scholarly journals Choice of Measurement Locations of Nonlinear Structures Using Proper Orthogonal Modes and Effective Independence Distribution Vector

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
T. G. Ritto
Keyword(s):  
Experimental Data ◽  
Computational Model ◽  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Nonlinear Structures ◽  
Nonlinear Structure ◽  
Proper Orthogonal Modes ◽  
Distribution Vector ◽  
Proper Orthogonal

This paper proposes a methodology to automatically choose the measurement locations of a nonlinear structure/equipment that needs to be monitored while operating. The response of the computational model (or experimental data) is used to construct the proper orthogonal modes applying the proper orthogonal decomposition (POD), and the effective independence distribution vector (EIDV) procedure is employed to eliminate, iteratively, locations that contribute less for the independence of the target proper orthogonal modes.

scholarly journals Identification of coexisting dynamics in boundary layer flows through proper orthogonal decomposition with weighting matrices

Meccanica ◽  
2021 ◽  
Author(s):  
Matteo Dellacasagrande ◽  
Dario Barsi ◽  
Patrizia Bagnerini ◽  
Davide Lengani ◽  
Daniele Simoni
Keyword(s):  
Experimental Data ◽  
Proper Orthogonal Decomposition ◽  
Fourier Transforms ◽  
Free Stream ◽  
Numerical Test ◽  
Separated Flow ◽  
Orthogonal Decomposition ◽  
Inner Product ◽  
Test Case ◽  
Proper Orthogonal

AbstractA different version of the classic proper orthogonal decomposition (POD) procedure introducing spatial and temporal weighting matrices is proposed. Furthermore, a newly defined non-Euclidean (NE) inner product that retain similarities with the POD is introduced in the paper. The aim is to emphasize fluctuation events localized in spatio-temporal regions with low kinetic energy magnitude, which are not highlighted by the classic POD. The different variants proposed in this work are applied to numerical and experimental data, highlighting analogies and differences with respect to the classic and other normalized variants of POD available in the literature. The numerical test case provides a noise-free environment of the strongly organized vortex shedding behind a cylinder. Conversely, experimental data describing transitional boundary layers are used to test the capability of the procedures in strongly not uniform flows. By-pass and separated flow transition processes developing with high free-stream disturbances have been considered. In both cases streaky structures are expected to interact with other vortical structures (i.e. free-stream vortices in the by-pass case and Kelvin–Helmholtz rolls in the separated type) that carry a significant different amount of energy. Modes obtained by the non-Euclidean POD (NE-POD) procedure (where weighted projections are considered) are shown to better extract low energy events sparse in time and space with respect to modes extracted by other variants. Moreover, NE-POD modes are further decomposed as a combination of Fourier transforms of the related temporal coefficients and the normalized data ensemble to isolate the frequency content of each mode.

Experimental Application of a Damage Localisation Technique Based on Smoothed Proper Orthogonal Modes

2007 ◽  
Vol 347 ◽  
pp. 121-126 ◽  
Author(s):  
U. Galvanetto ◽  
L. Monopoli ◽  
Cecilia Surace ◽  
Alessandra Tassotti
Keyword(s):  
Damage Detection ◽  
Proper Orthogonal Decomposition ◽  
Real Time ◽  
Orthogonal Decomposition ◽  
Steel Beams ◽  
Acceleration Response ◽  
Experimental Application ◽  
Lab Experiments ◽  
Proper Orthogonal Modes ◽  
Proper Orthogonal

The paper presents an experimental application of the Proper Orthogonal Decomposition (POD) to damage detection in steel beams. A damaged beam has been excited with a sinusoidal force, the acceleration response at points regularly spaced along the structure has been recorded and the relevant Proper Orthogonal Modes calculated. In this way it is possible to locate damage by comparing the measured dominant Proper Orthogonal Mode with a smoothed version of it which does not exhibit apparent peaks in correspondence with the damage. One of the principal advantages of the proposed damage detection technique is that it does not require vibration measurements to be performed on the undamaged structure. Moreover the ‘optimality’ of the proper orthogonal modes only requires the use of a few (one-two) of them which can be computed in real time during lab experiments or while the structure is functioning in the field.

