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At least 91 records · Page 5

Mass balances for a biological life support system simulation model

Design decisions to aid the development of future space based biological life support systems (BLSS) can be made with simulation models. The biochemistry stoichiometry was developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady state system with wheat as the sole food source. The large scale dynamics of a materially closed (BLSS) computer model is described in a companion paper. An extension of this methodology can explore multifood systems and more complex biochemical dynamics while maintaining whole system closure as a focus.

Volk, Tyler

Cognitive engineering models in space systems

NASA space systems, including mission operations on the ground and in space, are complex, dynamic, predominantly automated systems in which the human operator is a supervisory controller. Models of cognitive functions in complex systems are needed to describe human performance and form the theoretical basis of operator workstation design, including displays, controls, and decision aids. Currently, there several candidate modeling methodologies. They include the Rasmussen abstraction/aggregation hierarchy and decision ladder, the goal-means network, the problem behavior graph, and the operator function model. The research conducted under the sponsorship of this grant focuses on the extension of the theoretical structure of the operator function model and its application to NASA Johnson mission operations and space station applications. The initial portion of this research consists of two parts. The first is a series of technical exchanges between NASA Johnson and Georgia Tech researchers. The purpose is to identify candidate applications for the current operator function model; prospects include mission operations and the Data Management System Testbed. The second portion will address extensions of the operator function model to tailor it to the specific needs of Johnson applications. At this point, we have accomplished two things. During a series of conversations with JSC researchers, we have defined the technical goal of the research supported by this grant to be the structural definition of the operator function model and its computer implementation, OFMspert. Both the OFM and OFMspert have matured to the point that they require infrastructure to facilitate use by researchers not involved in the evolution of the tools. The second accomplishment this year was the identification of the Payload Deployment and Retrieval System (PDRS) as a candidate system for the case study. In conjunction with government and contractor personnel in the Human-Computer Interaction Lab, the PDRS was identified as the most accessible system for the demonstration. Pursuant to this a PDRS simulation was obtained from the HCIL and an initial knowledge engineering effort was conducted to understand the operator's tasks in the PDRS application. The preliminary results of the knowledge engineering effort and an initial formulation of an operator function model (OFM) are contained in the appendices.

Mitchell, Christine M.

Spatial operator algebra for flexible multibody dynamics

This paper presents an approach to modeling the dynamics of flexible multibody systems such as flexible spacecraft and limber space robotic systems. A large number of degrees of freedom and complex dynamic interactions are typical in these systems. This paper uses spatial operators to develop efficient recursive algorithms for the dynamics of these systems. This approach very efficiently manages complexity by means of a hierarchy of mathematical operations.

Jain, A.

Cognitive engineering models in space systems

NASA space systems, including mission operations on the ground and in space, are complex, dynamic, predominantly automated systems in which the human operator is a supervisory controller. The human operator monitors and fine-tunes computer-based control systems and is responsible for ensuring safe and efficient system operation. In such systems, the potential consequences of human mistakes and errors may be very large, and low probability of such events is likely. Thus, models of cognitive functions in complex systems are needed to describe human performance and form the theoretical basis of operator workstation design, including displays, controls, and decision support aids. The operator function model represents normative operator behavior-expected operator activities given current system state. The extension of the theoretical structure of the operator function model and its application to NASA Johnson mission operations and space station applications is discussed.

Mitchell, Christine M.

ASCIE: An integrated experiment to study CSI in large segmented optical systems

A description of the advanced structures/control integrated experiment (ASCIE) experimental setup, a generic test bed for several essential technologies was presented. In particular its multi-input, multi-output, non-collocated control system and its complex structural dynamics, characteristic of large segmented systems make it an ideal test bed for Control-Structure Interaction (CSI) experiments. The high accuracy of its measurement system will make it possible to investigate the dynamics of microvibrations and its implication for the CSI phenomenon.

Aubrun, Jean-Noel

A Galerkin method for linear PDE systems in circular geometries with structural acoustic applications

A Galerkin method for systems of PDE's in circular geometries is presented with motivating problems being drawn from structural, acoustic, and structural acoustic applications. Depending upon the application under consideration, piecewise splines or Legendre polynomials are used when approximating the system dynamics with modifications included to incorporate the analytic solution decay near the coordinate singularity. This provides an efficient method which retains its accuracy throughout the circular domain without degradation at singularity. Because the problems under consideration are linear or weakly nonlinear with constant or piecewise constant coefficients, transform methods for the problems are not investigated. While the specific method is developed for the two dimensional wave equations on a circular domain and the equation of transverse motion for a thin circular plate, examples demonstrating the extension of the techniques to a fully coupled structural acoustic system are used to illustrate the flexibility of the method when approximating the dynamics of more complex systems.

