Results for “Flight dynamics” — Page 31

NASA NTRS2014

Application and Evaluation of Control Modes for Risk-Based Engine Performance Enhancements

The engine control system for civil transport aircraft imposes operational limits on the propulsion system to ensure compliance with safety standards. However, during certain emergency situations, aircraft survivability may benefit from engine performance beyond its normal limits despite the increased risk of failure. Accordingly, control modes were developed to improve the maximum thrust output and responsiveness of a generic high-bypass turbofan engine. The algorithms were designed such that the enhanced performance would always constitute an elevation in failure risk to a consistent predefined likelihood. This paper presents an application of these risk-based control modes to a combined engine/aircraft model. Through computer and piloted simulation tests, the aim is to present a notional implementation of these modes, evaluate their effects on a generic airframe, and demonstrate their usefulness during emergency flight situations. Results show that minimal control effort is required to compensate for the changes in flight dynamics due to control mode activation. The benefits gained from enhanced engine performance for various runway incursion scenarios are investigated. Finally, the control modes are shown to protect against potential instabilities during propulsion-only flight where all aircraft control surfaces are inoperable.

aircraft engine performance↗

NASA NTRS2015

Application and Evaluation of Control Modes for Risk-Based Engine Performance Enhancements

The engine control system for civil transport aircraft imposes operational limits on the propulsion system to ensure compliance with safety standards. However, during certain emergency situations, aircraft survivability may benefit from engine performance beyond its normal limits despite the increased risk of failure. Accordingly, control modes were developed to improve the maximum thrust output and responsiveness of a generic high-bypass turbofan engine. The algorithms were designed such that the enhanced performance would always constitute an elevation in failure risk to a consistent predefined likelihood. This paper presents an application of these risk-based control modes to a combined engine/aircraft model. Through computer and piloted simulation tests, the aim is to present a notional implementation of these modes, evaluate their effects on a generic airframe, and demonstrate their usefulness during emergency flight situations. Results show that minimal control effort is required to compensate for the changes in flight dynamics due to control mode activation. The benefits gained from enhanced engine performance for various runway incursion scenarios are investigated. Finally, the control modes are shown to protect against potential instabilities during propulsion-only flight where all aircraft control surfaces are inoperable.

emergency operation↗

NASA NTRSDate not supplied

Neo – Mars Adaptive Training Integrative Knowledge System (MATRIKS) to Improve Operational Performance and its Neural Basis for Spaceflight

