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This presentation reviews the following: (i) Cause and effect of gas turbine blade tip seal wear (ii) Current clearance control practices (iii) Present approaches under investigation at GRC.
The Lunar Reconnaissance Orbiter (LRO), a spacecraft designed and built at the National Aeronautics and Space Administration s (NASA) Goddard Space Flight Center (GSFC) in Greenbelt, MD, was launched on June 18, 2009 from Cape Canaveral. It is currently in orbit about the Moon taking detailed science measurements and providing a highly accurate mapping of the suface in preparation for the future return of astronauts to a permanent moon base. Onboard the spacecraft is a complex set of algorithms designed by the attitude control engineers at GSFC to control the pointig for all operational events, including anomalies that require the spacecraft to be put into a well known attitude configuration for a sufficiently long duration to allow for the investigation and correction of the anomaly. GSFC level requirements state that each spacecraft s control system design must include a configuration for this pointing and lso be able to maintain a thermally safe and power positive attitude. This stable control algorithm for anomalous events is commonly referred to as the safe mode and consists of control logic thatwill put the spacecraft in this safe configuration defined by the spacecraft s hardware, power and environment capabilities and limitations. The LRO Sun Safe mode consists of a coarse sun-pointing set of algorithms that puts the spacecraft into this thermally safe and power positive attitude and can be achieved wihin a required amount of time from any initial attitude, provided that the system momentum is within the momentum capability of the reaction wheels. On LRO the Sun Safe mode makes use of coarse sun sensors (CSS), an inertial reference unit (IRU) and reaction wheels (RW) to slew the spacecraft to a solar inertial pointing. The CSS and reaction wheels have some level of redundancy because of their numbers. However, the IRU is a single-point-failure piece of hardware. Without the rate information provided by the IRU, the Sun Safe control algorithms could not maintain the required pointing, so a sub-mode of the Sun Safe mode that does not use the IRU was designed. This submode, referred to as the Sun Safe Gyroless control mode, consists of an algorithm that estimates rate information from the CSS and the RW measurements. RW momentum information is used to estimate the body rate parallel to the target sunline, which CSS alone would not be able to observe. Sun Safe can be autonomously, or via ground command, entered from any other control mode and in the event the IRU is not providing rate information, the control mode is switched to the gyroless submode. This paper looks at the design of the Sun Safe modes and discusses the constraints placed on the algorithm and how the mode wored around these constraints. Items of particular interest include CSS placement on the Solar Array (SA) and its implications to design, estimation of body rate information for the Sun Safe Gyroless control mode, and the effect of solar eclipse on each of the Sun Safe modes. Placing CSS on the SA was necessary for the means to put the Sun along the targeted sun-line, nominally normal to the SA panels, for all operational considerations. This had design implications for determining a sun vector during normal SA operations, if one or both gimbals become inoperable and when the SA is in a stowed configuration. The ability of body rate estimation in Sun Safe Gyroless not only uses CSS sun vector data but requires RW momentum measuremens to estimate rates parallel to the sun-line. LRO encounters solar eclipses of some length for most of its orbits about the Moon. With the lack of CSS measurement data a design was implemented in both Sun Safe and Sun Safe Gyroless, they differ because of having or not having IRU measurement data, to carry the spacecraft through these eclipse periods. This paper also includes some discussion of sun avoidance and how it affected design decisions during nominal and eclipse perids for each of the Sun Safe modes.
To reduce the dry mass of a spacecraft pressurization system, helium pressurant may be stored at low temperature and high pressure to increase mass in a given tank volume. Warming this gas through an engine heat exchanger prior to tank pressurization both increases the system efficiency and simplifies the designs of intermediate hardware such as regulators, valves, etc. since the gas is no longer cryogenic. If this type of cold helium pressurization system is used in conjunction with a cryogenic propellant, though, a loss in overall system efficiency can be expected due to heat transfer from the warm ullage gas to the cryogenic propellant which results in a specific volume loss for the pressurant, interpreted as the Collapse Factor. Future spacecraft with cryogenic propellants will likely have a cold helium system, with increasing collapse factor effects as vehicle sizes decrease. To determine the collapse factor effects and overall implementation strategies for a representative design point, a cold helium system was hotfire tested on the Integrated Cryogenic Propulsion Test Article (ICPTA) in a thermal vacuum environment at the NASA Glenn Research Center Plum Brook Station. The ICPTA vehicle is a small lander-sized spacecraft prototype built at NASA Johnson Space Center utilizing cryogenic liquid oxygen/liquid methane propellants and cryogenic helium gas as a pressurant to operate one 2,800lbf 5:1 throttling main engine, two 28lbf Reaction Control Engines (RCE), and two 7lbf RCEs (Figure 1). This vehicle was hotfire tested at a variety of environmental conditions at NASA Plum Brook, ranging from ambient temperature/simulated high altitude, deep thermal/high altitude, and deep thermal/high vacuum conditions. A detailed summary of the vehicle design and testing campaign may be found in Integrated Cryogenic Propulsion Test Article Thermal Vacuum Hotfire Testing, AIAA JPC 2017.
