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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

The inclusion of rotor dynamics in controller design for helicopters.

State-feedback-controllers and state-estimators (filters) are designed for the roll-pitch-horizontal motions of a helicopter near hover, using a new quadratic synthesis technique. One model (tenth order) uses a dynamic model of the rotor, whereas the other model (sixth order) assumes the rotor can be tilted instantaneously. It is shown that, for tight control, neglecting the rotor dynamics in designing the autopilot can produce unstable closed-loop response on the model that includes rotor dynamics. Two filters are designed to use only fuselage sensors and two are designed to use both fuselage and rotor sensors. It is shown that rotor states can be estimated with sufficient accuracy using only fuselage sensors so that it does not seem worthwhile to use rotor sensors. The mean square response of the vehicle to a gusty, random wind, using several different filter/state-feedback compensators, is shown to be satisfactory.

Hall, W. E., Jr.↗
NASA NTRS1986

Intercomparison of UT1 measurements during the MERIT campaign period

Universal time (UT1) measurements obtained using VLBI, lunar laser ranging (LLR), and BIH optical astronomy are compared. The JPL Kalman filter for the earth rotation and the polar motion is utilized to smooth one data set or combine data sets for intercomparison. The differences between raw UT1 data and independently smoothed data are employed to assess the accuracy of the measured series and the sufficiency of the error budget. Systematic errors in periodic signatures and length of day estimates are analyzed. The data reveal that the techniques of LLR and VLBI agree to within their formal errors. It is determined that the residual error for the LLR is too large and the residual error estimated for the BIH data is too small.

Spieth, M. A.↗
NASA NTRS2004

System design, modelling, and tracking filter for bearings only analog camera

In this paper, each subsystem of the Celestial Sensor is discussed with emphasis given to the filtering algorithms. The celestial sensor software processes sequential frame based bearing measurements on a peripheral CPY specifically designed for this application. A frame preprocessor is used to normalize each bearing measurement and apply a number of accept/reject rules. The accepted set of measurements is then passed to an Extended Kalman Filter (EKP) that is tuned to track the motion of the robot within the room.

Ahmed, Asif↗
NASA NTRS2002

Design parameters for rotating cylindrical filtration

Rotating cylindrical filtration displays significantly reduced plugging of filter pores and build-up of a cake layer, but the number and range of parameters that can be adjusted complicates the design of these devices. Twelve individual parameters were investigated experimentally by measuring the build-up of particles on the rotating cylindrical filter after a fixed time of operation. The build-up of particles on the filter depends on the rotational speed, the radial filtrate flow, the particle size and the gap width. Other parameters, such as suspension concentration and total flow rate are less important. Of the four mechanisms present in rotating filters to reduce pore plugging and cake build-up, axial shear, rotational shear, centrifugal sedimentation and vortical motion, the evidence suggests rotational shear is the dominant mechanism, although the other mechanisms still play minor roles. The ratio of the shear force acting parallel to the filter surface on a particle to the Stokes drag acting normal to the filter surface on the particle due to the difference between particle motion and filtrate flow can be used as a non-dimensional parameter that predicts the degree of particle build-up on the filter surface for a wide variety of filtration conditions. c2002 Elsevier Science B.V. All rights reserved.

