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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Computational requirements for on-orbit identification of space systems

For the future space systems, on-orbit identification (ID) capability will be required to complement on-orbit control, due to the fact that the dynamics of large space structures, spacecrafts, and antennas will not be known sufficiently from ground modeling and testing. The computational requirements for ID of flexible structures such as the space station (SS) or the large deployable reflectors (LDR) are however, extensive due to the large number of modes, sensors, and actuators. For these systems the ID algorithm operations need not be computed in real-time, only in near real-time, or an appropriate mission time. Consequently the space systems will need advanced processors and efficient parallel processing algorithm design and architectures to implement the identification algorithms in near real-time. The MAX computer currently being developed may handle such computational requirements. The purpose is to specify the on-board computational requirements for dynamic and static identification for large space structures. The computational requirements for six ID algorithms are presented in the context of three examples: the JPL/AFAL ground antenna facility, the space station (SS), and the large deployable reflector (LDR).

Hadaegh, Fred Y.↗
NASA NTRS1998

Interior Noise Reduction by Adaptive Feedback Vibration Control

The objective of this project is to investigate the possible use of adaptive digital filtering techniques in simultaneous, multiple-mode identification of the modal parameters of a vibrating structure in real-time. It is intended that the results obtained from this project will be used for state estimation needed in adaptive structural acoustics control. The work done in this project is basically an extension of the work on real-time single mode identification, which was performed successfully using a digital signal processor (DSP) at NASA, Langley. Initially, in this investigation the single mode identification work was duplicated on a different processor, namely the Texas Instruments TMS32OC40 DSP. The system identification results for the single mode case were very good. Then an algorithm for simultaneous two mode identification was developed and tested using analytical simulation. When it successfully performed the expected tasks, it was implemented in real-time on the DSP system to identify the first two modes of vibration of a cantilever aluminum beam. The results of the simultaneous two mode case were good but some problems were identified related to frequency warping and spurious mode identification. The frequency warping problem was found to be due to the bilinear transformation used in the algorithm to convert the system transfer function from the continuous-time domain to the discrete-time domain. An alternative approach was developed to rectify the problem. The spurious mode identification problem was found to be associated with high sampling rates. Noise in the signal is suspected to be the cause of this problem but further investigation will be needed to clarify the cause. For simultaneous identification of more than two modes, it was found that theoretically an adaptive digital filter can be designed to identify the required number of modes, but the algebra became very complex which made it impossible to implement in the DSP system used in this study. The on-line identification algorithm developed in this research will be useful in constructing a state estimator for feedback vibration control.

Lim, Tae W.↗
NASA NTRS1975

Manned Orbital Systems Concepts Study. Book 1: Executive Summary

Requirements for and definitions of a cost effective orbital facility concept, capable of supporting extended manned operations in earth orbit beyond those visualized for the 7 to 30 day shuttle/spacelab system, were studied. Data are given on requirements derivation, concepts identification, systems analysis and definition, and programmatics.

Source record↗
NASA NTRS2008

Ares-I-X Stability and Control Flight Test: Analysis and Plans

The flight test of the Ares I-X vehicle provides a unique opportunity to reduce risk of the design of the Ares I vehicle and test out design, math modeling, and analysis methods. One of the key features of the Ares I design is the significant static aerodynamic instability coupled with the relatively flexible vehicle - potentially resulting in a challenging controls problem to provide adequate flight path performance while also providing adequate structural mode damping and preventing adverse control coupling to the flexible structural modes. Another challenge is to obtain enough data from the single flight to be able to conduct analysis showing the effectiveness of the controls solutions and have data to inform design decisions for Ares I. This paper will outline the modeling approaches and control system design to conduct this flight test, and also the system identification techniques developed to extract key information such as control system performance (gain/phase margins, for example), structural dynamics responses, and aerodynamic model estimations.

Brandon, Jay M.↗
DOE OSTI2024

STOPGAP—A time-of-flight extension for the Belle II TOP barrel PID system

The Belle II barrel region is instrumented with the Time of Propagation (TOP) particle identification system. Due to its mechanical design, the individual TOP modules do not overlap, leaving a gap of around 2 cm between them in the azimuthal direction. This leads to a 6%–9% drop in acceptance, depending on the track’s momentum. We propose a solution to remedy these gaps by instrumenting them with fast silicon detectors to directly measure the time-of-flight of traversing particles. We present here a simulation study discussing the performance requirements and the possible sensor technologies, and we demonstrate that such a project could be realized with novel, fast monolithic CMOS sensors, or alternatively AC-LGAD sensors, both of which are expected to reach MIP timing resolutions of down to 50 ps or better.

