, Joseph H.↗
NASA NTRS1990

Orthogonal series generalized likelihood ratio test for failure detection and isolation

A new failure detection and isolation algorithm for linear dynamic systems is presented. This algorithm, the Orthogonal Series Generalized Likelihood Ratio (OSGLR) test, is based on the assumption that the failure modes of interest can be represented by truncated series expansions. This assumption leads to a failure detection algorithm with several desirable properties. Computer simulation results are presented for the detection of the failures of actuators and sensors of a C-130 aircraft. The results show that the OSGLR test generally performs as well as the GLR test in terms of time to detect a failure and is more robust to failure mode uncertainty. However, the OSGLR test is also somewhat more sensitive to modeling errors than the GLR test.

Hall, Steven R.↗
NASA NTRS2013

Estimating the Concentration of Large Raindrops from Polarimetric Radar and Disdrometer Observations

Estimation of rainfall integral parameters, including radar observables, and empirical relations between them are sensitive to the truncation of the drop size distribution (DSD), particularly at the large drop end. The sensitivity of rainfall integral parameters to the maximum drop diameter (D(sub max)) is exacerbated at C‐band since resonance effects are pronounced for large drops in excess of 5 mm diameter (D). Due to sampling limitations, it is often difficult to reliably estimate D(sub max) with disdrometers. The resulting uncertainties in D(sub max0 potentially increase errors in radar retrieval methods, particularly at C‐band, that rely on disdrometer observations for DSD input to radar models. In fact, D(sub max) is typically an assumed DSD parameter in the development of radar retrieval methods. Because of these very uncertainties, it is difficult to independently confirm disdrometer estimates of D(sub max) with polarimetric radar observations. A couple of approaches can be taken to reduce uncertainty in large drop measurement. Longer integration times can be used for the collection of larger disdrometer samples. However, integration periods must be consistent with a radar resolution volume (RRV) and the temporal and spatial scales of the physical processes affecting the DSD therein. Multiple co‐located disdrometers can be combined into a network to increase the sample size within a RRV. However, over a reasonable integration period, a single disdrometer sample volume is many orders of magnitudes less than a RRV so it is not practical to devise a network of disdrometers that has an equivalent volume to a typical RRV. Since knowledge of DSD heterogeneity and large drop occurrence in time and space is lacking, the specific accuracy or even general representativeness of disdrometer based D(sub max) and large drop concentration estimates within a RRV are currently unknown. To address this complex issue, we begin with a simpler question. Is the frequency of occurrence of large rain drops (D > 5 mm) in disdrometer observations, either stand alone or networked, generally representative and consistent with polarimetric radar observations? We first show from simulations that the concentration of large (D > 5 mm) rain drops (N(sub T5)) can be estimated from polarimetric observations of specific differential phase (K(sub dp)) and differential reflectivity (Z(sub dr)), N(sub T5)=F(K(sub dp),Z(sub dr)), or horizontal reflectivity (Z(sub h)) and Z(sub dr), N(sub T5)=(Z(sub h),Z(sub dr)). We assess the error associated with polarimetric retrieval of N(sub T5), including sensitivity to D(sub max) parameterization assumptions and measurement error in the radar simulations. Polarimetric measurements at S‐band and C‐band will then be used to retrieve estimates of N(sub T5) and compared to disdrometer estimates of N(sub T5). After careful consideration of retrieval error, we will check consistency between disdrometer and polarimetric radar estimates of N(sub T5) and the frequency of occurrence of large rain drops in a variety of precipitating regimes using data from NASA's Global Precipitation Measurement (GPM) Ground Validation (GV) program, including field campaigns such as MC3E (Oklahoma) and IFloodS (Iowa) and extended measurements over Huntsville, Alabama and NASA Wallops Flight Facility in coastal Virginia.

