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At least 73 records · Page 4

Failure Behavior and Control Based Mitigation for a Parallel Hybrid Propulsion System

NASA is pursuing research to advance Electrified Aircraft Propulsion (EAP) technologies that address fuel burn and emission reduction goals. EAP brings the potential for improved performance over the state of the art. However, for these systems to be practical and certifiable, they need to possess adequate robustness to adverse conditions including a variety of system failures that are not applicable to conventional turbofans today. Numerous EAP concepts interface gas turbine engines with an electrical power system that includes electric machines and sometimes electrical energy storage. The expansion of the powertrain increases the probability of encountering a failure and introduces new failure modes. Failures within the electrical power system may also impact the gas turbine engine(s) to which the electrical powertrain is coupled. This effort investigates failures originating in the electrical power system and their impact on the parallel hybrid propulsion system. Reversionary control strategies are also demonstrated to reduce the impact of the failures. Failure mitigation strategies were devised and employed in simulation. Various failure scenarios were simulated including those occurring during steady state operation, transients, and takeoff and landing scenarios. The timing of the failure and delay in failure identification and activation of mitigation strategies are noteworthy variables in the study. While the system remained stable throughout all failure scenarios, delays in failure identification could result in undesirable conditions such as increased operating temperatures and reduced stall margin. The results demonstrate successful mitigation of failures through reversionary control modes and help to generate confidence in the robustness of the conceptual parallel hybrid propulsion system.

Failure behavior↗

Lessons Learned and Flight Results from the F15 Intelligent Flight Control System Project

A viewgraph presentation on the lessons learned and flight results from the F15 Intelligent Flight Control System (IFCS) project is shown. The topics include: 1) F-15 IFCS Project Goals; 2) Motivation; 3) IFCS Approach; 4) NASA F-15 #837 Aircraft Description; 5) Flight Envelope; 6) Limited Authority System; 7) NN Floating Limiter; 8) Flight Experiment; 9) Adaptation Goals; 10) Handling Qualities Performance Metric; 11) Project Phases; 12) Indirect Adaptive Control Architecture; 13) Indirect Adaptive Experience and Lessons Learned; 14) Gen II Direct Adaptive Control Architecture; 15) Current Status; 16) Effect of Canard Multiplier; 17) Simulated Canard Failure Stab Open Loop; 18) Canard Multiplier Effect Closed Loop Freq. Resp.; 19) Simulated Canard Failure Stab Open Loop with Adaptation; 20) Canard Multiplier Effect Closed Loop with Adaptation; 21) Gen 2 NN Wts from Simulation; 22) Direct Adaptive Experience and Lessons Learned; and 23) Conclusions

Bosworth, John↗

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

This paper describes the performance of a simplified dynamic inversion controller with neural network supplementation. This 6 DOF (Degree-of-Freedom) simulation study focuses on the results with and without adaptation of neural networks using a simulation of the NASA modified F-15 which has canards. One area of interest is the performance of a simulated surface failure while attempting to minimize the inertial cross coupling effect of a [B] matrix failure (a control derivative anomaly associated with a jammed or missing control surface). Another area of interest and presented is simulated aerodynamic failures ([A] matrix) such as a canard failure. The controller uses explicit models to produce desired angular rate commands. The dynamic inversion calculates the necessary surface commands to achieve the desired rates. The simplified dynamic inversion uses approximate short period and roll axis dynamics. Initial results indicated that the transient response for a [B] matrix failure using a Neural Network (NN) improved the control behavior when compared to not using a neural network for a given failure, However, further evaluation of the controller was comparable, with objections io the cross coupling effects (after changes were made to the controller). This paper describes the methods employed to reduce the cross coupling effect and maintain adequate tracking errors. The IA] matrix failure results show that control of the aircraft without adaptation is more difficult [leas damped) than with active neural networks, Simulation results show Neural Network augmentation of the controller improves performance in terms of backing error and cross coupling reduction and improved performance with aerodynamic-type failures.

