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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Superconductivity devices: Commercial use of space

The high T(sub c) superconducting ceramic materials, developed in 1987, are now being extensively investigated for a variety of engineering applications. These applications include such devices as conducting links, rotating and linear bearings, sensors, filters, switches, high Q cavities, magnets, and motors. Some of these devices take advantage of the material's ability to lose all electrical resistance at a critical temperature, T(sub c), while others make use of the repulsion forces generated between the magnetic field of a permanent magnet and a superconductor which is cooled below its T(sub c), Meissner effect. This report describes the work accomplished to date by: (1) reviewing the present state of the art in actuator technology, (2) evaluating processing and fabrication of high strain electrostrictive materials, and (3) testing these electrostrictive materials.

Haertling, Gene↗
NASA NTRS1992

Information processing in the primate visual system - An integrated systems perspective

The primate visual system contains dozens of distinct areas in the cerebral cortex and several major subcortical structures. These subdivisions are extensively interconnected in a distributed hierarchical network that contains several intertwined processing streams. A number of strategies are used for efficient information processing within this hierarchy. These include linear and nonlinear filtering, passage through information bottlenecks, and coordinated use of multiple types of information. In addition, dynamic regulation of information flow within and between visual areas may provide the computational flexibility needed for the visual system to perform a broad spectrum of tasks accurately and at high resolution.

Van Essen, David C.↗
NASA NTRS1991

Estimation of optimal Kalman filter gain from non-optimal filter residuals

This paper presents a novel method of estimating the optimal steady state Kalman filter gain of a linear discrete time-invariant system from a non-optimal Kalman filter residual sequence. The relation between the optimal residual sequence and a signal derived from the non-optimal residual sequence is described by a Moving Average (MA) model whose coefficients are expressed in terms of the state space parameters and the optimal steady state Kalman filter gain. In order to identify the MA model, a whitening filter of the derived signal, which corresponds to an AutoRegressive (AR) model of the signal, is first identified using the least-squares method. Then the inverse filter of the whitening filter, which corresponds to the MA model, is calculated. From the coefficients of the identified MA model, the optimal steady state Kalman filter gain can be obtained. Numerical example is provided to illustrate the feasibility of this approach.

Chen, Chung-Wen↗
NASA NTRS1993

Multiple degree of freedom force-state component identification

Force-state mapping is extended to allow the quasistatic characterization of realistic multiple degree of freedom systems whose constitutive relations are nonlinear, dissipative, coupled and depend on memory of past states. A general constitutive force-state model is formulated, which includes dynamic hysteresis phenomena typical of that found in deployable structures. A two step parameter identification approach is developed, which employs a linear extended Kalman filter and a nonlinear least squares fit. A six degree of freedom force-state testing device was constructed, and used to obtain data on one bay of a simple truss and on one bay of the MODE deployable truss.

Masters, Brett P.↗
NASA NTRS2013

Multi-Pass Quadrupole Mass Analyzer

Analysis of the composition of planetary atmospheres is one of the most important and fundamental measurements in planetary robotic exploration. Quadrupole mass analyzers (QMAs) are the primary tool used to execute these investigations, but reductions in size of these instruments has sacrificed mass resolving power so that the best present-day QMA devices are still large, expensive, and do not deliver performance of laboratory instruments. An ultra-high-resolution QMA was developed to resolve N2 +/CO+ by trapping ions in a linear trap quadrupole filter. Because N2 and CO are resolved, gas chromatography columns used to separate species before analysis are eliminated, greatly simplifying gas analysis instrumentation. For highest performance, the ion trap mode is used. High-resolution (or narrow-band) mass selection is carried out in the central region, but near the DC electrodes at each end, RF/DC field settings are adjusted to allow broadband ion passage. This is to prevent ion loss during ion reflection at each end. Ions are created inside the trap so that low-energy particles are selected by low-voltage settings on the end electrodes. This is beneficial to good mass resolution since low-energy particles traverse many cycles of the RF filtering fields. Through Monte Carlo simulations, it is shown that ions are reflected at each end many tens of times, each time being sent back through the central section of the quadrupole where ultrahigh mass filtering is carried out. An analyzer was produced with electrical length orders of magnitude longer than its physical length. Since the selector fields are sized as in conventional devices, the loss of sensitivity inherent in miniaturizing quadrupole instruments is avoided. The no-loss, multi-pass QMA architecture will improve mass resolution of planetary QMA instruments while reducing demands on the RF electronics for high-voltage/high-frequency production since ion transit time is no longer limited to a single pass. The QMA-based instrument will thus give way to substantial reductions of the mass of flight instruments.

