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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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NASA NTRS1983

Design, implementation and flight testing of PIF autopilots for general aviation aircraft

The designs of Proportional-Integrated-Filter (PIF) auto-pilots for a General Aviation (NAVION) aircraft are presented. The PIF autopilot uses the sampled-data regulator and command generator tracking to determine roll select, pitch select, heading select, altitude select and localizer/glideslope capture and hold autopilot modes. The PIF control law uses typical General Aviation sensors for state feedback, command error integration for command tracking, digital complementary filtering and analog prefiltering for sensor noise suppression, a control filter for computation delay accommodation and the incremental form to eliminate trim values in implementation. Theoretical developments described in detail, were needed to combine the sampled-data regulator with command generator tracking for use as a digital flight control system. The digital PIF autopilots are evaluated using closed-loop eigenvalues and linear simulations. The implementation of the PIF autopilots in a digital flight computer using a high order language (FORTRAN) is briefly described. The successful flight test results for each PIF autopilot mode is presented.

Broussard, J. R.↗
NASA NTRS1983

PIFCGT: A PIF autopilot design program for general aviation aircraft

This report documents the PIFCGT computer program. In FORTRAN, PIFCGT is a computer design aid for determing Proportional-Integral-Filter (PIF) control laws for aircraft autopilots implemented with a Command Generator Tracker (CGT). The program uses Linear-Quadratic-Regulator synthesis algorithms to determine feedback gains, and includes software to solve the feedforward matrix equation which is useful in determining the command generator tracker feedforward gains. The program accepts aerodynamic stability derivatives and computes the corresponding aerodynamic linear model. The nine autopilot modes that can be designed include four maneuver modes (ROLL SEL, PITCH SEL, HDG SEL, ALT SEL), four final approach models (APR GS, APR LOCI, APR LOCR, APR LOCP), and a BETA HOLD mode. The program has been compiled and executed on a CDC computer.

Broussard, J. R.↗
NASA NTRS1982

Design and flight testing of a digital optimal control general aviation autopilot

This paper presents the designs of Proportional-Integral-Filter (PIF) autopilots for a General Aviation (NAVION) aircraft. The PIF autopilots use modern control theory to determine heading select and altitude select and hold autopilot modes. The PIF control law uses typical General Aviation sensors for state feedback; command error integration for command tracking; digital complimentary filtering and analog prefiltering for sensor noise suppression; a control filter for computation delay accommodation; and the incremental form to eliminate trim values in implementation. Theoretical developments for the control law are described which combine the sampled-data regulator with command generator tracking for use as a digital flight control system. The digital PIF autopilots are evaluated using closed-loop eigenvalues and simulations. Successful flight test results for the PIF autopilots are presented for different turbulence conditions and quadratic weights.

Broussard, J. R.↗
NASA NTRS2011

USM3D Simulations of Saturn V Plume Induced Flow Separation

The NASA Constellation Program included the Ares V heavy lift cargo vehicle. During the design stage, engineers questioned if the Plume Induced Flow Separation (PIFS) that occurred along Saturn V rocket during moon missions at some flight conditions, would also plague the newly proposed rocket. Computational fluid dynamics (CFD) was offered as a tool for initiating the investigation of PIFS along the Ares V rocket. However, CFD best practice guidelines were not available for such an investigation. In an effort to establish a CFD process and define guidelines for Ares V powered simulations, the Saturn V vehicle was used because PIFS flight data existed. The ideal gas, computational flow solver USM3D was evaluated for its viability in computing PIFS along the Saturn V vehicle with F-1 engines firing. Solutions were computed at supersonic freestream conditions, zero degree angle of attack, zero degree sideslip, and at flight Reynolds numbers. The effects of solution sensitivity to grid refinement, turbulence models, and the engine boundary conditions on the predicted PIFS distance along the Saturn V were discussed and compared to flight data from the Apollo 11 mission AS-506.

Deere, Karen↗
NASA NTRS2003

Scoping Planning Agents With Shared Models

In this paper we provide a formal framework to define the scope of planning agents based on a single declarative model. Having multiple agents sharing a single model provides numerous advantages that lead to reduced development costs and increase reliability of the system. We formally define planning in terms of extensions of an initial partial plan, and a set of flaws that make the plan unacceptable. A Flaw Filter (FF) allows us to identify those flaws relevant to an agent. Flaw filters motivate the Plan Identification Function (PIF), which specifies when an agent is is ready hand control to another agent for further work. PIFs define a set of plan extensions that can be generated from a model and a plan request. FFs and PIFs can be used to define the scope of agents without changing the model. We describe an implementation of PIFsand FFswithin the context of EUROPA, a constraint-based planning architecture, and show how it can be used to easily design many different agents.