Smith, Ralph C.

REDUCE 2: A computer program for the symbolic reduction of large block diagrams

REDUCE 2 is reported as a FORMAC program which symbolically calculates the transfer function(s) of any linear-block-diagram output variable to any or all input variables. The program requires as input a set of algebraic expressions representing the block diagram, the desired transfer function(s), and a string of variables indicating the desired order of reduction. The solution is presented in the compact form of a set of nested functions (super G's). The program can handle systems as large as 600 equations and is intended as a tool for the analysis of complex control and dynamic systems. A companion FORTRAN program, EVAL 2, which numerically evaluates the solution set to obtain amplitude ratio and phase angle as functions of frequency is also presented.

Lorenzo, C. F.

The complex coronal transient of 1980 March 23

The time evolution of the coronal transient of 1980 March 23 is described, which contains as substructures a dark loop and an area of depletion similar to those seen by Fisher, Garcia, and Seagraves. The mass ejection pushes aside preexisting streamers, giving rise to the characteristic dark area with bright flanks seen in difference images of depletion transients. Time-height plots for five identifiable features in the transient event are shown; these substructures have velocities interrelated in a way approximately consistent with the hypothesis of self-similar MHD propagation. This implies that the event as a whole may be a self-similar dynamical system, and that the substructure loops are not independent units. A scenario for the event is presented, in which it is considered as a large, complex system which evolves dynamically as a whole.

Illing, R. M. E.

Algorithm for Training a Recurrent Multilayer Perceptron

An improved algorithm has been devised for training a recurrent multilayer perceptron (RMLP) for optimal performance in predicting the behavior of a complex, dynamic, and noisy system multiple time steps into the future. [An RMLP is a computational neural network with self-feedback and cross-talk (both delayed by one time step) among neurons in hidden layers]. Like other neural-network-training algorithms, this algorithm adjusts network biases and synaptic-connection weights according to a gradient-descent rule. The distinguishing feature of this algorithm is a combination of global feedback (the use of predictions as well as the current output value in computing the gradient at each time step) and recursiveness. The recursive aspect of the algorithm lies in the inclusion of the gradient of predictions at each time step with respect to the predictions at the preceding time step; this recursion enables the RMLP to learn the dynamics. It has been conjectured that carrying the recursion to even earlier time steps would enable the RMLP to represent a noisier, more complex system.

Parlos, Alexander G.

A Theoretical Solid Oxide Fuel Cell Model for Systems Controls and Stability Design

As the aviation industry moves toward higher efficiency electrical power generation, all electric aircraft, or zero emissions and more quiet aircraft, fuel cells are sought as the technology that can deliver on these high expectations. The hybrid solid oxide fuel cell system combines the fuel cell with a micro-turbine to obtain up to 70% cycle efficiency, and then distributes the electrical power to the loads via a power distribution system. The challenge is to understand the dynamics of this complex multidiscipline system and the design distributed controls that take the system through its operating conditions in a stable and safe manner while maintaining the system performance. This particular system is a power generation and a distribution system, and the fuel cell and micro-turbine model fidelity should be compatible with the dynamics of the power distribution system in order to allow proper stability and distributed controls design. The novelty in this paper is that, first, the case is made why a high fidelity fuel cell mode is needed for systems control and stability designs. Second, a novel modeling approach is proposed for the fuel cell that will allow the fuel cell and the power system to be integrated and designed for stability, distributed controls, and other interface specifications. This investigation shows that for the fuel cell, the voltage characteristic should be modeled but in addition, conservation equation dynamics, ion diffusion, charge transfer kinetics, and the electron flow inherent impedance should also be included.

Kopasakis, George

Comprehensive Static and Dynamic Modeling of a Magnetic Suspension and Balance System

Magnetic Suspension and Balance Systems (MSBS) are inherently complex multi-degree-of-freedom dynamic systems. Comprehensive, high-fidelity dynamic models are increasingly important due to the application of model-based controllers as well as demands for unsteady aerodynamic data derived from post-test system identification. This paper reviews some aspects of the development of a dynamic model of the NASA/ODU 6-inch MSBS.

blunt body

Comprehensive Static and Dynamic Modeling of a Magnetic Suspension and Balance System

Magnetic Suspension and Balance Systems (MSBS) are inherently complex multi-degree-of-freedom dynamic systems. Comprehensive, high-fidelity dynamic models are increasingly important due to the application of model-based controllers as well as demands for unsteady aerodynamic data derived from post-test system identification. This paper reviews some aspects of the development of a dynamic model of the NASA/ODU 6-inch MSBS.

