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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Experiences with Probabilistic Analysis Applied to Controlled Systems

This paper presents a semi-analytic method for computing frequency dependent means, variances, and failure probabilities for arbitrarily large-order closed-loop dynamical systems possessing a single uncertain parameter or with multiple highly correlated uncertain parameters. The approach will be shown to not suffer from the same computational challenges associated with computing failure probabilities using conventional FORM/SORM techniques. The approach is demonstrated by computing the probabilistic frequency domain performance of an optimal feed-forward disturbance rejection scheme.

Kenny, Sean P.↗
NASA NTRS2016

Performance of International Space Station Alpha Trace Contaminant Control Systems

The analysis presented herein was conducted during the early transitional period between the Space Station Freedom and the International Space Station programs as part of an effort to evaluate key design specifications and standards used by the United States and Russia. The analysis was originally documented under NASA cover letter ED62(36-94) dated August 16, 1994. The analysis was revised and rereleased under NASA cover letter ED62(51-94) dated November 14, 1994. These cover letters are provided here to guide programmatic context for the reader.

Perry, J. L.↗
NASA NTRS2018

Electrolyzer Exergy Analysis for an Environmental Control and Life Support System

An exergy based analysis of the Environmental Control and Life Support System (ECLSS) aboard the International Space Station (ISS) is conducted to assess its overall performance. Exergy is chosen as a measure of performance because it accounts for both the first and second laws of thermodynamics. The exergy efficiency of a system is first defined as the total exergy destroyed by the system relative to the total exergy input to the system. To determine the ECLSS exergy efficiency, the system is divided into constituent subsystems which in turn are divided into assemblies and components. Based on this system decomposition, exergy balances are derived for each assembly or component. Exergy balances and supporting calculations are implemented in MATLAB® code. The major subsystems of the ECLSS considered in this analysis include the Atmosphere Revitalization Subsystem (ARS), Atmosphere Control and Supply Subsystem (ACS), Temperature and Humidity Control Subsystem (THC), Water Recovery and Management Subsystem (WRM), and Waste Management Subsystem (WM). This paper focuses on the ARS and its constituent assemblies and components. Exergy efficiency of the ARS and its constituent assemblies and components is first presented. The Oxygen Generation Assembly (OGA), an assembly within the ARS, is then highlighted because the exergy destruction by the OGA is a large magnitude contributor to the overall exergy destruction of the ECLSS. The OGA produces oxygen to meet the crew's metabolic demand via water electrolysis in a proton exchange membrane (PEM) electrolyzer. The exergy destruction of the OGA's PEM electrolyzer is a function of the amount of oxygen produced, which determines the necessary current density and voltage drop across the PEM electrolyzer. In addition, oxygen production in the PEM electrolyzer requires deviation from the Nernst potential, presenting trade-offs between the exergy efficiency and critical life support functions. The results of parametric studies of PEM electrolyzer performance are presented with an emphasis on the impacts of polarization and operational conditions on exergy efficiency.

Chow, Raymond↗
NASA NTRS1984

A frequency domain stability analysis of a phase plane control system

A describing function is used to model a phase plane controller which is part of the Space Shuttle on-orbit Reaction Control System autopilot. A frequency domain stability analysis of the closed-loop control system is applied to a study of potential flight control system interaction with the Orbiter and a class of payloads deployed from a tilt table. Phase-gain plot techniques are used to show that expansion of phase plane angular rate limits and stiffening of the tilt table pivot do not always enhance system stability. Instability region approximations are mapped as a function of rate limit, payload geometry, jet used, and natural frequency of the pivot. Comparison of the describing function analysis with simulation results shows excellent correlation.