Non-NASA Center↗
NASA NTRS2009

Motion Cueing Algorithm Modification for Improved Turbulence Simulation

Atmospheric turbulence cueing produced by flight simulator motion systems has been less than satisfactory because the turbulence profiles have been attenuated by the motion cueing algorithms. Cardullo and Ellor initially addressed this problem by directly porting the turbulence model output to the motion system. Reid and Robinson addressed the problem by employing a parallel aircraft model, which is only stimulated by the turbulence inputs and adding a filter specially designed to pass the higher turbulence frequencies. There have been advances in motion cueing algorithm development at the Man-Machine Systems Laboratory, at SUNY Binghamton. In particular, the system used to generate turbulence cues has been studied. The Reid approach, implemented by Telban and Cardullo, was employed to augment the optimal motion cueing algorithm installed at the NASA LaRC Simulation Laboratory, driving the Visual Motion Simulator. In this implementation, the output of the primary flight channel was added to the output of the turbulence channel and then sent through a non-linear cueing filter. The cueing filter is an adaptive filter; therefore, it is not desirable for the output of the turbulence channel to be augmented by this type of filter. The likelihood of the signal becoming divergent was also an issue in this design. After testing on-site it became apparent that the architecture of the turbulence algorithm was generating unacceptable cues. As mentioned above, this cueing algorithm comprised a filter that was designed to operate at low bandwidth. Therefore, the turbulence was also filtered, augmenting the cues generated by the model. If any filtering is to be done to the turbulence, it will utilize a filter with a much higher bandwidth, above the frequencies produced by the aircraft response to turbulence. The authors have developed an implementation wherein only the signal from the primary flight channel passes through the nonlinear cueing filter. This paper discusses three new algorithms. Testing shows that the new methods provide the pilot with a more realistic sensation of turbulence; the cues are not attenuated by algorithm. Results of offline testing show the credibility of the models. Offline test verification was based primarily on the evaluation of the power spectral density of the outputs and the time response.

Ercole, Anthony V.↗
NASA NTRS2011

Imaging the Moon's Core with Seismology

Constraining the structure of the lunar core is necessary to improve our understanding of the present-day thermal structure of the interior and the history of a lunar dynamo, as well as the origin and thermal and compositional evolution of the Moon. We analyze Apollo deep moonquake seismograms using terrestrial array processing methods to search for the presence of reflected and converted energy from the lunar core. Although moonquake fault parameters are not constrained, we first explore a suite of theoretical focal spheres to verify that fault planes exist that can produce favorable core reflection amplitudes relative to direct up-going energy at the Apollo stations. Beginning with stacks of event seismograms from the known distribution of deep moonquake clusters, we apply a polarization filter to account for the effects of seismic scattering that (a) partitions energy away from expected components of ground motion, and (b) obscures all but the main P- and S-wave arrivals. The filtered traces are then shifted to the predicted arrival time of a core phase (e.g. PcP) and stacked to enhance subtle arrivals associated with the Moon s core. This combination of filtering and array processing is well suited for detecting deep lunar seismic reflections, since we do not expect scattered wave energy from near surface (or deeper) structure recorded at varying epicentral distances and stations from varying moonquakes at varying depths to stack coherently. Our results indicate the presence of a solid inner and fluid outer core, overlain by a partial-melt-containing boundary layer (Table 1). These layers are consistently observed among stacks from four classes of reflections: P-to-P, S-to-P, P-to-S, and S-to-S, and are consistent with current indirect geophysical estimates of core and deep mantle properties, including mass, moment of inertia, lunar laser ranging, and electromagnetic induction. Future refinements are expected following the successful launch of the GRAIL lunar orbiter and SELENE 2 lunar lander missions.

Weber, Renee C.↗
NASA NTRS1980

The influence of orbit selection on the accuracy of the Stanford Relativity gyroscope experiment

This paper discusses an error analysis for the Stanford Relativity experiment, designed to measure the precession of a gyroscope's spin-axis predicted by general relativity. Measurements will be made of the spin-axis orientations of 4 superconducting spherical gyroscopes carried by an earth-satellite. Two relativistic precessions are predicted: a 'geodetic' precession associated with the satellite's orbital motion and a 'motional' precession due to the earth's rotation. Using a Kalman filter covariance analysis with a realistic error model we have computed the error in determining the relativistic precession rates. Studies show that a slightly off-polar orbit is better than a polar orbit for determining the 'motional' drift.

