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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1957

Nonmetallic Material Compatibility with Liquid Fluorine

Static tests were made on the compatibility of liquid fluorine with several nonmetallic materials at -3200 F and at pressures of 0 and 1500 pounds per square inch gage. The results are compared with those from previous work with gaseous fluorine at the same pressures, but at atmospheric temperature. In general, although environmental effects were not always consistent, reactivity was least with the low-temperature, low-pressure liquid fluorine. Reactivity was greatest with the warm, high-pressure gaseous fluorine. None of the liquids and greases tested was found to be entirely suitable for use in fluorine systems. Polytrifluorochloroethylene and N-43, the formula for which is (C4F9)3N, did not react with liquid fluorine at atmospheric pressure or 1500 pounds per square inch gage under static conditions, but they did react when injected into liquid fluorine at 1500 pounds per square inch gage; they also reacted with gaseous fluorine at 1500 pounds per square inch gage. While water did not react with liquid fluorine at 1500 pounds per square inch gage, it is known to react violently with fluorine under other conditions. The pipe-thread lubricant Q-Seal did not react with liquid fluorine, but did react with gaseous fluorine at 1500 pounds per square inch gage. Of the solids, ruby (Al2O3) and Teflon did not react under the test conditions. The results show that the compatibility of fluorine with nonmetals depends on the state of the fluorine and the system design.

Price, Harold G , Jr↗
NASA NTRS2005

Data Assimilation and Data Fusion for Planetary Atmospheres

The overarching goal of this Cooperative Agreement was to develop a model and procedures for the data assimilation of planetary spacecraft atmospheric observations. Data assimilation - in its application to weather analysis and prediction - is the process of finding an initial state of the meteorological variables (winds, temperatures, pressures, etc.) of an atmosphere, which, when propagated forward in time using a deterministic general circulation model, reproduces all of the available observations over that time to within the measurement and computational errors. With this definition, data assimilation is seen to be a natural extension of well-known least-squares minimization techniques. The primary complication arises from the scale of the problem: For the Martian atmosphere with the available nadir-viewing Thermal Emission Spectrometer data from Mars Global Surveyor, approximately 1,000,000 individual measurements of channel radiances (in the 15-micrometer region, where these radiances relate directly to the surface and atmospheric temperature) were made per day. A suitable general circulation model for dealing with this data set has on the order of 20,000 independent variables. After some spatial and temporal averaging of the data - which provides a necessary statistical estimate of the representativeness of the measurements, a crucial issue in data assimilation - the problem reduces in scale to the solution of approximately 50,000 equations for the 20,000 variables.

Houben, Howard↗
NASA NTRS1979

Maximum likelihood estimation for life distributions with competing failure modes

The general model for the competing failure modes assuming that location parameters for each mode are expressible as linear functions of the stress variables and the failure modes act independently is presented. The general form of the likelihood function and the likelihood equations are derived for the extreme value distributions, and solving these equations using nonlinear least squares techniques provides an estimate of the asymptotic covariance matrix of the estimators. Monte-Carlo results indicate that, under appropriate conditions, the location parameters are nearly unbiased, the scale parameter is slightly biased, and the asymptotic covariances are rapidly approached.

Sidik, S. M.↗
NASA NTRS1984

Design of infrasound-detection system via adaptive LMSTDE algorithm

A proposed solution to an aviation safety problem is based on passive detection of turbulent weather phenomena through their infrasonic emission. This thesis describes a system design that is adequate for detection and bearing evaluation of infrasounds. An array of four sensors, with the appropriate hardware, is used for the detection part. Bearing evaluation is based on estimates of time delays between sensor outputs. The generalized cross correlation (GCC), as the conventional time-delay estimation (TDE) method, is first reviewed. An adaptive TDE approach, using the least mean square (LMS) algorithm, is then discussed. A comparison between the two techniques is made and the advantages of the adaptive approach are listed. The behavior of the GCC, as a Roth processor, is examined for the anticipated signals. It is shown that the Roth processor has the desired effect of sharpening the peak of the correlation function. It is also shown that the LMSTDE technique is an equivalent implementation of the Roth processor in the time domain. A LMSTDE lead-lag model, with a variable stability coefficient and a convergence criterion, is designed.

