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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

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NASA NTRS1986

Optimal airframe synthesis for gust loads

An optimization capability for sizing airframe structures that are subjected to a combination of deterministic and random flight loads was established. The random vibration environment introduces the need for selecting a statistical process that best describes the random loads and permits computation of the dynamic response parameters of interest. Furthermore, it requires a formulation of design constraints that would minimize the conservativeness in the design and retain computational viability. The random loads are treated as a stationary, homogeneous process with a Gaussian probability distribution. The formulation of the analysis problem, the structure of the optimization programming system and a representative numerical example are discussed.

Hajela, P.↗

NASA NTRS1986

Noise transmission into enclosures

This paper describes analytical and experimental studies of noise transmission into rectangular and cylindrical enclosures. The solutions of the governing acoustic-structural equations are developed by modal decomposition of structural vibrations and the interior acoustic field. Particular attention is directed toward the low frequencies, that is, frequencies up through the first few structural and cavity resonant modes. The structural vibrations are driven by the external acoustic and/or mechanical point loads which are taken to be Gaussian stationary random processes. The structural models include rectangular panels and cylindrical shells.

Vaicaitis, R.↗

NASA NTRS1988

Optimum structural sizing for gust induced response

The present paper describes an optimization capability for sizing airframe structures that are subjected to a combination of deterministic and random loads. Design constraints are implemented to prevent structural failure in fatigue and due to a single exceedance of the allowable stress. The random load is treated as a stationary, homogeneous process with a Gaussian probability distribution, and a frequency domain method is used for the computation of dynamic response parameters. An equal-probability-of-load-combination criterion is proposed in the formulation of strength constraints. This alleviates problems associated with the incomplete phase information available when using power spectral density methods. The optimization procedure is illustrated by examples using typical built-up structures.

Hajela, P.↗

NASA NTRS1990

An analysis of scatter decomposition

A formal analysis of a powerful mapping technique known as scatter decomposition is presented. Scatter decomposition divides an irregular computational domain into a large number of equal sized pieces, and distributes them modularly among processors. A probabilistic model of workload in one dimension is used to formally explain why, and when scatter decomposition works. The first result is that if correlation in workload is a convex function of distance, then scattering a more finely decomposed domain yields a lower average processor workload variance. The second result shows that if the workload process is stationary Gaussian and the correlation function decreases linearly in distance until becoming zero and then remains zero, scattering a more finely decomposed domain yields a lower expected maximum processor workload. Finally it is shown that if the correlation function decreases linearly across the entire domain, then among all mappings that assign an equal number of domain pieces to each processor, scatter decomposition minimizes the average processor workload variance. The dependence of these results on the assumption of decreasing correlation is illustrated with situations where a coarser granularity actually achieves better load balance.

Nicol, David M.↗

NASA NTRS1990

An analysis of scatter decomposition

A formal analysis of a mapping method known as scatter decomposition (SD) is presented. SD divides an irregular domain into many equal-size pieces and distributes them modularly among processors. It is shown that, if a correlation in workload is a convex function of distance, then scattering a more finely decomposed domain yields a lower average processor workload variance; if the workload process is stationary Gaussian and the correlation function decreases linearly in distance to zero and then remains zero, scattering a more finely decomposed domain yields a lower expected maximum processor workload. Finally, if the correlation function decreases linearly across the entire domain, then (among all mappings that assign an equal number of domain pieces to each processor) SD minimizes the average processor workload variance. The dependence of these results on the assumption of decreasing correlation is illustrated with cases where a coarser granularity actually achieves better load balance.

Nicol, David M.↗

NASA NTRS1990

Active control test on the Mini-Mast

A Linear Quadratic Gaussian (LQG) design process is presented and applied to a large flexible ground test facility, the Mini-Mast, for validation. For the design, nine displacement sensors were used. Three torque wheel actuators were used for damping augmentation. Results were dramatic, indicating an improvement in damping from 3 percent to 30 percent of critical. The tests proved the effectiveness of the procedure in designing effective vibration damping systems.

