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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 181 records · Page 10

CASPEr: an Approach to Characterize the Performance of Onboard Airplane Energy State and Automation Mode Prediction Functions

The Commercial Aviation Safety Team (CAST) has identified a set of safety enhancements to mitigate the risks of loss of control in-flight (LOCI) accidents and incidents involving commercial transport airplanes. In support of this, NASA has been developing technologies intended to enhance flight crew awareness of airplane systems, attitude, and energy state. This report describes preliminary ideas for a methodology to assess the goodness of onboard airplane energy state and automation mode prediction functions. The methodology is intended to contribute to the goal of moving these prediction technologies to the readiness level required for transition to industry and reduce the technology certification risks. In addition, this report describes a simulation-based approach named CASPEr (Characterization of Airplane State Prediction Error) to characterize the performance of these predictive functions over a wide range of operational conditions. The first exploratory version of this approach is described. The bulk of the report documents the initial results of tests to characterize the performance of an airplane trajectory prediction function. Future reports will give additional performance characterization results for this function and a complete description of the proposed methodology to assess such functions.

Torres-Pomales, Wilfredo↗

Defects in silicon effect on device performance and relationship to crystal growth conditions

A relationship between material defects in silicon and the performance of electronic devices will be described. A role which oxygen and carbon in silicon play during the defects generation process will be discussed. The electronic properties of silicon are a strong function of the oxygen state in the silicon. This state controls mechanical properties of silicon efficiency for internal gettering and formation of defects in the device's active area. In addition, to temperature, time, ambience, and the cooling/heating rates of high temperature treatments, the oxygen state is a function of the crystal growth process. The incorporation of carbon and oxygen into silicon crystal is controlled by geometry and rotation rates applied to crystal and crucible during crystal growths. Also, formation of nucleation centers for oxygen precipitation is influenced by the growth process, although there is still a controversy which parameters play a major role. All these factors will be reviewed with special emphasis on areas which are still ambiguous and controversial.

Jastrzebski, L.↗

Adaptive Fuzzy Control of a Direct Drive Motor: Experimental Aspects

This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is experimentally verified. The real-time performance is compared with simulation results.

Medina, E.↗

Adaptive Fuzzy Control of a Direct Drive Motor

This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is verified by simulation results.

Medina, E.↗

Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculations

This paper discusses numerical aspects of computing maximum likelihood estimates for linear dynamical systems in state-vector form. Different gradient-based nonlinear programming methods are discussed in a unified framework and their applicability to maximum likelihood estimation is examined. The problems due to singular Hessian or singular information matrix that are common in practice are discussed in detail and methods for their solution are proposed. New results on the calculation of state sensitivity functions via reduced order models are given. Several methods for speeding convergence and reducing computation time are also discussed.

Gupta, N. K.↗

Architecture for robot intelligence

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Peters, II, Richard Alan↗

Apparatus for multiprocessor-based control of a multiagent robot

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Peters, II, Richard Alan↗

Architecture for Multiple Interacting Robot Intelligences

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a database associative memory (DBAM) that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Peters, Richard Alan, II↗

Application of dynamical systems theory to nonlinear aircraft dynamics

Dynamical systems theory has been used to study nonlinear aircraft dynamics. A six degree of freedom model that neglects gravity has been analyzed. The aerodynamic model, supplied by NASA, is for a generic swept wing fighter and includes nonlinearities as functions of the angle of attack. A continuation method was used to calculate the steady states of the aircraft, and bifurcations of these steady states, as functions of the control deflections. Bifurcations were used to predict jump phenomena and the onset of periodic motion for roll coupling instabilities and high angle of attack maneuvers. The predictions were verified with numerical simulations.

Culick, Fred E. C.↗

A viscoplastic model with application to LiF-22 percent CaF2 hypereutectic salt

A viscoplastic model for class M (metal-like behavior) materials is presented. One novel feature is its use of internal variables to change the stress exponent of creep (where n is approximately = 5) to that of natural creep (where n = 3), in accordance with experimental observations. Another feature is the introduction of a coupling in the evolution equations of the kinematic and isotropic internal variables, making thermal recovery of the kinematic variable implicit. These features enable the viscoplastic model to reduce to that of steady-state creep in closed form. In addition, the hardening parameters associated with the two internal state variables (one scalar-valued, the other tensor-valued) are considered to be functions of state, instead of being taken as constant-valued. This feature enables each internal variable to represent a much wider spectrum of internal states for the material. The model is applied to a LiF-22 percent CaF2 hypereutectic salt, which is being considered as a thermal energy storage material for space-based solar dynamic power systems.

Freed, A. D.↗

An efficient sampling technique for sums of bandpass functions

A well known sampling theorem states that a bandlimited function can be completely determined by its values at a uniformly placed set of points whose density is at least twice the highest frequency component of the function (Nyquist rate). A less familiar but important sampling theorem states that a bandlimited narrowband function can be completely determined by its values at a properly chosen, nonuniformly placed set of points whose density is at least twice the passband width. This allows for efficient digital demodulation of narrowband signals, which are common in sonar, radar and radio interferometry, without the side effect of signal group delay from an analog demodulator. This theorem was extended by developing a technique which allows a finite sum of bandlimited narrowband functions to be determined by its values at a properly chosen, nonuniformly placed set of points whose density can be made arbitrarily close to the sum of the passband widths.

