N00014-11-1-0271:
Predictive Modeling of Structural Sensing
for Navy Applications
Dr. Victor Giurgiutiu
University of South Carolina
Laboratory for Active Materials and Smart Structures (LAMSS)
ONR Structural Composites and NDE Program Review
Wednesday August 20, 2014
Objective
Global objective: develop the science for unprecedented SHM systems
based on novel piezoelectric and optical sensing principles and methods
Sensor development
• Piezo-optical sensing
• Resonance-enhanced AE sensing (the ring sensor)
• High-rate multi-channel ultrasonic FBG sensing
Structural state assessment
• Predictive modeling of wave-damage interaction
• Connect sensor signal to structural state
Software development
• Integrated SHM software package
• Signal processing
Specific objectives:
(a) Predictive modeling of structural
sensors response to changes in the
structural state and/or the presence of
structural flaws or damage
(b) Development of novel guided-wave
sensors combining piezo-optical
sensing with mechanical resonance in
100 – 300 kHz ultrasonic range
Hardware development
• Combine piezo and optical sensing principles
2
Technical Approach
 Predictive modeling:
• Develop fast analytical modeling of 2-D guided waves
propagation in interaction with linear and nonlinear damage
• Combine local FEM modeling of realistic damage with fast
analytical modeling of the global wave propagation in a
hybrid global-local (HGL) approach
 Develop new sensor concepts that combine
piezo-optical sensing with resonant amplification:
• Analytical and FEM modeling
• Prototyping
• Extensive testing for ultrasonic pitch-catch, impact
detection, and acoustic emission detection
3
HGL Predictive Modeling of 2-D Wave Propagation
in Interaction with Damage
G1S (ω , RIN ) = −π i
a 2κ PWAS (ω )
J1 (ξ S a ) N S (ξ S ) (1) S
H1 (ξ RIN )
∑
2µ
DS′ (ξ S )
ξS
G1A (ω , RIN ) = −π i
a 2κ PWAS (ω )
J1 (ξ A a ) N A (ξ A ) (1) A
H1 (ξ RIN )
∑
2µ
D′A (ξ A )
ξA
Giurgiutiu V., [Structural Health Monitoring with
Piezoelectric Wafer Active Sensors], Second Edition
∞
ur = ∑ an ( z ) H1(1) (ξ n r ) e − iωt
n =1
Giurgiutiu V., [Structural Health
Monitoring with Piezoelectric Wafer
Active Sensors], Second Edition
Glushkov E., et al. “ Lamb wave
excitation and propagation in elastic
plates with surface obstacles: proper
choice of central frequencies. (2011)
For comparison with laser
measurements
4
Analytical Wave Propagation: WFR-2D
Scatter Information Platform
WFR Main Interface
Real time sensing signal
Parameter control panel
Dispersion and
tuning curves
Excitation
control
T-PWAS properties Module
Spatial Propagation Solver
5
Local FEM w NRB: WDICs Extraction
∞
Sensing boundary
Lamb waves S0, A0:
ur = ∑ an ( z ) H1(1) (ξ n r ) e − iωt
n =1
∞
Shear horizontal waves, SH0:
uθ = ∑ bn ( z ) H 0( ) (ξ nSH r ) e − iωt
1
n =1
Separation of guided wave modes:
uθT + uθB
urT + urB
urT − urB
A0
SH 0
=
; uSC
=
; uSC
;
2
2
2
S0
=
uSC
Local FEM analysis
=
WSC WTOTAL − WIN
Pristine
Relationship between incident and scattered waves:
NRB
Α − iϕ IN
Β
⋅ CΑΒ (ω , θ ) e − iϕΑΒ (ω ,θ ) ⋅ H m(1) (ξ Β r ) =
uIN
e
uSC
(θ ) e−iϕSC (θ )
Β
NRB
Sensing
nodes
NRB
Α
CΑΒ (ω , θ ) e
NRB
Excitation nodes
Damaged
NRB
WDICs:
− iϕ ΑΒ (ω ,θ )
Β
uSC
(θ )
1
− i∆ϕ θ
Β
=
e ΑΒ ( ) ; ∆ϕ ΑΒ (θ ) = ϕ SC
(θ ) − ϕ INΑ
Α
(1)
Β
uIN H m (ξ r )
Β
uSC
(θ )
1
CΑΒ (ω , θ ) =
Α
(1)
uIN H m (ξ Β r )

NRB
NRB
NRB
ϕ ΑΒ (ω ,θ ) = ∆ϕ ΑΒ (θ ) − ∠

1
H m(1) (ξ Β r )
−∠


H m(1) ( 0+ ) 
1
Harmonic FEM analysis: all frequencies in one run!
6
Discussion of WDICs
S0 incidence at 200 kHz
400 kHz
A0 incidence at 200 kHz

