Search NASA⌕ Search

SEARCH · Search NASA

Results for “Integrating Flight Dynamics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

Modeling and Simulation of Variable Mass, Flexible Structures

The advent of the new Ares I launch vehicle has highlighted the need for advanced dynamic analysis tools for variable mass, flexible structures. This system is composed of interconnected flexible stages or components undergoing rapid mass depletion through the consumption of solid or liquid propellant. In addition to large rigid body configuration changes, the system simultaneously experiences elastic deformations. In most applications, the elastic deformations are compatible with linear strain-displacement relationships and are typically modeled using the assumed modes technique. The deformation of the system is approximated through the linear combination of the products of spatial shape functions and generalized time coordinates. Spatial shape functions are traditionally composed of normal mode shapes of the system or even constraint modes and static deformations derived from finite element models of the system. Equations of motion for systems undergoing coupled large rigid body motion and elastic deformation have previously been derived through a number of techniques [1]. However, in these derivations, the mode shapes or spatial shape functions of the system components were considered constant. But with the Ares I vehicle, the structural characteristics of the system are changing with the mass of the system. Previous approaches to solving this problem involve periodic updates to the spatial shape functions or interpolation between shape functions based on system mass or elapsed mission time. These solutions often introduce misleading or even unstable numerical transients into the system. Plus, interpolation on a shape function is not intuitive. This paper presents an approach in which the shape functions are held constant and operate on the changing mass and stiffness matrices of the vehicle components. Each vehicle stage or component finite element model is broken into dry structure and propellant models. A library of propellant models is used to describe the distribution of mass in the fuel tank or Solid Rocket Booster (SRB) case for various propellant levels. Based on the mass consumed by the liquid engine or SRB, the appropriate propellant model is coupled with the dry structure model for the stage. Then using vehicle configuration data, the integrated vehicle model is assembled and operated on by the constant system shape functions. The system mode shapes and frequencies can then be computed from the resulting generalized mass and stiffness matrices for that mass configuration. The rigid body mass properties of the vehicle are derived from the integrated vehicle model. The coupling terms between the vehicle rigid body motion and elastic deformation are also updated from the constant system shape functions and the integrated vehicle model. This approach was first used to analyze variable mass spinning beams and then prototyped into a generic dynamics simulation engine. The resulting code was tested against Crew Launch Vehicle (CLV-)class problems worked in the TREETOPS simulation package and by Wilson [2]. The Ares I System Integration Laboratory (SIL) is currently being developed at the Marshall Space Flight Center (MSFC) to test vehicle avionics hardware and software in a hardware-in-the-loop (HWIL) environment and certify that the integrated system is prepared for flight. The Ares I SIL utilizes the Ares Real-Time Environment for Modeling, Integration, and Simulation (ARTEMIS) tool to simulate the launch vehicle and stimulate avionics hardware. Due to the presence of vehicle control system filters and the thrust oscillation suppression system, which are tuned to the structural characteristics of the vehicle, ARTEMIS must incorporate accurate structural models of the Ares I launch vehicle. The ARTEMIS core dynamics simulation models the highly coupled nature of the vehicle flexible body dynamics, propellant slosh, and vehicle nozzle inertia effects combined with mass and flexible body properties that vary significant with time during the flight. All forces that act on the vehicle during flight must be simulated, including deflected engine thrust force, spatially distributed aerodynamic forces, gravity, and reaction control jet thrust forces. These forces are used to excite an integrated flexible vehicle, slosh, and nozzle dynamics model for the vehicle stack that simulates large rigid body translations and rotations along with small elastic deformations. Highly effective matrix math operations on a distributed, threaded high-performance simulation node allow ARTEMIS to retain up to 30 modes of flex for real-time simulation. Stage elements that separate from the stack during flight are propagated as independent rigid six degrees of freedom (6DOF) bodies. This paper will present the formulation of the resulting equations of motion, solutions to example problems, and describe the resulting dynamics simulation engine within ARTEMIS.