Bedrax-Weiss, Tania↗
NASA NTRS1988

Analysis of Pioneer Venus Orbiter ultraviolet spectrometer Lyman alpha data from near the subsolar region

Pioneer Venus Orbiter ultraviolet spectrometer data from 20 orbits which span 3 years have been analyzed to determine the atomic hydrogen number density and vertical flux at the exobase as a function of solar zenith angle, F(10.7) index, and spacecraft latitude. From 1979 through 1981, the exobase number density n(c) and flux phi(c) are remarkably constant at n(c) = 6.0 + or - 1.5 x 10 to the 4th/cu cm and phi(e) = 7.5 + or - 1.5 x 10 to the 7th/sq cm per s in the subsolar region. The integrated vertical column density above 110 km is 3.6 + or - 1 x 10 to the 13th/sq cm. An empirical relationship is determined between the line center solar flux at H Lyman alpha, piF(0), and the F(10.7) index.

Paxton, L. J.↗
NASA NTRS2000

Inception of Snapover and Gas Induced Glow Discharges

Ground based experiments of the snapover phenomenon were conducted in the large vertical simulation chamber at the Glenn Research Center (GRC) Plasma Interaction Facility (PIF). Two Penning sources provided both argon and xenon plasmas for the experiments. The sources were used to simulate a variety of ionospheric densities pertaining to a spacecraft in a Low Earth Orbital (LEO) environment. Secondary electron emission is believed responsible for dielectric surface charging, and all subsequent snapover phenomena observed. Voltage sweeps of conductor potentials versus collected current were recorded in order to examine the specific charging history of each sample. The average time constant for sample charging was estimated between 25 and 50 seconds for all samples. It appears that current drops off by approximately a factor of 3 over the charging time of the sample. All samples charged in the forward and reverse bias directions, demonstrated hysteresis. Current jumps were only observed in the forward or positive swept voltage direction. There is large dispersion in tile critical snapover potential when repeating sweeps on any one sample. The current ratio for the first snapover region jumps between 2 and 4.6 times, with a standard deviation less than 1.6. Two of the samples showed even larger current ratios. It is believed the second large snapover region is due to sample outgassing. Under certain preset conditions, namely at the higher neutral gas background pressures, a perceptible blue-green glow was observed around the conductor. The glow is believed to be a result of secondary electrons undergoing collisions with an expelled tenuous cloud of gas, that is outgassed from the sample. Spectroscopic measurements of the glow discharge were made in an attempt to identify specific lines contributing to the observed glow.

Galofaro, J. T.↗
NASA NTRS2003

Identifying Executable Plans

Generating plans for execution imposes a different set of requirements on the planning process than those imposed by planning alone. In highly unpredictable execution environments, a fully-grounded plan may become inconsistent frequently when the world fails to behave as expected. Intelligent execution permits making decisions when the most up-to-date information is available, ensuring fewer failures. Planning should acknowledge the capabilities of the execution system, both to ensure robust execution in the face of uncertainty, which also relieves the planner of the burden of making premature commitments. We present Plan Identification Functions (PIFs), which formalize what it means for a plan to be executable, md are used in conjunction with a complete model of system behavior to halt the planning process when an executable plan is found. We describe the implementation of plan identification functions for a temporal, constraint-based planner. This particular implementation allows the description of many different plan identification functions. characteristics crf the ~xec~~tieonfvii r~nm-enft,h e best plan to hand to the execution system will contain more or less commitment and information.

Bedrax-Weiss, Tania↗
NASA NTRS2005

New Integrated Modeling Capabilities: MIDAS' Recent Behavioral Enhancements

The Man-machine Integration Design and Analysis System (MIDAS) is an integrated human performance modeling software tool that is based on mechanisms that underlie and cause human behavior. A PC-Windows version of MIDAS has been created that integrates the anthropometric character "Jack (TM)" with MIDAS' validated perceptual and attention mechanisms. MIDAS now models multiple simulated humans engaging in goal-related behaviors. New capabilities include the ability to predict situations in which errors and/or performance decrements are likely due to a variety of factors including concurrent workload and performance influencing factors (PIFs). This paper describes a new model that predicts the effects of microgravity on a mission specialist's performance, and its first application to simulating the task of conducting a Life Sciences experiment in space according to a sequential or parallel schedule of performance.

Gore, Brian F.↗