Carey, Lawrence D.↗
DOE OSTI2025

From chiral effective field theory to perturbative QCD: A Bayesian model mixing approach to symmetric nuclear matter

Constraining the equation of state (EOS) of strongly interacting, dense matter is the focus of intense experimental, observational, and theoretical effort. Chiral effective field theory (𝜒⁢EFT ) can describe the EOS between the typical densities of nuclei and those in the outer cores of neutron stars, while perturbative QCD (pQCD) can be applied to properties of deconfined quark matter, both with quantified theoretical uncertainties. However, describing the full range of densities in between with a single EOS that has well-quantified uncertainties is a challenging problem. Bayesian multimodel inference from 𝜒⁢EFT and pQCD can help bridge the gap between the two theories. In this work, we introduce a correlated Bayesian model mixing framework that uses a Gaussian process (GP) to assimilate different information into a single QCD EOS for symmetric nuclear matter. The present implementation uses a stationary GP to infer this mixed EOS solely from the EOSs of 𝜒⁢EFT and pQCD while accounting for the truncation errors of each theory. The GP is trained on the pressure as a function of number density in the low- and high-density regions where 𝜒⁢EFT and pQCD are, respectively, valid. We impose priors on the GP kernel hyperparameters to suppress unphysical correlations between these regimes. This, together with the assumption of stationarity, results in smooth 𝜒⁢EFT-to-pQCD curves for both the pressure and the speed of sound. We show that using uncorrelated mixing requires uncontrolled extrapolation of at least one of 𝜒⁢EFT or pQCD into regions where the perturbative series breaks down and leads to an acausal EOS. Here, we also discuss extensions of this framework to nonstationary and less differentiable GP kernels, its future application to neutron-star matter, and the incorporation of additional constraints from nuclear theory, experiment, and multimessenger astronomy.

Bayesian methods↗
NASA NTRS2020

Spatial distribution of the X-ray-emitting plasma of U Geminorum in quiescence and outburst

We present our analysis of the Suzaku data of U Geminorum (U Gem) from 2012 both in quiescence and outburst. Unlike SS Cygni (SS Cyg), the hard X-ray flux of U Gem is known to increase at times of optical outburst. A sophisticated spectral model and reliable distance estimate now reveal that this can be attributed to the fact that the mass accretion rate onto the white dwarf (WD) does not exceed the critical rate that causes the optically thin to thick transition of the boundary layer. From comparison of the X-ray and optical light curves, the X-ray outburst peak seems to be retarded by 2.1 ± 0.5 d, although there remains uncertainty in the X-ray peak identification, due to short data coverage. The larger delay than SS Cyg (0.9–1.4 d) also supports the lower accretion rate in U Gem. A fluorescent iron 6.4 keV emission line bears significant information about the geometry of the X-ray-emitting hot plasma and the accretion disk (AD) that reflects the hard X-ray emission. Our reflection simulation has shown that the optically thick AD is truncated at a distance of 1.20–1.25 times the white dwarf radius (RWD) in quiescence, and the accreting matter in the disk turns into the optically thin hard-X-ray-emitting plasma at this radius. In outburst, on the other hand, our spectral analysis favors the picture that the optically thick disk reaches the WD surface, although disk truncation can take place in the region of <1.012 RWD. From the profile of the 6.4 keV line, we have also discovered that the accreting matter is heated up close to the maximum temperature immediately after the matter enters the boundary layer at the disk truncation radius. This is consistent with the fact that the hard X-ray spectra of dwarf novae, in general, can be well represented with the cooling flow model.

Mai Takeo↗
DOE OSTI2020

A Data-Driven Nonparametric Approach for Probabilistic Load-Margin Assessment Considering Wind Power Penetration

A modern power system is characterized by an increasing penetration of wind power, which results in large uncertainties in its states. These uncertainties must be quantified properly; otherwise, the system security may be threatened. Facing this challenge, here we propose a cost-effective, data-driven approach to assessing a power system's load margin probabilistically. Using actual wind data, a kernel density estimator is applied to infer the nonparametric wind speed distributions, which are further merged into the framework of a vine copula. The latter enables us to simulate complex multivariate and highly dependent model inputs with a variety of bivariate copulae that precisely represent the tail dependence in the correlated samples. Furthermore, to reduce the prohibitive computational time of traditional Monte-Carlo simulations that process a large amount of samples, we propose to use a nonparametric, Gaussian-process-emulator-based reduced-order model to replace the original complicated continuation power-flow model through a Bayesian-learning framework. To accelerate the convergence rate of this Bayesian algorithm, a truncated polynomial chaos surrogate, which serves as a highly efficient, parametric Bayesian prior, is developed. This emulator allows us to execute the time-consuming continuation power-flow solver at the sampled values with a negligible computational cost. Results of simulations that are performed on several test systems reveal the impressive performance of the proposed method in the probabilistic load-margin assessment.

