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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Rotorcraft control system design for uncertain vehicle dynamics using quantitative feedback theory

Quantitative Feedback Theory describes a frequency-domain technique for the design of multi-input, multi-output control systems which must meet time or frequency domain performance criteria when specified uncertainty exists in the linear description of the vehicle dynamics. This theory is applied to the design of the longitudinal flight control system for a linear model of the BO-105C rotorcraft. Uncertainty in the vehicle model is due to the variation in the vehicle dynamics over a range of airspeeds from 0-100 kts. For purposes of exposition, the vehicle description contains no rotor or actuator dynamics. The design example indicates the manner in which significant uncertainty exists in the vehicle model. The advantage of using a sequential loop closure technique to reduce the cost of feedback is demonstrated by example.

Hess, R. A.↗
NASA NTRS1997

The Uncertain Nature of Cometary Motions

The number of active short- and long-periodic comets crossing the Earth's orbit each year is less than 10 percent of the corresponding number of asteroids crossing the Earth's orbit. However, the higher relative velocities of comets with respect to the Earth and the uncertainties associated with accurately computing their future trajectories can cause considerable problems when assessing the risks of Earth-crossing objects. Unlike asteroids, the motions of active comets are often affected by so-called nongravitational (outgassing) forces that are imperfectly modeled. In addition, the astrometric optical observations that are used to refine a comet's orbit are often imprecise because a comet's center of mass can be hidden by atmospheric gas and dust. For long-period comets, there is the additional problem of having to base orbital solutions on relatively short observational data intervals. Long-term numerical integrations extending two centuries into the future have been carried out to investigate upcoming Earth-close approaches by known periodic comets. Error analyses and impact probabilities have been computed for those comets that will pass closest to the Earth. Although there are no known comets that will make dangerously close Earth approaches in the next two centuries, there are a few objects that warrant future monitoring.

Yeomans, Donald K.↗
NASA NTRS1998

Buckling of structures with uncertain imperfections - Personal perspective

The previous review on stochastic buckling of structures was written by Amazigo in 1976. This review summarizes some of the developments which took place in recent two decades. A brief overview is given of the effect on uncertainty in the initial geometric imperfections, elastic moduli, applied forces, and thickness variation. For the benefit of the thinking reader, the review has a critical nature. It should be noted that this manuscript has yet to be completed.

Elishakoff, Isaac↗
NASA NTRS1998

The Other Side of Multidisciplinary Design Optimization: Accommodating a Multiobjective, Uncertain and Non-Deterministic World

The evolution of multidisciplinary design optimization (MDO) over the past several years has been one of rapid expansion and development. In this paper, the evolution of MDO as a field is investigated as well as the evolution of its individual linguistic components: multidisciplinary, design, and optimization. The theory and application of each component have indeed evolved on their own, but the true net gain for MDO is how these piecewise evolutions coalesce to form the basis for MDO, present and future. Originating in structural applications, MDO technology has also branched out into diverse fields and application arenas. The evolution and diversification of MDO as a discipline is explored but details are left to the references cited.

Lewis, Kemper↗
NASA NTRS1997

Fixed Future and Uncertain Past: Theorems Explain Why It Is Often More Difficult to Reconstruct the Past Than to Predict the Future

At first glance. it may seem that reconstructing the past is, in general, easier than predicting the future, because the past has already occurred and it has already left its traces, while the future is still yet to come, and so no traces of the future are available. However, in many real life situations, including problems from geophysics and celestial mechanics, reconstructing the past is much more computationally difficult than predicting the future. In this paper, we give an explanation of this difficulty. This explanation is given both on a formal level (as a theorem) and on the informal level (as a more intuitive explanation).

