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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Induction of models under uncertainty

This paper outlines a procedure for performing induction under uncertainty. This procedure uses a probabilistic representation and uses Bayes' theorem to decide between alternative hypotheses (theories). This procedure is illustrated by a robot with no prior world experience performing induction on data it has gathered about the world. The particular inductive problem is the formation of class descriptions both for the tutored and untutored cases. The resulting class definitions are inherently probabilistic and so do not have any sharply defined membership criterion. This robot example raises some fundamental problems about induction; particularly, it is shown that inductively formed theories are not the best way to make predictions. Another difficulty is the need to provide prior probabilities for the set of possible theories. The main criterion for such priors is a pragmatic one aimed at keeping the theory structure as simple as possible, while still reflecting any structure discovered in the data.

Cheeseman, Peter↗
NASA NTRS1986

A guidance law for the aeroassisted plane change maneuver in the presence of atmospheric uncertainties

A stochastic feedback control law for a space vehicle performing an aeroassisted plane-change maneuver is developed. The stochastic control law is designed to minimize the energy loss while taking into consideration the uncertainty in the atmospheric density. The solution is based on expansion of the stochastic Hamilton-Jacobi-Bellman equation (or dynamic programming) about a zeroth-order known integrable solution. The resulting guidance law is expressed as a series expansion in the noise power spectral densities. A numerical example indicates the potential improvement of this method.

Mishne, D.↗
NASA NTRS1988

Error dynamics and relative orbital uncertainty of the Magellan spacecraft

Relative error is discussed in light of a proposed orbiter mission to Venus. It is hypothesized that the relative (position) error of the orbiting spacecraft between disjoint data sets will be large because of residual uncertainties of the absolute estimates and their decorrelation caused by succeeding estimates. A method is proposed to limit relative error by inducing correlations between the estimates on successive data arcs. These correlations are induced by overlapping the data arcs. Covariance analyses of the data sets are undertaken at two distinct mapping times, yielding the relative error between those mapping times. The technique is applied to a mosaicking problem on a specific day in the mission.

Haw, R. J.↗
NASA NTRS1988

Effect of model uncertainty on failure detection - The threshold selector

The performance of all failure detection, isolation, and accomodation (DIA) algorithms is influenced by the presence of model uncertainty. A unique framework is presented to incorporate a knowledge of modeling error in the analysis and design of failure detection systems. The tools being used are very similar to those in robust control theory. A concept is introduced called the threshold selector, which is a nonlinear inequality whose solution defines the set of detectable sensor failure signals. The threshold selector represents an innovative tool for analysis and synthesis of DIA algorithms. It identifies the optimal threshold to be used in innovations-based DIA algorithms. The optimal threshold is shown to be a function of the bound on modeling errors, the noise properties, the speed of DIA filters, and the classes of reference and failure signals. The size of the smallest detectable failure is also determined. The results are applied to a multivariable turbofan jet engine example, which demonstrates improvements compared to previous studies.

Emami-Naeini, Abbas↗
NASA NTRS1988

Uncertainty management in intelligent design aiding systems

A novel approach to uncertainty management which is particularly effective in intelligent design aiding systems for large-scale systems is presented. The use of this approach in the materials handling system design domain is discussed. It is noted that, during any point in the design process, a point value can be obtained for the evaluation of feasible designs; however, the techniques described provide unique solutions for these point values using only the current information about the design environment.

Brown, Donald E.↗
NASA NTRS1989

A new adaptive control approach for aerospace vehicles with parameter uncertainties

A new stochastic adaptive control structure is developed for the problem of combined parameter estimation and control of aerospace vehicles with changing parameters. Parameter uncertainties are modeled as first-order Gauss-Markov processes, and are introduced to the system dynamics through a small parameter. It is assumed that an accurate inertial measurement unit gives perfect measurements of the state variables. Since the stochastic system is assumed to be Gauss-Markov, the density function of the parameters given these measurements is conditionally Gaussian. Based on this conditionally Gaussian density, the problem of minimizing a quadratic cost over an infinite time horizon can be set up within the framework of stochastic optimal control theory. The optimal feedback control law is derived from a straightforward expansion of the Hamilton-Jacobi-Bellman equation, based on the LQG solution. The resulting nonlinear controller is applied to the pitch axis control of a space platform with uncertain moments of inertia and is shown to produce marked improvement over a fixed controller.

Hahn, Yungsun↗
NASA NTRS1989

Probabilistic modeling for simulation of aerodynamic uncertainties in propulsion systems

The numerical simulation of the probabilistic aerothermodynamic response of propulsion system components to randomness in their environment was explored. The reusable rocket engine turbopumps were selected as an example because of the severe cryogenic environment in which they operate. The thermal and combustion instabilities, coupled with the engine thrust requirements from start up to shut down, lead to randomness in the flow variables and uncertainties in the aerodynamic loading. The probabilistic modeling of the turbopumps aerodynamic response was accomplished using the panel method coupled with fast probability integration methods. The aerodynamic response in the form of probabilistic rotor blades and splitter loading were predicted and the results presented for specified flow coefficient and rotor preswirl variance. Possible future applications of the aerothermodynamic probabilistic modeling in engine transient simulation, condition monitoring and engine life prediction are briefly discussed.

Hamed, Awatef↗
NASA NTRS1989

Multiresolutional models of uncertainty generation and reduction

Kolmogorov's axiomatic principles of the probability theory, are reconsidered in the scope of their applicability to the processes of knowledge acquisition and interpretation. The model of uncertainty generation is modified in order to reflect the reality of engineering problems, particularly in the area of intelligent control. This model implies algorithms of learning which are organized in three groups which reflect the degree of conceptualization of the knowledge the system is dealing with. It is essential that these algorithms are motivated by and consistent with the multiresolutional model of knowledge representation which is reflected in the structure of models and the algorithms of learning.

