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Results for “parameter identification”

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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

The determination of operational and support requirements and costs during the conceptual design of space systems

The primary objective is to develop a methodology for predicting operational and support parameters and costs of proposed space systems. The first phase consists of: (1) the identification of data sources; (2) the development of a methodology for determining system reliability and maintainability parameters; (3) the implementation of the methodology through the use of prototypes; and (4) support in the development of an integrated computer model. The phase 1 results are documented and a direction is identified to proceed to accomplish the overall objective.

Ebeling, Charles↗
NASA NTRS1998

A Methodology for Flight-Time Identification of Helicopter-Slung Load Frequency Response Characteristics Using CIFER

Helicopter slung load operations are common in both military and civil contexts. The slung load adds load rigid body modes, sling stretching, and load aerodynamics to the system dynamics, which can degrade system stability and handling qualities, and reduce the operating envelope of the combined system below that of the helicopter alone. Further, the effects of the load on system dynamics vary significantly among the large range of loads, slings, and flight conditions that a utility helicopter will encounter in its operating life. In this context, military helicopters and loads are often qualified for slung load operations via flight tests which can be time consuming and expensive. One way to reduce the cost and time required to carry out these tests and generate quantitative data more readily is to provide an efficient method for analysis during the flight, so that numerous test points can be evaluated in a single flight test, with evaluations performed in near real time following each test point and prior to clearing the aircraft to the next point. Methodology for this was implemented at Ames and demonstrated in slung load flight tests in 1997 and was improved for additional flight tests in 1999. The parameters of interest for the slung load tests are aircraft handling qualities parameters (bandwidth and phase delay), stability margins (gain and phase margin), and load pendulum roots (damping and natural frequency). A procedure for the identification of these parameters from frequency sweep data was defined using the CIFER software package. CIFER is a comprehensive interactive package of utilities for frequency domain analysis previously developed at Ames for aeronautical flight test applications. It has been widely used in the US on a variety of aircraft, including some primitive flight time analysis applications.

Sahai, Ranjana↗
DOE OSTI2019

A generalized deep learning approach for local structure identification in molecular simulations

Identifying local structure in molecular simulations is of utmost importance. The most common existing approach to identify local structure is to calculate some geometrical quantity referred to as an order parameter. In simple cases order parameters are physically intuitive and trivial to develop (e.g., ion-pair distance), however in most cases, order parameter development becomes a much more difficult endeavor (e.g., crystal structure identification). Using ideas from computer vision, we adapt a specific type of neural network called a PointNet to identify local structural environments in molecular simulations. A primary challenge in applying machine learning techniques to simulation is selecting the appropriate input features. This challenge is system-specific and requires significant human input and intuition. In contrast, our approach is a generic framework that requires no system-specific feature engineering and operates on the raw output of the simulations, i.e., atomic positions. We demonstrate the method on crystal structure identification in Lennard-Jones (four different phases), water (eight different phases), and mesophase (six different phases) systems. The method achieves as high as 99.5% accuracy in crystal structure identification. The method is applicable to heterogeneous nucleation and it can even predict the crystal phases of atoms near external interfaces. We demonstrate the versatility of our approach by using our method to identify surface hydrophobicity based solely upon positions and orientations of surrounding water molecules. Our results suggest the approach will be broadly applicable to many types of local structure in simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1981

Large modal survey testing using the Ibrahim time domain /ITD/ identification technique

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

Ibrahim, S. R.↗
NASA NTRS1985

Large Modal Survey Testing Using the Ibrahim Time Domain Identification Technique

The ability of the ITD identification algorithm in identifying a complete set of structural modal parameters using a large number of free-response time histories simultaneously in one analysis, assuming a math model with a high number of degrees-of-freedom, has been studied. Identification results using simulated free responses of a uniform rectangular plate, with 225 measurement stations, and experimental responses from a ground vibration test of the Long Duration Exposure Facility (LDEF) Space Shuttle payload, with 142 measurement stations, are presented. As many as 300 degrees-of-freedom were allowed in analyzing these data. In general, the use of a significantly oversized math model in the identification process was found to maintain or increase identification accuracy and to identify modes of low response level that are not identified with smaller math model sizes. The concept of a Mode Shape Correlation Constant is introduced for use when more than one identification analysis of the same structure are conducted. This constant quantifies the degree of correlation between any two sets of complex mode shapes identified using different excitation conditions, different user-selectable algorithm constants, or overlapping sets of measurements.

