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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Relative Navigation In Elliptical Orbits Using An Iterative Nonlinear Filter

The two step filter is applied to process intersatellite radar measurements to determine the motion of one satellite relative to another in close elliptical orbits. This filter breaks a nonlinear estimation problem into two state vectors. The 'first step' state is chosen so as to have a linear measurement equation. This is nonlinearly related to the 'second step' state which describes the dynamics. Two different forms are used. In one, the first step state is the second step state vector augmented by the measurement equation. In the other, the first step and second step state vectors are of equal dimension. The two step filter is compared against an iterated extended Kalman filter and a Kalman filter using a change of variables. Analytical differences between the two step estimator and these conventional filters are highlighted. Special concerns for initializing the first step state covariance matrix and handling the possibility of numerically rank deficient covariance matrices are addressed. Numerical simulations are performed which show that the Two Step estimator produces a lower estimation bias under two circumstances; large apriori initial error; and small dimension observation vectors which require a longer arc of measurements to generate observability of the state.

Garrison, James L.↗
NASA NTRS2023

Automated Machine Learning to Evaluate the Information Content of Tropospheric Trace Gas Columns for Fine Particle Estimates Over India: A Modeling Testbed

India is largely devoid of high-quality and reliable on-the-ground measurements of fine particulate matter (PM 2.5 ). Ground-level PM 2.5 concentrations are estimated from publicly available satellite Aerosol Optical Depth (AOD) products combined with other information. Prior research has largely overlooked the possibility of gaining additional accuracy and insights into the sources of PM using satellite retrievals of tropospheric trace gas columns. We evaluate the information content of tropospheric trace gas columns for PM 2.5 estimates over India within a modeling testbed using an Automated Machine Learning (AutoML) approach, which selects from a menu of different machine learning tools based on the data set. We then quantify the relative information content of tropospheric trace gas columns, AOD, meteorological fields, and emissions for estimating PM 2.5 over four Indian sub-regions on daily and monthly time scales. Our findings suggest that, regardless of the specific machine learning model assumptions, incorporating trace gas modeled columns improves PM 2.5 estimates. We use the ranking scores produced from the AutoML algorithm and Spearman’s rank correlation to infer or link the possible relative importance of primary versus secondary sources of PM 2.5 as a first step toward estimating particle composition. Our comparison of AutoML-derived models to selected baseline machine learning models demonstrates that AutoML is at least as good as user-chosen models. The idealized pseudo-observations (chemical-transport model simulations) used in this work lay the groundwork for applying satellite retrievals of tropospheric trace gases to estimate fine particle concentrations in India and serve to illustrate the promise of AutoML applications in atmospheric and environmental research.

Machine learning↗
NASA NTRS1983

Seismic velocity structure of the lunar mantle

The recently completed set of seismic arrival times from the Apollo lunar seismic network are inverted to estimate the average seismic velocities in three sections of the lunar mantle: two for the upper mantle and one for the middle mantle. The method used is a variation of the linearized least squares inversion where the inversion is accomplished in steps. The estimated average velocities in the upper mantle decrease from Vp = 7.74 km/sec and Vs = 4.49 km/sec in the section above 270-km depth to Vp = 7.46 km/sec and Vs = 4.25 km/sec in the section between 270- and 500-km depth, confirming the earlier finding of negative gradients based on seismic amplitude variations. The average velocities in the middle mantle between the depths of 500 km and 1000 km of Vp = 8.26 km/sec and Vs = 4.65 km/sec are significantly higher than those in the upper mantle, contradicting earlier estimates based on more limited data. The higher velocities may suggest initial melting of the moon down to at least 1000-km depth.

Nakamura, Y.↗
NASA NTRS2020

Attribution of Chemistry-Climate Model Initiative (CCMI) Ozone Radiative Flux Bias from Satellites