Hattis, P. D.↗
NASA NTRS1986

Nonlinear system controller design based on domain of attaction: An application to CELSS analysis and control

Nonlinear system controller design based on the domain of attraction is presented. This is particularly suited to investigating Closed Ecological Life Support Systems (CELSS) models. In particular, the dynamic consequences of changes in the waste storage capacity and system mass, and how information is used for control in CELSS models are examined. The models' high dimensionality and nonlinear state equations make them difficult to analyze by any other technique. The domain of attraction is the region in initial conditions that tend toward an attractor and it is delineated by randomly selecting initial conditions from the region of state space being investigated. Error analysis is done by repeating the domain simulations with independent samples. A refinement of this region is the domain of performance which is the region of initial conditions meeting a performance criteria. In nonlinear systems, local stability does not insure stability over a larger region. The domain of attraction marks out this stability region; hence, it can be considered a measure of a nonlinear system's ability to recovery from state perturbations. Considering random perturbations, the minimum radius of the domain is a measure of the magnitude of perturbations for which recovery is guaranteed. Design of both linear and nonlinear controllers are shown. Three CELSS models, with 9 to 30 state variable, are presented. Measures of the domain of attraction are used to show the global behavior of these models under a variety of design and controller scenarios.

Babcock, P. S., IV↗
NASA NTRS1987

Independent Orbiter Assessment (IOA): Analysis of the reaction control system, volume 2

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results for the Reaction Control System (RCS). The RCS is situated in three independent modules, one forward in the orbiter nose and one in each OMS/RCS pod. Each RCS module consists of the following subsystems: Helium Pressurization Subsystem; Propellant Storage and Distribution Subsystem; Thruster Subsystem; and Electrical Power Distribution and Control Subsystem. Volume 2 continues the presentation of IOA analysis worksheets.

Burkemper, V. J.↗
NASA NTRS1987

Independent Orbiter Assessment (IOA): Analysis of the reaction control system, volume 3

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results for the Reaction Control System (RCS). The RCS is situated in three independent modules, one forward in the orbiter nose and one in each OMS/RCS pod. Each RCS module consists of the following subsystems: Helium Pressurization Subsystem; Propellant Storage and Distribution Subsystem; Thruster Subsystem; and Electrical Power Distribution and Control Subsystem. Volume 3 continues the presentation of IOA analysis worksheets and the potential critical items list.

Burkemper, V. J.↗
NASA NTRS1994

Microgravity isolation system design: A modern control analysis framework

Many acceleration-sensitive, microgravity science experiments will require active vibration isolation from the manned orbiters on which they will be mounted. The isolation problem, especially in the case of a tethered payload, is a complex three-dimensional one that is best suited to modern-control design methods. These methods, although more powerful than their classical counterparts, can nonetheless go only so far in meeting the design requirements for practical systems. Once a tentative controller design is available, it must still be evaluated to determine whether or not it is fully acceptable, and to compare it with other possible design candidates. Realistically, such evaluation will be an inherent part of a necessary iterative design process. In this paper, an approach is presented for applying complex mu-analysis methods to a closed-loop vibration isolation system (experiment plus controller). An analysis framework is presented for evaluating nominal stability, nominal performance, robust stability, and robust performance of active microgravity isolation systems, with emphasis on the effective use of mu-analysis methods.

Hampton, R. D.↗
NASA NTRS1987

Independent Orbiter Assessment (IOA): Analysis of the reaction control system, volume 1

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results for the Reaction Control System (RCS). The purpose of the RCS is to provide thrust in and about the X, Y, Z axes for External Tank (ET) separation; orbit insertion maneuvers; orbit translation maneuvers; on-orbit attitude control; rendezvous; proximity operations (payload deploy and capture); deorbit maneuvers; and abort attitude control. The RCS is situated in three independent modules, one forward in the orbiter nose and one in each OMS/RCS pod. Each RCS module consists of the following subsystems: Helium Pressurization Subsystem; Propellant Storage and Distribution Subsystem; Thruster Subsystem; and Electrical Power Distribution and Control Subsystem. Of the failure modes analyzed, 307 could potentially result in a loss of life and/or loss of vehicle.