Alefeld, Goetz↗
NASA NTRS2000

Predictive and Neural Predictive Control of Uncertain Systems

Accomplishments and future work are:(1) Stability analysis: the work completed includes characterization of stability of receding horizon-based MPC in the setting of LQ paradigm. The current work-in-progress includes analyzing local as well as global stability of the closed-loop system under various nonlinearities; for example, actuator nonlinearities; sensor nonlinearities, and other plant nonlinearities. Actuator nonlinearities include three major types of nonlineaxities: saturation, dead-zone, and (0, 00) sector. (2) Robustness analysis: It is shown that receding horizon parameters such as input and output horizon lengths have direct effect on the robustness of the system. (3) Code development: A matlab code has been developed which can simulate various MPC formulations. The current effort is to generalize the code to include ability to handle all plant types and all MPC types. (4) Improved predictor: It is shown that MPC design using better predictors that can minimize prediction errors. It is shown analytically and numerically that Smith predictor can provide closed-loop stability under GPC operation for plants with dead times where standard optimal predictor fails. (5) Neural network predictors: When neural network is used as predictor it can be shown that neural network predicts the plant output within some finite error bound under certain conditions. Our preliminary study shows that with proper choice of update laws and network architectures such bound can be obtained. However, much work needs to be done to obtain a similar result in general case.

Kelkar, Atul G.↗
NASA NTRS2002

Dynamic Stability of Uncertain Laminated Beams Under Subtangential Loads

Because of the inherent complexity of fiber-reinforced laminated composites, it can be challenging to manufacture composite structures according to their exact design specifications, resulting in unwanted material and geometric uncertainties. In this research, we focus on the deterministic and probabilistic stability analysis of laminated structures subject to subtangential loading, a combination of conservative and nonconservative tangential loads, using the dynamic criterion. Thus a shear-deformable laminated beam element, including warping effects, is derived to study the deterministic and probabilistic response of laminated beams. This twenty-one degrees of freedom element can be used for solving both static and dynamic problems. In the first-order shear deformable model used here we have employed a more accurate method to obtain the transverse shear correction factor. The dynamic version of the principle of virtual work for laminated composites is expressed in its nondimensional form and the element tangent stiffness and mass matrices are obtained using analytical integration The stability is studied by giving the structure a small disturbance about an equilibrium configuration, and observing if the resulting response remains small. In order to study the dynamic behavior by including uncertainties into the problem, three models were developed: Exact Monte Carlo Simulation, Sensitivity Based Monte Carlo Simulation, and Probabilistic FEA. These methods were integrated into the developed finite element analysis. Also, perturbation and sensitivity analysis have been used to study nonconservative problems, as well as to study the stability analysis, using the dynamic criterion.

Goyal, Vijay K.↗
NASA NTRS2003

Scheduling in the Face of Uncertain Resource Consumption and Utility

We discuss the problem of scheduling tasks that consume a resource with known capacity and where the tasks have varying utility. We consider problems in which the resource consumption and utility of each activity is described by probability distributions. In these circumstances, we would like to find schedules that exceed a lower bound on the expected utility when executed. We first show that while some of these problems are NP-complete, others are only NP-Hard. We then describe various heuristic search algorithms to solve these problems and their drawbacks. Finally, we present empirical results that characterize the behavior of these heuristics over a variety of problem classes.