17 WIND ENERGY↗
DOE OSTI2020

Randomized Projection for Rank-Revealing Matrix Factorizations and Low-Rank Approximations

Rank-revealing matrix decompositions provide an essential tool in spectral analysis of matrices, including the Singular Value Decomposition (SVD) and related low-rank approximation techniques. QR with Column Pivoting (QRCP) is usually suitable for these purposes, but it can be much slower than the unpivoted QR algorithm. For large matrices, the difference in performance is due to increased communication between the processor and slow memory, which QRCP needs in order to choose pivots during decomposition. Our main algorithm, Randomized QR with Column Pivoting (RQRCP), uses randomized projection to make pivot decisions from a much smaller sample matrix, which we can construct to reside in a faster level of memory than the original matrix. This technique may be understood as trading vastly reduced communication for a controlled increase in uncertainty during the decision process. Furthermore, for rank-revealing purposes, the selection mechanism in RQRCP produces results that are the same quality as the standard algorithm, but with performance near that of unpivoted QR (often an order of magnitude faster for large matrices). Additionally, we also propose two formulas that facilitate further performance improvements. The first efficiently updates sample matrices to avoid computing new randomized projections. The second avoids large trailing updates during the decomposition in truncated low-rank approximations. Our truncated version of RQRCP also provides a key initial step in our truncated SVD approximation, TUXV. These advances open up a new performance domain for large matrix factorizations that will support efficient problem-solving techniques for challenging applications in science, engineering, and data analysis.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Numerical Experimentation with Maximum Likelihood Identification in Static Distributed Systems

Many important issues in the control of large space structures are intimately related to the fundamental problem of parameter identification. One might also ask how well this identification process can be carried out in the presence of noisy data since no sensor system is perfect. With these considerations in mind the algorithms herein are designed to treat both the case of uncertainties in the modeling and uncertainties in the data. The analytical aspects of maximum likelihood identification are considered in some detail in another paper. The questions relevant to the implementation of these schemes are dealt with, particularly as they apply to models of large space structures. The emphasis is on the influence of the infinite dimensional character of the problem on finite dimensional implementations of the algorithms. Those areas of current and future analysis are highlighted which indicate the interplay between error analysis and possible truncations of the state and parameter spaces.

Scheid, R. E., Jr.↗
NASA NTRS1985

Dynamic modeling and adaptive control for space stations

Of all large space structural systems, space stations present a unique challenge and requirement to advanced control technology. Their operations require control system stability over an extremely broad range of parameter changes and high level of disturbances. During shuttle docking the system mass may suddenly increase by more than 100% and during station assembly the mass may vary even more drastically. These coupled with the inherent dynamic model uncertainties associated with large space structural systems require highly sophisticated control systems that can grow as the stations evolve and cope with the uncertainties and time-varying elements to maintain the stability and pointing of the space stations. The aspects of space station operational properties are first examined, including configurations, dynamic models, shuttle docking contact dynamics, solar panel interaction, and load reduction to yield a set of system models and conditions. A model reference adaptive control algorithm along with the inner-loop plant augmentation design for controlling the space stations under severe operational conditions of shuttle docking, excessive model parameter errors, and model truncation are then investigated. The instability problem caused by the zero-frequency rigid body modes and a proposed solution using plant augmentation are addressed. Two sets of sufficient conditions which guarantee the globablly asymptotic stability for the space station systems are obtained.

Ih, C. H. C.↗
DOE OSTI2026

Computational schemes for the Magnus expansion of the in-medium similarity renormalization group

The in-medium similarity renormalization group (IMSRG) is a popular many-body method used for computations of nuclei. It solves the many-body Schrödinger equation through a continuous unitary transformation of the many-body Hamiltonian. The IMSRG transformation is typically truncated at the normal-ordered two-body level, the IMSRG(2), but recently several approaches have been developed to capture the effects of normal-ordered three-body operators, the IMSRG(3). In particular, a factorized approximation to the IMSRG(3) proposes to capture the leading effects of three-body operators at the same computational cost as the IMSRG(2) approximation. This approach often employs an approximate scheme for solving the IMSRG equations, the so-called hunter-gatherer scheme. In this work, I study the uncertainty associated with this scheme. I find that the hunter-gatherer scheme differs by up to 7MeV for ground-state energies and 0.5MeV for excitation energies from standard IMSRG(2) approaches. These differences are in some cases comparable to the expected size of IMSRG(3) corrections.