Montgomery, Raymond C.↗

NASA NTRS2025

Simultaneous Localization and Mapping for Spacecraft Rendezvous and Proximity Operations Using Random Finite Sets

Future space missions require spacecraft to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current navigation filters used for RPO can have difficulty when optical sensors are used, due to complications with data association, high measurement uncertainty, and clutter. This paper provides an initial demonstration of the feasibility of using random finite set (RFS) filters for spacecraft relative navigation and pose estimation. Spacecraft relative navigation is formulated as a simultaneous localization and mapping (SLAM) problem, in which an observer spacecraft seeks to simultaneously estimate the location of features on a target object or spacecraft as well as its relative position, velocity and attitude. Simulated flash LIDAR measurements are processed using a Gaussian Mixture Probability Hypothesis Density (GMPHD) filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer over time. Results show that an RFS-based filter can successfully perform SLAM in a spacecraft relative navigation scenario.

David E Gaylor↗

NASA NTRS2012

Statistical Orbit Determination using the Particle Filter for Incorporating Non-Gaussian Uncertainties

The tracking of space objects requires frequent and accurate monitoring for collision avoidance. As even collision events with very low probability are important, accurate prediction of collisions require the representation of the full probability density function (PDF) of the random orbit state. Through representing the full PDF of the orbit state for orbit maintenance and collision avoidance, we can take advantage of the statistical information present in the heavy tailed distributions, more accurately representing the orbit states with low probability. The classical methods of orbit determination (i.e. Kalman Filter and its derivatives) provide state estimates based on only the second moments of the state and measurement errors that are captured by assuming a Gaussian distribution. Although the measurement errors can be accurately assumed to have a Gaussian distribution, errors with a non-Gaussian distribution could arise during propagation between observations. Moreover, unmodeled dynamics in the orbit model could introduce non-Gaussian errors into the process noise. A Particle Filter (PF) is proposed as a nonlinear filtering technique that is capable of propagating and estimating a more complete representation of the state distribution as an accurate approximation of a full PDF. The PF uses Monte Carlo runs to generate particles that approximate the full PDF representation. The PF is applied in the estimation and propagation of a highly eccentric orbit and the results are compared to the Extended Kalman Filter and Splitting Gaussian Mixture algorithms to demonstrate its proficiency.

Mashiku, Alinda↗

NASA NTRS2010

A Method to Estimate the Probability That Any Individual Cloud-to-Ground Lightning Stroke Was Within Any Radius of Any Point

A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station.

Huddleston, Lisa L.↗

NASA NTRS2011

A Method to Estimate the Probability that Any Individual Cloud-to-Ground Lightning Stroke was Within Any Radius of Any Point

Huddleston, Lisa↗

NASA NTRS2011

A Method to Estimate the Probability that any Individual Cloud-to-Ground Lightning Stroke was Within any Radius of any Point

A new technique has been developed to estimate the probability that a nearby cloud to ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology.

Huddleston, Lisa L.↗

NASA NTRS2012

A Probabilistic, Facility-Centric Approach to Lightning Strike Location

A new probabilistic facility-centric approach to lightning strike location has been developed. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision~ith spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology.

Huddleston, Lisa L.↗

NASA NTRS1980

A generalized formulation of minimum shift keying modulation

The modulator structure consisting of a single-input two-output sequential transducer whose output sequences control the modulated signal in the manner s(t) = x(i)p(t) + y(i)q(t) is considered. Here, iT is less than or equal to t, which is less than iT + T, where T is the modulation bit duration and where x(i) and y(i) take values in /+1, -1, 0/. The behavior of a sequential transducer is characterized by means of a 'trellis'. It is shown that, provided only that the 'carriers' p(t) and q(t) have the same energy in every bit interval, the optimum demodulator for the additive white Gaussian noise channel need process the received signal over only two bit intervals in making each data bit decision. It is demonstrated that particular choices of the sequential transducer yield differential minimum shift keying and differential staggered quadriphase shift keying. Possible generalizations of this approach are discussed.