In support of a facility characterization test, the Integrated Cryogenic Propulsion Test Article (ICPTA) was hotfire tested at a variety of simulated altitude and thermal conditions in the NASA Glenn Research Center Plum Brook Station In-Space Propulsion Thermal Vacuum Chamber (formerly B2). The ICPTA utilizes liquid oxygen and liquid methane propellants for its main engine and four reaction control engines, and uses a cold helium system for tank pressurization. The hotfire test series included high altitude, high vacuum, ambient temperature, and deep cryogenic environments, and several hundred sensors on the vehicle collected a range of system level data useful to characterize the operation of an integrated LOX/Methane spacecraft in the space environment - a unique data set for this propellant combination.
My time here at KSC has involved creating and updating HMI displays to support Pad 39B and the Mobile Launcher. I also had the opportunity to be involved with testing PLC hardware for Electromagnetic interferences. This report explains in more detail of the steps involved in successfully completing these responsibilities I have been fortunate enough to be involved with.
This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.
A typical engine control design cycle consists of developing a dynamic engine simulation from steady-state component performance data, designing a control based upon this simulation, and then testing and modifying the control in an engine test cell to meet performance requirements. This design cycle was successful for state-of-the-art engines. However, for more advanced multivariable engines that exhibit strong variable interactions, this procedure will result in substantial trial and error modification of the control during the testing phase. One method to automate the design process and reduce control modification testing and development cost would be to identify accurate dynamic models directly from the closed-loop test data. These identified models would then be used in conjunction with a synthesis procedure to systematically refine the control. Recent advances in closed-loop identifiability present a methodology for this direct identification of engine model dynamics from closed-loop test data. The application of an identification method to simulated and actual closed-loop F100 engine data is described. This study was undertaken to determine if useful dynamic engine models could be identified directly from closed-loop engine test data.
The highly integrated digital electronic control (HIDEC) program will integrate the propulsion and flight control systems on an F-15 airplane at NASA Ames Research Center's Dryden Flight Research Facility. Ames-Dryden has conducted several propulsion control programs that have contributed to the HIDEC program. The digital electronic engine control (DEEC) flight evaluation investigated the performance and operability of the F100 engine equipped with a full-authority digital electronic control system. Investigations of nozzle instability, fault detection and accommodation, and augmentor transient capability provided important information for the HIDEC program. The F100 engine model derivative (EMD) was also flown in the F-15 airplane, and airplane performance was significantly improved. A throttle response problem was found and solved with a software fix to the control logic. For the HIDEC program, the F100 EMD engines equipped with DEEC controls will be integrated with the digital flight control system. The control modes to be implemented are an integrated flightpath management mode and an integrated adaptive engine control system mode. The engine control experience that will be used in the HIDEC program is discussed.
Distributed engine control (DEC) systems alter aircraft engine design constraints because of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.
Distributed engine control (DEC) systems alter aircraft engine design constraints be- cause of fundamental differences in the input and output communication between DEC and centralized control architectures. The change in the way communication is implemented may create new optimum engine-aircraft configurations. This paper continues the exploration of digital network communication by demonstrating a Network-In-the-Loop simulation at the NASA Glenn Research Center. This simulation incorporates a real-time network protocol, the Engine Area Distributed Interconnect Network Lite (EADIN Lite), with the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) software. The objective of this study is to assess digital control network impact to the control system. Performance is evaluated relative to a truth model for large transient maneuvers and a typical flight profile for commercial aircraft. Results show that a decrease in network bandwidth from 250 Kbps (sampling all sensors every time step) to 40 Kbps, resulted in very small differences in control system performance.
The NASA Dryden Flight Research Center has been conducting integrated flight-propulsion control flight research using the NASA F-15 airplane for the past 12 years. The research began with the digital electronic engine control (DEEC) project, followed by the F100 Engine Model Derivative (EMD). HIDEC (Highly Integrated Digital Electronic Control) became the umbrella name for a series of experiments including: the Advanced Digital Engine Controls System (ADECS), a twin jet acoustics flight experiment, self-repairing flight control system (SRFCS), performance-seeking control (PSC), and propulsion controlled aircraft (PCA). The upcoming F-15 project is ACTIVE (Advanced Control Technology for Integrated Vehicles). This paper provides a brief summary of these activities and provides background for the PCA and PSC papers, and includes a bibliography of all papers and reports from the NASA F-15 project.
