The Digital Twin paradigm is based on the idea that a component’s serviceable life and performance can be better predicted and monitored by creating a faithful virtual counterpart of a real component, which in turn leads to improvements in end-product safety and cost. Such a model requires accurate inputs for the initial material state of the part as well as in-service loads and damage states throughout its service life. The resonance frequencies of a part correlate to a part’s material state and damage state. Similarly, changes in resonance frequencies correlate to changes in the part’s material state resulting from in-service loads and damage. Process Compensated Resonance Testing (PCRT) leverages these physical relationships to perform nondestructive evaluation (NDE) and material characterization using the measured resonance frequencies of a component. Prior work has established techniques for modeling the effects of material property variation, crystal orientation, and damage states on resonance, as well as quantifying uncertainty propagation from model inputs to outputs. This study examines the use of PCRT model inversion to obtain material properties and calibrate digital twins of real components. Digital twin instances were first created for a population of single crystal Nickel-base superalloy samples using dimension and mass measurements. Then, after collecting resonance spectra from the physical counterparts, model inversion techniques were employed to estimate elastic properties and crystal orientation for each part. The digital twins were then calibrated with the model inversion output. These digital twins were subsequently validated by comparing the inversion results to resonance and x-ray diffraction measurements on a statistically significant population of physical specimens. The results highlight the value of part-specific material properties for digital twin performance, as well as the ability of PCRT to evaluate and improve digital twin fidelity.

1.
E. H.
Glaessgen
and
D. S.
Stargel
, “The digital twin paradigm for future NASA and U.S. Air Force vehicles,”
53rd Structures, Structural Dynamics, and Materials Conference
, pp.
1
14
,
Honolulu, Hawaii
, (
2012
).
2.
Li
,
Chenzhao
&
Mahadevan
,
Sankaran
&
Ling
,
You
&
Wang
,
Liping
&
Choze
,
Sergio
, “
A Dynamic Bayesian Network Approach for Digital Twin
,”
19ᵗʰ AIAA Non-Deterministic Approaches Conference, AIAA Sci-Tech Forum, AIAA 2017-1566
, (
2017
).
3.
M.
Dowell
,
G.
Sylvester
,
R.
Krupp
, and
G.
Zipfel
, “
Progress in Turbomachinery Prognostics and Health Management via Eddy Current Sensing
,”
2000 IEEE Aerospace Conference Proceedings, IEEE
, (
2000
)
4.
I.
Garcia
,
J.
Zubia
,
G.
Durana
,
G.
Aldabaldetreku
, and
M. A.
Villatoro
, “
Optical Fiber Sensors for Aircraft Structural Health Monitoring
,”
Sensors
,
15
, pp.
15494
15519
, (
2015
).
5.
D.
Piotrowski
,
L.
Hunter
, and
T.
Sloan
, “
Process Compensated Resonance Testing JT8D-219 1st Stage Blades
,”
ATA NDT Forum 2008
, (
2008
), avaliable at: http://www.vibrantndt.com/wp-content/uploads/Delta-TechOps-Vibrant-casestudy.pdf.
6.
ASTM Standard E2534-15
, (
2015
), “
Standard Practice for Process Compensated Resonance Testing via Swept Sine Input for Metallic and Non-Metallic Parts
,
ASTM International
, www.astm.org.
7.
J.
Schwarz
,
J.
Saxton
, and
L.
Jauriqui
, “
Process Compensated Resonant Testing in Manufacturing Process Control
,”
Material Evaluation
,
63
, pp.
736
739
, (
2005
).
8.
D. M.
Craig
, “
NDT Technology Readiness: A P&WC Case Study
,”
2016 Airlines for America NDT Forum
, (
2016
), available at: http://airlines.org/wp-content/uploads/2016/11/9_28_1100.pdf
9.
D.
Piotrowski
,
G.
Weaver
, “
Enhancing Reliability with Process Compensated Resonance Testing (PCRT) at Delta TechOps
,”
2016 Airlines for America NDT Forum
, (
2016
), available at: http://airlines.org/wp-content/uploads/2016/10/9_28_1315.pdf.
10.
E.
Biedermann
,
J.
Heffernan
,
A.
Mayes
,
G.
Gatewood
,
L.
Jauriqui
,
B.
Goodlet
,
T.
Pollock
,
C.
Torbet
,
J. C.
Aldrin
, and
S.
Mazdiyasni
, “
Process Compensated Resonance Testing Modeling for Damage Evolution and Uncertainty Quantification
,”
43rd Annual Review of Progress in QNDE
,
AIP Conf. Proc
,
1806
, pp.
090005
, (
2017
).
11.
J.
Heffernan
,
L.
Jauriqui
,
E.
Biedermann
,
A.
Mayes
,
R.
Livings
,
B.
Goodlet
, and
S.
Mazdiyasni
, “
Process compensated resonance testing models for quantification of creep damage in single crystal nickel-based superalloys
Materials Evaluation
,
75
, n
7
, pp.
