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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.

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216 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

An Analysis of the Optimal Control Modification Method Applied to Flutter Suppression

Unlike basic Model Reference Adaptive Control (MRAC)l, Optimal Control Modification (OCM) has been shown to be a promising MRAC modification with robustness and analytical properties not present in other adaptive control methods. This paper presents an analysis of the OCM method, and how the asymptotic property of OCM is useful for analyzing and tuning the controller. We begin with a Lyapunov stability proof of an OCM controller having two adaptive gain terms, then the less conservative and easily analyzed OCM asymptotic property is presented. Two numerical examples are used to show how this property can accurately predict steady state stability and quantitative robustness in the presence of time delay, and relative to linear plant perturbations, and nominal Loop Transfer Recovery (LTR) tuning. The asymptotic property of the OCM controller is then used as an aid in tuning the controller applied to a large scale aeroservoelastic longitudinal aircraft model for flutter suppression. Control with OCM adaptive augmentation is shown to improve performance over that of the nominal non-adaptive controller when significant disparities exist between the controller/observer model and the true plant model.

aeroservoelasti↗
NASA NTRS2019

Flight Control Research at NASA Ames

An overview of the flight control work in the Intelligent Systems Division at NASA Ames is presented. The highlight focuses on efforts surrounding performance-adaptive aeroelastic wing shaping for aircraft with flexible wings. Topics covered include aeroservoelastic modeling capabilities, online drag-optimizing control designs, gust and maneuver load alleviation techniques, and related wind tunnel demonstrations.

Hashemi, Kelley↗
NASA NTRS2018

Update on the Development of a Flutter Analysis Capability for Unconventional Aircraft Concepts Using HCDstruct

Following years of development, the Higher-fidelity Conceptual Design and structural optimization (HCDstruct) tool is being extended to support dynamic aeroservoelastic analysis and structural optimization for advanced aircraft concepts. These required enhancements include: the development of an aerodynamic matching routine for correcting Nastran’s doublet-lattice method aerodynamics; the implementation of control surface structural models; and the implementation of support for Nastran’s flutter solution sequence (SOL 145). This paper presents an update on the implementation of generalized control surface structural models and support for Nastran SOL 145.

Quinlan, Jesse R.↗
NASA NTRS2020

Optimal Aircraft Control Surface Layouts for Maneuver and Gust Load Alleviation

The goal of this work is to conduct aeroservoelastic optimization of a high aspect ratio transport wingbox with distributed control surfaces along the trailing edge. The control surfaces are utilized for both quasi-steady maneuver load alleviation (MLA) and unsteady gust load alleviation (GLA). The optimizer dictates the sizing details of the wingbox, the steady and unsteady control surface rotations, and also the control surface layout. Layout design variables specifically dictate which control surfaces to retain, and which to remove. The objective function is to minimize the sum of the actuator weight and the structural weight, with several imposed constraints related to structural failure and actuator saturation. The optimizer’s preferences with regards to control surface layout for MLA are in strong contrast to GLA-driven designs. The GLA-driven design space also suffers from local minima not evident in the MLA space.

Stanford, Bret K.↗
DOE OSTI2021

Validation Efforts of an Open-Source Aeroacoustics Model for Wind Turbines: Preprint

The open source aeroservoelastic wind turbine solver, OpenFAST, now includes an aeroacoustics model, which is described here and validated against experimental measurements recorded on a GE 1.5-MW wind turbine installed at the Flatirons Campus of the National Renewable Energy Laboratory in Boulder, Colorado. The validation demonstrates satisfactory agreement between numerical predictions and experimental recordings, with discrepancies up to 7 dB in the overall sound pressure levels at low wind speeds and a better agreement around the rated wind speed of the turbine.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
NASA NTRS2014

Static Aeroelastic and Longitudinal Trim Model of Flexible Wing Aircraft Using Finite-Element Vortex-Lattice Coupled Solution

This paper presents a static aeroelastic model and longitudinal trim model for the analysis of a flexible wing transport aircraft. The static aeroelastic model is built using a structural model based on finite-element modeling and coupled to an aerodynamic model that uses vortex-lattice solution. An automatic geometry generation tool is used to close the loop between the structural and aerodynamic models. The aeroelastic model is extended for the development of a three degree-of-freedom longitudinal trim model for an aircraft with flexible wings. The resulting flexible aircraft longitudinal trim model is used to simultaneously compute the static aeroelastic shape for the aircraft model and the longitudinal state inputs to maintain an aircraft trim state. The framework is applied to an aircraft model based on the NASA Generic Transport Model (GTM) with wing structures allowed to flexibly deformed referred to as the Elastically Shaped Aircraft Concept (ESAC). The ESAC wing mass and stiffness properties are based on a baseline "stiff" values representative of current generation transport aircraft.

Aeroelasticity↗
NASA NTRS2014

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↗
NASA NTRS2014

Static Aeroelastic Scaling and Analysis of a Sub-Scale Flexible Wing Wind Tunnel Model

This paper presents an approach to the development of a scaled wind tunnel model for static aeroelastic similarity with a full-scale wing model. The full-scale aircraft model is based on the NASA Generic Transport Model (GTM) with flexible wing structures referred to as the Elastically Shaped Aircraft Concept (ESAC). The baseline stiffness of the ESAC wing represents a conventionally stiff wing model. Static aeroelastic scaling is conducted on the stiff wing configuration to develop the wind tunnel model, but additional tailoring is also conducted such that the wind tunnel model achieves a 10% wing tip deflection at the wind tunnel test condition. An aeroelastic scaling procedure and analysis is conducted, and a sub-scale flexible wind tunnel model based on the full-scale's undeformed jig-shape is developed. Optimization of the flexible wind tunnel model's undeflected twist along the span, or pre-twist or wash-out, is then conducted for the design test condition. The resulting wind tunnel model is an aeroelastic model designed for the wind tunnel test condition.