39 ≤ A ≤ 58↗
NASA NTRS1999

Lunar Prospector Orbit Determination Uncertainties Using the High Resolution Lunar Gravity Models

The Lunar Prospector (LP) mission began on January 6, 1998, when the LP spacecraft was launched from Cape Canaveral, Florida. The objectives of the mission were to determine whether water ice exists at the lunar poles, generate a global compositional map of the lunar surface, detect lunar outgassing, and improve knowledge of the lunar magnetic and gravity fields. Orbit determination of LP performed at the Jet Propulsion Laboratory (JPL) is conducted as part of the principal science investigation of the lunar gravity field. This paper will describe the JPL effort in support of the LP Gravity Investigation. This support includes high precision orbit determination, gravity model validation, and data editing. A description of the mission and its trajectory will be provided first, followed by a discussion of the orbit determination estimation procedure and models. Accuracies will be examined in terms of orbit-to-orbit solution differences, as a function of oblateness model truncation, and inclination in the plane-of-sky. Long term predictions for several gravity fields will be compared to the reconstructed orbits to demonstrate the accuracy of the orbit determination and oblateness fields developed by the Principal Gravity Investigator.

Carranza, Eric↗
DOE OSTI2021

Constrained Extrapolation Problem and Order-Dependent Mappings

In this work, we consider the problem of extrapolating the perturbation series for the dilute Fermi gas in three dimensions to the unitary limit of infinite scattering length and into the BEC region, using the available strong-coupling information to constrain the extrapolation problem. In this constrained extrapolation problem (CEP) the goal is to find classes of approximants that give well converged results already for low perturbative truncation orders. First, we show that standard Padé and Borel methods are too restrictive to give satisfactory results for this CEP. A generalization of Borel extrapolation is given by the so-called Maximum Entropy extrapolation method (MaxEnt). However, we show that MaxEnt requires extensive elaborations to be applicable to the dilute Fermi gas and is thus not practical for the CEP in this case. Instead, we propose order-dependent-mapping extrapolation (ODME) as a simple, practical, and general method for the CEP. Here, we find that the ODME approximants for the ground-state energy of the dilute Fermi gas are robust with respect to changes of the mapping choice and agree with results from quantum Monte Carlo simulations within uncertainties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2016

Spectro-Timing Study of GX 339-4 in a Hard Intermediate State

We present an analysis of Nuclear Spectroscopic Telescope Array observations of a hard intermediate state of the transient black hole GX 339-4 taken in 2015 January. With the source softening significantly over the course of the 1.3 day long observation we split the data into 21 sub-sets and find that the spectrum of all of them can be well described by a power-law continuum with an additional relativistically blurred reflection component. The photon index increases from approx. 1.69 to approx. 1.77 over the course of the observation. The accretion disk is truncated at around nine gravitational radii in all spectra. We also perform timing analysis on the same 21 individual data sets, and find a strong type-C quasi-periodic oscillation (QPO), which increases in frequency from approx. 0.68 to approx. 1.05 Hz with time. The frequency change is well correlated with the softening of the spectrum. We discuss possible scenarios for the production of the QPO and calculate predicted inner radii in the relativistic precession model as well as the global disk mode oscillations model. We find discrepancies with respect to the observed values in both models unless we allow for a black hole mass of approx. 100 Mass compared to the Sun, which is highly unlikely. We discuss possible systematic uncertainties, in particular with the measurement of the inner accretion disk radius in the relativistic reflection model. We conclude that the combination of observed QPO frequencies and inner accretion disk radii, as obtained from spectral fitting, is difficult to reconcile with current models.

accretion disks↗
DOE OSTI2022

Detailed analysis of excited-state systematics in a lattice QCD calculation of 𝑔 𝐴

Excited state contamination remains one of the most challenging sources of systematic uncertainty to control in lattice QCD calculations of nucleon matrix elements and form factors: early time separations are contaminated by excited states and late times suffer from an exponentially bad signal-to-noise problem. High-statistics calculations at large time separations ≳ 1 fm are commonly used to combat these issues. In this work, focusing on g A , we explore the alternative strategy of utilizing a large number of relatively low-statistics calculations at short to medium time separations (0.2–1 fm), combined with a multistate analysis. On an ensemble with a pion mass of approximately 310 MeV and a lattice spacing of approximately 0.09 fm, we find this provides a more robust and economical method of quantifying and controlling the excited state systematic uncertainty. A quantitative separation of various types of excited states enables the identification of the transition matrix elements as the dominant contamination. The excited state contamination of the Feynman-Hellmann correlation function is found to reduce to the 1% level at approximately 1 fm while, for the more standard three-point functions, this does not occur until after 2 fm. Critical to our findings is the use of a global minimization, rather than fixing the spectrum from the two-point functions and using them as input to the three-point analysis. We find that the ground state parameters determined in such a global analysis are stable against variations in the excited state model, the number of excited states, and the truncation of early-time or late-time numerical data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Isovector Axial Charge and Form Factors of Nucleons from Lattice QCD