Vassar, R.↗
NASA NTRS2001

State Estimation for K9

The goal of 'Estimate' is to take advantage of attitude information to produce better pose while staying flexible and robust. Currently there are several instruments that are used for attitude: gyros, inclinometers, and compasses. However, precise and useful attitude information cannot come from one instrument. Integration of rotational rates, from gyro data for example, would result in drift. Therefore, although gyros are accurate in the short-term, accuracy in the long term is unlikely. Using absolute instruments such as compasses and inclinometers can result in an accurate measurement of attitude in the long term. However, in the short term, the physical nature of compasses and inclinometers, and the dynamic nature of a mobile platform result in highly volatile and therefore useless data. The solution then is to use both absolute and relative data. Kalman Filtering is known to be able to combine gyro and compass/inclinometer data to produce stable and accurate attitude information. Since the model of motion is linear and the data comes in as discrete samples, a Discrete Kalman Filter was selected as the core of the new estimator. Therefore, 'Estimate' can be divided into two parts: the Discrete Kalman Filter and the code framework.

Xu, Ru-Gang↗
NASA NTRS2002

A Nonlinear, Human-Centered Approach to Motion Cueing with a Neurocomputing Solver

This paper discusses the continuation of research into the development of new motion cueing algorithms first reported in 1999. In this earlier work, two viable approaches to motion cueing were identified: the coordinated adaptive washout algorithm or 'adaptive algorithm', and the 'optimal algorithm'. In this study, a novel approach to motion cueing is discussed that would combine features of both algorithms. The new algorithm is formulated as a linear optimal control problem, incorporating improved vestibular models and an integrated visual-vestibular motion perception model previously reported. A control law is generated from the motion platform states, resulting in a set of nonlinear cueing filters. The time-varying control law requires the matrix Riccati equation to be solved in real time. Therefore, in order to meet the real time requirement, a neurocomputing approach is used to solve this computationally challenging problem. Single degree-of-freedom responses for the nonlinear algorithm were generated and compared to the adaptive and optimal algorithms. Results for the heave mode show the nonlinear algorithm producing a motion cue with a time-varying washout, sustaining small cues for a longer duration and washing out larger cues more quickly. The addition of the optokinetic influence from the integrated perception model was shown to improve the response to a surge input, producing a specific force response with no steady-state washout. Improved cues are also observed for responses to a sway input. Yaw mode responses reveal that the nonlinear algorithm improves the motion cues by reducing the magnitude of negative cues. The effectiveness of the nonlinear algorithm as compared to the adaptive and linear optimal algorithms will be evaluated on a motion platform, the NASA Langley Research Center Visual Motion Simulator (VMS), and ultimately the Cockpit Motion Facility (CMF) with a series of pilot controlled maneuvers. A proposed experimental procedure is discussed. The results of this evaluation will be used to assess motion cueing performance.

Telban, Robert J.↗
NASA NTRS2019

Interannual Oscillations in Earth Rotation

At seasonal and shorter time scales, polar motion and length‐of‐day (LOD) change are dominated by mass redistribution in the Earth climate system, including the atmosphere, oceans, and hydrosphere. Long‐term polar motion and LOD change are believed to be forced by solid Earth geophysical process, such as glacial isostatic adjustment. Decadal LOD variations are also connected to core‐mantle coupling. This study provides a comprehensive analysis of interannual oscillations in all three components of Earth rotation using accurately measured polar motion and LOD time series, and geophysical excitations computed from atmospheric, oceanic, and hydrological models over the period 1962 to 2018. Strong interannual oscillations remain in all three components after detrending and band‐pass filtering to retain variations at periods between 2 and 8 years. Polar motion Y is dominated by a 3.65‐year oscillation, plus others at periods of 2.5 and 5.9 years. Polar motion X shows a strong oscillation near 5.9 years, plus smaller variations at shorter periods. A 5.9‐year LOD variation has been recognized in earlier studies, but oscillations at periods of 2.36, 3.65, and 4.9 years are also observed. Atmosphere, ocean, and hydrosphere (AOH) sources largely account for 2.5‐ and 3.65‐year components in polar motion Y, but not for the 5.9‐year component in polar motion X and Y. The 2.36‐, 3.65‐, and 4.9‐year components in LOD can largely be accounted for by AOH sources. The 5.9‐year LOD component becomes more prominent after AOH sources have been subtracted. The presence of a 5.9‐year variation in all three components of Earth rotation suggests a source in Earth's interior, probably from the core.