Burken, John J.↗

An Enhanced Model for Evaluating Failure Propagation in Launch Vehicle Engine Sections

An important component in the assessment of launch vehicle safety is the estimation of the likelihood of large-scale explosions given the existence of failures that manifest as a localized energy release. A failure propagation model is presented for simulating cascading failures of energetic components in proximity where the primary modes of energy transfer are fragments/shrapnel and blast overpressure. The model is an extension of the model developed by Mathias and Motiwala (2015) [1] with enhancements to include the effects of fragment ricochet, fragment drag, fragment ballistic limit equation thresholds, and blast impulse thresholds. A series of sensitivity studies were conducted for a generic launch vehicle engine section and results are presented that illustrate the effects of the model modifications.

Susie Go↗

An Enhanced Model for Evaluating Failure Propagation in Launch Vehicle Engine Sections

An important component in the assessment of launch vehicle safety is the estimation of the likelihood of large-scale explosions given the existence of failures that manifest as a localized energy release. A failure propagation model is presented for simulating cascading failures of energetic components in proximity where the primary modes of energy transfer are fragments/shrapnel and blast overpressure. The model is an extension of the model developed by Mathias and Motiwala (2015) [1] with enhancements to include the effects of fragment ricochet, fragment drag, fragment ballistic limit equation thresholds, and blast impulse thresholds. A series of sensitivity studies were conducted for a generic launch vehicle engine section and results are presented that illustrate the effects of the model modifications.

Susie Go↗

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Modal Filtering↗

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Modal Filtering↗

Level of Automation and Failure Frequency Effects on Simulated Lunar Lander Performance

A human-in-the-loop experiment was conducted at the NASA Ames Research Center Vertical Motion Simulator, where instrument-rated pilots completed a simulated terminal descent phase of a lunar landing. Ten pilots participated in a 2 x 2 mixed design experiment, with level of automation as the within-subjects factor and failure frequency as the between subjects factor. The two evaluated levels of automation were high (fully automated landing) and low (manual controlled landing). During test trials, participants were exposed to either a high number of failures (75% failure frequency) or low number of failures (25% failure frequency). In order to investigate the pilots' sensitivity to changes in levels of automation and failure frequency, the dependent measure selected for this experiment was accuracy of failure diagnosis, from which D Prime and Decision Criterion were derived. For each of the dependent measures, no significant difference was found for level of automation and no significant interaction was detected between level of automation and failure frequency. A significant effect was identified for failure frequency suggesting failure frequency has a significant effect on pilots' sensitivity to failure detection and diagnosis. Participants were more likely to correctly identify and diagnose failures if they experienced the higher levels of failures, regardless of level of automation

performance↗

A Simulator Study of the Effectiveness of a Pilot's Indicator which Combined Angle of Attack and Rate of Change of Total Pressure as Applied to the Take-Off Rotation and Climbout of a Supersonic Transport

A simulator study has been made to determine the effectiveness of a single instrument presentation as an aid to the pilot in controlling both rotation and climbout path in take-off. The instrument was basically an angle-of-attack indicator, biased with a total-pressure-rate input as a means of suppressing the phugoid oscillation. Linearized six-degree-of-freedom equations of motion were utilized in simulating a hypothetical supersonic transport as the test vehicle. Each of several experienced pilots performed a number of simulated take-offs, using conventional flight instruments and either an angle-of-attack instrument or the combined angle-of-attack and total-pressure-rate instrument. The pilots were able to rotate the airplane, with satisfactory precision, to the 15 deg. angle of attack required for lift-off when using either an angle-of-attack instrument or the instrument which combined total-pressure-rate with angle of attack. At least 4 to 6 second-S appeared to be required for rotation to prevent overshoot, particularly with the latter instrument. The flight paths resulting from take-offs with simulated engine failures were relatively smooth and repeatable within a reasonably narrow band when the combined angle-of-attack and total-pressure-rate instrument presentation was used. Some of the flight paths resulting from take-offs with the same engine-failure conditions were very oscillatory when conventional instruments and an angle-of-attack instrument were used. The pilots considered the combined angle-of-attack and total- pressure-rate instrument a very effective aid. Even though they could, with sufficient practice, perform satisfactory climbouts after simulated engine failure by monitoring the conventional instruments and making correction based on their readings, it was much easier to maintain a smooth flight path with the single combined angle-of-attack and total-pressure-rate instrument.