Tobbe, Patrick A.↗

Status of a digital integrated propulsion/flight control system for the YF-12 airplane

The NASA Flight Research Center is engaged in a program with the YF-12 airplane to study the control of interactions between the airplane and the propulsion system. The existing analog air data computer, autothrottle, autopilot, and inlet control system are to be converted to digital systems by using a general purpose airborne computer and interface unit. First, the existing control laws will be programmed in the digital computer and flight tested. Then new control laws are to be derived from a dynamic propulsion model and a total force and moment aerodynamic model to integrate the systems. These control laws are to be verified in a real time simulation and flight tested.

Reukauf, P. J.↗

System identification methods for aircraft flight control development and validation

System-identification methods compose a mathematical model, or series of models, from measurements of inputs and outputs of dynamic systems. The extracted models allow the characterization of the response of the overall aircraft or component subsystem behavior, such as actuators and on-board signal processing algorithms. This paper discusses the use of frequency-domain system-identification methods for the development and integration of aircraft flight-control systems. The extraction and analysis of models of varying complexity from nonparametric frequency-responses to transfer-functions and high-order state-space representations is illustrated using the Comprehensive Identification from FrEquency Responses (CIFER) system-identification facility. Results are presented for test data of numerous flight and simulation programs at the Ames Research Center including rotorcraft, fixed-wing aircraft, advanced short takeoff and vertical landing (ASTOVL), vertical/short takeoff and landing (V/STOL), tiltrotor aircraft, and rotor experiments in the wind tunnel. Excellent system characterization and dynamic response prediction is achieved for this wide class of systems. Examples illustrate the role of system-identification technology in providing an integrated flow of dynamic response data around the entire life-cycle of aircraft development from initial specifications, through simulation and bench testing, and into flight-test optimization.

Tischler, Mark B.↗

Fully integrated aerodynamic/dynamic optimization of helicopter rotor blades

A fully integrated aerodynamic/dynamic optimization procedure is described for helicopter rotor blades. The procedure combines performance and dynamic analyses with a general purpose optimizer. The procedure minimizes a linear combination of power required (in hover, forward flight, and maneuver) and vibratory hub shear. The design variables include pretwist, taper initiation, taper ratio, root chord, blade stiffnesses, tuning masses, and tuning mass locations. Aerodynamic constraints consist of limits on power required in hover, forward flight and maneuvers; airfoil section stall; drag divergence Mach number; minimum tip chord; and trim. Dynamic constraints are on frequencies, minimum autorotational inertia, and maximum blade weight. The procedure is demonstrated for two cases. In the first case, the objective function involves power required (in hover, forward flight and maneuver) and dynamics. The second case involves only hover power and dynamics. The designs from the integrated procedure are compared with designs from a sequential optimization approach in which the blade is first optimized for performance and then for dynamics. In both cases, the integrated approach is superior.

Walsh, Joanne L.↗

An integrated model of the Space Station Freedom active thermal control system

A flexible, generic model of the Space Station Freedom active thermal control system has been developed which is designed to analyze dynamic interactions of the major subsystems of the ATCS. Models are described for the components of the central thermal bus, the radiator external thermal environment, and the internal thermal control system. Two programs are described which facilitate the development of the integrated ATCS model. The first, SIMRAD, simplifies an external thermal environment model given a desired level of accuracy in integrated model performance. The model reduction technique is shown to reduce model execution time significantly while maintaining the desired accuracy. The second, GENFLU, generates SINDA/FLUINT input code for the evaporator and load interface models and automates the integration of load submodels. The component submodels and integration techniques were used to create an integrated model of the thermal control system for an early assembly flight configuration. The results demonstrate the utility of the integrated model in studying dynamic interactions of the ATCS subsystems.

Tandler, John J.↗

Software Management Environment (SME) installation guide

This document contains installation information for the Software Management Environment (SME), developed for the Systems Development Branch (Code 552) of the Flight Dynamics Division of Goddard Space Flight Center (GSFC). The SME provides an integrated set of management tools that can be used by software development managers in their day-to-day management and planning activities. This document provides a list of hardware and software requirements as well as detailed installation instructions and trouble-shooting information.