A survey of the calculations of the isovector axial vector form factor of the nucleon using lattice QCD is presented. Attention is paid to statistical and systematic uncertainties, in particular those due to excited state contributions. Based on a comparison of results from various collaborations, a case is made that lattice results are consistent within 10%. A similar level of uncertainty is in the axial charge gAu−d, the mean squared axial charge radius ⟨rA2⟩, the induced pseudoscalar charge gP∗, and the pion–nucleon coupling gπNN. Even with the current methodology, a significant reduction in errors is expected over the next few years with higher statistics data on more ensembles closer to the physical point. Lattice QCD results for the form factor GA(Q2) are compatible with those obtained from the recent MINERνA experiment but lie 2–3σ higher than the phenomenological extraction from the old ν–deuterium bubble chamber scattering data for Q2>0.3 GeV2. Current data show that the dipole ansatz does not have enough parameters to fit the form factor over the range 0≤Q2≤1 GeV2, whereas even a z2 truncation of the z expansion or a low order Padé are sufficient. Looking ahead, lattice QCD calculations will provide increasingly precise results over the range 0≤Q2≤1 GeV2, and MINERνA-like experiments will extend the range to Q2∼2 GeV2 or higher. Nevertheless, improvements in lattice methods to (i) further control excited state contributions and (ii) extend the range of Q2 are needed.

Astronomy & Astrophysics↗
DOE OSTI2024

Optimization of algorithmic errors in analog quantum simulations

Due to rapidly improving quantum computing hardware, Hamiltonian simulations of relativistic lattice field theories have seen a resurgence of attention. Furthermore, this computational tool requires turning the formally infinite-dimensional Hilbert space of the full theory into a finite-dimensional one. For gauge theories, a widely used basis for the Hilbert space relies on the representations induced by the underlying gauge group, with a truncation that keeps only a set of the lowest dimensional representations. This works well at large bare gauge coupling, but becomes less efficient at small coupling, which is required for the continuum limit of the lattice theory. In this work, we develop a new basis suitable for the simulation of an SU(2) lattice gauge theory in the maximal tree gauge. In particular, we show how to perform a Hamiltonian truncation so that the eigenvalues of both the magnetic and electric gauge-fixed Hamiltonian are mostly preserved, which allows for this basis to be used at all values of the coupling. Little prior knowledge is assumed, so this may also be used as an introduction to the subject of Hamiltonian formulations of lattice gauge theories.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2019

Three CA-Related Covariance Issues and Their Solutions

This presentation addresses three issues that arise in the use of DoD-produced satellite state estimate covariances in the conjunction assessment process: the realism of the provided covariances, how to address correlated error between two satellites' covariance matrices, and how to proceed when a furnished covariance is non-positive-definite. To address the first, DoD has implemented a set of two "consider parameters" with which to alter/expand the covariance to account for atmospheric density forecast error and satellite frontal area uncertainty, the two largest sources of unmodeled position prediction error for LEO orbits; these values are governed by a satellite's orbital parameters and ballistic coefficient histories, as well as the current and predicted space weather situation. This approach substantially improves the realism of the covariance by accounting for expected prediction errors that are not part of the fit process that generates the covariance. The second issue of covariance correlation is a complicated one, but the main shared error source—global atmospheric density error that is common to both satellites can be characterized and, through sensitivity vectors, quantified at the conjunction's time of closest approach and removed from the joint covariance, which is used in the CA probability of collision (Pc) calculation. Finally, while according to the orbit determination theory a non-positive-definite (NPD) covariance is not possible, numerical truncation and covariance interpolation can conspire to produce NPD results, which render the covariance unusable for certain CA risk assessment calculations, such as Monte Carlo Pc determination. Three similar techniques are profiled and the simplest of them recommended as a reasonable remediation technique when NPD covariances are encountered by CA practitioners.

Dynamic Consider Parameter↗