With prolonged mission durations, spaceflight crews will become increasingly dependent on onboard technologies for knowledge acquisition and maintenance. It is expected that not all skills and knowledge required for these missions can be retained and retrieved based on pre-mission training alone. Limited and delayed communication will significantly constrain support from Mission Control and crews will increasingly rely on autonomous onboard technologies to successfully perform post-landing operations. With the present project we will target NASA’s particular interest in developing and assessing an adaptive, just-in-time countermeasure that will consolidate and improve skills that are most relevant to space flight operations. To achieve this aim, NASA established a Virtual NASA Specialized Center of Research (VNSCOR)referred to as “Mars Adaptive Training Integrative Knowledge System (MATRIKS)”, comprising the following three projects: (1) “Trinity–Multi-Environment Virtual Training for Long Duration Exploration Missions”, PI: A. Anderson (UC Boulder); (2) “Morpheus–A Haptic Sensory Supplement to Optimize In-Flight Adaptive Training for Human Control of Spacecraft Robotic Arms”, PI: S. Robinson, UC Davis); and the present project “Neo–Adaptive Training integrative knowledge System to Improve Operational Performance and its Neural Basis for Spaceflight” (UPenn, PI: A.C. Stahn). Neo leverages a validated workstation called 6DF that simulates a rendezvous and docking maneuver using real spacecraft flight dynamics. It is designed to (1) train and improve sensorimotor skills relevant for inflight and post-landing operational tasks; (2) feature an autonomous and adaptive training approach that does not rely on feedback from flight operations on the ground; (3) maximize the transfer of mission-relevant motor skills; (4) allow the assessment of the neural circuitry underlying the task; and (5) deliver the training in a motivating and meaningful way to astronauts. Neocomprises two overarching aims: First, we will identify the neural circuitry underlying spaceflight relevant tasks by performing a subset of the 6DFtaskduring functional magnetic resonance imaging (MRI)in a total of up to N=30 subjects with varying levels of 6DF training experience. Second, as part of the above-mentioned VNSCOR MATRIKS the proposed 6DF autonomous intelligent tutor system will be integrated in an additive manner with a haptic feedback intervention (Morpheus), and a multi-environment virtual trainer(Trinity).It is expected that Neo, Morpheus and Trinity mutually complement each other to facilitate an effective countermeasure tool to acquire and retain operational skills that are critical for exploration class missions. To assess the efficacy of this combined effort, the VNSCOR MATRIKS will collect data inN=16 crew members in one HERA campaign of 45 days duration with N=16 crew members(four missions with N=4 crew member seach).The primary goal is to identify changes in operational performance as assessed by NASA’s simulator of Canadarm2 operations, i.e., Robotic On-board Trainer (ROBoT-r) in response to MATRIKS. As part of Neo we will also identify if, and to what extent MATRIKS will promote transfer to general cognitive performance (Cognition battery), distinctive visuo-spatial tasks critical for telerobotic tasks (Spatial Cognition battery), and affect brain structural changes and the neural circuitry of key brain networks expected to be relevant for spaceflight-related performance. At the conclusion of the research, we will have defined and demonstrated the use of a neuroscience-based, adaptive training integrative knowledge system to potentially mitigate visuo-spatial and sensorimotor brain changes associated with prolonged isolation and confinement to reduce the likelihood or impact of potential decrements in human performance capabilities during long-duration space missions. The expected significance of this 4-year project relates to its relevance for facilitating effective countermeasure tools to acquire and retain operational skills that are critical for exploration class missions. This will support the development of necessary countermeasures and technologies in support of human space exploration, focusing on mitigating operational performance risks.

A C Stahn↗

NASA NTRSDate not supplied

Wind Tunnel Testing of Static Aerodynamic and Power Consumption Characteristics of an Octocopter

The introduction of multirotor unmanned aircraft systems (UAS) in low-altitude airspace poses significant safety challenges. Further development of advanced aviation systems is needed to realize the full potential of UAS applications, particularly for urban and beyond visual line-of-sight (BVLOS) operations. The NASA System Wide Safety (SWS) project is developing key technologies to mitigate future airspace safety risks involving autonomous aircraft operation in densely populated areas. An important part of these technologies requires flight dynamics and performance models to assess feasible trajectories, power consumption requirements, and operational envelope limitations. To support these efforts, this research seeks to improve the accuracy of multirotor aerodynamic models and investigate stability characteristics relevant to flight safety. This paper presents a recent study of an octocopter vehicle using the NASA Langley 12-Foot Low-Speed Tunnel (LST). Results from isolated-airframe (no propellers) and powered-airframe tests are presented. A one-factor-at-a-time (OFAT) approach was used to explore the effect of propeller advance ratio and vehicle angle of attack on vehicle forces, moments, and power consumption. The results show nonlinear aerodynamic behavior and indicate regions where aerodynamic interaction effects may be significant.

George V. Altamirano↗

NASA NTRS1981

Development of a comprehensive analysis for rotorcraft. I - Rotor model and wake analysis

The development of a comprehensive analytical model of rotorcraft aerodynamics and dynamics is described. Particular emphasis is given to describing the reasons behind the choices and decisions involved in constructing the model. The analysis is designed to calculate rotor performance, loads and noise; helicopter vibration and gust response; flight dynamics and handling qualities; and system aeroelastic stability. It is intended for use in the design, testing and evaluation of a wide class of rotors and rotorcraft, and to be the basis for further development of rotary wing theories. The general characteristics of the geometric, structural, inertial, and aerodynamic models used for the rotorcraft components are described, including the assumptions introduced by the chosen models and the resulting capabilities and limitations. Finally, some examples from recent applications of the analysis are given.

