On the analysis of linear and nonlinear dynamical systems from transient-response data
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Shinbrot, Marvin↗
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Cognitive engineering models: A prerequisite to the design of human-computer interaction in complex dynamic systems
This chapter examines a class of human-computer interaction applications, specifically the design of human-computer interaction for the operators of complex systems. Such systems include space systems (e.g., manned systems such as the Shuttle or space station, and unmanned systems such as NASA scientific satellites), aviation systems (e.g., the flight deck of 'glass cockpit' airplanes or air traffic control) and industrial systems (e.g., power plants, telephone networks, and sophisticated, e.g., 'lights out,' manufacturing facilities). The main body of human-computer interaction (HCI) research complements but does not directly address the primary issues involved in human-computer interaction design for operators of complex systems. Interfaces to complex systems are somewhat special. The 'user' in such systems - i.e., the human operator responsible for safe and effective system operation - is highly skilled, someone who in human-machine systems engineering is sometimes characterized as 'well trained, well motivated'. The 'job' or task context is paramount and, thus, human-computer interaction is subordinate to human job interaction. The design of human interaction with complex systems, i.e., the design of human job interaction, is sometimes called cognitive engineering.
Mitchell, Christine M.↗
Earth system dynamics: The interrelation of atmospheric, ocean and solid earth dynamics
The research work performed during the time period 16 Oct. 1992 through 31 Dec. 1993 is summarized. The overall research activity, including a list of the major findings of the EOS IDS research to date, is described, the publications and presentations are listed, and a budget request for the subsequent year is attached. Specifically, the report covers: EOS panel activities; major findings of research; team member contributions; new research directions; EOS restructuring effect; changes in requirements; plans for using existing data; collaborations with other EOS and non-EOS investigations; EOS instrument team interaction; instrument development verification and validation; interaction with EOSDIS and DAAC's; team coordination; overall management; summary of response to site review questions and comments; science computing facility; and additional new research activities.
Tapley, Byron D.↗
Hidden Markov models and neural networks for fault detection in dynamic systems
Neural networks plus hidden Markov models (HMM) can provide excellent detection and false alarm rate performance in fault detection applications, as shown in this viewgraph presentation. Modified models allow for novelty detection. Key contributions of neural network models are: (1) excellent nonparametric discrimination capability; (2) a good estimator of posterior state probabilities, even in high dimensions, and thus can be embedded within overall probabilistic model (HMM); and (3) simple to implement compared to other nonparametric models. Neural network/HMM monitoring model is currently being integrated with the new Deep Space Network (DSN) antenna controller software and will be on-line monitoring a new DSN 34-m antenna (DSS-24) by July, 1994.
Smyth, Padhraic↗
Hidden Markov models for fault detection in dynamic systems
The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.
Smyth, Padhraic J.↗
Orbital Injection of the SEDSAT Satellite: Tethered Systems Dynamics and Flight Data Analysis
This report deals with the following topics which are all related to the orbital injection of the SEDSAT satellite: Dynamics and Stability of Tether Oscillations after the First Cut. The dynamics of the tether after the first cut (i.e., without the Shuttle attached to it) is investigated. The tether oscillations with the free end are analyzed in order to assess the stability of the rectilinear configuration in between the two tether cuts; analysis of Unstable Modes. The unstable modes that appear for high libration angles are further investigated in order to determine their occurrences and the possible transition from bound librations to rotations; Orbital Release Strategies for SEDSAT. A parametric analysis of the orbital decay rate of the SEDSAT satellite after the two tether cuts has been carried out as a function of the following free parameters: libration amplitude at the end of deployment, deviation angle from LV at the first cut, and orbital anomaly at the second cut. The values of these parameters that provide a minimum orbital decay rate of the satellite (after the two cuts) have been computed; and Dynamics and Control of SEDSAT. The deployment control law has been modified to cope with the new ejection velocity of the satellite from the Shuttle cargo bay. New reference profiles have been derived as well as new control parameters. Timing errors at the satellite release as a function of the variations of the initial conditions and the tension model parameters have been estimated for the modified control law.
Lorenzini, Enrico C.↗
Assimilation of Altimeter Data into a Quasigeostrophic Model of the Gulf Stream System: Dynamical Considerations - Part 1
The dynamical consequences of constraining a numerical model with sea surface height data have been investigated. The model used for this study is a quasigeostrophic model of the Gulf Stream region. The data that have been assimilated are maps of sea surface height obtained as the superposition of sea surface height variability deduced from the Geosat altimeter measurements and a mean field constructed from historical hydrographic data. The method used for assimilating the data is the nudging technique. Nudging has been implemented in such a way as to achieve a high degree of convergence of the surface model fields toward the observations. The assimilation of the surface data is thus equivalent to the prescription of a surface pressure boundary condition. The authors analyzed the mechanisms of the model adjustment and the characteristics of the resultant equilibrium state when the surface data are assimilated. Since the surface data are the superposition of a mean component and an eddy component, in order to understand the relative role of these two components in determining the characteristics of the final equilibrium state, two different experiments have been considered: in the first experiment only the climatological mean field is assimilated, while in the second experiment the total surface streamfunction field (mean plus eddies) has been used. It is shown that the model behavior in the presence of the surface data constraint can be conveniently described in terms of baroclinic Fofonoff modes. The prescribed mean component of the surface data acts as a 'surface topography' in this problem. Its presence determines a distortion of the geostrophic contours in the subsurface layers, thus constraining the mean circulation in those layers. The intensity of the mean flow is determined by the inflow/outflow conditions at the open boundaries, as well as by eddy forcing and dissipation.