Ibrahim, S. R.↗
DOE OSTI2021

Identification of Life Models for Li-Ion Batteries Using Penalized Regression and Bilevel Optimization

Reduced-order physics-based life models are extremely useful for rapidly predicting battery state-of-health and for simulating battery lifetime in arbitrary aging conditions. However, identification of well-parameterized models is difficult. This is because, for maximum usefulness in predicting lifetime under a variety of conditions, aging test data exhibits many degradation mechanisms, which all need to be accurately modeled. However, because aging tests are time-consuming and expensive, especially for large-format batteries, a minimum of tests are conducted while probing many stress factors. Building a well-parameterized model is then very challenging: an under-parameterized model will neglect critical degradation modes, and an over-parameterized model will extrapolate poorly to new testing conditions. To complicate this matter, the functional form of the model for any individual degradation rate can be very difficult to identify. In this work, the statistical tools of penalized regression and bilevel optimization are used to help identify both the functional forms of and optimize the parameters of reduced-order life models, accelerating identification of robust models. Model robustness is demonstrated through traditional statistics methods of cross-validation and sensitivity analysis, uncertainty quantification through bootstrap resampling and Monte-Carlo simulation, and simulation of real-world use cases.

47 OTHER INSTRUMENTATION↗
NASA NTRS1973

Identification of a mechanical vibration system

The actual values of the parameters of a precision instrument assembly vibration system are determined according to experimental amplitude-frequency characteristics. The assembly is considered as a complex mechanical vibrating system, consisting of elements with concentrated and distributed parameters. A calculation procedure was compiled.

Korablev, S. S.↗
NASA NTRS1992

Using partially labeled data for normal mixture identification with application to class definition

The problem of estimating the parameters of a normal mixture density when, in addition to the unlabeled samples, sets of partially labeled samples are available is addressed. The density of the multidimensional feature space is modeled with a normal mixture. It is assumed that the set of components of the mixture can be partitioned into several classes and that training samples are available from each class. Since for any training sample the class of origin is known but the exact component of origin within the corresponding class is unknown, the training samples as considered to be partially labeled. The EM iterative equations are derived for estimating the parameters of the normal mixture in the presence of partially labeled samples. These equations can be used to combine the supervised and nonsupervised learning processes.

Shahshahani, Behzad M.↗
NASA NTRS1985

Space station on-orbit identification and performance monitor

This paper describes the generic applications of on-orbit identification to the reference Space Station configuration currently under consideration by NASA. Identification functions are categorized, and the various methods for extracting parameter estimates are correlated with the sensing of specific characteristics of interest to both engineering subsystems and users of the Station's commercial and scientific facilities. A case study of crew motion detection and identification is included to illustrate the application to the Station's disturbance environment and plant characterization using accelerometer sensing. Onboard implementation architecture is discussed from the viewpoint of maximizing integration of the identification process with the flight subsystem's data and signal flow.

Mettler, E.↗
NASA NTRS1976

Specification of inputs and instrumentation for flutter testing of multivariable systems

The application of system identification methods in flutter testing of aeroelastic structure is discussed. The accuracy with which flutter parameters are estimated depends upon the test plan and on the algorithms used to reduce the data. The techniques for selecting the kinds and optimal positions of inputs and instrumentation, under typical test constraints, are presented. Identification results for both the input/output transfer function and the value of physical parameters are given. Numerical results on the optimal input spectrum and the accelerometer location for estimating flutter parameters of a two dimensional wing are obtained using these algorithms. Current work on applying system identification methods to high order three dimensional aeroelastic structures is reported.

Gupta, N. K.↗
NASA NTRS1972

Adaptive control and identification via Liapunov's direct method.

The adaptive control and identification problems for single input, single output, time invariant systems with unknown parameters are considered here. A model reference is used and Liapunov's direct method provides the mechanisms for deriving the adaptive and identification algorithms. The Kalman Lemma (derived in connection with the Lure' problem) is shown to be extremely helpful in the design of these systems.

Monopoli, R. V.↗
NASA NTRS1997

Linear and nonlinear ARMA model parameter estimation using an artificial neural network

This paper addresses parametric system identification of linear and nonlinear dynamic systems by analysis of the input and output signals. Specifically, we investigate the relationship between estimation of the system using a feedforward neural network model and estimation of the system by use of linear and nonlinear autoregressive moving-average (ARMA) models. By utilizing a neural network model incorporating a polynomial activation function, we show the equivalence of the artificial neural network to the linear and nonlinear ARMA models. We compare the parameterization of the estimated system using the neural network and ARMA approaches by utilizing data generated by means of computer simulations. Specifically, we show that the parameters of a simulated ARMA system can be obtained from the neural network analysis of the simulated data or by conventional least squares ARMA analysis. The feasibility of applying neural networks with polynomial activation functions to the analysis of experimental data is explored by application to measurements of heart rate (HR) and instantaneous lung volume (ILV) fluctuations.