The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6-μm ozone band is a fundamental quantity for understanding chemistry-climate coupling. However, observed TOA fluxes are hard to estimate as they exhibit considerable variability in space and time that depend on the distributions of clouds, ozone (O3), water vapor (H2O), air temperature (Ta), and surface temperature (Ts). Benchmarking present day fluxes and quantifying the relative influence of their drivers is the first step for estimating climate feedbacks from ozone radiative forcing and predicting radiative forcing evolution. To that end, we constructed observational instantaneous radiative kernels (IRKs) under clear-sky conditions, representing the sensitivities of the TOA flux in the 9.6-μm ozone band to the vertical distribution of geophysical variables, including O3, H2O, Ta, and Ts based upon the Aura Tropospheric Emission Spectrometer (TES) measurements. Applying these kernels to present-day simulations from the Chemistry-Climate Model Initiative (CCMI) project as compared to a 2006 reanalysis assimilating satellite observations, we show that the models have large differences in TOA flux, attributable to different geophysical variables. In particular, model simulations continue to diverge from observations in the tropics, as reported in previous studies of the Atmospheric Chemistry Climate Model Inter-comparison Project (ACCMIP) simulations. The principal culprits are tropical mid and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mWm-2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mWm-2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mWm-2). We found that AM3 and CMAM have the lowest TOA flux biases globally but are a result of cancellation of opposite biases due to difference processes. Overall, the multi-model ensemble mean bias is –133±98 mWm-2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 and these competing effects add more uncertainties on the ozone radiative forcing. We find that the inter-model TOA outgoing longwave radiation (OLR) difference is well anti-correlated with their ozone band flux bias. This suggests that there is significant radiative compensation in the calculation of model outgoing longwave radiation.

Aura Tropospheric Emission Spectrometer (TES) meas↗
NASA NTRS1986

Senstitivity analysis of horizontal heat and vapor transfer coefficients for a cloud-topped marine boundary layer during cold-air outbreaks

The effects of external parameters on the surface heat and vapor fluxes into the marine atmospheric boundary layer (MABL) during cold-air outbreaks are investigated using the numerical model of Stage and Businger (1981a). These fluxes are nondimensionalized using the horizontal heat (g1) and vapor (g2) transfer coefficient method first suggested by Chou and Atlas (1982) and further formulated by Stage (1983a). In order to simplify the problem, the boundary layer is assumed to be well mixed and horizontally homogeneous, and to have linear shoreline soundings of equivalent potential temperature and mixing ratio. Modifications of initial surface flux estimates, time step limitation, and termination conditions are made to the MABL model to obtain accurate computations. The dependence of g1 and g2 in the cloud topped boundary layer on the external parameters (wind speed, divergence, sea surface temperature, radiative sky temperature, cloud top radiation cooling, and initial shoreline soundings of temperature, and mixing ratio) is studied by a sensitivity analysis, which shows that the uncertainties of horizontal transfer coefficients caused by changes in the parameters are reasonably small.

Chang, Y. V.↗
NASA NTRS2014

Noise and Fuel Burn Reduction Potential of an Innovative Subsonic Transport Configuration

A study is presented for the noise and fuel burn reduction potential of an innovative double deck concept aircraft with two three-shaft direct-drive turbofan engines. The engines are mounted from the fuselage so that the engine inlet is over the main wing. It is shown that such an aircraft can achieve a cumulative Effective Perceived Noise Level (EPNL) about 28 dB below the current aircraft noise regulations of Stage 4. The combination of high bypass ratio engines and advanced wing design with laminar flow control technologies provide fuel burn reduction and low noise levels simultaneously. For example, the fuselage mounted engine position provides more than 4 EPNLdB of noise reduction by shielding the inlet radiated noise. To identify the potential effect of noise reduction technologies on this concept, parametric studies are presented to reveal the system level benefits of various emerging noise reduction concepts, for both engine and airframe noise reduction. These concepts are discussed both individually to show their respective incremental noise reduction potential and collectively to assess their aggregate effects on the total noise. Through these concepts approximately about 8 dB of additional noise reduction is possible, bringing the cumulative noise level of this aircraft to 36 EPNLdB below Stage 4, if the entire suite of noise reduction technologies would mature to practical application. In a final step, an estimate is made for this same aircraft concept but with higher bypass ratio, geared, turbofan engines. With this geared turbofan propulsion system, the noise is estimated to reach as low as 40-42 dB below Stage 4 with a fuel burn reduction of 43-47% below the 2005 best-in-class aircraft baseline. While just short of the NASA N+2 goals of 42 dB and 50% fuel burn reduction, for a 2025 in service timeframe, this assessment shows that this innovative concept warrants refined study. Furthermore, this design appears to be a viable potential future passenger aircraft, not only in meeting the regulatory requirements, but also in competing with aircraft of different advanced designs within this N+2 timeframe and goal framework.