941
952
, (
2017
).
12.
J.
Heffernan
,
E.
Biedermann
,
A.
Mayes
,
R.
Livings
,
L.
Jauriqui
, and
S.
Mazdiyasni
, “
Validation of Process Compensated Resonance Testing (PCRT) Sorting Modules with Modeled Data
,”
45th Annual Review of Progress in QNDE
,
AIP Conf. Proc
, (expected 2019).
13.
R.
Livings
,
A.
Mayes
,
E.
Biedermann
,
J.
Heffernan
,
L.
Jauriqui
,
B.
Goodlet
, and
S.
Mazdiyasni
, “
Detection of Microtexture Regions in Titanium Turbine Engine Disks using Process Compensated Resonance Testing: A Modeling Study
,”
45th Annual Review of Progress in QNDE
,
AIP Conf. Proc.
(expected 2019).
14.
A.
Migliori
,
J.
Sarrao
,
M. W.
Visscher
,
T.
Bell
, M Lei,
Z.
Fisk
, and
R.
Leisure
, “
Resonant ultrasound spectroscopy techniques for measurement of the elastic moduli of solids
,”
Physica B
,
183
, pp.
1
24
, (
1993
).
15.
A.
Migliori
, and
J. L.
Sarrao
,
Resonant Ultrasound Spectroscopy
,
New York
,
Wiley
, (
1997
).
16.
G.
Liu
, and
J. D.
Maynard
, “
Measuring elastic constants of arbitrarily shaped samples using resonant ultrasound spectroscopy
,”
Journal of the Acoustical Society of America
,
131
, n.
3
, pp.
2068
2078
, (
2012
).
17.
M. C.
Remmillieux
,
T. J.
Ulrich
,
C.
Payan
,
J.
Riviere
,
C. R.
Lake
, and
P.-Y.
Le Bas
, “
Resonant ultrasound spectroscopy for materials with high damping and samples with arbitrary geometry
,”
Journal of Geophysical Research: Solid Earth
,
120
, pp.
4898
4916
, (
2015
).
18.
L. H.
Rettberg
,
B. R.
Goodlet
,
T. M.
Pollock
, “
Detecting recrystallization in a single crystal Ni-base alloy using resonant ultrasound spectroscopy
,”
NDT & E International
,
83
, pp.
68
77
, (
2016
).
19.
T. J.
Lesthaeghe
,
R. A.
Adebisi
,
S.
Sathish
,
M. R.
Cherry
, and
P. A.
Shade
, “
Toward characterization of single crystal elastic properties in polycrystalline materials using resonant ultrasound spectroscopy
,”
Materials Evaluation
,
75
, n
7
, pp.
930
940
, (
2017
).
20.
B. R.
Goodlet
,
C. J.
Torbet
,
E.
Biedermann
,
L.
Jauriqui
,
J. C.
Aldrin
, and
T. M.
Pollock
, “
Forward models for extending the mechanical damage evaluation capability of resonant ultrasound spectroscopy
,”
Ultrasonics
,
77
, pp.
183
196
, (
2017
).
21.
J.
Plesek
,
R.
Kolman
, and
M.
Landa
, “
Using finite element method for the determination of elastic moduli by resonant ultrasound spectroscopy
,”
Journal of the Acoustical Society of America
,
116
, n.
1
, pp.
282
287
, (
2004
).
23.
R. L.
Iman
,
J. M.
Davenport
,
D. K.
Zeigler
,
Latin Hypercube Sampling (Program User’s Guide)
,
Albuquerque
,
Sandia Laboratories and Texas Tech University
, (
1980
).
24.
A.
Migliori
and
J. D.
Maynard
, “
Implementation of a Modern Resonant Ultrasound Spectroscopy System for the Measurement of the Elastic Moduli of Small Solid Specimens
,”
Review of Scientific Instruments, AIP
,
76
, pp.
121301
, (
2005
).
25.
J. C.
Aldrin
,
A.
Mayes
,
L.
Jauriqui
,
E.
Biedermann
,
J.
Heffernan
,
R.
Livings
,
B.
Goodlet
,
S.
Mazdiyasni
, “
Uncertainty Quantification of Resonant Ultrasound Spectroscopy for Material Property and Single Crystal Orientation Estimation on a Complex Part
,”
44th Annual Review of Progress in QNDE
,
AIP Conf. Proc.
,
1949
, pp.
140010
, (
2018
).
26.
Kuhn
,
H-A.
and
Sockel
,
H-G
, “
Elastic Properties of Textured and Directionally Solidified Nickel-based Superalloys Between 25 and 1200° C
,”
Materials Science and Engineering
,
A112
,
177
126
, (
1989
).
27.
C.
Zener
,
Elasticity and Anelasticity of Metals
,
Chicago
,
University of Chicago
, (
1948
).
This content is only available via PDF.