Johnson, W.↗

NASA NTRS1981

Development of a comprehensive analysis for rotorcraft. II - Aircraft model, solution procedure and applications

The development of a comprehensive analytical model of rotorcraft aerodynamics and dynamics is described. Particular emphasis is given to describing the reasons behind the choices and decisions involved in constructing the model. The analysis is designed to calculate rotor performance, loads and noise; helicopter vibration and gust response; flight dynamics and handling qualities; and system aeroelastic stability. It is intended for use in the design, testing and evaluation of a wide class of rotors and rotorcraft and to be the basis for further development of rotary wing theories. The general characteristics of the geometric, structural, inertial and aerodynamic models used for the rotorcraft components are described, including the assumptions introduced by the chosen models and the resulting capabilities and limitations. Finally, some examples from recent applications of the analysis are given.

Johnson, W.↗

NASA NTRS1993

Spaceflight dynamics 1993; AAS/NASA International Symposium, 8th, Greenbelt, MD, Apr. 26-30, 1993, Parts 1 & 2

A conference on spaceflight dynamics produced papers in the areas of orbit determination, spacecraft tracking, autonomous navigation, the Deep Space Program Science Experiment Mission (DSPSE), the Global Positioning System, attitude control, geostationary satellites, interplanetary missions and trajectories, applications of estimation theory, flight dynamics systems, low-Earth orbit missions, orbital mechanics, mission experience in attitude dynamics, mission experience in sensor studies, attitude dynamics theory and simulations, and orbit-related experience. These papaers covered NASA, European, Russian, Japanese, Chinese, and Brazilian space programs and hardware.

Teles, Jerome↗

NASA NTRS2002

Evaluation of Standard Gear Metrics in Helicopter Flight Operation

Each false alarm made by a machine monitoring system carries a high price tag. The machine must be taken out of service, thoroughly inspected with possible disassembly, and then made ready for service. Loss of use of the machine and the efforts to inspect it are costly. In addition, if a monitoring system is prone to false alarms, the system will soon be turned off or ignored. For aircraft applications, one growing concern is that the dynamic flight environment differs from the laboratory environment where fault detection methods are developed and tested. Vibration measurements made in flight are less stationary than those made in a laboratory, or test facility, and thus a given fault detection method may produce more false alarms in flight than might be anticipated. In 1977. Stewart introduced several metrics, including FM0 and FM4, for evaluating the health of a gear. These metrics are single valued functions of the vibration signal that indicate if the signal deviates from an ideal model of the signal. FM0 is a measure of the ratio of the peak-to-peak level to the harmonic energy in the signal. FM4 is the kurtosis of the signal with the gear mesh harmonics and first order side bands removed. The underlying theory is that a vibration signal from a gear in good condition is expected to be dominated by a periodic signal at the gear mesh frequency. If one or a small number of gear teeth contain damage or faults, the signal will change, possibly showing increased amplitude, local phase changes or both near the damaged region of the gear. FM0 increases if a signal contains a local increase in amplitude. FM4 increases if a signal contains a local increase in amplitude or local phase change in a periodic signal. Over the years, other single value metrics were also introduced to detect the onset and growth of damage in gears. These various metrics have detected faults in several gear tests in experimental test rigs. Conditions in these tests have been steady state in the sense that the rpm, torque and forces on the gear have been held steady. For gears used in a dynamic environment such as that occurring in aircraft, the rpm, torque and forces on the gear are constantly changing. The authors have measured significant variation in rpm and torque in the transmissions of helicopters in controlled steady flight conditions flown by highly proficient test pilots. Statistical analyses of the data taken in flight show significant nonstationarity in the vibration measurements. These deviations from stationarity may increase false alarms in gear monitoring during aircraft flight. In the proposed paper, the authors will study vibration measurements made in flight on an AH- 1 Cobra and an OH-58C Kiowa helicopters. The primary focus will be the development of a methodology to assess the impact of nonstationarity on false alarms. Issues to be addressed include how time synchronous averages are constructed from raw data as well as how lack of stationarity effects the behavior of single value metrics. Emphasis will be placed on the occurrence of false alarms with the use of standard metrics. In order to maintain an acceptable level of false alarms in the flight environment, this study will also address the determination of appropriate threshold levels, which may need to be higher than for test rigs.