Lawton, W. M.↗

Modeling and Simulation of Semiconductor Quantum Well Structures and Lasers

In this talk I will cover two aspects of modeling and simulation efforts at NASA Ames Research Center. In the quantum well structure simulation, we typically start from the quantum mechanical calculation of the quantum well structures for the confined/and unconfined eigen states and functions. A bandstructure calculation of the k*p type is then performed for the confined valence states. This information is then used to computer the optical gain and refractive index of the quantum well structures by solving the linearized multiband semiconductor Bloch equations with the many-body interactions included. In our laser simulation, we typically solve the envelope equations for the laser field in space-time domain, coupled with a reduced set of material equations using the microscopic calculation of the first step. Finally I will show some examples of both aspects of simulation and modeling.

Ning, Cun-Zheng↗

Determining Concentration of Nanoparticles from Ellipsometry

A method of using ellipsometry or polarization analysis of light in total internal reflection of a surface to determine the number density of gold nanoparticles on a smooth substrate has been developed. The method can be modified to enable determination of densities of sparse distributions of nanoparticles in general, and is expected to be especially useful for measuring gold-nanoparticle-labeled biomolecules on microarrays. The method is based on theoretical calculations of the ellipsometric responses of gold nanoparticles. Elements of the calculations include the following: For simplicity, the gold nanoparticles are assumed to be spherical and to have the same radius. The distribution of gold nanoparticles is assumed to be a sub-monolayer (that is, sparser than a monolayer). The optical response of the sub-monolayer is modeled by use of a thin-island-film theory, according to which the polarizabilities parallel and perpendicular to the substrate are functions of the wavelength of light, the dielectric functions (permittivities expressed as complex functions of frequency or wavelength) of the gold and the suspending medium (in this case, the suspending medium is air), the fraction of the substrate area covered by the nanoparticles, and the radius of the nanoparticles. For the purpose of the thin-island-film theory, the dielectric function of the gold nanoparticles is modeled as the known dielectric function of bulk gold plus a correction term that is necessitated by the fact that the mean free path length for electrons in gold decreases with decreasing radius, in such a manner as to cause the imaginary part of the dielectric function to increase with decreasing radius (see figure). The correction term is a function of the nanoparticle radius, the wavelength of light, the mean free path and the Fermi speed of electrons in bulk gold, the plasma frequency of gold, and the speed of light in a vacuum. These models are used to calculate ellipsometric responses for various concentrations of gold nanoparticles having an assumed radius. The modeled data indicates distinct spectral features for both the real and the imaginary part of the dielectric function. An ellipsometric measurement would determine this distinct feature and thus can be used to measure nanoparticle concentration. By "ellipsometric responses" is meant the intensities of light measured in various polarization states as functions of the angle of incidence and the polarization states of the incident light. These calculated ellipsometric responses are used as calibration curves: Data from subsequent ellipsometric measurements on real specimens are compared with the calibration curves. The concentration of the nanoparticles on a specimen is assumed to be that of the calibration curve that most closely matches the data pertaining to that specimen.

Venkatasubbarao, Srivatsa↗

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

Machine learning↗

Robust control design with real parameter uncertainty using absolute stability theory

The purpose of this thesis is to investigate an extension of mu theory for robust control design by considering systems with linear and nonlinear real parameter uncertainties. In the process, explicit connections are made between mixed mu and absolute stability theory. In particular, it is shown that the upper bounds for mixed mu are a generalization of results from absolute stability theory. Both state space and frequency domain criteria are developed for several nonlinearities and stability multipliers using the wealth of literature on absolute stability theory and the concepts of supply rates and storage functions. The state space conditions are expressed in terms of Riccati equations and parameter-dependent Lyapunov functions. For controller synthesis, these stability conditions are used to form an overbound of the H2 performance objective. A geometric interpretation of the equivalent frequency domain criteria in terms of off-axis circles clarifies the important role of the multiplier and shows that both the magnitude and phase of the uncertainty are considered. A numerical algorithm is developed to design robust controllers that minimize the bound on an H2 cost functional and satisfy an analysis test based on the Popov stability multiplier. The controller and multiplier coefficients are optimized simultaneously, which avoids the iteration and curve-fitting procedures required by the D-K procedure of mu synthesis. Several benchmark problems and experiments on the Middeck Active Control Experiment at M.I.T. demonstrate that these controllers achieve good robust performance and guaranteed stability bounds.

How, Jonathan P.↗

The use of the articulated total body model as a robot dynamics simulation tool

The Articulated Total Body (ATB) model is a computer sumulation program which was originally developed for the study of aircrew member dynamics during ejection from high-speed aircraft. This model is totally three-dimensional and is based on the rigid body dynamics of coupled systems which use Euler's equations of motion with constraint relations of the type employed in the Lagrange method. In this paper the use of the ATB model as a robot dynamics simulation tool is discussed and various simulations are demonstrated. For this purpose the ATB model has been modified to allow for the application of torques at the joints as functions of state variables of the system. Specifically, the motion of a robotic arm with six revolute articulations with joint torques prescribed as functions of angular displacement and angular velocity are demonstrated. The simulation procedures developed in this work may serve as valuable tools for analyzing robotic mechanisms, dynamic effects, joint load transmissions, feed-back control algorithms employed in the actuator control and end-effector trajectories.

Obergfell, Louise A.↗