Koga, Dennis↗
NASA NTRS2005

Performance of a Checkerboard Liner With Uncertain Impedances

The current fleet of large commercial aircraft has successfully achieved FAA noise certifications because of, in part, the successful application of uniform passive duct liner treatments to control engine system noise. One goal of NASA's engine system noise reduction program is to develop technologies to improve the sound absorbing properties of duct liner treatments so that they remain effective in modern turbo fan engines. One such technology being studied is checkerboard or periodic axially and circumferentially segmented liners. A preliminary assessment of the potential of this technology was conducted by applying uncertainties associated with manufacturing, installation, source structure, and tonal frequency to a liner developed using deterministic design methods and generating a measure of improvement with respect to a uniform liner subjected to the same uncertainties. Deterministic design and analysis of the candidate checkerboard liner showed that it obtains a 1.5 dB per duct aspect ratio improvement in liner attenuation over a similarly designed uniform liner. When uncertainties in liner impedances, source structure, and frequency are considered, the performance of the checkerboard liner drops off dramatically. The final results of this paper show that the candidate checkerboard liner has a less than 25 percent chance of outperforming the uniform liner when moderate levels of uncertainty are considered. It is important to note that this study did not include the effects of mean flow on liner performance and, more important to note, that as a gradient based optimization process was used to design the checkerboard liner, it is almost certain that a global optimal design was not found for the candidate checkerboard liner. Had it been possible to find a better deterministically performing checkerboard liner, the probability that this candidate liner would outperform the uniform liner would certainly have been higher.

Robinson, J. H.↗
NASA NTRS2005

Multi-Resolution Planning in Large Uncertain Domains

This project spanned three and one half years of research. This report covers three major lines of work that were done most recently and reported on in a talk given by the PI at NASA Ames on March 23, 2004. There are have been additional publications related to this work (Lane & Kaelbling, 2001a, 2001b, 2002; Zettlemoyer, Pasula, & Kaelbling, 2003; Gardiol & Kaelbling, 2003; Pasula, Zettlemoyer, & Kaelbling, 2004).

Kaelbling, Leslie Pack↗
NASA NTRS2005

Reliability-Based Control Design for Uncertain Systems

This paper presents a robust control design methodology for systems with probabilistic parametric uncertainty. Control design is carried out by solving a reliability-based multi-objective optimization problem where the probability of violating design requirements is minimized. Simultaneously, failure domains are optimally enlarged to enable global improvements in the closed-loop performance. To enable an efficient numerical implementation, a hybrid approach for estimating reliability metrics is developed. This approach, which integrates deterministic sampling and asymptotic approximations, greatly reduces the numerical burden associated with complex probabilistic computations without compromising the accuracy of the results. Examples using output-feedback and full-state feedback with state estimation are used to demonstrate the ideas proposed.

Crespo, Luis G.↗
NASA NTRS2009

Uncertain Representations of Sub-Grid Pollutant Transport in Chemistry-Transport Models and Impacts on Long-Range Transport and Global Composition

Sub-grid transport, by convection and turbulence, is known to play an important role in lofting pollutants from their source regions. Consequently, the long-range transport and climatology of simulated atmospheric composition are impacted. This study uses the Goddard Earth Observing System, Version 5 (GEOS-5) atmospheric model to study pollutant transport. The baseline model uses a Relaxed Arakawa-Schubert (RAS) scheme that represents convection through a sequence of linearly entraining cloud plumes characterized by unique detrainment levels. Thermodynamics, moisture and trace gases are transported in the same manner. Various approximate forms of trace-gas transport are implemented, in which the box-averaged cloud mass fluxes from RAS are used with different numerical approaches. Substantial impacts on forward-model simulations of CO (using a linearized chemistry) are evident. In particular, some aspects of simulations using a diffusive form of sub-grid transport bear more resemblance to space-biased CO observations than do the baseline simulations with RAS transport. Implications for transport in the real atmosphere will be discussed. Another issue of importance is that many adjoint/inversion computations use simplified representations of sub-grid transport that may be inconsistent with the forward models: implications will be discussed. Finally, simulations using a complex chemistry model in GEOS-5 (in place of the linearized CO model) are underway: noteworthy results from this simulation will be mentioned.