Khalaf, C. S.↗
NASA NTRS2011

Actuator Grouping Optimization on Flexible Space Reflectors

With the rapid advances in deployable membrane and mesh antenna technologies, the feasibility of developing large, lightweight reflectors has greatly improved. In order to achieve the required surface accuracy, precision surface control is needed on these lightweight reflectors. For this study, an analytical model is shown which combines a flexible Kapton reflector with Polyvinylidene fluoride (PVDF) actuators for surface control. Surface errors are introduced that are similar to real world scenarios, and a least squares control algorithm is developed for surface control. Experimental results on a 2.4 meter reflector show that while the analytical reflector model is generally correct, due to idiosyncrasies in the reflector it cannot be used for online control. A new method called the En Mass Elimination algorithm is used to determine the optimal grouping of actuators when the number of actuators in the system exceeds the number of power supplies available.

en masse elimination (EME) algorithm↗
NASA NTRS1989

The relationship between IR, optical, and UV extinction

An analysis is presented for the variability of absolute IR, optical, and UV extinction, A(sub lambda), derived through the ratio of total-to-selective extinction, R, for 31 lines of sight for which reliable UV extinction parameters were derived. These data sample a wide range of environments and are characterized by 2.5 is less than or equal to R is less than or equal to 6.0. It was found that there is a strong linear dependence between extinction expressed as A(sub lambda)/A(sub V) and 1/R for 1.25 micron is less than or equal to lambda is less than or equal to 0.12 micron. Differences in the general shape of extinction curves are largely due to variations in shape of optical/near-UV extinction corresponding to changes in R, with A(sub lambda)/A(sub V) decreasing for increasing R. From a least-squares fit of the observed R-dependence as a function of wavelength for 0.8/micron is less than or greater than 1/lambda is less than or equal to 8.3/micron, an analytic expression was generated from which IR, optical, and UV extinction curves of the form A(sub lambda)/A(sub V) can be reproduced with reasonable accuracy from a knowledge of R. It was also found that the absolute bump strength normalized to A(sub V) shows a general decrease with increasing R, suggesting that some fraction of bump grains may be selectively incorporated into coagulated grains. Finally, it was found that absolute extinction normalized by suitably chosen color indices results in a minimization of the R-dependence of portions of the UV curve, allowing A(sub lambda) to be estimated for these wavelengths independent of R.

Cardelli, Jason A.↗
DOE OSTI2022

A micromorphic filter for determining stress and deformation measures from direct numerical simulations of lower length scale behavior

A micromorphic filter is presented for the extraction of stress and deformation measures from underlying direct numerical simulation (DNS) of microstructural mechanical response. The filter is consistent with the micromorphic continuum theory of Eringen and Suhubi (1964), and allows the interrogation of a DNS to generate higher order constitutive models. The filter adopts aspects of the overlap coupling techniques for atomistic-continuum scale-bridging in order to update the nodal degrees of freedom of the finite-element-based filter. Here, two methods for the extraction of quantities of interest from the underlying DNS are presented. The first is a least squares fitting technique which is appropriate for finite-element-style macro-scale domains, and the second is a variationally based approach which generalizes the method to any macro-scale domain which has a variational form. No restrictions on the form of the micro-scale simulation are inherent to the approach, provided that the required quantities (stress, position, etc.) can be provided. The filter is applied to a simple homogeneous medium undergoing homogeneous deformation to demonstrate the recovery of a classical continuum response, what we call the null case. We then apply the framework to the same homogeneous medium with a central and edge penny-shaped crack to show micromorphic effects. We demonstrate that varying the size of the filter causes the micromorphic behaviors to arise and then dissipate as the filter becomes smaller than the crack's length scale. Additionally we show the effect of filter size on a chiral element network along with a plate perforated with evenly spaced and perturbed holes through the thickness. The micromorphic effects are shown to be present for the chiral elements under any loading but become most pronounced when a single element is located within each averaging domain. Micromorphic effects become pronounced for the plate upon the onset of localization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Tunnel-FET Switching Is Governed by Non-Lorentzian Spectral Line Shape