Kistler, David↗

Moving base simulation of an ASTOVL lift-fan aircraft

Using a generalized simulation model, a moving-base simulation of a lift-fan short takeoff/vertical landing fighter aircraft was conducted on the Vertical Motion Simulator at Ames Research Center. Objectives of the experiment were to (1) assess the effects of lift-fan propulsion system design features on aircraft control during transition and vertical flight including integration of lift fan/lift/cruise engine/aerodynamic controls and lift fan/lift/cruise engine dynamic response, (2) evaluate pilot-vehicle interface with the control system and head-up display including control modes for low-speed operational tasks and control mode/display integration, and (3) conduct operational evaluations of this configuration during takeoff, transition, and landing similar to those carried out previously by the Ames team for the mixed-flow, vectored thrust, and augmentor-ejector concepts. Based on results of the simulation, preliminary assessments of acceptable and borderline lift-fan and lift/cruise engine thrust response characteristics were obtained. Maximum pitch, roll, and yaw control power used during transition, hover, and vertical landing were documented. Control and display mode options were assessed for their compatibility with a range of land-based and shipboard operations from takeoff to cruise through transition back to hover and vertical landing. Flying qualities were established for candidate control modes and displays for instrument approaches and vertical landings aboard an LPH assault ship and DD-963 destroyer. Test pilot and engineer teams from the Naval Air Warfare Center, Boeing, Lockheed, McDonnell Douglas, and the British Defence Research Agency participated in the program.

Chung, William W. Y.↗

Real-Time Minimization of Tracking Error for Aircraft Systems

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

Garud, Sumedha↗

Flight control design considerations for STOVL powered-lift flight

Short Takeoff Vertical Landing (STOVL) aircraft rely on the propulsion system for the lift and control functions during slow speed flight. The propulsion system provides the entire lifting force and all of the control power for hovering flight at zero airspeed. STOVL designs such as the General Dynamics E-7D ejector configuration incorporate an integrated flight/propulsion control system to manage the aerodynamic and propulsive-lift control effectors and to reduce the pilot's workload for powered-lift flight. Desired flying qualities characteristics are implemented through the utilization of an explicit model following flight control system. With the model following control system, the pilot commands the desired response (e.g., throttle commands vertical velocity in hover, instead of power lever angle). Design considerations for developing a multivariable model-following flight control system are presented in this paper. When the regulator gains are defined in terms of generalized controls, the design problem becomes how to best transform the generalized controls to aerodynamic control surface, thrust and thrust vectoring commands.

Vincent, James H.↗

Impact of aeroelasticity on propulsion and longitudinal flight dynamics of an air-breathing hypersonic vehicle

Many air-breathing hypersonic aerospacecraft design concepts incorporate an elongated fuselage forebody acting as the aerodynamic compression surface for a hypersonic combustion module, or scram jet. This highly integrated design approach creates the potential for an unprecedented form of aero-propulsive-elastic interaction in which deflections of the vehicle fuselage give rise to propulsion transients, producing force and moment variations that may adversely impact the rigid body flight dynamics and/or further excite the fuselage bending modes. To investigate the potential for such interactions, a math model was developed which included the longitudinal flight dynamics, propulsion system, and first seven elastic modes of a hypersonic air-breathing vehicle. Perturbation time histories from a simulation incorporating this math model are presented that quantify the propulsive force and moment variations resulting from aeroelastic vehicle deflections. Root locus plots are presented to illustrate the effect of feeding the propulsive perturbations back into the aeroelastic model. A concluding section summarizes the implications of the observed effects for highly integrated hypersonic air-breathing vehicle concepts.

