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Results for “FRF estimation”

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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8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Local modeling for FRF estimation with noisy input measurements

The frequency response function (FRF) is an essential means by which dynamic systems are qualified. In recent years, local modeling approaches have been extensively researched and shown to significantly outperform traditional FRF estimators. However, the standard local modeling approach assumes a perfectly-known system input, which results in biased FRF estimates in the presence of input noise. This paper derives a simple adjustment that can be used to improve FRF estimation for systems subjected to random excitation with noisy input data. This improvement can be implemented with little modification to standard local modeling algorithms and with little additional computational burden. The adjustment is coupled with a model selection procedure to avoid underfitting and overfitting. In conclusion, the methods presented in this paper are validated on a simulation, and they are shown to reduce bias due to input noise.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Quantification and prediction of error in MIMO tests

Dynamic testing of systems is most realistic of real-world conditions when multiple input and multiple output (MIMO) techniques are used. To replicate measured environmental conditions, a series of desired outputs (responses) on the system must be realized by inverting the frequency response functions (FRF) matrix for input estimation. System identification is dependent on the number of inputs and outputs, which affect the type of solutions. In input estimation, the auto spectra of the determined inputs are affected by both the auto spectra and cross spectra of the desired outputs. This research evaluates errors and investigates two sources in an experimental setting. The first significant error source is test-to-test variability in FRFs from system identification tests, quantified by magnitude variability from long-duration tests. The second significant error source is the realization of time histories from frequency domain inputs. The spectral content of the realized random process deviates from the desired content and is also quantified. The structure is a linear three-story frame fixed at the base; two inputs are provided uniaxially with the use of suspended electrodynamic shakers. The proposed model for error sources was found to be effective in predicting errors in a SISO (single-input single-output) and a square (2-input 2-output) MIMO test.

Yousef, Odey↗
DOE OSTI2025

Structural response reconstruction using a system-equivalent singular vector basis

Here, this paper develops a novel method for reconstructing the full-field response of structural dynamic systems using sparse measurements. The singular value decomposition is applied to a frequency response matrix relating the structural response to physical loads, base motion, or modal loads. The left singular vectors form a non-physical reduced basis that can be used for response reconstruction with far fewer sensors than existing methods. The contributions of the singular vectors to measured response are termed singular-vector loads (SVLs) and are used in a regularized Bayesian framework to generate full-field response estimates and confidence intervals. The reconstruction framework is applicable to the estimation of single data records and power spectral densities from multiple records. Reconstruction is successfully performed in configurations where the number of SVLs to identify is less than, equal to, and greater than the number of sensors used for reconstruction. In a simulation featuring a seismically excited shear structure, SVL reconstruction significantly outperforms modal FRF-based reconstruction and successfully estimates full-field responses with as few as two uniaxial accelerometers. SVL reconstruction is further verified in a simulation featuring an acoustically excited cylinder. Finally, response reconstruction and uncertainty quantification are performed on an experimental structure with three shaker inputs and 27 triaxial accelerometer outputs.

42 ENGINEERING↗
DOE OSTI2025

ForceFinder

SAND2025-11750O ForceFinder extends the Structural Dynamics Python Libraries (SDynPy) with comprehensive tools for inverse source estimation (ISE) tasks via frequency response function (FRF) matrix inversion. The software is designed for transfer path analysis and multiple-input/multiple-output (MIMO) vibration control problems. It allows users to estimate sources through various algorithms, from the basic Moore-Penrose pseudo-inverse to statistical learning methods such as Tikhonov regularization via an L-curve and elastic net regularization via an information criterion. ForceFinder uses an object-oriented framework, where all components of the ISE problem—such as FRFs, responses, and transformations—are stored in a "SourcePathReceiver" object. This software can be applied to any noise and vibration problem. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Carter, Steven [Sandia National Lab. (SNL-CA), Liv↗
NASA NTRS1981

Modal analysis using a Fourier analyzer, curve-fitting, and modal tuning

The proposed modal test program differs from single-input methods in that preliminary data may be acquired using multiple inputs, and modal tuning procedures may be employed to define closely spaced frquency modes more accurately or to make use of frequency response functions (FRF's) which are based on several input locations. In some respects the proposed modal test proram resembles earlier sine-sweep and sine-dwell testing in that broadband FRF's are acquired using several input locations, and tuning is employed to refine the modal parameter estimates. The major tasks performed in the proposed modal test program are outlined. Data acquisition and FFT processing, curve fitting, and modal tuning phases are described and examples are given to illustrate and evaluate them.

Craig, R. R., Jr.↗
NASA NTRS2016

Unsteady Heat-Flux Measurements of Second-Mode Instability Waves in a Hypersonic Boundary Layer

In this paper we report on the application of the atomic layer thermopile (ALTP) heat- flux sensor to the measurement of laminar-to-turbulent transition in a hypersonic flat plate boundary layer. The centerline of the flat-plate model was instrumented with a streamwise array of ALTP sensors and the flat-plate model was exposed to a Mach 6 freestream over a range of unit Reynolds numbers. Here, we observed an unstable band of frequencies that are associated with second-mode instability waves in the laminar boundary layer that forms on the flat-plate surface. The measured frequencies, group velocities, phase speeds, and wavelengths of these instability waves are in agreement with data previously reported in the literature. Heat flux time series, and the Morlet-wavelet transforms of them, revealed the wave-packet nature of the second-mode instability waves. In addition, a laser-based radiative heating system was developed to measure the frequency response functions (FRF) of the ALTP sensors used in the wind tunnel test. These measurements were used to assess the stability of the sensor FRFs over time and to correct spectral estimates for any attenuation caused by the finite sensor bandwidth.

Kergerise, Michael A.↗
NASA NTRS2008

Measurement of Fire Radiative Energy from Space and Implications for Fire-Disaster Monitoring and Smoke Emissions Modeling

Measurement of fire radiative energy (FRE) release rate or power (FRP) from satellite provides a vital mechanism for distinguishing different strengths of fires. Analysis of 1-km resolution fire data, acquired globally by the MODerate-resolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites from 2000 to 2006, showed instantaneous FRP values ranging between 0.02 MW and 1866 MW, to which simple thresholds can be applied to categorize fires by strength, in a similar fashion as the strengths of earthquakes and hurricanes. Analysis of regional mean FRP per unit area of land (FRP flux) shows that at peak fire season in certain regions, fires can be responsible for up to 0.2 W/m2 at peak time of day. When considered as the active fire contribution to the direct surface radiative forcing (RF) in the different fire regions, this order of magnitude of FRF fluxes is non negligible. It has been determined experimentally that the amount of FRE released by a fire over the course of its duration is directly proportional to the amount of biomass consumed by it. Furthermore, at the satellite observation scale, the rate of release of FRE (i.e. FRP) is proportional to the rate of biomass consumption, and that of emission of smoke particulates and eventually also other smoke constituents. Therefore, current research efforts are geared toward deriving simple parameterizations that will facilitate direct input of FRP measurements in models, not only to improve the accuracy of burned-biomass and smoke emissions estimations, but also to reduce the hitherto practiced heavy reliance on multiple indirect parameters with indeterminate uncertainties.

Ichoku, Charles↗