Mosher, M.↗

NASA NTRSDate not supplied

Dynamic Vehicle Assessment for Intelligent Contingency Management for Urban Air Mobility Vehicles

New algorithms will be required to ensure passenger and bystander safety during the expected era of autonomous urban air mobility (UAM) aircraft. This paper examines an approach for assessing the vehicle capability to fly itself and to complete a mission safely. The concepts combine elements of system identification, adaptive control, flight dynamics, envelope predictions, and handling qualities, as well as human pilot intuition. The approach is applied to a simulation of a generic distributed electric propulsion urban air mobility-type aircraft, which was developed under the NASA Transformational Tools and Technologies (TTT) project, Autonomous Systems / Intelligent Contingency Management subproject.

flight envelope prediction↗

NASA NTRSDate not supplied

Dynamic Vehicle Assessment for Intelligent Contingency Management of Urban Air Mobility Vehicles

New algorithms will be required to ensure passenger and bystander safety during the expected era of autonomous urban air mobility (UAM) aircraft. This paper examines an approach for assessing the vehicle capability to fly itself and to complete a mission safely. The concepts combine elements of system identification, adaptive control, flight dynamics, envelope predictions, and handling qualities, as well as human pilot intuition. The approach is applied to a simulation of a generic distributed electric propulsion urban air mobility-type aircraft, which was developed under the NASA Transformational Tools and Technologies (TTT) project, Autonomous Systems / Intelligent Contingency Management subproject.

flight envelope↗

NASA NTRS1982

Integrated airframe propulsion control

Perturbation equations which describe flight dynamics and engine operation about a given operating point are combined to form an integrated aircraft/propulsion system model. Included in the model are the dependence of aerodynamic coefficients upon atmospheric variables along with the dependence of engine variables upon flight condition and inlet performance. An off-design engine performance model is used to identify interaction parameters in the model. Inclusion of subsystem interaction effects introduces coupling between flight and propulsion variables. To analyze interaction effects on control, consideration is first given to control requirements for separate flight and engine models. For the separate airframe model, feedback control provides substantial improvement in short period damping. For the integrated system, feedback control compensates for the coupling present in the model and provides good overall system stability. However, this feedback control law involves many non-zero gains. Analysis of suboptimal control strategies indicates that performance of the closed loop integrated system can be maintained with a feedback matrix in which the number of non-zero gains is small relative to the number of components in the feedback matrix.

Fennell, R. E.↗

NASA NTRS1983

Distributed asynchronous microprocessor architectures in fault tolerant integrated flight systems

The paper discusses the implementation of fault tolerant digital flight control and navigation systems for rotorcraft application. It is shown that in implementing fault tolerance at the systems level using advanced LSI/VLSI technology, aircraft physical layout and flight systems requirements tend to define a system architecture of distributed, asynchronous microprocessors in which fault tolerance can be achieved locally through hardware redundancy and/or globally through application of analytical redundancy. The effects of asynchronism on the execution of dynamic flight software is discussed. It is shown that if the asynchronous microprocessors have knowledge of time, these errors can be significantly reduced through appropiate modifications of the flight software. Finally, the papear extends previous work to show that through the combined use of time referencing and stable flight algorithms, individual microprocessors can be configured to autonomously tolerate intermittent faults.