Raney, David L.↗

Proportional and Integral Thermal Control System for Large Scale Heating Tests

The National Aeronautics and Space Administration Armstrong Flight Research Center (Edwards, California) Flight Loads Laboratory is a unique national laboratory that supports thermal, mechanical, thermal/mechanical, and structural dynamics research and testing. A Proportional Integral thermal control system was designed and implemented to support thermal tests. A thermal control algorithm supporting a quartz lamp heater was developed based on the Proportional Integral control concept and a linearized heating process. The thermal control equations were derived and expressed in terms of power levels, integral gain, proportional gain, and differences between thermal setpoints and skin temperatures. Besides the derived equations, user's predefined thermal test information generated in the form of thermal maps was used to implement the thermal control system capabilities. Graphite heater closed-loop thermal control and graphite heater open-loop power level were added later to fulfill the demand for higher temperature tests. Verification and validation tests were performed to ensure that the thermal control system requirements were achieved. This thermal control system has successfully supported many milestone thermal and thermal/mechanical tests for almost a decade with temperatures ranging from 50 F to 3000 F and temperature rise rates from -10 F/s to 70 F/s for a variety of test articles having unique thermal profiles and test setups.

Thermal Control System↗

Integration of Dynamic Weather Routes Automation with Air/Ground Data Communications

The Dynamic Weather Routes (DWR) toolcontinuously and automatically analyzes airborne flights in en route airspace to identify flights where a route correction could save significant flight time and still avoid weather. A partnership between NASA, American Airlines (AA), and the FAA has enabled testing of DWR in real-world air traffic operations. En route Data Communications (Data Comm) could significantly reduce the controller and pilot workload needed to communicate DWR route changes under today’s voice-based operations and thereby enable more timely and frequent high-value corrections to weather avoidance routes. Sample data from the DWR trial at AA illustrate how Data Comm could improve DWR operations. Two operating concepts that integrate DWR with Data Comm are described:(1) route corrections are initiated by air traffic control and implemented using Airborne Reroutes and Data Comm, and (2) route corrections are initiated by the dispatcher and pilot and implemented via Data Comm. Both concepts align with Federal Aviation Administration (FAA) plans for implementation ofData Comm in en route airspace.

weather avoidance↗

Propulsion system performance resulting from an integrated flight/propulsion control design

Propulsion-system-specific results are presented from the application of the integrated methodology for propulsion and airframe control (IMPAC) design approach to integrated flight/propulsion control design for a 'short takeoff and vertical landing' (STOVL) aircraft in transition flight. The IMPAC method is briefly discussed and the propulsion system specifications for the integrated control design are examined. The structure of a linear engine controller that results from partitioning a linear centralized controller is discussed. The details of a nonlinear propulsion control system are presented, including a scheme to protect the engine operational limits: the fan surge margin and the acceleration/deceleration schedule that limits the fuel flow. Also, a simple but effective multivariable integrator windup protection scheme is examined. Nonlinear closed-loop simulation results are presented for two typical pilot commands for transition flight: acceleration while maintaining flightpath angle and a change in flightpath angle while maintaining airspeed. The simulation nonlinearities include the airframe/engine coupling, the actuator and sensor dynamics and limits, the protection scheme for the engine operational limits, and the integrator windup protection. Satisfactory performance of the total airframe plus engine system for transition flight, as defined by the specifications, was maintained during the limit operation of the closed-loop engine subsystem.

Mattern, Duane↗

Dynamic Control System Mode Performance of the Space Technology-7 Disturbance Reduction System