Capotondi, Antonietta↗
Dynamical System Analysis of Reynolds Stress Closure Equations
In this paper, we establish the causality between the model coefficients in the standard pressure-strain correlation model and the predicted equilibrium states for homogeneous turbulence. We accomplish this by performing a comprehensive fixed point analysis of the modeled Reynolds stress and dissipation rate equations. The results from this analysis will be very useful for developing improved pressure-strain correlation models to yield observed equilibrium behavior.
Girimaji, Sharath S.↗
Toward Failure Modeling In Complex Dynamic Systems: Impact of Design and Manufacturing Variations
When designing vehicle vibration monitoring systems for aerospace devices, it is common to use well-established models of vibration features to determine whether failures or defects exist. Most of the algorithms used for failure detection rely on these models to detect significant changes during a flight environment. In actual practice, however, most vehicle vibration monitoring systems are corrupted by high rates of false alarms and missed detections. Research conducted at the NASA Ames Research Center has determined that a major reason for the high rates of false alarms and missed detections is the numerous sources of statistical variations that are not taken into account in the. modeling assumptions. In this paper, we address one such source of variations, namely, those caused during the design and manufacturing of rotating machinery components that make up aerospace systems. We present a novel way of modeling the vibration response by including design variations via probabilistic methods. The results demonstrate initial feasibility of the method, showing great promise in developing a general methodology for designing more accurate aerospace vehicle vibration monitoring systems.
Tumer, Irem Y.↗
Melt Redistribution in Dynamic Systems: Applications to Core Formation
Samples of olivine + Fe-S were fabricated by hot-pressing a mechanical mixture of the two phases. Olivine powders with a starting grain size of approx. 10 microns were prepared by crushing crystals of San Carlos olivine followed by pulverization in a fluid energy mill. Iron sulfide powder with a particle size of approx. 5 microns was prepared from a 2:1 mixture of reagent grade iron sulfide (FeS) plus iron. Rods 20 mm in length by 10 mm in diameter were cold-pressed into iron capsules with a uniaxial stress of approx. 200 MPa. These rods were then hot-pressed at 1523 K and 300 MPa for 4 h to obtain a starting material with <2% porosity. Samples for shear experiments were cut perpendicular to the long axis of these rods. The discs were shaped into ellipses approx. 6 mm by approx. 8 mm with a thickness ranging from 0.6 to 1.0 mm. An iron foil strain marker was inserted into a cut made along the minor axis. The sample was placed between two thoriated tungsten pistons cut at 45 deg to the long axis and then placed into an iron sleeve capped by alumina discs. The sample was then sheared in a gas pressure-medium apparatus at a temperature of 1523 K and a confining pressure of 300 MPa.
Hustoft, J. W.↗
What Sensing Tells Us: Towards a Formal Theory of Testing for Dynamical Systems
Just as actions can have indirect effects on the state of the world, so too can sensing actions have indirect effects on an agent's state of knowledge. In this paper, we investigate "what sensing actions tell us", i.e., what an agent comes to know indirectly from the outcome of a sensing action, given knowledge of its actions and state constraints that hold in the world. To this end, we propose a formalization of the notion of testing within a dialect of the situation calculus that includes knowledge and sensing actions. Realizing this formalization requires addressing the ramification problem for sensing actions. We formalize simple tests as sensing actions. Complex tests are expressed in the logic programming language Golog. We examine what it means to perform a test, and how the outcome of a test affects an agent's state of knowledge. Finally, we propose automated reasoning techniques for test generation and complex-test verification, under certain restrictions. The work presented in this paper is relevant to a number of application domains including diagnostic problem solving, natural language understanding, plan recognition, and active vision.
McIlraith, Sheila↗
Stirling Engine Dynamic System Modeling
The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.
Nakis, Christopher G.↗
Evaluation of a Stirling Solar Dynamic System for Lunar Oxygen Production
An evaluation of a solar concentrator-based system for producing oxygen from the lunar regolith was performed. The system utilizes a solar concentrator mirror to provide thermal energy for the oxygen production process as well as thermal energy to power a Stirling heat engine for the production of electricity. The electricity produced is utilized to operate the equipment needed in the oxygen production process. The oxygen production method utilized in the analysis was the hydrogen reduction of ilmenite. Utilizing this method of oxygen production a baseline system design was produced. This baseline system had an oxygen production rate of 0.6 kg/hr with a concentrator mirror size of 5 m. Variations were performed on the baseline design to show how changes in the system size and process rate effected the oxygen production rate.
Colozza, Anthony J.↗
JPL standard for spacecraft system dynamic and static testing
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dynamic static testing spacecraft testing↗
Temporal Variation of the Geopotential: Insights into Earth System Dynamics on Regional and Global Scales
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interfacial stresses Earth fluid solid region grav↗
Synthesis of Optimal Nonlinear Feedback Laws for Dynamic Systems Using Neural Networks
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Neural Networks↗
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.↗