Burkemper, V. J.↗
NASA NTRS2005

A unifying framework for systems modeling, control systems design, and system operation

Current engineering practice in the analysis and design of large-scale multi-disciplinary control systems is typified by some form of decomposition- whether functional or physical or discipline-based-that enables multiple teams to work in parallel and in relative isolation. Too often, the resulting system after integration is an awkward marriage of different control and data mechanisms with poor end-to-end accountability. System of systems engineering, which faces this problem on a large scale, cries out for a unifying framework to guide analysis, design, and operation. This paper describes such a framework based on a state-, model-, and goal-based architecture for semi-autonomous control systems that guides analysis and modeling, shapes control system software design, and directly specifies operational intent. This paper illustrates the key concepts in the context of a large-scale, concurrent, globally distributed system of systems: NASA's proposed Array-based Deep Space Network.

systems modeling↗
NASA NTRS2007

Laboratory Reproduction and Failure Analysis of Cracked Orbiter Reaction Control System Niobium Thruster Injectors

A viewgraph presentation describing cracks and failure analysis of an orbiter reaction control system is shown. The topics include: 1) Endeavour STS-113 Landing; 2) RCS Thruster; 3) Thruster Cross-Section; 4) RCS Injector; 5) RCS Thruster, S/N 120l 6) Counterbore Cracks; 7) Relief Radius Cracks; 8) RCS Thruster Cracking History; 9) Thruster Manufacturing Timelines; 10) Laboratory Reproduction of Injector Cracking; 11) The Brownfield Specimen; 12) HF EtchantTests/Specimen Loading; 13) Specimen #3 HF + 600F; 14) Specimen #3 IG Fracture; 15) Specimen #5 HF + 600F; 16) Specimen #5 Popcorn ; 17) Specimen #5 Cleaned and Bent; 18) HF Exposure Test Matrix; 19) Krytox143AC Tests; 20) KrytoxTests/Specimen Loading; 21) Specimen #13 Krytox + 600F; and 22) KrytoxExposure Test Matrix.

Jacobs, Jeremy B.↗
NASA NTRS2015

Robust Stability Analysis of the Space Launch System Control Design: A Singular Value Approach

Classical stability analysis consists of breaking the feedback loops one at a time and determining separately how much gain or phase variations would destabilize the stable nominal feedback system. For typical launch vehicle control design, classical control techniques are generally employed. In addition to stability margins, frequency domain Monte Carlo methods are used to evaluate the robustness of the design. However, such techniques were developed for Single-Input-Single-Output (SISO) systems and do not take into consideration the off-diagonal terms in the transfer function matrix of Multi-Input-Multi-Output (MIMO) systems. Robust stability analysis techniques such as H(sub infinity) and mu are applicable to MIMO systems but have not been adopted as standard practices within the launch vehicle controls community. This paper took advantage of a simple singular-value-based MIMO stability margin evaluation method based on work done by Mukhopadhyay and Newsom and applied it to the SLS high-fidelity dynamics model. The method computes a simultaneous multi-loop gain and phase margin that could be related back to classical margins. The results presented in this paper suggest that for the SLS system, traditional SISO stability margins are similar to the MIMO margins. This additional level of verification provides confidence in the robustness of the control design.

Pei, Jing↗
NASA NTRS2011

Design of Launch Vehicle Flight Control Systems Using Ascent Vehicle Stability Analysis Tool

A launch vehicle represents a complicated flex-body structural environment for flight control system design. The Ascent-vehicle Stability Analysis Tool (ASAT) is developed to address the complicity in design and analysis of a launch vehicle. The design objective for the flight control system of a launch vehicle is to best follow guidance commands while robustly maintaining system stability. A constrained optimization approach takes the advantage of modern computational control techniques to simultaneously design multiple control systems in compliance with required design specs. "Tower Clearance" and "Load Relief" designs have been achieved for liftoff and max dynamic pressure flight regions, respectively, in the presence of large wind disturbances. The robustness of the flight control system designs has been verified in the frequency domain Monte Carlo analysis using ASAT.

Jang, Jiann-Woei↗