This paper describes a design for fiber-optic sensing and control in advanced aircraft Electronic Engine Control (EEC). The recommended architecture is an on-engine EEC which contains electro-optic interface circuits for fiber-optic sensors. Size and weight are reduced by multiplexing arrays of functionally similar sensors on a pairs of optical fibers to common electro-optical interfaces. The architecture contains interfaces to seven sensor groups. Nine distinct fiber-optic sensor types were found to provide the sensing functions. Analysis revealed no strong discriminator (except reliability of laser diodes and remote electronics) on which to base a selection of preferred common interface type. A hardware test program is recommended to assess the relative maturity of the technologies and to determine real performance in the engine environment.
Mechanical and thermal requirements of attitude, translation and descent engine controls of Lunar Excursion Module /LEM/
This report documents the activities and research results obtained under a grant (NAG3-998) from the NASA Lewis Research Center. The focus of the research was the investigation of dynamic interactions between airframe and engines for advanced ASTOVL aircraft configurations, and the analysis of the implications of these interactions on the stability and performance of the airframe and engine control systems. In addition, the need for integrated flight and propulsion control for such aircraft was addressed. The major contribution of this research was the exposition of the fact that airframe and engine interactions could be present, and their effects could include loss of stability and performance of the control systems. Also, the significance of two directional, as opposed to one-directional, coupling was identified and explained. A multi variable stability and performance analysis methodology was developed, and applied to several candidate aircraft configurations. Also exposed was the fact that with interactions present along with some integrated control approaches, the engine command/limiting logic (which represents an important non-linear component of the engine control system) can impact closed-loop airframe/engine system stability. Finally, a brief investigation of control-law synthesis techniques appropriate for the class of systems was pursued, and it was determined that multi variable techniques, included model-following formulations of LQG and/or H (infinity) methods showed promise. However, for practical reasons, decentralized control architectures are preferred, which is an architecture incompatible with these synthesis methods.
A control method applicable to multiple-input multiple-output nonlinear time-invariant systems in which desired behavior can be expressed explicitly as a trajectory in system state space is developed. The precomputed state dependent control method is basically a synthesis technique in which a suboptimal control law is developed off-line, prior to system operation. This law is obtained by conducting searches at a finite number of points in state space, in the vicinity of some desired trajectory, to obtain a set of constant control vectors which tend to return the system to the desired trajectory. These vectors are used to evaluate the unknown coefficients in a control law having an assumed hyperellipsoidal form. The resulting coefficients constitute the heart of the controller and are used in the on-line computation of control vectors. Two examples of PSDC are given prior to the more detailed description of the NERVA control system development.
With modern digital control systems, using engine thrust for emergency flight control to supplement or replace failed aircraft normal flight controls has become a practical consideration. The NASA Dryden Flight Research Center has developed a propulsion-controlled aircraft (PCA) system in which computer-controlled engine thrust provides emergency flight control. An F-15 and an MD-11 airplane have been landed without using any flight control surfaces. Preliminary studies have also been conducted that show that engines on only one wing can provide some flight control capability if the lateral center of gravity can be shifted toward the side of the airplane that has the operating engine(s). Simulator tests of several airplanes with no flight control surfaces operating and all engines out on the left wing have all shown positive control capability within the available range of lateral center-of-gravity offset. Propulsion-controlled aircraft systems that can operate without modifications to engine control systems, thus allowing PCA technology to be installed on less capable airplanes or at low cost, are also desirable. Further studies have examined simplified 'PCA Lite' and 'PCA Ultralite' concepts in which thrust control is provided by existing systems such as auto-throttles or a combination of existing systems and manual pilot control.
Computer and engine performance study of jet engine generalized parameter fuel control
In-flight sensor fault detection and isolation (FDI) is critical to maintaining reliable engine operation during flight. The aircraft engine control system, which computes control commands on the basis of sensor measurements, operates the propulsion systems at the demanded conditions. Any undetected sensor faults, therefore, may cause the control system to drive the engine into an undesirable operating condition. It is critical to detect and isolate failed sensors as soon as possible so that such scenarios can be avoided. A challenging issue in developing reliable sensor FDI systems is to make them robust to changes in engine operating characteristics due to degradation with usage and other faults that can occur during flight. A sensor FDI system that cannot appropriately account for such scenarios may result in false alarms, missed detections, or misclassifications when such faults do occur. To address this issue, an enhanced bank of Kalman filters was developed, and its performance and robustness were demonstrated in a simulation environment. The bank of filters is composed of m + 1 Kalman filters, where m is the number of sensors being used by the control system and, thus, in need of monitoring. Each Kalman filter is designed on the basis of a unique fault hypothesis so that it will be able to maintain its performance if a particular fault scenario, hypothesized by that particular filter, takes place.