Guo, Yueping↗
NASA NTRS2015

Kinematic and Microphysical Control of Lightning Flash Rate over Northern Alabama

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to examine the relationship between deep convection and the production of nitrogen oxides (NO (sub x)) via lightning (LNO (sub x)). A critical step in estimating LNO (sub x) production in a cloud-resolving model (CRM) without explicit lightning is to estimate the flash rate from available model parameters that are statistically and physically correlated. As such, the objective of this study is to develop, improve and evaluate lightning flash rate parameterizations in a variety of meteorological environments and storm types using radar and lightning mapping array (LMA) observations taken over Northern Alabama from 2005-2012, including during DC3. UAH's Advanced Radar for Meteorological and Operational Research (ARMOR) and the Weather Surveillance Radar - 1988 Doppler (WSR 88D) located at Hytop (KHTX) comprises the dual-Doppler and polarimetric radar network, which has been in operation since 2004. The northern Alabama LMA (NA LMA) in conjunction with Vaisala's National Lightning Detection Network (NLDN) allow for a detailed depiction of total lightning during this period. This study will integrate ARMOR-KHTX dual Doppler/polarimetric radar and NA LMA lightning observations from past and ongoing studies, including the more recent DC3 results, over northern Alabama to form a large data set of 15-20 case days and over 20 individual storms, including both ordinary multicell and supercell convection. Several flash rate parameterizations will be developed and tested, including those based on 1) graupel/small hail volume; 2) graupel/small hail mass, and 3) convective updraft volume. Sensitivity of the flash rate parameterizations to storm intensity, storm morphology and environmental conditions will be explored.

Carey, Lawrence D.↗
NASA NTRS2017

Hydrogen in Martian Meteorites

Most volatile studies of Mars have targeted its surface via spacecraft and rover data, and have evidenced surficial water in polar caps and the atmosphere, in the presence of river channels, and in the detection of water bearing minerals. The other focus of Martian volatile studies has been on Martian meteorites which are all from its crust. Most of these studies are on hydrous phases like apatite, a late-stage phase, i.e. crystallizing near the end of the differentiation sequence of Martian basalts and cumulates. Moreover, calculating the water content of the magma a phosphate crystallized from is not always possible, and yet is an essential step to estimate how much water was present in a parent magma and its source. Water, however, is primarily dissolved in the interiors of differentiated planets as hydrogen in lattice defects of nominally anhydrous minerals (olivine, pyroxene, feldspar) of the crust and mantle. This hydrogen has tremendous influence, even in trace quantities, on a planet's formation, geodynamics, cooling history and the origin of its volcanism and atmosphere as well as its potential for life. Studies of hydrogen in nominally anhydrous phases of Martian meteorites are rare. Measuring water contents and hydrogen isotopes in well-characterized nominally anhydrous minerals of Martian meteorites is the goal of our study. Our work aims at deciphering what influences the distribution and origin of hydrogen in Martian minerals, such as source, differentiation, degassing and shock.

Peslier, A. H.↗
NASA NTRS1971

An Empirical Method for Determining the Lunar Gravity Field

A method has been devised to determine the spherical harmonic coefficients of the lunar gravity field. This method consists of a two-step data reduction and estimation process. In the first step, a weighted least-squares empirical orbit determination scheme is applied to Doppler tracking data from lunar orbits to estimate long-period Kepler elements and rates. Each of the Kepler elements is represented by an independent function of time. The long-period perturbing effects of the earth, sun, and solar radiation are explicitly modeled in this scheme. Kepler element variations estimated by this empirical processor are ascribed to the non-central lunar gravitation features. Doppler data are reduced in this manner for as many orbits as are available. In the second step, the Kepler element rates are used as input to a second least-squares processor that estimates lunar gravity coefficients using the long-period Lagrange perturbation equations.

Ferrari, A. J.↗
NASA NTRS1973

Lunar gravity derived from long-period satellite motion - A proposed method.

A new method has been devised to determine the spherical harmonic coefficients of the lunar gravity field. This method consists of a two-step data reduction and estimation process. In the first step, a weighted least-squares empirical orbit determination scheme is applied to Doppler tracking data from lunar orbits to estimate long-period Kepler elements and rates. Each of the Kepler elements is represented by an independent function of time. The long-period perturbing effects of the earth, sun, and solar radiation are explicitly modeled in this scheme. Kepler element variations estimated by this empirical processor are then ascribed to the non-central lunar gravitation features. Doppler data are reduced in this manner for as many orbits as are available. In the second step, the Kepler element rates are used as input to a second least-squares processor that estimates lunar gravity coefficients using the long-period Lagrange perturbation equations.

Ferrari, A. J.↗
NASA NTRSDate not supplied

Advances in Estimation of the Earth Orientation Parameters From Observation

Historically, a two-step procedure for estimation of Universal Time and polar motion from observations was adopted: night averages from individual observatories formed a raw non-equidistant time series that was edited for outliers, smoothed, and formed the final data product. This approach was by inertia used for processing modern space geodesy observations. I will present an alternative one-step approach and its application for processing a dataset of VLBI observations since 1990.0 through present. The essence of this approach is to represent the Earth orientation parameters in a form of an expansion into basic functions and estimate of the expansion coefficients directly from observations. A further extension of this approach is to assimilate not only space geodesy data, but atmospheric and ocean angular momentum from assimilation numerical weather models and their forecasts. That makes a smooth bridge between Earth rotation estimation and prediction. I will talk about my experience of running data analysis in such a way on a semi-operational basis, present results, and discuss advantages and disadvantages of this approach.