Pawson, Steven↗
NASA NTRS2011

Developing Flexible Discrete Event Simulation Models in an Uncertain Policy Environment

On February 1st, 2010 U.S. President Barack Obama submitted to Congress his proposed budget request for Fiscal Year 2011. This budget included significant changes to the National Aeronautics and Space Administration (NASA), including the proposed cancellation of the Constellation Program. This change proved to be controversial and Congressional approval of the program's official cancellation would take many months to complete. During this same period an end-to-end discrete event simulation (DES) model of Constellation operations was being built through the joint efforts of Productivity Apex Inc. (PAl) and Science Applications International Corporation (SAIC) teams under the guidance of NASA. The uncertainty in regards to the Constellation program presented a major challenge to the DES team, as to: continue the development of this program-of-record simulation, while at the same time remain prepared for possible changes to the program. This required the team to rethink how it would develop it's model and make it flexible enough to support possible future vehicles while at the same time be specific enough to support the program-of-record. This challenge was compounded by the fact that this model was being developed through the traditional DES process-orientation which lacked the flexibility of object-oriented approaches. The team met this challenge through significant pre-planning that led to the "modularization" of the model's structure by identifying what was generic, finding natural logic break points, and the standardization of interlogic numbering system. The outcome of this work resulted in a model that not only was ready to be easily modified to support any future rocket programs, but also a model that was extremely structured and organized in a way that facilitated rapid verification. This paper discusses in detail the process the team followed to build this model and the many advantages this method provides builders of traditional process-oriented discrete event simulations.

Miranda, David J.↗
NASA NTRS2012

Robust Control Design for Uncertain Nonlinear Dynamic Systems

Robustness to parametric uncertainty is fundamental to successful control system design and as such it has been at the core of many design methods developed over the decades. Despite its prominence, most of the work on robust control design has focused on linear models and uncertainties that are non-probabilistic in nature. Recently, researchers have acknowledged this disparity and have been developing theory to address a broader class of uncertainties. This paper presents an experimental application of robust control design for a hybrid class of probabilistic and non-probabilistic parametric uncertainties. The experimental apparatus is based upon the classic inverted pendulum on a cart. The physical uncertainty is realized by a known additional lumped mass at an unknown location on the pendulum. This unknown location has the effect of substantially altering the nominal frequency and controllability of the nonlinear system, and in the limit has the capability to make the system neutrally stable and uncontrollable. Another uncertainty to be considered is a direct current motor parameter. The control design objective is to design a controller that satisfies stability, tracking error, control power, and transient behavior requirements for the largest range of parametric uncertainties. This paper presents an overview of the theory behind the robust control design methodology and the experimental results.

Kenny, Sean P.↗
NASA NTRS2012

Space Radiation Cancer Risks and Uncertainities for Different Mission Time Periods

Space radiation consists of solar particle events (SPEs), comprised largely of medium energy protons (less than several hundred MeV); and galactic cosmic ray (GCR), which includes high energy protons and high charge and energy (HZE) nuclei. For long duration missions, space radiation presents significant health risks including cancer mortality. Probabilistic risk assessment (PRA) is essential for radiation protection of crews on long term space missions outside of the protection of the Earth s magnetic field and for optimization of mission planning and costs. For the assessment of organ dosimetric quantities and cancer risks, the particle spectra at each critical body organs must be characterized. In implementing a PRA approach, a statistical model of SPE fluence was developed, because the individual SPE occurrences themselves are random in nature while the frequency distribution of SPEs depends strongly upon the phase within the solar activity cycle. Spectral variability of SPEs was also examined, because the detailed energy spectra of protons are important especially at high energy levels for assessing the cancer risk associated with energetic particles for large events. An overall cumulative probability of a GCR environment for a specified mission period was estimated for the temporal characterization of the GCR environment represented by the deceleration potential (theta). Finally, this probabilistic approach to space radiation cancer risk was coupled with a model of the radiobiological factors and uncertainties in projecting cancer risks. Probabilities of fatal cancer risk and 95% confidence intervals will be reported for various periods of space missions.

Kim,Myung-Hee Y.↗
NASA NTRS2014

Improving FermiI Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecrafts ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45 improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

orbit prediction↗
NASA NTRS2014

Improving Fermi Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecraft's ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45% improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

orbit prediction↗