The Space Technology-7 (ST-7) Disturbance Reduction System (DRS) is an experiment package aboard the European Space Agency (ESA) LISA Pathfinder spacecraft, launched on December 3, 2015. DRS consists of three primary components: Colloidal MicroNewton Thrusters (CMNTs), an Integrated Avionics Unit (IAU), and flight-software implementing the Command and Data Handling (C&DH) and Dynamic Control System (DCS) algorithms. The CMNTs were designed to provide thrust from 5 to 30 micro Newton, with thrust controllability and resolution of 0.1 micro Newton and thrust noise of 0.1 micro Newton/(square root of (Hz)) in the measurement band from 1-30 mHz. The IAU hosts the C&DH and DCS flight software, as well as interfaces with both the CMNT electronics and the LISA Pathfinder spacecraft. When in control, the DCS uses star tracker attitude data and capacitive or optically-measured position and attitude information from LISA Pathfinder and the LISA Technology Package (LTP) to control the attitude and position of the spacecraft and the two test masses inside the LTP. After completion of the nominal ESA LISA Pathfinder mission, the DRS experiment was commissioned followed by its nominal mission. DRS operations extended over the next five months, interspersed with station keeping, anomaly resolution, and periods where control was handed back to LISA Pathfinder for them to conduct further experiments. The primary DRS mission ended on December 6, 2016, with the experiment meeting all of its Level 1 requirements. The DCS, developed at the NASA Goddard Space Flight Center, consists of five spacecraft control modes and six test mass control modes, combined into six 'DRS Mission Modes'. Attitude Control and Zero-G were primarily used to control the spacecraft during initial handover and during many of the CMNT characterization experiments. The other Mission Modes, Drag Free Low Force, 18-DOF Transitional, and 18-DOF, were used to provide drag-free control of the spacecraft about the test masses. This paper will discuss the performance of these DCS spacecraft and test mass control modes. Flight data will be shown from each mode throughout the mission, both from nominal operations and during various flight experiments. The DCS team also made some changes to controller, filter, and limit parameters during operations; the motivation and results of these changes will be shown and discussed.

O'Donnell, James R., Jr.↗

Software Management Environment (SME) release 9.4 user reference material

This document contains user reference material for the Software Management Environment (SME) prototype, developed for the Systems Development Branch (Code 552) of the Flight Dynamics Division (FDD) of Goddard Space Flight Center (GSFC). The SME provides an integrated set of management tools that can be used by software development managers in their day-to-day management and planning activities. This document provides an overview of the SME, a description of all functions, and detailed instructions concerning the software's installation and use.

Hendrick, R.↗

Technology Integration (Task 20) Aeroservoelastic Modeling and Design Studies: Evaluation of Aeroservoelastic Effects on Flutter and Dynamic Gust Response - Part A

The HSCT Flight Controls Group has developed longitudinal control laws, utilizing PTC aeroelastic flexible models to minimize aeroservoelastic interaction effects, for a number of flight conditions. The control law design process resulted in a higher order controller and utilized a large number of sensors distributed along the body for minimizing the flexibility effects. Processes were developed to implement these higher order control laws for performing the dynamic gust loads and flutter analyses. The processes and its validation were documented in Reference 2, for selected flight condition. The analytical results for additional flight conditions are presented in this document for further validation.

Nagaraja, K. S.↗

Benefits Analysis of Multi-Center Dynamic Weather Routes

Dynamic weather routes are flight plan corrections that can provide airborne flights more than user-specified minutes of flying-time savings, compared to their current flight plan. These routes are computed from the aircraft's current location to a flight plan fix downstream (within a predefined limit region), while avoiding forecasted convective weather regions. The Dynamic Weather Routes automation has been continuously running with live air traffic data for a field evaluation at the American Airlines Integrated Operations Center in Fort Worth, TX since July 31, 2012, where flights within the Fort Worth Air Route Traffic Control Center are evaluated for time savings. This paper extends the methodology to all Centers in United States and presents benefits analysis of Dynamic Weather Routes automation, if it was implemented in multiple airspace Centers individually and concurrently. The current computation of dynamic weather routes requires a limit rectangle so that a downstream capture fix can be selected, preventing very large route changes spanning several Centers. In this paper, first, a method of computing a limit polygon (as opposed to a rectangle used for Fort Worth Center) is described for each of the 20 Centers in the National Airspace System. The Future ATM Concepts Evaluation Tool, a nationwide simulation and analysis tool, is used for this purpose. After a comparison of results with the Center-based Dynamic Weather Routes automation in Fort Worth Center, results are presented for 11 Centers in the contiguous United States. These Centers are generally most impacted by convective weather. A breakdown of individual Center and airline savings is presented and the results indicate an overall average savings of about 10 minutes of flying time are obtained per flight.

NAS based Benefits Analysis↗