Jianli Chen↗
NASA NTRS1992

Performance of the ice motion tracker at the Alaska SAR facility

An ice motion tracker has been implemented as part of the Ice/Ocean Geophysical Processor System (GPS) at the Alaska Synthetic Aperture Radar (SAR) Facility. The motion tracker operates in an unsupervised mode and utilizes a combination of feature-based and area-based matching to construct the displacement field from time-separated SAR imagery. The tracker is used to generate routine motion products for investigations of the kinematics and dynamics of sea ice in the polar regions. A number of filters for elimination of outliers and incorrect matches have been implemented to maintain the quality of the motion vector product. Preliminary evaluation of the tracking algorithm with European Space Agency Remote Sensing Satellite (ERS-1) data indicate that these requirements are satisfied. The performance and shortcomings of the motion tracker are discussed.

Kwok, Ronald↗
NASA NTRS1987

Approximating SIR-B response characteristics and estimating wave height and wavelength for ocean imagery

NASA Space Shuttle Challenger SIR-B ocean scenes are used to derive directional wave spectra for which speckle noise is modeled as a function of Rayleigh random phase coherence downrange and Poisson random amplitude errors inherent in the Doppler measurement of along-track position. A Fourier filter that preserves SIR-B image phase relations is used to correct the stationary and dynamic response characteristics of the remote sensor and scene correlator, as well as to subtract an estimate of the speckle noise component. A two-dimensional map of sea surface elevation is obtained after the filtered image is corrected for both random and deterministic motions.

Tilley, David G.↗
NASA NTRS1992

Large eddy simulation of compressible turbulent channel flows

The development of turbulence within rocket propulsion chamber flows remains a difficult problem to predict. Within solid propellant rockets, the flow can exhibit multiple regions of transition to turbulence, and is susceptible to various modes of aero-acoustic interaction. The objective is to formulate, develop, and validate, a large eddy simulation (LES) method for compressible channel flows. The LES method separates the resolvable scale motions from the unresolvable scales by applying a spatial filter to the compressible Navier-Stokes equations. The equations are solved numerically using a modified four-step Runge-Kutta procedure in time and second or fourth order finite differences in space. The current simulations have validated the algorithm in the incompressible limit and have demonstrated the ability of the method to simulate high subsonic Mach number flows.