Hartbrich, Oskar↗
NASA NTRS1999

Signal Prediction With Input Identification

A novel coding technique is presented for signal prediction with applications including speech coding, system identification, and estimation of input excitation. The approach is based on the blind equalization method for speech signal processing in conjunction with the geometric subspace projection theory to formulate the basic prediction equation. The speech-coding problem is often divided into two parts, a linear prediction model and excitation input. The parameter coefficients of the linear predictor and the input excitation are solved simultaneously and recursively by a conventional recursive least-squares algorithm. The excitation input is computed by coding all possible outcomes into a binary codebook. The coefficients of the linear predictor and excitation, and the index of the codebook can then be used to represent the signal. In addition, a variable-frame concept is proposed to block the same excitation signal in sequence in order to reduce the storage size and increase the transmission rate. The results of this work can be easily extended to the problem of disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. Simulations are included to demonstrate the proposed method.

Juang, Jer-Nan↗
DOE OSTI2020

Affinity propagation clustering of full-field, high-spatial-dimensional measurements for robust output-only modal identification: A proof-of-concept study

Determination of the model order is a challenging problem in system identification, especially in output-only or operational modal identification where some modes are weakly excited. While existing methods such as the stabilization diagram method (spectral information) are effective, they do not scale to high-dimensional data, which is usually needed for high-fidelity characterization of structural dynamics and has been made available in the emerging full-field measurement techniques using optical methods such as photogrammetry and laser vibrometers. In this proof-of-concept study we present a new non-parametric, data-driven approach for robust output-only identification of high-spatial-dimensional modal parameters of basic structures by efficiently processing and interactively exploiting the full-field measurement (i.e., very dense spatial measurement points). Specifically, we first over-estimate the system model once, producing a pool of candidate modes associated with their modal frequencies and full-field, high-spatial-dimensional mode shapes. This is accomplished by a data-driven method termed affinity propagation clustering (APC), where the active clusters, which are the active modes in our formulations, emerge from the "message-passing" procedure and does not require a pre-determination of the cluster number (mode or model order). Next, rather than using the spectral information to distinguish the physical and spurious modes in the stabilization diagram method, we exploit and visualize the spatial, full-field mode shape associated with each candidate mode to do so. We conduct extensive experiments on basic structural models with comparisons to a few existing methods. The results indicate that the new method is computationally efficient for identifying high-spatial-dimensional modal parameters, and robust to identify weak modes by exploiting the full-field measurement. We also discuss its applicability and limitations for structures with complex geometry (shapes).

42 ENGINEERING↗
NASA NTRS1991

Parameter identification for nonlinear aerodynamic systems

Work continues on frequency analysis for transfer function identification, both with respect to the continued development of the underlying algorithms and in the identification study of two physical systems. Some new results of a theoretical nature were recently obtained that lend further insight into the frequency domain interpretation of the research. Progress in each of those areas is summarized. Although not related to the system identification problem, some new results were obtained on the feedback stabilization of linear time lag systems.

Pearson, Allan E.↗
DOE OSTI2013

Technical Assessment of the Passive Neutron Enrichment Meter (PNEM) for an Unattended Cylinder Verification Station (UCVS)

The International Atomic Energy Agency (IAEA) is exploring the potential roles of an Unattended Cylinder Verifications Station (UCVS) in a new generation of safeguards technology for uranium enrichment plants. The UCVS is envisioned to combine an operator accountancy scale, a nondestructive assay (NDA) system such as the Passive Neutron Enrichment Meter (PNEM), a cylinder identification system, and a surveillance system for verification of product, feed, and tails cylinders as well as continuity of knowledge at material balance area boundaries. The IAEA has identified several preliminary requirements and development questions for the UCVS. Specifically, the IAEA has identified the accuracy of the enrichment assay as the key metric for the NDA system with uncertainty targets of 3%, 6%, and 9% on product, feed, and tails cylinders, respectively. The NDA system should also provide full volume interrogation of the cylinders in order to ensure detection of partial defects within the cylinder. The development questions are concerned primarily with the sources and magnitude of the uncertainty and quantitative analysis of the interrogation depth and partial defect sensitivity. The objective of this report is to address these requirements and questions based on Monte Carlo modeling and field trial experience with the PNEM.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1983

Structural control research and experiments at NASA/LaRC

The advances made in the area of structural dynamics and control using the flexible beam facility at the NASA Langley Research Center are surveyed. Spectral attention is given to the progress in adaptive control and reliability improvements using advanced control concepts. Both theoretical and experimental results are given to delineate the nature of the work being undertaken. With regard to adaptive control, emphasis is placed on parameter and system identification and on comparisons between competing on-line algorithms. In addition, results are presented for on-line modal control laws that are interfaced to a parameter identification scheme. This gives an on-line distributed adaptive control system. With regard to reliability, a design process is outlined that incorporates reliability over the design mission life.