blunt body

Effects of Buoyancy on Laminar and Turbulent Premixed V-Flame

Turbulent combustion occurs naturally in almost all combustion systems and involves complex dynamic coupling of chemical and fluid mechanical processes. It is considered as one of the most challenging combustion research problems today. Though buoyancy has little effect on power generating systems operating under high pressures (e.g., IC engines and turbines), flames in atmospheric burners and the operation of small to medium furnaces and boilers are profoundly affected by buoyancy. Changes in burner orientation impacts on their blow-off, flash-back and extinction limits, and their range of operation, burning rate, heat transfer, and emissions. Theoretically, buoyancy is often neglected in turbulent combustion models. Yet the modeling results are routinely compared with experiments of open laboratory flames that are obviously affected by buoyancy. This inconsistency is an obstacle to reconciling experiments and theories. Consequently, a fundamental understanding of the coupling between turbulent flames and buoyancy is significant to both turbulent combustion science and applications. The overall effect of buoyancy relates to the dynamic interaction between the flame and its surrounding, i.e., the so-called elliptical problem. The overall flame shape, its flowfield, stability, and mean and local burning rates are dictated by both upstream and downstream boundary conditions. In steady propagating premixed flames, buoyancy affects the products region downstream of the flame zone. These effects are manifested upstream through the mean and fluctuating pressure fields to influence flame stretch and flame wrinkling. Intuitively, the effects buoyancy should diminish with increasing flow momentum. This is the justification for excluding buoyancy in turbulent combustion models that treats high Reynolds number flows. The objectives of our experimental research program is to elucidate flame-buoyancy coupling processes in laminar and turbulent premixed flames, and to characterize microgravity (micro g) premixed flames. The results are used to derive appropriate scaling parameters for guiding the development of theoretical models to include the effects of buoyancy. Knowledge gain from the analysis will also contribute to further understanding of the elliptical nature of premixed flames. Our current emphasis is to examine the momentum limit above which the effects of buoyancy would become insignificant. This is accomplished by comparing the flowfields and the mean properties of normal gravity flames (+g), and reversed gravity flames (-g, up-side-down flames) at different flow velocities and turbulence intensities. Microgravity (micro g) flames experiments provide the key reference data to reconcile the differences between flames in +g and -g. As flame configuration has significant impact on premixed flames characteristics we have studied axi-symmetric conical flames and plane-symmetric rod-stabilized v-flames. The two configurations produce distinct features that dictates how the flames couple with buoyancy. In a conical flame, the hot products plume completely envelopes the flame cone and shields the flame from direct interaction with the ambient air. The plume originates at the burner rim and generates a divergent flowfield. In comparison, the products region of v-flames forms between the twin flame sheets and it is convergent towards the center-plane. Interaction with ambient air is limited to the two end regions of the stabilized rod and beyond the flame sheets.

Cheng, Robert K.

Cyclic Symmetry Finite Element Forced Response Analysis of a Distortion-Tolerant Fan with Boundary Layer Ingestion

Accurate prediction of the blade vibration stress is required to determine overall durability of fan blade design under Boundary Layer Ingestion (BLI) distorted flow environments. Traditional single blade modeling technique is incapable of representing accurate modeling for the entire rotor blade system subject to complex dynamic loading behaviors and vibrations in distorted flow conditions. A particular objective of our work was to develop a high-fidelity full-rotor aeromechanics analysis capability for a system subjected to a distorted inlet flow by applying cyclic symmetry finite element modeling methodology. This reduction modeling method allows computationally very efficient analysis using a small periodic section of the full rotor blade system. Experimental testing by the use of the 8-foot by 6-foot Supersonic Wind Tunnel Test facility at NASA Glenn Research Center was also carried out for the system designated as the Boundary Layer Ingesting Inlet/Distortion-Tolerant Fan (BLI2DTF) technology development. The results obtained from the present numerical modeling technique were evaluated with those of the wind tunnel experimental test, toward establishing a computationally efficient aeromechanics analysis modeling tool facilitating for analyses of the full rotor blade systems subjected to a distorted inlet flow conditions. Fairly good correlations were achieved hence our computational modeling techniques were fully demonstrated. The analysis result showed that the safety margin requirement set in the BLI2DTF fan blade design provided a sufficient margin with respect to the operating speed range.