Prestage, John D.↗
NASA NTRS2019

GOES-17 Magnetometer On-Orbit Calibration Design and Results

The Geostationary Operational Environmental Satellite-R (GOES-R) is a series of four NOAA weather satellites. Each spacecraft flies a Magnetometer instrument which includes two boom mounted fluxgate sensors located 6.3 and 8.5 meters from the spacecraft. Sensor readings are corrupted by both internal (bias and scale factor) and external (spacecraft emitted fields and misalignments) error sources. In order to estimate the bias, an on-orbit calibration is performed, slewing the spacecraft about multiple axes and then performing a fit of the data to determine zero offset and misalignment terms. The first satellite in the series, GOES-16 was launched in November 2016. Its magnetometer calibration maneuver was found to be inadequate providing insufficient rotation about orthogonal axes. The uncertainty in the estimated biases was found to be in the 3-5 nanotesla range, exceeding the magnetometer accuracy requirement of 1.0 nanotesla. Based on lessons learned, the maneuver was redesigned to provide multiple 360 degree rotations about two orthogonal axes, providing optimal visibility into bias and misalignment. Varying ambient fields over the duration of the calibration maneuvers, corrupts the ability to accurately determine parameters of interest. To address this issue, rather than assuming a constant field for the duration of the maneuver, a non-linear least squares filter was employed that uses a series of spline functions to better fit the ambient field. The number of splines can be varied to minimize the least squares filter residuals. Simulations were performed using 360 days of GOES-16 data to bound the uncertainty in the biases for given residuals of the fit to the ambient field. Following the launch of the second satellite in the series, GOES-17 in March 2018, the new calibration maneuver and enhanced bias estimation algorithm were exercised twice. Based on the residuals of the fit, the uncertainty of the estimated zero offset was reduced by an order of magnitude from 3-5 nanotesla to approximately 0.4 nanotesla per axis. This paper provides details of the maneuver design and the innovative algorithm used to estimate the GOES-17 biases and misalignments.

GOES-17↗
NASA NTRS2021

L’Ralph Integration and Testing

This paper describes the plans, flows, key facilities, components and equipment necessary to fully integrate, functionally test, qualify and calibrate the L’Ralph instrument on the Lucy observatory. Lucy is currently in the final design and fabrication phase (phase C) of mission development. It is scheduled to launch out of Cape Canaveral, Florida, in October 2021. Lucy will be the first space mission to study the Trojan asteroids associated with Jupiter, that are thought to be remnants of the primordial material that formed the outer planets. Lucy will fly by and carry out remote sensing on six different Trojan asteroids. The mission takes its name from the fossilized human ancestor (called “Lucy” by her discoverers) whose skeleton provided unique insight into humanity's evolution. Likewise, the Lucy mission will revolutionize our knowledge of planetary origins and the formation of the solar system. L’Ralph is one of the instruments on Lucy and it is provided by the NASA Goddard Space Flight Center (GSFC). L’Ralph is a combined multi-band visible imager (the Multi-spectral Visible Imaging Camera, MVIC, 0.4-0.85 microns) and wedge-filter infrared spectrometer (Linear Etalon Imaging Spectral Array, LEISA, 1-3.6 microns). LEISA will allow the team to look for the absorption lines that serve as the fingerprints for different silicates, ices and organics that likely will be on the surface of the Trojan asteroids. MVIC will take color images of the Trojan asteroid targets, and help determine how active they are. This paper will focus on the Integration and Test (I&T) activities for L’Ralph while it is at the NASA GSFC. L’Ralph has two assemblies, the telescope detector assembly (TDA) and main electronics box (MEB). The TDA is a single telescope feeding two focal planes, MVIC and LEISA. L’Ralph integration consists of assembly and alignment of the telescope, electronics box integration, thermal systems integration and the final assembly and testing. This I&T phase will be followed by the L’Ralph calibration and characterization, environmental tests which include electromagnetic interference (EMI)/electromagnetic compatibility (EMC), vibration with sine sweep, acoustics, shock, thermal balance, thermal vacuum, mass properties and center of gravity determination. This paper will briefly discuss L’Ralph shipment and delivery to the spacecraft vendor for observatory level I&T as well as some launch preparation activities.

Spaceflight Instruments↗
NASA NTRS2021

Detection and Tracking of Aircraft in the Far-Field from Small Unmanned Aerial Systems

Onboard far-field aircraft detection is needed for safe non-cooperative traffic mitigation in autonomous small Unmanned Aerial System (sUAS) operations. Machine vision systems, based on standard optics and visible light detectors, possess the ideal size, weight, and power (SWaP) requirements for sUAS. This work presents the design and analysis of a novel aircraft detection and tracking pipeline based on optical sensing alone. Key contributions of the work include a refined range inequality model based on sensing and detection with FAA well-clear separation assurance distances between aircraft in mind, a detector fusion method to maximize the benefit of two image detectors, and a comparative analysis of Linear Kalman-filtering and Extended Kalman-filtering to seek optimal tracking performance. The pipeline is evaluated offline against multiple intruder platforms, using two types of flight encounters: multirotor sUAS vs. fixed-wing sUAS and multirotor sUAS vs. general aviation(GA)plane. Analysis is restricted to the rate-limiting head-on and departing collision volume cases vertically separated for safety. Results indicate that it is feasible to use the proposed optical spatial-temporal tracking algorithm to provide adequate alerting time to prevent penetration of well-clear separation volumes for both sUAS and GA aircraft.