Beddini, Robert A.↗
NASA NTRSDate not supplied

TOWARD A METHOD FOR SCALING HUMAN BODY MODELS IN AN IMU-BASED WORKFLOW

BACKGROUND Scaled biomechanical models can more accurately inform crew health decisions when tailored to the wide range of astronaut sizes. One component to improve scaling of existing models to better represent each unique astronaut’s size is the individual length scaling of limbs. Traditionally, these lengths are determined by motion capture or manual measurement. A new method is herein proposed for length scaling which can be done by measuring linear and angular accelerations at a desired point during isolated motion around a point of rotation, then calculating the distance between the desired point and point of rotation. When an Inertial Measurement Unit (IMU) device is placed at the distal point of a limb, the isolated motion is about that limb’s proximal joint. For example, to measure forearm length, an IMU is placed at the wrist, the point of rotation is at the elbow, and the isolated motion is forearm flexion and extension. These calculated lengths are then used to scale models to each unique astronaut’s size, thereby improving the applicability of the model. This method of scaling limb segments can be used for any limb that has an easily defined proximal joint for the limb to rotate around including hands, arms, legs, feet. Utilizing IMUs for data collection also provides the synergistic ability to record data without a dedicated space in a room with many cameras, therefore reducing the data collection footprint, or record data where optical motion capture is not possible, such as inside a spacesuit. METHODS AND RESULTS To test this method, upper body data collection was performed with 5 Xsens DOT IMUs on a single subject. IMUs consist of an accelerometer, a gyroscope, and a magnetometer which collect linear acceleration, angular velocity, and magnetic fluctuations, respectively. Before any ground-based laboratory collection, the magnetic fluctuations are used to correct the heading of the IMU in space relative to the Earth’s magnetic field. The direct measurement of angular velocity is integrated to calculate angular acceleration. Then the linear acceleration ( a ) and angular acceleration (α) are solved using r = at/α to calculate the radius, which in this case is the distance between the IMU and the point of rotation (i.e., segment length). The IMU must be placed at the most distal point of the limb being measured (i.e., ankle if measuring lower leg length) and the test plan must consist of an isolated motion about that limb’s proximal joint (i.e., knee flexion and extension if measuring lower leg length). The distances (radii) calculated at every time interval were filtered (bandpass filter keeping 5th-90th percentile data) to eliminate outliers and spurious data that occur when the isolated motion was stopped or nearly stopped. The remaining distances were averaged, resulting in the calculated limb length. Scaling factors were then computed by dividing the calculated limb length by the unscaled model’s length. These scale factors are plugged into the Scale Tool in OpenSim [1,2] to apply the scaling to the OpenSim Full Body Rajagopal Model [3,4]. Manual measurements of limb lengths were taken before data collection started and used for comparing against the calculated lengths. The Anthropometric Survey of US Army Personnel (ANSUR II) [5] was also used as a third source of reference for limb length measurements. The following measurements were retrieved from the subject before data collection: 34.5 cm from L1 to C7 (thorax), 25.7 cm from C7 Joint Center (JC) to head vertex (neck and head), 36.3 cm from shoulder JC to elbow JC (humerus), 29.5 cm from elbow JC to wrist JC (forearm), and 16.2 cm from clavicle to acromion (clavicle). Of those five, forearm and humerus lengths were calculated using this proposed method to obtain preliminary results. The forearm length after filtering and averaging was calculated to be 37.6 cm. This is a 28% overestimation from the measured forearm length (29.5 cm). The humerus length after filtering and averaging was calculated to be 47.8 cm. This is a 31% difference from the measured subject length (36.3 cm). Sources of error include imperfect isolated motion (method currently expects that motion should be perfectly circular in a 2D plane, include no rotation of the IMU, and be relatively smooth; a more secure IMU attachment method will help), unrefined filter techniques (removed highest and lowest values with 20% high and low pass filters and no smoothing filters), arbitrary removal of stopped or near stopped data (kept data for only a short range before and after the angular velocity peaking), and a more representative method for removing gravitational acceleration is needed (current method is to zero all accelerations against a baseline taken just before the isolated motion which does not account for the gravitational acceleration changed due to IMU rotation during movement). Addressing these error sources will improve the accuracy of the limb length calculation. Next steps include creating a method for whole-body scaling estimation using individual limb scale factors. Continued pursuit of these techniques is expected to enable acquiring anthropometric information using only IMUs in real-time.

E. K. Marecki↗
NASA NTRS1993

Motion measurement of acoustically levitated object

A system is described for determining motion of an object that is acoustically positioned in a standing wave field in a chamber. Sonic energy in the chamber is sensed, and variation in the amplitude of the sonic energy is detected, which is caused by linear motion, rotational motion, or drop shape oscillation of the object. Apparatus for detecting object motion can include a microphone coupled to the chamber and a low pass filter connected to the output of the microphone, which passes only frequencies below the frequency of sound produced by a transducer that maintains the acoustic standing wave field. Knowledge about object motion can be useful by itself, can be useful to determine surface tension, viscosity, and other information about the object, and can be useful to determine the pressure and other characteristics of the acoustic field.