Montgomery, R. C.↗
NASA NTRS1983

Structural control research and experiments at NASA/LaRC

Research progress in the area of structural dynamics and control using the flexible beam facility at the NASA Langley Research Center is reviewed. Particular attention is placed on the progress in adaptive control and reliability improvements using advanced control concepts. Both theoretical and experimental results are given to indicate the nature of the work being undertaken. In the adaptive control area, emphasis is placed on parameter and system identification and in comparison of competing on-line algorithms. Also, results are presented for on-line modal control laws that are interfaced to a parameter identification scheme. This provides an on-line distributed adaptive control system. In the reliability area, a design process is outlined that incorporates reliability over the design mission life.

Montgomery, R. C.↗
NASA NTRS2000

Structural Modeling Using "Scanning and Mapping" Technique

Supported by NASA Glenn Center, we are in the process developing a structural damage diagnostic and monitoring system for rocket engines, which consists of five modules: Structural Modeling, Measurement Data Pre-Processor, Structural System Identification, Damage Detection Criterion, and Computer Visualization. The function of the system is to detect damage as it is incurred by the engine structures. The scientific principle to identify damage is to utilize the changes in the vibrational properties between the pre-damaged and post-damaged structures. The vibrational properties of the pre-damaged structure can be obtained based on an analytic computer model of the structure. Thus, as the first stage of the whole research plan, we currently focus on the first module - Structural Modeling. Three computer software packages are selected, and will be integrated for this purpose. They are PhotoModeler-Pro, AutoCAD-R14, and MSC/NASTRAN. AutoCAD is the most popular PC-CAD system currently available in the market. For our purpose, it plays like an interface to generate structural models of any particular engine parts or assembly, which is then passed to MSC/NASTRAN for extracting structural dynamic properties. Although AutoCAD is a powerful structural modeling tool, the complexity of engine components requires a further improvement in structural modeling techniques. We are working on a so-called "scanning and mapping" technique, which is a relatively new technique. The basic idea is to producing a full and accurate 3D structural model by tracing on multiple overlapping photographs taken from different angles. There is no need to input point positions, angles, distances or axes. Photographs can be taken by any types of cameras with different lenses. With the integration of such a modeling technique, the capability of structural modeling will be enhanced. The prototypes of any complex structural components will be produced by PhotoModeler first based on existing similar components, then passed to AutoCAD for modification and correction of any discrepancies seen in the Photomodeler version of the 3Dmodel. These three software packages are fully compatible. The DXF file can be used to transfer drawings among those packages. To begin this entire process, we are using a small replica of an actual engine blade as a test object. This paper introduces the accomplishment of our recent work.

Amos, Courtney L.↗
NASA NTRS1997

Flutter Boundary Identification From Simulation Time Histories

While there has been much recent progress in simulating nonlinear aeroelastic systems, and in predicting many of the aeroelastic phenomena of concern in transport aircraft design (i.e. transonic flutter buckets), the utility of a simulation in generating an understanding of the flutter behavior is limited. This is due in part to the high cost of generating these simulations; and the implied limitation on the number of conditions that can be analyzed, but there are also some difficulties introduced by the very nature of a simulation. Flutter engineers have traditionally worked in the frequency domain, and are accustomed to describing the flutter behavior of an airplane in terms of its V-G and V-F (or Q-G and Q-F) plots and flutter mode shapes. While the V-G and V-F plots give information about how the dynamic response of an airplane changes as the airspeed is increased, the simulation only gives information about one isolated condition (Mach, airspeed, altitude, etc.). Therefore, where a traditional flutter analysis can let the engineer determine an airspeed at which an airplane becomes unstable, while a simulation only serves as a binary check: either the airplane is fluttering at this condition, or it is not. In this document, a new technique is described in which system identification is used to easily extract modal frequencies and damping ratios from simulation time histories, and shows how the identified parameters can be used to determine the variation in frequency and dampin,o ratio as the airspeed is changed. This technique not only provides the flutter engineer with added insight into the aeroelastic behavior of the airplane, but it allows calculation of flutter mode shapes, and allows estimation of flutter boundaries while minimizing the number of simulations required.