Experimental Investigation of Transitional Natural Convection in a Cube Using Particle Image Velocimetry—Part II: Turbulence Quantities and Proper Orthogonal Decomposition

2016 ◽  
Vol 139 (1) ◽  
Author(s):  
Marios D. Georgiou ◽  
Aristides M. Bonanos ◽  
John G. Georgiadis
Keyword(s):  
Experimental Data ◽  
Experimental Investigation ◽  
Particle Image Velocimetry ◽  
Natural Convection ◽  
Proper Orthogonal Decomposition ◽  
Particle Image ◽  
Orthogonal Decomposition ◽  
Number Range ◽  
Image Velocimetry ◽  
Proper Orthogonal

An experimental investigation of transitional natural convection in an air filled cube was conducted in this research. The characteristic dimension of the enclosure was H = 0.35 m, and data were collected in the middle plane of the cavity. The Rayleigh number range examined was 5.0×107≤Ra≤3.4×108. In Part I, the authors presented the mean velocity profiles in the enclosure and conducted heat transfer measurements on the hot wall. An expression between Nu and Ra numbers was concluded and compared against other correlations available in literature. In the present work, the authors present a complete description of the flow in the enclosure by quantifying the low turbulence regime developed in the cavity. This was accomplished by estimating Reynolds stresses, turbulent kinetic energy, vorticity, and swirling strength. Proper orthogonal decomposition (POD) was employed to analyze the flow fields obtained from the experimental data and retain the most salient features of the flow field. This study attempts to close the gap of available experimental data in the literature and provide experimental benchmark data that can be used to validate CFD codes since the estimated error from particle image velocimetry (PIV) measurements is within 1–2%.

Proper Orthogonal Decomposition of Tapping Microcantilevers in Liquid Atomic Force Microscopy

2015 ◽  
Author(s):  
Il Kwang Kim ◽  
Soo Il Lee
Keyword(s):  
Atomic Force Microscopy ◽  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Modal Decomposition ◽  
Tapping Mode ◽  
Force Microscopy ◽  
Atomic Force ◽  
Proper Orthogonal Modes ◽  
Proper Orthogonal ◽  
Mode Atomic Force Microscopy

The modal decomposition of tapping mode atomic force microscopy microcantilevers in liquid environments was studied experimentally. Microcantilevers with different lengths and stiffnesses and two sample surfaces with different elastic moduli were used in the experiment. The response modes of the microcantilevers were extracted as proper orthogonal modes through proper orthogonal decomposition. Smooth orthogonal decomposition was used to estimate the resonance frequency directly. The effects of the tapping setpoint and the elastic modulus of the sample under test were examined in terms of their multi-mode responses with proper orthogonal modes, proper orthogonal values, smooth orthogonal modes and smooth orthogonal values. Regardless of the stiffness of the microcantilever under test, the first mode was dominant in tapping mode atomic force microscopy under normal operating conditions. However, at lower tapping setpoints, the flexible microcantilever showed modal distortion and noise near the tip when tapping on a hard sample. The stiff microcantilever had a higher mode effect on a soft sample at lower tapping setpoints. Modal decomposition for tapping mode atomic force microscopy can thus be used to estimate the characteristics of samples in liquid environments.

scholarly journals Proper Orthogonal Decomposition–Radial Basis Function Surrogate Model-Based Inverse Analysis for Identifying Nonlinear Burgers Model Parameters From Nanoindentation Data

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
Salah U. Hamim ◽  
Raman P. Singh
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Radial Basis Function ◽  
Proper Orthogonal Decomposition ◽  
Basis Function ◽  
Surrogate Model ◽  
Orthogonal Decomposition ◽  
Model Parameters ◽  
Radial Basis ◽  
Proper Orthogonal

This study explores the application of a proper orthogonal decomposition (POD) and radial basis function (RBF)-based surrogate model to identify the parameters of a nonlinear viscoelastic material model using nanoindentation data. The inverse problem is solved by reducing the difference between finite element simulation-trained surrogate model approximation and experimental data through genetic algorithm (GA)-based optimization. The surrogate model, created using POD–RBF, is trained using finite element (FE) data obtained by varying model parameters within a parametric space. Sensitivity of the model parameters toward the load–displacement output is utilized to reduce the number of training points required for surrogate model training. The effect of friction on simulated load–displacement data is also analyzed. For the obtained model parameter set, the simulated output matches well with experimental data for various experimental conditions.

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