proper orthogonal decomposition and wavelet analysis of

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Proper Orthogonal Decomposition and Wavelet Analysis of Sloshing Flows T. Pagliaroli * , F. Gambioli , F. Saltari , J. Cooper z * Niccol`oCusanoUniversity, Airbus, Sapienza University of Rome, z University of Bristol B [email protected] EASN–Italy–2 nd /4 th September 2020

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Page 1: Proper Orthogonal Decomposition and Wavelet Analysis of

Proper Orthogonal Decomposition and Wavelet Analysis of SloshingFlows

T. Pagliaroli∗, F. Gambioli†, F. Saltari‡, J. Cooperz

∗Niccolo Cusano University, †Airbus, ‡Sapienza University of Rome, zUniversity of BristolB [email protected]

EASN–Italy–2nd/4th September 2020

Page 2: Proper Orthogonal Decomposition and Wavelet Analysis of

Overview

Introduction

Material and MethodsData processing strategiesExperimental setupTest cases

ResultsData prequalificationAcceleration wavelet transformWavelet–based dampingMathematical modelProper Orthogonal Decomposition & WaveletWavelet Coherency

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 2

Page 3: Proper Orthogonal Decomposition and Wavelet Analysis of

Objective

Sloshing and structural dynamics coupling is important in the design phase, modeling, andcontrol of several aerospace systems: rockets, satellites, and aircrafts.

Figure: Example of coupling between sloshing and structural dynamics: an integral tank within a wing.

The aim of this work is to develop a data analysis technique able to highlight theinteraction between fluid and structure.

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 3

Page 4: Proper Orthogonal Decomposition and Wavelet Analysis of

Data processing strategy (1)

The main idea is to combine Proper Orthogonal Decomposition (POD) andWavelet Transform (WT) to analyse an image time-resolved sequence.

I (x , t) ≈N∑i=1

ai (t)φi (x) ≈N∑i=1

M∑j=1

aψij (t)φi (x) (1)

Decomposition characteristics:

I φi (x) coherent in space

I aψij (t) coherent in time

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 4

Page 5: Proper Orthogonal Decomposition and Wavelet Analysis of

Data processing strategy (2)

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 5

Page 6: Proper Orthogonal Decomposition and Wavelet Analysis of

Data processing strategy (3)

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 6

Page 7: Proper Orthogonal Decomposition and Wavelet Analysis of

Data processing strategy (4)

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Page 8: Proper Orthogonal Decomposition and Wavelet Analysis of

Experimental setup

x

l = 0.70m

L = 2.35m

y

root tip

H-beam

static load andrelease mechanism

y(L, t)

1 2 3 4 5 6 7

camera FOV

water tank

Instrumentation and acquisition details:

I Accelerometer – isotron model 65L-100, S = 102.7mV /g , f ys = 1 kHz ,T y = 6 s

I Fast camera – photron fastcam SA1.1, f Is = 3kHz ,T I = 10 s

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 8

Page 9: Proper Orthogonal Decomposition and Wavelet Analysis of

Test cases

x

l = 0.70m

L = 2.35m

y

root tip

H-beam

static load andrelease mechanism

y(L, t)

1 2 3 4 5 6 7

camera FOV

water tank

Water volume ratio:α = Vw

Vtot

Test Cases:I Test case 1: α = 0, dry;

I Test case 2: α = 0.3, wet;

I Test case 3: α = 0.5, wet.

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 9

Page 10: Proper Orthogonal Decomposition and Wavelet Analysis of

Data prequalification

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 10

Page 11: Proper Orthogonal Decomposition and Wavelet Analysis of

Wavelet Transform of the Acceleration

Structural dynamicsMode freq. [Hz] Description

f ′1l 7.4 1st mode and 1st harmonicf ′1h 7.9 1st mode and 1st harmonic

f ′′1 13.9 1st mode 2nd harmonic

f2 50.2 2nd mode

H–Beam modes characteristics:I First mode is affected by an abrupt drift in frequency

from 7.4 to 7.9 Hz;

I Second mode has the frequency weakly time dependent.

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 11

Page 12: Proper Orthogonal Decomposition and Wavelet Analysis of

Wavelet Coefficients of the Acceleration

0 1 2 3 4 5

-5

0

5(a)

=0

=0.3

=0.5

0 1 2 3 4 5

-10

-5

0

5

(b) =0

=0.3

=0.5

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 12

Page 13: Proper Orthogonal Decomposition and Wavelet Analysis of

Wavelet–Based Damping

1 2 3 4 5

0.02

0.04

0.06

0.08

0.1(a)

2 4 6 8

0.02

0.04

0.06

0.08

0.1(b)

Wavelet–based damping1:

ζψ(τ) = − 1

ωn

∂ ln |w(f ′1 , τ)|∂τ

(2)

I Test case 2–3: damping is higher andappears before than case 1 (see fig.a)

I Test case 2–3: damping is higher for allacceleration values (see fig.b)

I Damping is a function of the acceleration→ ζ = f (y)

[1] Chen et al., Wavelet analysis for identification of damping ratios and natural frequencies, J. Sound Vib., 323(1-2), 130–147.