In tunnel field-effect transistors (tFETs), the preferred mechanism for switching occurs by alignment (on) or misalignment (off) of two energy levels or band edges. Unfortunately, energy levels are never perfectly sharp. When a quantum dot interacts with a wire, its energy is broadened. Its actual spectral shape controls the current/voltage response of such transistor switches, from on (aligned) to off (misaligned). The most common model of spectral line shape is the Lorentzian, which falls off as reciprocal energy offset squared. Unfortunately, this is too slow a turnoff, algebraically, to be useful as a transistor switch. Electronic switches generally demand an on/off ratio of at least a million. Steep exponentially falling spectral tails would be needed for rapid off-state switching. This requires a new electronic feature, not previously recognized: narrowband, heavy-effective mass, quantum wire electrical contacts, to the tunneling quantum states. These are a necessity for spectrally sharp switching.

42 ENGINEERING↗
DOE OSTI2021

The updated ITPA global H-mode confinement database: description and analysis

The multi-machine ITPA Global H-mode Confinement Database has been upgraded with new data from JET with the ITER-like wall and ASDEX Upgrade with the full tungsten wall. This paper describes the new database and presents results of regression analysis to estimate the global energy confinement scaling in H-mode plasmas using a standard power law. Various subsets of the database are considered, focusing on type of wall and divertor materials, confinement regime (all H-modes, ELMy H or ELM-free) and ITER-like constraints. Apart from ordinary least squares, two other, robust regression techniques are applied, which take into account uncertainty on all variables. Regression on data from individual devices shows that, generally, the confinement dependence on density and the power degradation are weakest in the fully metallic devices. Using the multi-machine scalings, predictions are made of the confinement time in a standard ELMy H-mode scenario in ITER. The uncertainty on the scaling parameters is discussed with a view to practically useful error bars on the parameters and predictions. One of the derived scalings for ELMy H-modes on an ITER-like subset is studied in particular and compared to the IPB98(y,2) confinement scaling in engineering and dimensionless form. Transformation of this new scaling from engineering variables to dimensionless quantities is shown to result in large error bars on the dimensionless scaling. Regression analysis in the space of dimensionless variables is therefore proposed as an alternative, yielding acceptable estimates for the dimensionless scaling. The new scaling, which is dimensionally correct within the uncertainties, suggests that some dependencies of confinement in the multi- machine database can be reconciled with parameter scans in individual devices. This includes vanishingly small dependence of confinement on line-averaged density and normalized plasma pressure (β), as well as a noticeable, positive dependence on effective atomic mass and plasma triangularity. Extrapolation of this scaling to ITER yields a somewhat lower confinement time compared to the IPB98(y, 2) prediction, possibly related to the considerably weaker dependence on major radius in the new scaling (slightly above linear). Further studies are needed to compare more flexible regression models with the power law used here. In addition, data from more devices concerning possible ‘hidden variables’ could help to determine their influence on confinement, while adding data in sparsely populated areas of the parameter space may contribute to further disentangling some of the global confinement dependencies in tokamak plasmas.