•
•
•
•
300 kHz
200 kHz
S0-incident wave results:

Mode conversion is captured
WDICs depend on direction
WDICs depend on frequency
Phase information is essential for correct constructive and
destructive wave interaction
A0-incident wave results – similar obs.
7
Detection Sensitivity vs. Frequency
Example:
Crack growth
in a rivet hole
No damage
1.6-mm cracks
WDIC_pristine
WDIC_damaged
WDIC_crack = WDIC_damaged – WDIC_pristine
CSS _crack
ϕ SS _ crack
90
90
2
120
1.5
60
1
150
120
30
300
90
60
200
150
0.5
120
30
150
100
180
0
210
180
330
240
CSSH _ crack
400
0
210
300
180
330
240
270
2.5
60
2
1.5
1
0.5
300
400
300
60
200
150
30
30
100
330
240
270
90
120
0
210
ϕ SSH _ crack
180
0
210
330
240
300
300
270
270
2.5
2
1.5
60
1
150
2
30
0.5
180
0
210
Amplitude
90
120
X: 482
Y: 2.039
1.5
482 kHz -- Yes!
X: 400
Y: 0.8081
1
330
0.5
240
X: 328
Y: 0.07469
300
270
0
0
200
X: 776
Y: 0.7684
328 kHz -- No!
600
400
Frequency (kHz)
800
1000
8
PIEZO-OPTICAL RING SENSOR
9
Piezo-Optical Ring Sensor -- Concept
 Enhance acousto-ultrasonic crack out of plane waves
propagation
detection
 Employ mechanical
AE source
resonance principles to
FBG
• Enhance sensitivity at desired
frequencies
• Filter out low-frequency noise
and vibration
 Bestow omnidirectionality
onto FBG optical sensing
 Permit design for specific
frequency ranges
T2
T1
T3
R
10
Ring Sensor - Overview
 Analyzed and designed three rings: 100 kHz, 200 kHz, 300 kHz
(any desired frequency may be accommodated)
 Fabricated the 100 kHz and the 300 kHz Ring Sensors.
 Tested for:
•
•
•
•
Resonance: E/M impedance and chirp FRF
Pitch-catch: comparison with conventional FBG sensors and PWAS
Impact detection (160-mg steel ball)
Simulated acoustic emission (pencil lead breaks -- PLB) detection
100 kHz
8.00-mm dia
316 stainless steel
Mill machining of
internal ellipse shape
$100 for one
(USC machine shop)
100 kHz
300 kHz
300 kHz
4.35-mm dia
304 stainless steel
EDM machining of
internal ellipse shape
$500 for two
(Alpha Manuf. Inc.)
11
EMIS Tests: 300 kHz Ring Sensor
277 kHz
fundamental
resonance
2.4
10
Impedance real (Z)
X: 277.1
Y: 245.7
2.3
10
50
100
150
250
200
Frequency (KHz)
300
350
400
Chirp FRF Tests: 100 kHz–Ring Sensor
Linear chirp frequency-time variation
PWAS
FBG
on side
FBG through hole
Frequency-Domain
Time-Domain
102 kHz
FFT
13
Pitch-Catch Tests
Longitudinal path
Transversal
path
FBG on plate
is directional!
FBG on Ring sensor
is not directional!
FBG bonded onto the plate
FBG bonded onto the ring sensor
A0
A0
Transversal
path
S0
Transversal
path
Longitudinal
path
S0
A0
Longitudinal
path
A0
14
Impact Detection:
Plate PWAS vs. Ring Sensor PWAS
Plate PWAS
Plate PWAS:
Time Domain
Plate PWAS:
Frequency Domain
Ring PWAS
Ring PWAS:
Time Domain
Ring PWAS:
Frequency Domain
Longitudinal
Transverse
15
Impact Detection:
Narrow-Band Ring Sensor Capability
PWAS: Time Domain
PWAS: Frequency Domain
Longitudinal
Transverse
160-mg small steel ball dropped from 100 mm height
16
AE Detection:
Narrow-Band Ring Sensor Capability
PWAS: Time Domain
PWAS: Frequency Domain
Longitudinal
Transverse
0.5-mm pencil lead break (PLB) at 100 mm from sensor
17
FBG on Plate vs. FBG on Ring Sensor
 FBG Ring Sensor chirp response shows a narrow
resonance peak
 FBG Ring Sensor is omnidirectional, whereas
FBG on plate is only sensitive along its axis
 FBG Ring Sensor attenuates undesired
frequencies
 FBG Ring Sensor can be designed for specific
frequency range, including frequency range of
acoustic emissions
18
Accomplishments
 Fast analytical modeling of 2-D guided
waves propagation in interaction
with linear and nonlinear damage
 Local FEM frequency-domain analysis
of realistic damage to determine the
damage interaction coefficients for
efficient HGL of realistic structures
 Novel omnidirectional piezo-optical ring sensor
for enhanced guided-wave SHM developed
ab initio through analytical and FEM modeling,
prototyping, and extensive testing for ultrasonic
pitch-catch, impact detection, and acoustic emission
19
Recent Publications, Patents, Awards
 Giurgiutiu, V.; Roman, C.; Lin, Frankforter, E. (2014) “Omnidirectional Piezo-Optical Ring Sensor for
Enhanced Guided Wave Structural Health Monitoring”, Smart Materials and Structures, under review,