Baker, Myles↗
DOE OSTI2024

Power System Frequency Dynamics Modeling, State Estimation, and Control using Neural Ordinary Differential Equations (NODEs) and Soft Actor-Critic (SAC) Machine Learning Approaches

With the global energy transition of the electric power system, grid control, supervision, and protection is becoming more challenging. With the increasing integration of renewable energy sources (RES), the system dynamics are changing, causing traditional power system dynamic modeling with swing equation-based modeling approaches to fail. Additionally, the converter-dominated power grid is decreasing the system inertia, making the power system more fragile to the frequency swings. This paper first investigates and compares the application of a model-based Kalman filter state estimation approach with (i) a model-free machine learning approach --- neural ordinary differential equations (NODEs) --- and (ii) a data-driven system identification (SysId) approach to model and infer critical state values of the power system frequency dynamics. Then a model predictive control (MPC) framework is compared to a model-free Soft Actor-Critic (SAC) reinforcement learning (RL) control algorithm in providing efficient fast frequency response (FFR) to the power system frequency dynamics. The approaches are compared in terms of their performance goals as well as their per-timestep computational efficiency. Furthermore, the comparative study for state estimation shows that for the model-free requirement, both NODEs and SysId can provide accurate state estimates; however, with increasing model complexity, NODEs can be a better choice for model identification. Similarly, the results from the FFR comparative study show that the SAC RL-based FFR, once trained, outperforms MPC with better control signals and faster computation time, making the SAC RL-based FFR better option for providing FFR to the power system.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Parameter identification in distributed systems

This paper describes a method for the identification of the parameters entering into the equations of motion of distributed systems. Because the motion of distributed systems is described in terms of partial differential equations, these parameters are in general continuous functions of the spatial variables. For vibrating systems, these parameters ordinarily represent the mass, stiffness and damping distributions. In this paper, these distributions are expanded in terms of finite series of known functions of the spatial variables multiplied by undetermined coefficients. It is assumed that the nature of the equations of motion is known and that a limited number of eigenvalues and eigenfunctions is identified in advance. Use is then made of the least squares method, in conjunction with the eigenfunctions' orthogonality, to compute the undetermined coefficients, thus identifying the system distributed parameters. A method for the identification of the eigensolution is also presented. The procedure for the identification of the eigensolution and of the system parameters is demonstrated via a numerical example.

Baruh, H.↗
NASA NTRSDate not supplied

Frequency Domain Quasi Maximum Likelihood Identification of Low Order Aeroservoelastic Models from Flight-Test Data

Background and Motivation - Low Order Equivalent System (LOES) - From handling qualities analysis - Traditionally simplifying complex control law and plant - More easily understood form - Extend LOES to a complex model due to aeroelasticity - Maximum likelihood (Filter Error) System Identification - Z = H_loes (U + W) + V - There are a lot of parameters - Estimate noise parameters - Extra outputs mean extra parameters to estimate - Usually assume noise model to simplify - Output Error and Equation Error - Results in biased estimates of the parameters - Sensing flexible aircraft have many outputs - Quasi maximum likelihood exploits redundancy of outputs

Jeffrey Ouellette↗
DOE OSTI2024

A Data-driven approach to Determining the Fidelity in the Hardware-in-the-loop Systems using Subspace Identification Method

One of the major questions in any Hardware-in-the-loop (HiL) simulation is to understand the fidelity of the HiL simulation itself which is most often indicated qualitatively as either high or low instead of quantifying it. Being cognizant of the level of fidelity forms the crux to assess the validity and credibility of the HiL simulation. In this work, we address this issue by developing a systematic, data-driven approach to assess the fidelity of any HiL simulation, and more specifically, the fidelity of the interface between the simulator and hardware in an HiL simulation. Applying a subspace identification method, a linear system representing the interface is obtained from the time-series data captured between the hardware and simulator in the HiL simulation. Finally, the fidelity is defined based on this linear system properties. The proposed data-driven fidelity quantification framework is illustrated on the IEEE 123 node feeder system running on HYPERSIM and interacting with virtual protection relays.

97 MATHEMATICS AND COMPUTING↗