Meystel, A.↗
NASA NTRS1990

The simulation of fluid dynamic uncertainties in the SSME turbopump

The aerodynamic uncertainties in the reusable rocket engine turbopumps due to randomness in their cryogenic environment are investigated. The probabilistic simulation of the turbopumps' aerodynamic response was accomplished using the panel method coupled with Fast Probability Integration methods. The results are presented for the probabilistic rotor blades and splitter loading and their sensitivity to specified flow coefficient and rotor preswirl variance.

Hamed, Awatef↗
NASA NTRS1990

Robust H(infinity) control design for the Space Station with structured parameter uncertainty

A robust H(infinity) control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multiparameter variations in the state-space formulation of H(infinity) control theory. An application of this robust control synthesis technique tothe Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73 percent in one of the structured uncertainty directions. The performance and stability of this new robust H(infinity) controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.

Byun, Kuk-Whan↗
NASA NTRS1990

Human subjects concerns in ground based ECLSS testing - Managing uncertainty in closely recycled systems

U.S. space missions have to this point used water either made on board or carried from earth and discarded after use. For Space Station Freedom, long duration life support will include air and water recycling using a series of physical-chemical subsystems. The Environmental Control and Life Support System (ECLSS) designed for this application must be tested extensively at all stages of hardware maturity. Human test subjects are required to conduct some of these tests, and the risks associated with the use of development hardware must be addressed. Federal guidelines for protection of human subjects require careful consideration of risks and potential benefits by an Institutional Review Board (IRB) before and during testing. This paper reviews the ethical principles guiding this consideration, details the problems and uncertainties inherent in current hardware testing, and presents an incremental approach to risk assessment for ECLSS testing.

Crump, William J.↗
NASA NTRS1989

Infrared-fiber-optic fire sensor developments - Role of measurement uncertainty in evaluation of background limited range

Fire-detector systems based on distributed infrared fiber-sensors have been investigated for potential applications in the aerospace industry. Responsivities to blackbody and flame radiations were measured with various design configurations of an infrared fiber-optic sensor. Signal processing techniques were also investigated, and the results show significant differences in the fire-sensor performance depending on the design configuration. Measurement uncertainties were used to determine the background-limited ranges for the various fire-sensor concepts, and the probability of producing false alarms caused by fluctuations in the background signals were determined using extreme probability theory. The results of the research show that infrared fiber-optic fire sensors are feasible for application on manned spacecraft; however, additional development work will be required to eliminate false alarms caused by high temperature objects such as incandescent lamps.

Tapphorn, Ralph M.↗
NASA NTRS1991

Robustness in the presence of mixed parametric uncertainty and unmodeled dynamics

Continuing the development of the structured singular value approach to robust control design, the authors investigate the problem of computing the structured singular value (mu) in the case of mixed real parametric and complex uncertainty. The problem is shown to be equivalent to a smooth constrained finite-dimensional optimization problem. In view of the fact that the functional to be maximized may have several local extrema, an upper bound on mu whose computation is numerically tractable is established; this leads to a sufficient condition of robust stability and performance. A historical perspective on the development of the mu theory is included.

Fan, Michael K. H.↗
NASA NTRS1991

Quantification of uncertainties in coupled material degradation processes - High temperature, fatigue and creep

This paper describes the development of methodology that provides for quantification of uncertainties in lifetime strength of aerospace materials subjected to a number of diverse effects. A probabilistic material degradation model, in the form of a randomized multifactor interaction equation, has been postulated for lifetime strength degradation of structural components of aerospace propulsion systems. The model includes effects that typically reduce lifetime strength and may include temperature, mechanical fatigue, creep and others. The paper also includes the analysis of experimental data from the open literature for Inconel 718. These data are used to provide an initial check for model validity, as well as for calibration of the model's empirical material constants. The model validity check and calibration is carried out for three effects, namely, high temperature, mechanical fatigue and creep.

Boyce, L.↗
NASA NTRS1990

Probabilistic modeling for simulation of aerodynamic uncertainties in propulsion systems

The numerical simulation of the probabilistic aerothermodynamic response of propulsion system components to randomness in their environment was explored. The reusable rocket engine turbopumps were selected as an example because of the severe cryogenic environment in which they operate. The thermal and combustion instabilities, coupled with the engine thrust requirements from start up to shut down, lead to randomness in the flow variables and uncertainties in the aerosynamic loading. The probabilistic modeling of the turbopumps' aerodynamic response was accomplished using the panel method coupled with fast probability integration methods. The aerodynamic response in the form of probabilistic rotor blades and splitter loading were predicted and the results presented for specified flow coefficient and rotor preswirl variance. Possible future applications of the aerothermodynamic probabilistic modeling in engine transient simulation, condition monitoring, and engine life prediction are briefly discussed.

Hamed, A.↗
NASA NTRS1991

Effect of chemical kinetics uncertainties on calculated constituents in a tropospheric photochemical model

Random photochemical reaction rates are employed in a 1D photochemical model to examine uncertainties in tropospheric concentrations and thereby determine critical kinetic processes and significant correlations. Monte Carlo computations are used to simulate different chemical environments and their related imprecisions. The most critical processes are the primary photodissociation of O3 (which initiates ozone destruction) and NO2 (which initiates ozone formation), and the OH/methane reaction is significant. Several correlations and anticorrelations between species are discussed, and the ozone/transient OH correlation is examined in detail. One important result of the modeling is that estimates of global OH are generally about 25 percent uncertain, limiting the precision of photochemical models. Techniques for reducing the imprecision are discussed which emphasize the use of species and radical species measurements.

Thompson, Anne M.↗