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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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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Chance-Constrained System Identification of Nonlinear Discrete Systems with Safety and Stability Guarantees

This paper presents a discrete-time nonlinear system identification method while satisfying the stability and safety properties of the system with high probability. An Extreme Learning Machine (ELM) is used with a Gaussian assumption on the function reconstruction error. A quadratically constrained quadratic program (QCQP) is developed with probabilistic safety and stability constraints that are only required to be satisfied at sampled points inside the invariant region. The proposed method is validated using two simulation examples: a two degrees-of-freedom (DoF) robot manipulator with constraints on joint angles whose trajectories are guaranteed to remain inside a safe set and on motion trajectories data of a hand-drawn shape.

Iman Salehi↗
DOE OSTI2026

Integral Kernel Methods for Nonlinear Parabolic-Elliptic Systems

Nonlinear parabolic-elliptic systems arise in many physical, biological, and chemical phenomena such as chemotaxis, ion transport, self-gravitating particles, and Brownian vortices. Existing methods struggle with the strong coupling and high nonlinearity and nonlocality of some of these systems, especially the ill-conditioned, convection-dominated problems. To overcome numerical difficulties, current approaches rely on initial guesses, preconditioning, or iterative techniques with no convergence guarantees. They might suffer from poor scalability, large memory usage, and difficulty to parallelize. Inspired by the connection of parabolic-elliptic systems to stochastic processes, we introduce a novel meshless, monolithic, and fully explicit method that naturally encapsulates the elliptic and parabolic operators into a single step which updates each node deterministically with global information. By being fully quadrature-based, it avoids solving systems of discretized equations and does not utilize initial guesses or preconditioning, while requiring little memory and being easy to parallelize. We first derive the method in an integral kernel formulation with quadratic complexity in the number of integration nodes and then leverage kernel-independent fast multipole methods (FMM) to present a scalable algorithm with linear complexity. We provide numerical examples for the Poisson-Nernst-Planck equations in one, two, and three dimensions, together with the derivation of the integral kernel for each case. Furthermore, the examples demonstrate the fast convergence and scalability of the FMM-accelerated algorithm, as well as its suitability for convection-dominated problems, making it competitive against traditional PDE solvers.

PDE systems↗
NASA NTRS1988

Dynamic analysis of nonlinear rotor-housing systems

Nonlinear analysis methods are developed which will enable the reliable prediction of the dynamic behavior of the space shuttle main engine (SSME) turbopumps in the presence of bearing clearances and other local nonlinearities. A computationally efficient convolution method, based on discretized Duhamel and transition matrix integral formulations, is developed for the transient analysis. In the formulation, the coupling forces due to the nonlinearities are treated as external forces acting on the coupled subsystems. Iteration is utilized to determine their magnitudes at each time increment. The method is applied to a nonlinear generic model of the high pressure oxygen turbopump (HPOTP). As compared to the fourth order Runge-Kutta numerical integration methods, the convolution approach proved to be more accurate and more highly efficient. For determining the nonlinear, steady-state periodic responses, an incremental harmonic balance method was also developed. The method was successfully used to determine dominantly harmonic and subharmonic responses fo the HPOTP generic model with bearing clearances. A reduction method similar to the impedance formulation utilized with linear systems is used to reduce the housing-rotor models to their coordinates at the bearing clearances. Recommendations are included for further development of the method, for extending the analysis to aperiodic and chaotic regimes and for conducting critical parameteric studies of the nonlinear response of the current SSME turbopumps.

Noah, Sherif T.↗
NASA NTRS2008

2007 Research and Engineering Annual Report

Selected research and technology activities at NASA Dryden Flight Research Center are summarized. These following activities exemplify the Center's varied and productive research efforts: Developing a Requirements Development Guide for an Automatic Ground Collision Avoidance System; Digital Terrain Data Compression and Rendering for Automatic Ground Collision Avoidance Systems; Nonlinear Flutter/Limit Cycle Oscillations Prediction Tool; Nonlinear System Identification Using Orthonormal Bases: Application to Aeroelastic/Aeroservoelastic Systems; Critical Aerodynamic Flow Feature Indicators: Towards Application with the Aerostructures Test Wing; Multidisciplinary Design, Analysis, and Optimization Tool Development Using a Genetic Algorithm; Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool; Extension of Ko Straight-Beam Displacement Theory to the Deformed Shape Predictions of Curved Structures; F-15B with Phoenix Missile and Pylon Assembly--Drag Force Estimation; Mass Property Testing of Phoenix Missile Hypersonic Testbed Hardware; ARMD Hypersonics Project Materials and Structures: Testing of Scramjet Thermal Protection System Concepts; High-Temperature Modal Survey of the Ruddervator Subcomponent Test Article; ARMD Hypersonics Project Materials and Structures: C/SiC Ruddervator Subcomponent Test and Analysis Task; Ground Vibration Testing and Model Correlation of the Phoenix Missile Hypersonic Testbed; Phoenix Missile Hypersonic Testbed: Performance Design and Analysis; Crew Exploration Vehicle Launch Abort System-Pad Abort-1 (PA-1) Flight Test; Testing the Orion (Crew Exploration Vehicle) Launch Abort System-Ascent Abort-1 (AA-1) Flight Test; SOFIA Flight-Test Flutter Prediction Methodology; SOFIA Closed-Door Aerodynamic Analyses; SOFIA Handling Qualities Evaluation for Closed-Door Operations; C-17 Support of IRAC Engine Model Development; Current Capabilities and Future Upgrade Plans of the C-17 Data Rack; Intelligent Data Mining Capabilities as Applied to Integrated Vehicle Health Management; STARS Flight Demonstration No. 2 IP Data Formatter; Space-Based Telemetry and Range Safety (STARS) Flight Demonstration No. 2 Range User Flight Test Results; Aerodynamic Effects of the Quiet Spike(tm) on an F-15B Aircraft; F-15 Intelligent Flight Controls-Increased Destabilization Failure; F-15 Integrated Resilient Aircraft Control (IRAC) Improved Adaptive Controller; Aeroelastic Analysis of the Ikhana/Fire Pod System; Ikhana: Western States Fire Missions Utilizing the Ames Research Center Fire Sensor; Ikhana: Fiber-Optic Wing Shape Sensors; Ikhana: ARTS III; SOFIA Closed-Door Flutter Envelope Flight Testing; F-15B Quiet Spike(TM) Aeroservoelastic Flight Test Data Analysis; and UAVSAR Platform Precision Autopilot Flight Results.

Stoliker, Patrick↗
DOE OSTI2020

Dynamic Performance Enhancement for Nonlinear Stochastic Systems Using RBF Driven Nonlinear Compensation with Extended Kalman Filter

In this paper, a novel hybrid control method is proposed to enhance the control performance of the PI based control system for a class of nonlinear and non-Gaussian stochastic dynamic processes with unmeasurable states. Firstly, to enhance the tracking performance of the PI controller where the PI parameters are fixed in many actual control systems, the compensative signal is formed using the extended Kalman filter(EKF) based state estimator and driven by the radial basis function (RBF) neural network based compensator. In addition, the weights of RBF is trained to minimize the entropy criterion of tracking error as the process is subjected to non-Gaussian disturbances. Meanwhile, since the precise statistical property of noises is hard to obtain for many industrial processes, the kernel density estimation (KDE) technique is employed in this paper to estimate the entropy. The convergence of RBF network is discussed and the stability of the resulted closed-loop hybrid control system is analyzed in mean square sense. Finally, a numerical example and a practical system testing are given to illustrate the effectiveness of the proposed control method.

stochastic systems, PI Controller, Entropy, Extend↗