Leonid Petrov↗
NASA NTRS1986

Polynomial elimination theory and non-linear stability analysis for the Euler equations

Numerical methods are presented that exploit the polynomial properties of discretizations of the Euler equations. It is noted that most finite difference or finite volume discretizations of the steady-state Euler equations produce a polynomial system of equations to be solved. These equations are solved using classical polynomial elimination theory, with some innovative modifications. This paper also presents some preliminary results of a new non-linear stability analysis technique. This technique is applicable to determining the stability of polynomial iterative schemes. Results are presented for applying the elimination technique to a one-dimensional test case. For this test case, the exact solution is computed in three iterations. The non-linear stability analysis is applied to determine the optimal time step for solving Burgers' equation using the MacCormack scheme. The estimated optimal time step is very close to the time step that arises from a linear stability analysis.

Kennon, S. R.↗
NASA NTRS2002

Linear-Quadratic-Gaussian Regulator Developed for a Magnetic Bearing

Linear-Quadratic-Gaussian (LQG) control is a modern state-space technique for designing optimal dynamic regulators. It enables us to trade off regulation performance and control effort, and to take into account process and measurement noise. The Structural Mechanics and Dynamics Branch at the NASA Glenn Research Center has developed an LQG control for a fault-tolerant magnetic bearing suspension rig to optimize system performance and to reduce the sensor and processing noise. The LQG regulator consists of an optimal state-feedback gain and a Kalman state estimator. The first design step is to seek a state-feedback law that minimizes the cost function of regulation performance, which is measured by a quadratic performance criterion with user-specified weighting matrices, and to define the tradeoff between regulation performance and control effort. The next design step is to derive a state estimator using a Kalman filter because the optimal state feedback cannot be implemented without full state measurement. Since the Kalman filter is an optimal estimator when dealing with Gaussian white noise, it minimizes the asymptotic covariance of the estimation error.

Choi, Benjamin B.↗
NASA NTRS1997

Application of the Two-Step Filter to Process Ranging Measurements for Relative Navigation in an Elliptical Orbit

This estimator breaks a nonlinear estimation problem into a set of over determined 'first step' states which are linear in the observations and 'second step' states which are ultimately the states of interest. Linear estimation methods are applied to filter the observations and produce the optimal first step state estimate. The 'second step' states are obtained through iterative nonlinear parameter estimation considering the first step states as observations. It has been shown that this process exactly minimizes the least squares cost function for static problems and provides a better solution than the iterated extended Kalman filter (EKF) for dynamic problems. The two step filter is applied in this paper to process range and range rate measurements between the two spacecraft. Details of the application of the two step estimator to this problem will be given, highlighting the use of a test for ill-conditioned covariance estimates that can result from the first order covariance propagation. A comparison will be made between the performance of the two step filter and the IEKF.

Garrison, James L.↗
NASA NTRS2024

A Phenomenological Durability Model for Environmental Barrier Coating Systems Subjected to Steam Oxidation

Environmental barrier coatings (EBC) are used to protect the silicon carbide fiber reinforced silicon carbide matrix (SiC/SiC) ceramic matrix composites (CMC) from rapid surface recession due to volatization by water vapor in a steam oxidation environment. A phenomenological modeling approach is outlined to estimate the durability of a given EBC system when exposed to steam oxidation. The report provides a step-by-step procedure to estimate the life of a given EBC system subjected to thermal loads only. Once calibrated, the methodology can predict the critical thickness of an oxide layer that will cause failure initiation/spallation as well as the remaining strength or stress that the EBC system can take for a given oxide layer thickness

Subodh K Mital↗
NASA NTRS1981

Estimating cell populations

An important step in the diagnosis of a cervical cytology specimen is estimating the proportions of the various cell types present. This is usually done with a cell classifier, the error rates of which can be expressed as a confusion matrix. We show how to use the confusion matrix to obtain an unbiased estimate of the desired proportions. We show that the mean square error of this estimate depends on a 'befuddlement matrix' derived from the confusion matrix, and how this, in turn, leads to a figure of merit for cell classifiers. Finally, we work out the two-class problem in detail and present examples to illustrate the theory.

White, B. S.↗