Design and development of prognostic and health management system for fly-by-wire primary flight control

Electro-Hydraulic Servo Actuators (EHSA) is the principal technology used for primary flight control in new aircrafts and legacy platforms. The development of Prognostic and Health Management technologies and their application to EHSA systems is of great interest in both the aerospace industry and the air fleet operators. This Ph.D. thesis is the results of research activity focused on the development of a PHM system for servovalve of fly-by-wire primary flight EHSA. One of the key features of the research is the implementation of a PHM system without the addition of new sensors, taking advantage of sensing and information already available. This choice allows extending the PHM capability to the EHSAs of legacy platforms and not only to new aircrafts. The enabling technologies borrow from the area of Bayesian estimation theory and specifically particle filtering and the information acquired from EHSA during pre-flight check is processed by appropriate algorithms in order to obtain relevant features, detect the degradation and estimate the Remaining Useful Life (RUL). The results are evaluated through appropriate metrics in order to assess the performance and effectiveness of the implemented PHM system. The major objective of this contribution is to develop an innovative fault diagnosis and failure prognosis framework for critical aircraft components that integrates effectively mathematically rigorous and validated signal processing, feature extraction, diagnostic and prognostic algorithms with novel uncertainty representation and management tools in a platform that is computationally efficient and ready to be transitioned on-board an aircraft

Grid generation for the solution of partial differential equations

A general survey of grid generators is presented with a concern for understanding why grids are necessary, how they are applied, and how they are generated. After an examination of the need for meshes, the overall applications setting is established with a categorization of the various connectivity patterns. This is split between structured grids and unstructured meshes. Altogether, the categorization establishes the foundation upon which grid generation techniques are developed. The two primary categories are algebraic techniques and partial differential equation techniques. These are each split into basic parts, and accordingly are individually examined in some detail. In the process, the interrelations between the various parts are accented. From the established background in the primary techniques, consideration is shifted to the topic of interactive grid generation and then to adaptive meshes. The setting for adaptivity is established with a suitable means to monitor severe solution behavior. Adaptive grids are considered first and are followed by adaptive triangular meshes. Then the consideration shifts to the temporal coupling between grid generators and PDE-solvers. To conclude, a reflection upon the discussion, herein, is given

Aeronautical engineering: A continuing bibliography with indexes (supplement 231)

This bibliography lists 469 reports, articles, and other documents introduced into the NASA scientific and technical information system in September, 1988

Model reduction for LPV systems based on approximate modal decomposition

The paper presents a novel model order reduction technique for large-scale linear parameter varying (LPV) systems. The approach is based on decoupling the original dynamics into smaller dimensional LPV subsystems that can be independently reduced by parameter varying reduction methods. The decomposition starts with the construction of a modal transformation that separates the modal subsystems. Hierarchical clustering is applied then to collect the dynamically similar modal subsystems into larger groups. The resulting parameter varying subsystems are then independently reduced. This approach substantially differs from most of the previously proposed LPV model reduction techniques, since it performs manipulations on the LPV model itself, instead of on a set of linear time-invariant (LTI) models defined at fixed scheduling parameter values. Therefore the interpolation, which is often a challenging part in reduction techniques, is inherently solved. The applicability of the developed algorithm is thoroughly investigated and demonstrated by numerical case studies

Machine Learning in Aerodynamic Shape Optimization

Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and provide a perspective on the state-of-the-art and future directions. We first introduce conventional ASO and current challenges. Next, we introduce ML fundamentals and detail ML algorithms that have been successful in ASO. Then, we review ML applications to ASO addressing three aspects: compact geometric design space, fast aerodynamic analysis, and efficient optimization architecture. In addition to providing a comprehensive summary of the research, we comment on the practicality and effectiveness of the developed methods. We show how cutting-edge ML approaches can benefit ASO and address challenging demands, such as interactive design optimization. Practical large-scale design optimizations remain a challenge because of the high cost of ML training. Further research on coupling ML model construction with prior experience and knowledge, such as physics-informed ML, is recommended to solve large-scale ASO problems

Aeronautical engineering: A continuing bibliography with indexes (supplement 246)

This bibliography lists 690 reports, articles, and other documents introduced into the NASA scientific and technical information system in November, 1989. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Design, Developement, Analysis and Control of a Bio-Inspired Robotic Samara Rotorcraft