NASA Discipline Regulatory Physiology↗
DOE OSTI2018

Study of performance of the ATLAS transition radiation tracker in run 1 of the LHC: Tracking characteristics

The ATLAS Transition Radiation Tracker (TRT) contains more than 350000 large straw tubes and it is the outermost of the three subsystems of the ATLAS Inner Detector (ID). The TRT contributes substantially to the ATLAS ID resolution for the tracks of high-energy particles, providing excellent particle identification capabilities and electron-pion separation. Basic performance parameters of the TRT related to its tracking function are described in this paper. The data used in this study were collected during the first period of the Large Hadron Collider (LHC) operation in 2012 with a proton collision energy of 8 TeV. The tracking performance of the TRT has been studied in the case of operating with a Xe-based gas mixture and as a function of the straw occupancy. Special attention was paid to investigation of tracking parameters inside hadronic jets. The experimental data and simulation are in reasonable agreement, even within the dense cores of the most energetic jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Diagnostics of Magnetohydrodynamic Modes in the Interstellar Medium through Synchrotron Polarization Statistics

One of the biggest challenges in understanding magnetohydrodynamic (MHD) turbulence is identifying the plasma mode components from observational data. Previous studies on synchrotron polarization from the interstellar medium (ISM) suggest that the dominant MHD modes can be identified via statistics of Stokes parameters, which would be crucial for studying various ISM processes such as the scattering and acceleration of cosmic rays, star formation, and dynamo. In this paper, we present a numerical study of the synchrotron polarization analysis (SPA) method through systematic investigation of the statistical properties of the Stokes parameters. We derive the theoretical basis for our method from the fundamental statistics of MHD turbulence, recognizing that the projection of the MHD modes allows us to identify the modes dominating the energy fraction from synchrotron observations. Based on the discovery, we revise the SPA method using synthetic synchrotron polarization observations obtained from 3D ideal MHD simulations with a wide range of plasma parameters and driving mechanisms, and present a modified recipe for mode identification. We propose a classification criterion based on a new SPA+ fitting procedure, which allows us to distinguish between Alfvén mode and compressible/slow mode dominated turbulence. We further propose a new method to identify fast modes by analyzing the asymmetry of the SPA+ signature and establish a new asymmetry parameter to detect the presence of fast mode turbulence. Additionally, we confirm through numerical tests that the identification of the compressible and fast modes is not affected by Faraday rotation in both the emitting plasma and the foreground.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

Low Order Equivalent System for the Tu-144LL Supersonic Transport Aircraft

Low order equivalent system models were identified from flight test data for the Tu- 144LL supersonic transport aircraft. Flight test maneuvers were executed by Russian and American test pilots flying the aircraft from Zhukovsky airfield outside Moscow, Russia. Flight tests included longitudinal and lateral/directional maneuvers at supersonic cruise flight conditions. Piloted frequency sweeps and multi-step maneuvers were used to Generate data for p closed loop low order equivalent system modeling Model parameters were estimated using a flexible, high accuracy Fourier transform and an equation error output error (EE/OE) formulation in the frequency domain. Results were compared to parameter estimates obtained using spectral estimation and subsequent least squares fit to frequency response data in Bode plots. Modeling results from the two methods a-reed well for both a frequency sweep and multiple concatenated multi-step maneuvers. For a single multi-step maneuver, the EE/OE method gave a better model fit with improved prediction capability. A summary of closed loop low order equivalent system identification results for the Tu-144LL. including estimated parameters, standard errors, and flying qualities level predictions, were computed and tabulated.

Morelli, Eugene A.↗
NASA NTRS2016

Adaptive Modal Identification for Flutter Suppression Control

In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

Aeroelasticity↗
NASA NTRS1986

Studies of modal identification performance using hybrid data

Modal identification accuracy can be affected significantly in practice by high modal density and nonlinearities. It may be difficult to determine the true number of modes, and many of the identified mode shapes may be questionable. Results can vary considerably using different analysis techniques. This paper introduces a new method for studying modal identification performance under such circumstances. A difficult set of test data from an erectable truss structure was modified numerically by adding two artificial modes with known parameters. These 'hybrid data' were then analyzed with the Polyreference technique and the Eigensystem Realization Algorithm (ERA). Identification performance is studied by comparing the identified modal parameters for the artificial modes with their known values.

Pappa, Richard S.↗