forced response analysis

Dynamic Assurance of Autonomous Systems through Ground Control Software

Assurance cases are being increasingly acknowledged as a way to build trust in complex systems with autonomous capabilities [1]. An assurance case is a comprehensive, defensible, and valid justification that a system will function as intended for the specific mission and operating environment. Such justifications for systems with autonomous capabilities are often based on various probabilistic quantifications [2]. Due to the dynamic nature of the environmental conditions in which these systems operate, as well as the changing nature of the autonomous systems themselves, these probabilistic quantifications cannot be simply estimated once during design time. Rather, they need to be continually evaluated during systems operations to ensure that the assurance case justifications are valid. We refer to the assurance case that combines both the static and dynamic elements as a Dynamic Assurance Case (DAC). Such complex systems with autonomous capabilities are often deployed with a Ground Control Software (GCS) component to enable remote operation. Whether the system is composed of a single unit or a fleet of units, deployed distributed or in remote environments, GCS acts as a window into the behavior of the deployed system. It receives telemetry from the system, issues commands to the system and provides various functionalities to visualize the system performance. We propose a dynamic assurance framework where the GCS acts as a relay between the autonomous system and its DAC. GCS can be used to measure both unit-specific as well as system-wide probabilistic quantifications using the incoming telemetry. We embed these quantifications throughout the DAC as variables that can be updated by external sources. We use the GCS to periodically update these variables, which allows us to continually evaluate the formally defined assurance case justifications. We demonstrate our dynamic assurance framework in the NASA Ames project Troupe1 that aims at developing a fleet of rovers capable of au- tonomously mapping their environment. The rovers work cooperatively, each collecting data for different parts of the environment. Each rover runs an identical core Flight System (cFS) [4] application. Troupe1 uses OpenC3 Cosmos [5] as the ground system, and AdvoCATE [3] to capture the system DAC. We show how we can measure both rover-specific and system-wide quantifications in Cosmos using its Ruby scripting editor and pass them into the DAC modelled in AdvoCATE. Then, we show how these incoming variables can be embedded in different parts of the DAC and how effects of their updates can be observed

Irfan Sljivo

Experimental Testing of Advanced Generalized Predictive Control for Stability Augmentation and Vibration Reduction of Tiltrotor Aircraft

Generalized Predictive Control (GPC) is an advanced form of an adaptive control algorithm that uses experimentally acquired data to determine the input-output relationship of complex systems through a process called system identification (system ID). GPC has historically been applied to wind tunnel tests of dynamically-scaled tiltrotor aircraft for stability augmentation and vibration reduction since the complex nature of these dynamic systems does not lend itself well to traditional control theory. Advanced GPC (AGPC) improves upon traditional GPC by enabling self-adaptation as conditions change from those used to acquire the system ID and controller performance would normally erode. The present research expands upon previous analytical development and demonstration of AGPC with experimental demonstration. To support AGPC, this present work also identifies and describes figures of merit that define a good working controller and quantifies the uniqueness of the control inputs and quality of the system ID parameters. The present research demonstrates that AGPC consistently performs better than traditional GPC and can successfully adapt to changing conditions.

Active Controls

Experimental Testing of Advanced Generalized Predictive Control for Stability Augmentation and Vibration Reduction of Tiltrotor Aircraft

Generalized Predictive Control (GPC) is an advanced form of an adaptive control algorithm that uses experimentally acquired data to determine the input-output relationship of complex systems through a process called system identification (system ID). GPC has historically been applied to wind tunnel tests of dynamically-scaled tiltrotor aircraft for stability augmentation and vibration reduction since the complex nature of these dynamic systems does not lend itself well to traditional control theory. Advanced GPC (AGPC) improves upon traditional GPC by enabling self-adaptation as conditions change from those used to acquire the system ID and controller performance would normally erode. The present research expands upon previous analytical development and demonstration of AGPC with experimental demonstration. To support AGPC, this present work also identifies and describes figures of merit that define a good working controller and quantifies the uniqueness of the control inputs and quality of the system ID parameters. The present research demonstrates that AGPC consistently performs better than traditional GPC and can successfully adapt to changing conditions.

Active Controls

A unified process for systems identification based on performance assessment

Many modern spacecraft are complex multi-body dynamic systems where the bodies are connected by several active control systems for pointing and isolation. Mission requirements indicate that many structural modes and possibly some nonlinear effects will require characterization. Thus, even characterization at the subsystem level will become more difficult than usual. System level characterization difficulties will be compounded by the fact that only limited ground testing will be possible on the full up system, and flight testing will be restricted by an extremely limited measurements set. The object of the present discussion is the application of matrix majorant theory to the problem of assessing dynamic system performance when knowledge of the system is uncertain. We show how majorants provide an effective tool to relate required performance output to system identification test quality in terms of residual uncertainty in input-output relations, parameter values, nonlinearities, and interactions. The underlying machinery consists of the block-norm matrix which is a nonnegative matrix each of whose elements is the norm of a block of a suitably partitioned matrix. A matrix which bounds the block-norm matrix in the sense of nonnegative matrices, i.e., element by element is known as a majorant.

Hyland, C.