THIS body of work details the development of the first at-scale (>15 cm) robotic samara, or winged seed. The design of prototypes inspired by autorotating plant seed geometries is presented along with a detailed experimental process that elucidates similarities between mechanical and robotic samara flight dynamics. The iterative development process and the implementation of working prototypes are discussed for robotic samara Micro-Air-Vehicles (MAV) that range in size from 7.5 cm to 27 cm. Vehicle design issues are explored as they relate to autorotation efficiency, stability, flight dynamics and control of single winged rotorcraft. In recent years a new paradigm of highly maneuverable aircraft has emerged that are ideally suited for operation in a confined environment. Different from conven- tional aircraft, viscous forces play a large role in the physics of flight at this scale. This results in relatively poor aerodynamic performance of conventional airfoil and rotorcraft configurations. This deficiency has led to the consideration of naturally occurring geometries and configurations, the simplest of which is the samara. To study the influence of geometric variation on autorotation efficiency, a high speed camera system was used to track the flight path and orientation of the mechan- ical samaras. The wing geometry is planar symmetric and resembles a scaled version of Acer diabolicum Blume. The airfoil resembles a scaled version of the maple seed with a blunt leading edge followed by a thin section without camber. Four mechan- ical samara geometries with equal wing loading were designed and fabricated using a high precision rapid prototyping machine that ensured similarity between models. It was found that in order to reduce the descent velocity of an autorotating samara the area centroid or maximum chords should be as far from the center of rotation as possible. Flight data revealed large oscillations in feathering and coning angles, and the resultant flight path was found to be dependent on the mean feathering angle. The different flight modalities provided the basis for the design of a control sys- tem for a powered robotic samara that does not require high frequency sensing and actuation typical of micro-scaled rotorcraft. A prototype mechanical samara with a variable wing pitch (feathering) angle was constructed and it was found that active control of the feathering angle allowed the variation of the radius of the helix carved by the samara upon descent. This knowledge was used to design a hovering robotic samara capable of lateral motion through a series of different size circles specified by precise actuation of the feathering angle. To mathematically characterize the flight dynamics of the aircraft, System identi- fication techniques were used. Using flight data, a linear model describing the heave dynamics of two robotic samara vehicles was verified. A visual positioning system was used to collect flight data while the vehicles were piloted in an indoor laboratory. Closed-loop implementation of the derived PID controller was demonstrated using the visual tracking system for position and velocity feedback. An approach to directional control that does not require the once-per-revolution actuation or high-frequency measurement of vehicle orientation has been demon- strated for the first time. Lateral flight is attained through the vehicles differing responses to impulsive and step inputs that are leveraged to create a control strategy that provides full controllability. Flight testing revealed several linear relationships, including turn rate, turn radius and forward speed. The steady turn discussed here has been observed in scaled versions of the robotic samara, therefore the open-loop control demonstrated and analyzed is considered to be appropriate for similar vehicles of reduced size with limited sensing and actuation capabilities

Vortex detection and tracking in massively separated and turbulent flows

The vortex produced at the leading edge of the wing, known as the leading edge vortex (LEV), plays an important role in enhancing or destroying aerodynamic force, especially lift, upon its formation or shedding during the flapping flight of birds and insects. In this thesis, we integrate multiple new and traditional vortex identification approaches to visualize and track the LEV dynamics during its shedding process. The study is carried out using a 2D simulation of a flat plate undergoing a 45 degree pitch-up maneuver. The Eulerian 1 function and criterion are used along with the Lagrangian coherent structures (LCS) analyses including the finite-time Lyapunov exponent (FTLE), the geodesic LCS, and the Lagrangian-Averaged Vorticity Deviation (LAVD). Each of \h{these} Lagrangian methods \h{is} applied at the centers and boundaries of the vortices to detect the vortex dynamics. The techniques enable the tracking of identifiable features in the flow organization using the FTLE-saddles and -saddles. The FTLE-saddle traces have shown potential to identify the timing and location of vortex shedding, more precisely than by only studying the vortex cores as identified by Eulerian techniques. The traces and the shedding times of the FTLE-saddles on the LEV boundary matches well with the plate lift fluctuation, and indicates a consistent timing of LEV formation, growth, shedding. The formation number and vortex shedding mechanisms are compared in the thesis with the shedding time and location by the FTLE-saddle, which validates the result of the FTLE-saddles and provide explanations of vortex shedding in different aspects (vortex strength and flow dynamics). The techniques are applied to more cases involving vortex dominated flows to explore and expand their application in providing insight of flow physics. For a set of experimental two-component PIV data in the wake of a purely pitching trapezoidal panel, the Lagrangian analysis of FTLE-saddle tracking identifies and tracks the vortex breakdown location with relatively less user interaction and provide a more direct and consistent analysis. For a simulation of wall-bounded turbulence in a channel flow, tracking FTLE-saddles shows that the average structure convection speed exhibits a similar trend as a previously published result based on velocity and pressure correlations, giving validity to the method. When these Lagrangian techniques are applied in a study of the evolution of an isolated hairpin vortex, it shows the connection between primary and secondary hairpin heads of their circulation and position, and the contribution to the generation of the secondary hairpin by the flow characteristics at the channel wall. The current method of tracking vortices yields insight into the behavior of the vortices in all of the diverse flows presented, highlighting the breadth of its potential application

Stability, Transient Response, Control, and Safety of a High-Power Electric Grid for Turboelectric Propulsion of Aircraft

This document contains the deliverables for the NASA Research and Technology for Aerospace Propulsion Systems (RTAPS) regarding the stability, transient response, control, and safety study for a high power cryogenic turboelectric distributed propulsion (TeDP) system. The objective of this research effort is to enumerate, characterize, and evaluate the critical issues facing the development of the N3-X concept aircraft. This includes the proposal of electrical grid architecture concepts and an evaluation of any needs for energy storage