Database↗
NASA NTRS2018

Real-Time Parameter Estimation for Flexible Aircraft

A method for estimating aeroelastic stability and control derivatives for flexible aircraft is developed and demonstrated using flight test data for the X-56A subscale demonstrator. The method uses the equation-error approach with frequency-domain data, and can be applied post-flight or in real time during flight. The non-dimensional aeroelastic forces and moments and the explanatory variables (including generalized displacement, rate, and acceleration states for the vibration modes) are estimated using a finite element model and onboard sensor measurements in both a least squares and Kalman filtering framework. The data are then transformed into the frequency domain for parameter estimation using equation error. This method can result in a more efficient analysis than with other iterative methods, and can leverage existing statistical tools for model structure determination, data collinearity detection, combining multiple maneuvers or prior information, and others to improve model quality.

Grauer, Jared A.↗
NASA NTRS1978

Heliocentric distance dependence of the interplanetary magnetic field

Numerous spacecraft measurements bearing on the heliocentric distance dependencies of both large- and small-scale properties of the interplanetary magnetic field (IMF) are assembled and compared. These data tend to indicate that the average of the radial field component varies as the inverse square of distance. However, the azimuthal component is rather strongly a function of time, being influenced by both the time-dependent solar wind speed and the evolution of the source field at the sun. Thus, unless the solar wind speed dependence is taken into account, individual sets of measurements by a single spacecraft give an azimuthal component gradient which is steeper than the inverse distance dependence predicted from the Parker spiral model. A least squares fit to the composite (five spacecraft) solar rotation average data set gives a result close to the inverse distance dependence. Preliminary Helios results suggest general consistency with the spiral model.

Behannon, K. W.↗
NASA NTRS2015

Adaptive State Predictor Based Human Operator Modeling on Longitudinal and Lateral Control

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to categorize these interactions of the pilot with an adaptive controller compensating during control surface failures. A general linear in-parameter model structure is used to represent a pilot. Three different estimation methods are explored. A gradient descent estimator (GDE), a least squares estimator with exponential forgetting (LSEEF), and a least squares estimator with bounded gain forgetting (LSEBGF) used the experiment data to predict pilot stick input. Previous results have found that the GDE and LSEEF methods are fairly accurate in predicting longitudinal stick input from commanded pitch. This paper discusses the accuracy of each of the three methods - GDE, LSEEF, and LSEBGF - to predict both pilot longitudinal and lateral stick input from the flight director's commanded pitch and bank attitudes.

Trujillo, Anna C.↗
NASA NTRS2024

Toward 2D Dynamo Models Calibrated by Global 3D Relativistic Accretion Disk Simulations

Two-dimensional models assuming axisymmetry are an economical way to explore the long-term evolution of black hole accretion disks, but they are only realistic if the feedback of the nonaxisymmetric turbulence on the mean momentum and magnetic fields is incorporated. Dynamo terms added to the 2D induction equation should be calibrated to 3D MHD simulations. For generality, the dynamo tensors should be calibrated as functions of local variables rather than explicit functions of spatial coordinates in a particular basis. In this paper, we study the feedback of non-axisymmetric features on the 2D mean fields using a global 3D, relativistic, Cartesian simulation from the Illinois GRMHD code. We introduce new methods for estimating overall dynamo alpha and turbulent diffusivity effects as well as measures of the dominance of non-axisymmetric components of energies and fluxes within the disk interior. We attempt closure models of the dynamo EMF using least squares fitting, considering both models where coefficient tensors are functions of space and more global, covariant models. None of these models are judged satisfactory, but we are able to draw conclusions on what sorts of generalizations are and are not promising.

Matthew D Duez↗
NASA NTRS1988

A general model for attitude determination error analysis

An overview is given of a comprehensive approach to filter and dynamics modeling for attitude determination error analysis. The models presented include both batch least-squares and sequential attitude estimation processes for both spin-stabilized and three-axis stabilized spacecraft. The discussion includes a brief description of a dynamics model of strapdown gyros, but it does not cover other sensor models. Model parameters can be chosen to be solve-for parameters, which are assumed to be estimated as part of the determination process, or consider parameters, which are assumed to have errors but not to be estimated. The only restriction on this choice is that the time evolution of the consider parameters must not depend on any of the solve-for parameters. The result of an error analysis is an indication of the contributions of the various error sources to the uncertainties in the determination of the spacecraft solve-for parameters. The model presented gives the uncertainty due to errors in the a priori estimates of the solve-for parameters, the uncertainty due to measurement noise, the uncertainty due to dynamic noise (also known as process noise or measurement noise), the uncertainty due to the consider parameters, and the overall uncertainty due to all these sources of error.