Watkins, John L.↗
NASA NTRS2008

Ultra-Stable Beacon Source for Laboratory Testing of Optical Tracking

The ultra-stable beacon source (USBS) provides a laser-beam output with a very low angular jitter and can be used as an absolute angular reference to simulate a beacon in the laboratory. The laser is mounted on the top of a very short (approximately equal to 1 m) inverted pendulum (IP) with its optical axis parallel to the carbon fiber pendulum leg. The 85-cm, carbon fiber rods making up the leg are very lightweight and rigid, and are supported by a flex-joint at the bottom (see figure). The gimbal-mounted laser is a weight-adjustable load of about 1.5 kg with its center of rotation co-located with the center of percussion of the inverted pendulum. This reduces the coupling of transverse motion at the base of the pendulum to angular motion of the laser at the top. The inverted pendulum is mounted on a gimbal with its center of rotation coinciding with the pivot position of the inverted pendulum flexure joint. This reduces coupling of ground tilt at the inverted pendulum base to motion of the laser mounted at the top. The mass of the top gimbal is adjusted to give the pendulum a very low resonant frequency (approximately equal to 10 mHz) that filters transverse seismic disturbances from the ground where the base is attached. The motion of the IP is monitored by an optical-lever sensor. The laser light is reflected by the mirror on the IP, and then is detected by a quadrant photo-detector (QPD). The position of the beam spot on the QPD corresponds to the tilt of the IP. Damping of this motion is provided by two coil and magnet pairs. The bottom gimbal mount consists of two plates. The IP is mounted on the second plate. The first plate is supported by two posts through needles and can be rotated about the axis connecting the tips of the needles. The second plate hangs from the first plate and can be rotated about the axis perpendicular to the first plate. As a result, the second plate acts as a two-axis rotation stage. Its center of rotation is located at the effective bending point of the flex-joint. The second plate is pressed against two screw actuators by the weight of the IP. The screw actuators are orthogonal to each other and are used to adjust the inclination of the second plate. The actuators are driven by stepper motors. The whole IP system is housed in a box made of Lexan plastic plates to provide isolation from air currents and temperature variations. The signals from the sensors are processed and recorded with a PC using the xPC Target realtime environment of Math- Works. The control algorithms are written using the Simulink package from The MathWorks.

Aso, Yoichi↗
NASA NTRS1997

Computational Investigations of Noise Suppression in Subsonic Round Jets

NASA Grant NAG1-1802, originally submitted in June 1996 as a two-year proposal, was awarded one-year's funding by NASA LaRC for the period 5 Oct., 1996, through 4 Oct., 1997. Because of the inavailability (from IT at NASA ARC) of sufficient supercomputer time in fiscal 1998 to complete the computational goals of the second year of the original proposal (estimated to be at least 400 Cray C-90 CPU hours), those goals have been appropriately amended, and a new proposal has been submitted to LaRC as a follow-on to NAG1-1802. The current report documents the activities and accomplishments on NAG1-1802 during the one-year period from 5 Oct., 1996, through 4 Oct., 1997. NASA Grant NAG1-1802, and its predecessor, NAG1-1772, have been directed toward adapting the numerical tool of Large-Eddy Simulation (LES) to aeroacoustic applications, with particular focus on noise suppression in subsonic round jets. In LES, the filtered Navier-Stokes equations are solved numerically on a relatively coarse computational grid. Residual stresses, generated by scales of motion too small to be resolved on the coarse grid, are modeled. Although most LES incorporate spatial filtering, time-domain filtering affords certain conceptual and computational advantages, particularly for aeroacoustic applications. Consequently, this work has focused on the development of SubGrid-Scale (SGS) models that incorporate time- domain filters. The author is unaware of any previous attempt at purely time-filtered LES; however, Aldama and Dakhoul and Bedford have considered approaches that combine both spatial and temporal filtering. In our view, filtering in both space and time is redundant, because removal of high frequencies effects the removal of small spatial scales and vice versa.

Pruett, C. David↗