Unmanned Aerial System↗
NASA NTRS2005

Adaptive Filtering Using Recurrent Neural Networks

A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.

Parlos, Alexander G.↗
NASA NTRS1990

The wavelength dependence of broadband linear polarization in cool stars

A model is developed to investigate the effect of wavelength dependence of magnetically generated broadband linear polarization (BLP) in late-type stars as a function of line blanketing, observation filters, and other variables. Linear polarization is assumed to be a single 'average' line and the line opacity, magnetic area filling factor, and continuum intensity are incorporated to establish an equation for disk-generated BLP. The method is investigated by computing special models for the flare star BY Dra and the sun which are compared to previous calculations. The model is shown to agree with the calculations of BLP, and the magnetic BLP dependent on wavelengths varies significantly from the simple power law dependences on wavelength. The model sets lower limits to the area occupied by magnetic regions, and an upper limit to the expected BLP also results from the formulation.

Saar, Steven H.↗
NASA NTRS1977

Stochastic optimal attitude control of spacecraft with movable appendages

This paper deals with the application of linear optimal control and filtering theory to control a spinning spacecraft with movable telescoping appendages. The equations of motion are linearized about the desired final state. A feedback control system is designed to maintain this final state, with plant noise and measurement noise present in the system. Analytic results are obtained for special cases and numerical results are presented for the general case.

Sellappan, R.↗
NASA NTRS1996

Satellite Angular Rate Estimation From Vector Measurements

This paper presents an algorithm for estimating the angular rate vector of a satellite which is based on the time derivatives of vector measurements expressed in a reference and body coordinate. The computed derivatives are fed into a spacial Kalman filter which yields an estimate of the spacecraft angular velocity. The filter, named Extended Interlaced Kalman Filter (EIKF), is an extension of the Kalman filter which, although being linear, estimates the state of a nonlinear dynamic system. It consists of two or three parallel Kalman filters whose individual estimates are fed to one another and are considered as known inputs by the other parallel filter(s). The nonlinear dynamics stem from the nonlinear differential equation that describes the rotation of a three dimensional body. Initial results, using simulated data, and real Rossi X ray Timing Explorer (RXTE) data indicate that the algorithm is efficient and robust.

Azor, Ruth↗
NASA NTRS1991

Frequency weighted system identification and linear quadratic controller design

Application of filters for frequency weighting of Markov parameters (pulse response functions) is described in relation to system/observer identification. The time domain identification approach recovers a model which has a pulse response weighted according to frequency. The identified model is composed of the original system and filters. The augmented system is in a form which can be used directly for frequency weighted linear quadratic controller design. Data from either single or multiple experiments can be used to recover the Markov parameters. Measured acceleration signals from a truss structure are used for system identification and the model obtained is used for frequency weighted controller design. The procedure makes the identification and controler design complementary problems.

Horta, Lucas G.↗
NASA NTRS1982

Optimal Regulator Algorithms for the Control of Linear Systems

Control-theory design package, called Optimal Regulator Algorithms for Control of Linear Systems (ORACLS), aids in design of controllers and optimal filters for systems modeled by linear, time invariant differential and difference equations. ORACLS is particularly attractive rigorous tool for dealing with multi-input and multi-output dynamic systems in both continuous and discrete forms.

Armstrong, E. S.↗
NASA NTRS1975

Linear polarization variations modulo 5.6 days in HDE 226868

Results are reported for observations of variations in the linear polarization in HDE 226868 (the optical counterpart of Cyg X-1) made with a photoelastic polarimeter and a U-filter. The UV linear-polarization variations, as folded on the 5.6-day orbital period, are found to have amplitudes of 0.25% and position-angle changes of 2.7 deg. These results are shown to be consistent with the geometry and phasing required by the model of the binary system.

Nolt, I. G.↗
NASA NTRS1978

ORACLS: A system for linear-quadratic-Gaussian control law design

A modern control theory design package (ORACLS) for constructing controllers and optimal filters for systems modeled by linear time-invariant differential or difference equations is described. Numerical linear-algebra procedures are used to implement the linear-quadratic-Gaussian (LQG) methodology of modern control theory. Algorithms are included for computing eigensystems of real matrices, the relative stability of a matrix, factored forms for nonnegative definite matrices, the solutions and least squares approximations to the solutions of certain linear matrix algebraic equations, the controllability properties of a linear time-invariant system, and the steady state covariance matrix of an open-loop stable system forced by white noise. Subroutines are provided for solving both the continuous and discrete optimal linear regulator problems with noise free measurements and the sampled-data optimal linear regulator problem. For measurement noise, duality theory and the optimal regulator algorithms are used to solve the continuous and discrete Kalman-Bucy filter problems. Subroutines are also included which give control laws causing the output of a system to track the output of a prescribed model.

Armstrong, E. S.↗