Markley, F. Landis↗
NASA NTRS1988

Multiple point least squares equalization in a room

Equalization filters designed to minimize the mean square error between a delayed version of the original electrical signal and the equalized response at a point in a room have previously been investigated. In general, such a strategy degrades the response at positions in a room away from the equalization point. A method is presented for designing an equalization filter by adjusting the filter coefficients to minimize the sum of the squares of the errors between the equalized responses at multiple points in the room and delayed versions of the original, electrical signal. Such an equalization filter can give a more uniform frequency response over a greater volume of the enclosure than can the single point equalizer above. Computer simulation results are presented of equalizing the frequency responses from a loudspeaker to various typical ear positions, in a room with dimensions and acoustic damping typical of a car interior, using the two approaches outlined above. Adaptive filter algorithms, which can automatically adjust the coefficients of a digital equalization filter to achieve this minimization, will also be discussed.

Elliott, S. J.↗
DOE OSTI2025

A machine learning framework for accurate and robust analysis of radiation detector pulses

The microscopic properties of atomic nuclei are used to study various scientific questions. They are essential for understanding the fundamental forces of nature and the chemical evolution of the universe. Detecting decay radiation from radioactive nuclei makes it possible to probe these fundamental nuclear properties. Detector waveform traces may contain additional information about the radiation. Generally, advanced signal processing techniques are needed to extract this additional information, often involving fitting the waveform with model response functions using non-linear least-squares optimization with second-order gradient methods. While this is a powerful technique, it is also computationally expensive, leading to slow processing time, which scales with the volume of data. To address this problem, we have developed a machine learning (ML) approach that infers the characteristics of traces from a model detector response function. In particular, we are interested in classifying whether a single recorded trace consists of one or two pulse constituents and estimating the pulse parameters. Furthermore, our proposed ML method can precisely extract the pulses’ parameters, such as energy and timing information, and accurately classify the pulse multiplicity of a trace. Unlike non-learning-based approaches, our ML approach uses neural networks that are significantly faster at inference, as they do not require any optimization during this stage.

Curve fitting↗
NASA NTRS1967

Automatic design of optical systems by digital computer

Computer program uses geometrical optical techniques and a least squares optimization method employing computing equipment for the automatic design of optical systems. It evaluates changes in various optical parameters, provides comprehensive ray-tracing, and generally determines the acceptability of the optical system characteristics.

Casad, T. A.↗
NASA NTRS1986

PROFILE user's guide

User information for program PROFILE, an aerodynamics design utility for refining, plotting, and tabulating airfoil profiles is provided. The theory and implementation details for two of the more complex options are also presented. These are the REFINE option, for smoothing curvature in selected regions while retaining or seeking some specified thickness ratio, and the OPTIMIZE option, which seeks a specified curvature distribution. REFINE uses linear techniques to manipulate ordinates via the central difference approximation to second derivatives, while OPTIMIZE works directly with curvature using nonlinear least squares techniques. Use of programs QPLOT and BPLOT is also described, since all of the plots provided by PROFILE (airfoil coordinates, curvature distributions) are achieved via the general purpose QPLOT utility. BPLOT illustrates (again, via QPLOT) the shape functions used by two of PROFILE's options. The programs were designed and implemented for the Applied Aerodynamics Branch at NASA Ames Research Center, Moffett Field, California, and written in FORTRAN and run on a VAX-11/780 under VMS.

Collins, L.↗