Aeroelasticity↗
NASA NTRS2015

Active Structural Control for Aircraft Efficiency with the X-56A Aircraft

The X-56A Multi-Utility Technology Testbed is an experimental aircraft designed to study active control of flexible structures. The vehicle is easily reconfigured to allow for testing of different configurations. The vehicle is being used to study new sensor, actuator, modeling and controls technologies. These new technologies will allow for lighter vehicles and new configurations that exceed the efficiency currently achievable. A description of the vehicle and the current research efforts that it enables are presented.

aeroservoelasticity↗
NASA NTRS2016

Towards an Aero-Propulso-Servo-Elasticity Analysis of a Commercial Supersonic Transport

This paper covers the development of an aero-propulso-servo-elastic (APSE) model using computational fluid dynamics (CFD) and linear structural deformations. The APSE model provides the integration of the following two previously developed nonlinear dynamic simulations: a variable cycle turbofan engine and an elastic supersonic commercial transport vehicle. The primary focus of this study is to provide a means to include relevant dynamics of a turbomachinery propulsion system into the aeroelastic studies conducted during a vehicle design, which have historically neglected propulsion effects. A high fidelity CFD tool is used here for the integration platform. The elastic vehicle neglecting the propulsion system serves as a comparison of traditional approaches to the APSE results. An overview of the methodology is presented for integrating the propulsion system and elastic vehicle. Static aeroelastic analysis comparisons between the traditional and developed APSE models for a wing tip detection indicate that the propulsion system impact on the vehicle elastic response could increase the detection by approximately ten percent.

aeroservoelasticity↗
NASA NTRS2016

Real-Time Adaptive Least-Squares Drag Minimization for Performance Adaptive Aeroelastic Wing

This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.

Aeroservoelasticity↗
NASA NTRS2016

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↗
NASA NTRS2017

Flight Control of Flexible Aircraft

This presentation presents an overview of flight control research for flexible high aspect wing aircraft in support of the NASA ARMD Advanced Air Transport Technology (AATT) project. It summarizes multi-objective flight control technology being developed for drag optimization, flutter suppression, and maneuver and gust load alleviation.

Aeroservoelasticity↗
NASA NTRSDate not supplied

Method for Real-Time State Estimation of Structural Modes for an Aeroelastic Wind Tunnel Model

A method for estimating displacements, velocities, and accelerations of structural modes in generalized coordinates from measured sensor data in real time is developed and demonstrated. Data from conventional strain gauges and fiber optic strain sensors (FOSS) were combined with strain mode shapes to produce least-squares estimates of the structural mode displacements. Similarly, accelerometer data were combined with displacement mode shapes to estimate structural mode accelerations. Estimates were then combined using a Kalman filter to refine the displacement estimates and produce structural mode velocity estimates. The approach was demonstrated using simulation data for the NASA-Boeing collaboration called the Integrated Adaptive Wing Technology Maturation (IAWTM) project in both a stable open-loop condition and an unstable condition where estimated displacement and velocity states were used for feedback control. Results supported the feasibility of using this approach for feedback control and system identification applications for wind tunnel tests.

Aeroservoelasticity↗
NASA NTRSDate not supplied

Overview of the Integrated Adaptive Wing Technology Maturation Wind-Tunnel Test Objectives

The Integrated Adaptive Wing Technology Maturation wind-tunnel test is the culmination of a cooperative effort between NASA and Boeing to develop control techniques that can improve the performance and safety of higher aspect ratio flexible transport aircraft. The wind-tunnel test article, to be tested at the NASA Langley Research Center Transonic Dynamics Tunnel, is a semispan model of a modern transport configuration based on the NASA Common Research Model with an aspect ratio 13.5 wing. Multiobjective control laws have been developed targeting drag optimization, maneuver load alleviation, gust load alleviation, and active flutter suppression. In this paper, the integrated model design, active control system, and sensor suite will be presented, and pretest modeling and characterization activities will be described. A summary of the planned wind-tunnel test entries will provide an overview of the experimental approach and expected outcomes.

wind-tunnel↗
NASA NTRSDate not supplied

Overview of the Integrated Adaptive Wing Technology Maturation Wind-Tunnel Test Objectives

The Integrated Adaptive Wing Technology Maturation wind-tunnel test is the culmination of a cooperative effort between NASA and Boeing to develop control techniques that can improve the performance and safety of higher aspect ratio flexible transport aircraft. The wind-tunnel test article, to be tested at the NASA Langley Research Center Transonic Dynamics Tunnel, is a semispan model of a modern transport configuration with an aspect ratio 13.5 wing based on the NASA Common Research Model. Multiobjective control laws have been developed targeting drag optimization, maneuver load alleviation, gust load alleviation, and modal suppression. In this paper, the integrated model design, active control system, and sensor suite will be presented, and pretest modeling and characterization activities will be described. A summary of the planned wind-tunnel test entries will provide an overview of the experimental approach and expected outcomes.

wind-tunnel↗