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 13

Page 14: Proper Orthogonal Decomposition and Wavelet Analysis of

Fourier Transfrom of the Wavelet Coefficients

2 4 6 8 10 12 14 16 18 20

0

0.5

1

The frequency of the second mode oscillates with a frequency f ′1 , equal to the frequencyof the first mode:

f2(t) = 〈f2(t)〉+ c sin (2πf ′1t) (3)

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 14

Page 15: Proper Orthogonal Decomposition and Wavelet Analysis of

Simple Mathematical Model

From the experimental evidences, we have a preliminary idea of the mathematical model:

I for the first modey + 2ζ(y)ω1y + ω2

1y = 0 (4)

I for the second modey + 2ζ(y)ω2(t)y + ω2

2(t)y = 0 (5)

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 15

Page 16: Proper Orthogonal Decomposition and Wavelet Analysis of

Proper Orthogonal Decomposition & Wavelet

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 16

Page 17: Proper Orthogonal Decomposition and Wavelet Analysis of

Test case 3: stabilised Spectra

Structural dynamicsMode freq. [Hz] Description

f ′1l 7.4 1st mode–1st harmonicf ′1h 7.9 1st mode– 1st harmonic

f ′′1 13.9 1st mode– 2nd harmonic

f2 50.2 2nd mode

Fluid dynamicsMode freq. [Hz] Description

f ′1l 7.4 Coupling between φ1 and yf ′1h 7.9 Coupling between φ3-φ4 and yf ′1cl 3.7 symmetric sloshingf ′1ch 4.0 symmetric sloshing

101

102

0.1

0.2

0.3

0.4

0.5

101

102

10-4

10-2

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 17

Page 18: Proper Orthogonal Decomposition and Wavelet Analysis of

Wavelet Coherency

Fluid dynamicsMode frequency [Hz] Description

f ′1l 7.4 Coupling φ1 and y (all the time)f ′1h 7.9 Coupling φ3 and φ4 (coherent regime)f ′1cl 3.7 symmetric sloshing (no coupling)f ′1ch 4.0 No coupling φ2 and y

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 18

Page 19: Proper Orthogonal Decomposition and Wavelet Analysis of

Summary & Conclusions

1. A novel technique to decompose the hydrodynamic flow field in coherent modes in timeand space (aψij and φi ) is developed and tested on an experimental database.

2. A wavelet–based damping ratio calculation is applied and it appears to be promising.

3. Water contributes to increase the damping ratio.

4. The frequency of the second mode of the beam is not constant in time and oscillateswith the same frequency as the first mode.

5. A simple mathematical model for the first and second mode of the beam is proposed

6. Strong coupling between structural dynamics and hydrodynamics is detected:I φ1 oscillates at the same frequency as the beam for all the time;I φ3 and φ4 oscillate at the same frequency as the beam only during the coherent regime;I φ2 no linear coupling with acceleration.

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 19

Page 20: Proper Orthogonal Decomposition and Wavelet Analysis of

Future Work

-10

-5

0

(a)

-5

-10 5-5 0

0

5

5 (b)

500 1000 1500 2000

Time, samples

500

1000

1500

2000

Tim

e, s

amp

les

0

5

10

15

(b)

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 20

Page 21: Proper Orthogonal Decomposition and Wavelet Analysis of

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Thank you for your Attention

K,Q, p, C À, h, a, j, !, #, %, $, L, T,B, r,K,Q, p, C À, h, a, j, !, #, %, $, L,T,B, r,K,Q, p, C À, h, a, j, !, #, %, $, L, T,B, r,K,Q, p, C À, h, a, j, !, #,%, $, L, T,B, r,K,Q, p, C À, h, a, j, !, #, %, $, L, T,B, r,K,Q, p, C À, h, a,j, !, #, %, $, L, T,B, r,K,Q, p, C À, h, a, j, !, #, %, $, L, T,B, r,K,Q, p, C À,h, a, j, !, #, %, $, L, T,B, r,K,Q, p, C À, h, a, j, !, #, %, $, L, T,B, r,K,Q

Tiziano Pagliaroli EASN–Italy–2nd /4th September 2020 21