Dunn, W. R.↗

NASA NTRS2000

Development of a Enhanced Thermal Barrier for RSRM Nozzle Joints

A carbon fiber rope is being considered as replacement for the RTV thermal barrier that is currently used to protect o-rings in RSRM nozzle joints, Performance requirements include its ability to cool propellant gases filter slag and particulates, and conform to various joint assembly conditions as well as dynamic flight motion. Testing has shown its superior heat resistance, even in oxidative and corrosive environments. Testing has also demonstrated excellent performance of this system in sub-scale motors. Cold flow testing, has demonstrated its ability to conform to motor dynamics. Manufacture and assembly testing have demonstrated the ease of gland machining as well as assembly in a full-scale nozzle.

Bauer, P. H.↗

NASA NTRS2016

AirSTAR Hardware and Software Design for Beyond Visual Range Flight Research

The National Aeronautics and Space Administration (NASA) Airborne Subscale Transport Aircraft Research (AirSTAR) Unmanned Aerial System (UAS) is a facility developed to study the flight dynamics of vehicles in emergency conditions, in support of aviation safety research. The system was upgraded to have its operational range significantly expanded, going beyond the line of sight of a ground-based pilot. A redesign of the airborne flight hardware was undertaken, as well as significant changes to the software base, in order to provide appropriate autonomous behavior in response to a number of potential failures and hazards. Ground hardware and system monitors were also upgraded to include redundant communication links, including ADS-B based position displays and an independent flight termination system. The design included both custom and commercially available avionics, combined to allow flexibility in flight experiment design while still benefiting from tested configurations in reversionary flight modes. A similar hierarchy was employed in the software architecture, to allow research codes to be tested, with a fallback to more thoroughly validated flight controls. As a remotely piloted facility, ground systems were also developed to ensure the flight modes and system state were communicated to ground operations personnel in real-time. Presented in this paper is a general overview of the concept of operations for beyond visual range flight, and a detailed review of the airborne hardware and software design. This discussion is held in the context of the safety and procedural requirements that drove many of the design decisions for the AirSTAR UAS Beyond Visual Range capability.

Laughter, Sean↗

NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗

NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗

NASA NTRSDate not supplied

In-flight System Identification of the Ingenuity Mars Helicopter

The 68th and 69th flights of NASA’s Ingenuity Mars Helicopter marked the first dedicated system identification flights of an aerial vehicle on another planet. Chirp signals were injected into the swashplate cyclic controls for both legs of the two out-and-back flights. Frequency responses were computed from the flight data, using both the Direct Method (DM) and the Joint-Input-Output (JIO) approach, for the identification of stability and control derivatives in forward flight conditions. The resulting identified state-space models were compared against existing flight dynamics simulation models, showing excellent correlation in the higher frequency range. External disturbances were seen to introduce a bias in the identified lower frequency responses, which was partially mitigated using the JIO method. These findings will inform future modeling and flight testing efforts of Mars rotorcraft.

Ingenuity↗

NASA NTRS1989

The effects of seasonal and latitudinal earth infrared radiance variations on ERBS attitude control

Analysis performed in the Flight Dynamics Facility by the Earth Radiation Budget Satellite (ERBS) Attitude Determination Support team illustrates the pitch attitude control motion and roll attitude errors induced by Earth infrared (IR) horizon radiance variations. IR scanner and inertial reference unit (IRU) pitch and roll flight data spanning 4 years of the ERBS mission are analyzed to illustrate the changes in the magnitude of the errors on time scales of the orbital period, months, and seasons. The analysis represents a unique opportunity to compare prelaunch estimates of radiance-induced attitude errors with flight measurements. As a consequence of this work the following additional information is obtained: an assessment of an average model of these errors and its standard deviation, a measurement to determine and verify previously proposed corrections to the current Earth IR radiance data base, and the possibility of a mean motion model derived from flight data in place of IRU data for ERBS fine attitude determination.

Phenneger, M. C.↗