manuscript # SMS-101065
 Shen, Y.; Giurgiutiu, V. (2014) “WaveFormRevealer: An analytical framework and predictive tool for
the simulation of multi-modal guided wave propagation and interaction with damage”, doi:
10.1177/1475921714532986 Structural Health Monitoring – An International Journal, May 13, 2014
 Shen, Y.; Giurgiutiu, V. (2014) ‘Predictive Modeling of Nonlinear Wave Propagation for Structural
Health Monitoring with Piezoelectric Wafer Active Sensors”, Journal of Intelligent Material Systems
and Structures, Vol. 25, No. 4, pp. 506-520
 Gresil, M.; Giurgiutiu, V. (2013) “Guided Wave Propagation in Composite Laminates Using
Piezoelectric Wafer Active Sensors”, Aeronautical Journal, Oct. 2013, Vol. 117, No. 1196, pp. 971995, Royal Aeronautical Society, London UK
 Lin, B.; Giurgiutiu, V. (2014) “Development of optical equipment for ultrasonic guided wave structural
health monitoring”, SPIE Vol. 9062, paper number 9062-27
 Shen, Y.; Giurgiutiu, V. (2014) “WFR-2D: an analytical model for PWAS-generated 2D ultrasonic
guided wave propagation”, SPIE Vol. 9064, paper number 9064-40
 Giurgiutiu, V.; Gresil, M.; Roman, C. (2013) Acousto-ultrasonic Sensor, US Patent application
publication # US 2013/0129275A1
20
AM-MF Materials Opportunities
 Sensing and excitation capabilities could be embedded
into the multifunctional material through additive
manufacturing
 The predictive modeling methodology developed in this
grant could be extended to simulate the behavior of AMMF materials:
• Hybrid global local (HGL) would provide an efficient modeling tool
• Anisotropy should be included in the analytical part of the HGL model
• Multi-physics description could be used both directionally to send and
transmit structurally interrogative signal
• The HGL approach and tuning principles could be extended to energy
harvesting AM-MF materials
 Incorporation of ‘intelligence’ through printed electronics
is an essential future need for AM-MF materials.
21
Navy Relevance and Impact
Increase
in-service
safety and
reliability
Assess
structural
state to
predict
operational
capability
Reduce
lifecycle
cost of
naval
assets
22
Significance and Originality
 The project has strong significance for the Navy efforts in
developing structural health monitoring (SHM) methods
and technologies. The predictive modeling part of the
project would allow the SHM system designer to produce
an optimal system and sensor installation with strong
damage detection sensitivity and rejection of other
confounding effects (loads, vibration, environment, etc.)
 The novel piezo-optical ring sensor is very original and
has not been reported anywhere else yet. It bestows
omnidirectionality to optical FBG sensors which are
preferred in Navy applications. It enhances certain
frequency band while inherently rejecting noise and
vibration perturbations.
23
Scientific Merit
 The project has significant scientific merit.
 The predictive modeling part of the project has
demonstrated a skillful combination of global analytical
prediction of wave propagation in a 2-D medium with
scatterers combined with a innovative use of local FEM
mesh with non-reflective boundaries to determine the
wave damage interaction coefficients for complicated
damage shapes
 The novel ring sensor part of the project has skillfully
combined analysis and CAD-FEM techniques to predict
the behavior of this new sensor concept and then validated
these predictions through carefully-conducted
professional quality experiments.
24
Risk and Potential Impact
 The novel piezo-optical ring sensor is very innovative and
interesting; it may have a strong impact on in-situ monitoring
especially for impact detection and acoustic emission with
FBG optical sensors
 The risk related to this novel sensor resides in the fact that it
has only been proven in laboratory. Its implementation in
actual applications will have to traverse the ‘valley of death’
between concept and a commercially viable product.
 To mitigate the risk and open the opportunity for the potential
impact to materialize, it might be advisable to use SBIR/STTR
or other small 6.2 funding in order to obtain an actual product
that can be tested on actual structures in collaboration with
Navy Labs.
25