Hall, Albert W.↗

Design and testing of a redundant skewed inertial sensor complex for integrated navigation and flight control

Requirements for a redundant strapdown inertial sensor complex applied to V/STOL aircraft as developed by NASA are presented. Flight test data of a redundant, skewed axis strapdown inertial system are given, demonstrating the feasibility of the primary design aspects. This data consisted of parity equation responses through various flight conditions, showing residual noise levels on redundant gyro and accelerometer comparisons as a measure of minimum failure-level detectability, plus failure isolation and navigation performance through several simulated instrument failures.

Ebner, R. E.↗

Reliable dual-redundant sensor failure detection and identification for the NASA F-8 DFBW aircraft

A technique was developed which provides reliable failure detection and identification (FDI) for a dual redundant subset of the flight control sensors onboard the NASA F-8 digital fly by wire (DFBW) aircraft. The technique was successfully applied to simulated sensor failures on the real time F-8 digital simulator and to sensor failures injected on telemetry data from a test flight of the F-8 DFBW aircraft. For failure identification the technique utilized the analytic redundancy which exists as functional and kinematic relationships among the various quantities being measured by the different control sensor types. The technique can be used not only in a dual redundant sensor system, but also in a more highly redundant system after FDI by conventional voting techniques reduced to two the number of unfailed sensors of a particular type. In addition the technique can be easily extended to the case in which only one sensor of a particular type is available.

Deckert, J. C.↗

A System for Integrated Reliability and Safety Analyses

We present an integrated reliability and aviation safety analysis tool. The reliability models for selected infrastructure components of the air traffic control system are described. The results of this model are used to evaluate the likelihood of seeing outcomes predicted by simulations with failures injected. We discuss the design of the simulation model, and the user interface to the integrated toolset.

Kostiuk, Peter↗

Decision Manifold Approximation for Physics-Based Simulations

With the recent surge of success in big-data driven deep learning problems, many of these frameworks focus on the notion of architecture design and utilizing massive databases. However, in some scenarios massive sets of data may be difficult, and in some cases infeasible, to acquire. In this paper we discuss a trajectory-based framework that quickly learns the underlying decision manifold of binary simulation classifications while judiciously selecting exploratory target states to minimize the number of required simulations. Furthermore, we draw particular attention to the simulation prediction application idealized to the case where failures in simulations can be predicted and avoided, providing machine intelligence to novice analysts. We demonstrate this framework in various forms of simulations and discuss its efficacy.

Wong, Jay Ming↗

Low-thrust mission risk analysis, with application to a 1980 rendezvous with the comet Encke

A computerized failure process simulation procedure is used to evaluate the risk in a solar electric space mission. The procedure uses currently available thrust-subsystem reliability data and performs approximate simulations of the thrust sybsystem burn operation, the system failure processes, and the retargeting operations. The method is applied to assess the risks in carrying out a 1980 rendezvous mission to the comet Encke. Analysis of the results and evaluation of the effects of various risk factors on the mission show that system component failure rates are the limiting factors in attaining a high mission relability. It is also shown that a well-designed trajectory and system operation mode can be used effectively to partially compensate for unreliable thruster performance.

Yen, C. L.↗

Low-thrust mission risk analysis.

A computerized multi-stage failure process simulation procedure is used to evaluate the risk in a solar electric space mission. The procedure uses currently available thrust-subsystem reliability data and performs approximate simulations of the thrust subsystem burn operation, the system failure processes, and the retargetting operations. The application of the method is used to assess the risks in carrying out a 1980 rendezvous mission to Comet Encke. Analysis of the results and evaluation of the effects of various risk factors on the mission show that system component failure rates is the limiting factor in attaining a high mission reliability. But it is also shown that a well-designed trajectory and system operation mode can be used effectively to partially compensate for unreliable thruster performance.

Yen, C. L.↗