Massey, J. L.↗

NASA NTRS1984

Application of optimization techniques to the design of a flutter suppression control law for the DAST ARW-2

The design of a candidate flutter suppression (FS) control law for the symmetric degrees of freedom for the DAST ARW-2 aircraft is discussed. The results illustrate the application of several currently employed control law design techniques. Subsequent designs, obtained as the mathematical model of the ARW-2 is updated, are expected to employ similar methods and to provide a control law whose performance will be flight tested. This study represents one of the steps necessary to provide an assessment of the validity of applying current control law synthesis and analysis techniques in the design of actively controlled aircraft. Mathematical models employed in the control law design and evaluation phases are described. The control problem is specified by presenting the flutter boundary predicted for the uncontrolled aircraft and by defining objectives and constraints that the controller should satisfy. A full-order controller is obtained by using Linear Quadratic Gaussian (LQG) techniques. The process of obtaining an implementable reduced-order controller is described. One example is also shown in which constrained optimization techniques are utilized to explicitly include robustness criteria within the design algorithm.

Adams, W. M., Jr.↗

NASA NTRS1989

Void statistics, scaling, and the origins of large-scale structure

The probability that a volume of the universe of given size and shape spaced at random will be void of galaxies is used here to study various models of the origin of cosmological structures. Numerical simulations are conducted on hot-particle and cold-particle-modulated inflationary models with and without biasing, on isothermal or initially Poisson models, and on models where structure is seeded by loops of cosmic string. For the Pisces-Perseus redshift compilation of Giovanelli and Haynes (1985), it is found that hierarchical scaling is obeyed for subsamples constructed with different limiting magnitudes and subsamples taken at random. This result confirms that the hierarchical ansatz holds valid to high order and supports the idea that structure in the observed universe evolves by a regular process from an almost Gaussian primordial state. Neutrino models without biasing show the effect of a strong feature in the initial power spectrum. Cosmic string models do not agree well with the galaxy data.

Fry, J. N.↗

NASA NTRSDate not supplied

Estimation With Range Depended Sensor Model

This paper focuses on the improvement of object detection accuracy taking into account the sensor’s reading degradation as the relative range increases. The approach is based on the assumption that range measurement error depends on the actual range. Specifically, we model the measurement error as a proportional to the actual range term plus a zero-mean, Gaussian distributed, and uncorrelated process. The tracking problem is considered in a mixed continuous-discrete time domain, where the target dynamics is in continuous-time and the measurements are in discrete-time, which is an optimal choice in many tracking and navigation applications. We adopt a commonly used continuous time coordinate-uncoupled white-noise acceleration model for a point object to describe the target motion, and use Extended Kalman Filter (EKF) framework to estimate the target's state and the unknown proportionality coefficient.

Vahram Stepanyan↗

NASA NTRSDate not supplied

Estimation With Range Dependent Sensor Model

This paper focuses on the improvement of target tracking accuracy taking into account the sensor’s reading degradation as the relative range increases. The approach is based on the assumption that range measurement error depends on the actual range. Specifically, we model the measurement error as a proportional to the actual range term plus a zero-mean, Gaussian distributed, and uncorrelated process. We present two approaches to tracking a target with constant velocity model. The first approach uses Extended Kalman Filter (EKF) framework to estimate target's states and the unknown proportionality coefficient with linearization on the observation model on the predicted states at each time step. The second one uses a measurement conversion method to estimate the target's scaled by the unknown constant term states, which is shown to be unbiased. This conversion results in linear state and observation models, hence the standard Kalman filter can be applied. The actual target state is computed by application of back scaling with the estimate of unknown scale factor. We evaluate the approaches in desktop simulations.

Target tracking↗

NASA NTRS1972

Receiver processing for direct-detection optical communication systems.

A model that is sufficiently general to describe the predominant statistical characteristics of the output of many real optical detectors is formulated. This model is used to study the optimum receiver processing for direct-detection optical communication systems. In particular, the structures of detectors and estimators for filtered doubly stochastic Poisson processes (DSPP) observed in additive white Gaussian noise are considered. Representations for the posterior statistics of a vector Markov process that modulates the intensity of the DSPP are obtained.

Hoversten, E. V.↗