1. Peter Hammersberg, Gert Persson, Håkan Wirdelius
Emulation of POD curves from synthetic data of phased array ultrasound testing
Peter Hammersberg, Gert Persson, Håkan Wirdelius

2. Variations in NDT responses is the sum of variations from many sources
Dominates and difficult to estimate makes
general modeling
difficult

3. …makes NDT modeling lag
Design Evolution
Trial & Error
Empirical
Mathematical
Statistical
Deterministic
(Factors of Safety)
Stochastic
(Risk Quantified)
Random Experimentation
Experience-based
Systematic Experimentation
Graphical Approaches
Physics-based Analytical Models
Nominal Solutions
Physics-based System Simulations
Robust Solutions
Provided by GE Aircraft Engine Division

4. NDE capability by POD Response Defect size Signal magnitude
Probability of detection (POD) a â
Experiments or simulation

5. Mathematical modelling of UT
simSUNDT
The simSUNDT program (freeware) consists of a Windows®-based pre-processor and postprocessor
The simSUNDT enables simulations of the entire ultrasonic testing situation.
The model is completely three-dimensional though the simulated component is two-dimensional
simSUNDT uses as a mathematical kernel, UTDefect, that employs various integral transforms and integral equation techniques
Model of ultrasonic backscattering due to grain growth in a welded region
The result can be read by a number of commercial analysis software
Reduce number of test pieces and synthetic defects

6. Development of simulation model
Phased array UT
E.A. Ginzel1 and D. Stewart2 , PHOTO-ELASTIC VISUALISATION OF PHASED ARRAY ULTRASONIC PULSES IN SOLIDS, Proc WCNDT 2004

7. Development of simulation model
gj =g0+jDg
p(r) g0 A0 A1 A2
A-1
A-2 xl
Figur 2
Phased array UT
Simulation time 5-15 minutes per run

8. Experimental verification of the model
Dimensions of used test specimen (12%Cr Steel) 20 40 60 10 80
300
5 Side-Drilled Holes 6 Flat- Bottom Holes all f = 2.4 mm 35 5
Depth 20, 40 and 60
Depth 10, 30 and 50

9. Experimental verification of the model

10. Procedure for synthetic data based POD
The inspection objectives
Nondestructive Testing (NDT).
UT, ET, RT UT, ET, RT
(technique, method)
Nondestructive Evaluation (NDE).
UT, ET, RT Hit/Miss
(procedure, calibration)
The NDT procedure
Essential parameters:
x0 = a x1 x2
... xn
Technical Justification:
x1 ±D x1 and
x2 ±D x2 and
...
xn ±D xn and

11. Problem
POD curves need to capture experimental variation from many sources:
Many variables > 10
Many simulations
amount of simulation runs grow very quickly
Emulation of model simulators by computer experiments using experimental design
Simulator
Real world
Emulator

12. Calibration of simulation model to experimental data collection
Simulation Control factors, Ci
Responses:
Input Signal M
SimsuNDT
Y = f(x)= f(M,Ci,Ni)
Measured phased array
signal amplitude (dB)
Diameter: 3mm
Depth: 15-75mm
Ref depth: cali. 55mm (0db)
Intended Output Signal Y
Delta= 0 [5,75mm]
Calibrate simulation to follow measurements for defect size 3mm for all defect depth
Noise Parameters Ni
(Uncontrollable Sources of Variation)
Variation in settings and input mtrl
Measurement variations
Piece-to-Piece variation
Side hole variations
Equipment between & over time
Simulation model
Operator usage
Environment
System interaction
Unintended Output (Error State)
Deviation between measurements and simulations

13. Work path – predictive modeling
Simulation control factors
Locked at
Reason for locking
Computer experimental stage
Factor
unit
low
high
Focal plane mm 20
500
Change scenario
Screening in three steps with fractional design of experiements
Focal adjustment %
-20
minor impact on both responses
Couple ant
0,05
0,4
0,2
Sound velocity tranvers (T)
mm/s
5404
6604
6004
Sound velocity tranvers (S)
2979
3641
3310
Frequence
MHz 4 6
5,75
Set to minimise difference between measure and simulated signal amplitude (delta=0) for the defect depth range tested - calibration of simulation
Full factorial design of experiments
Band width 3 5
Sensor length 11 22
Defect depth 15 75
Control factors for emulation of the simulation by predictive modelling: meta-modelling
Amplitude damping
Angle 41 49
Sensor elements # 2

14. Make simulator follow real world variations with simulation factors with limited physical meaning
Keep flat

15. Emulation of simulator by experimental design - 2 order model
47 simulations
Adding defect characteristic:
Defect Diameter

16. Emulation of simulated signal amplitude (meta-model)

17. Response surface
Sim signal vs defect size and depth

18. Emulation of signal response variation Monte-Carlo estimation of 5000 points per setting (<1sec) (compared to simulation 5-15 minutes per point)

19. Example of Probability of detection
Detectability limit -6 [dB]
Defect depth: 65 mm
Defect diameter: 1,5 mm
POD: 17,58 %

20. POD
Example of emulated POD curves from synthetic data of phased array ultrasound testing
Detection threshold:
-6dB from reference defect

21. Conclusion
simSUNDT has the possibility to simulate Phase Array, and is experimentally verified for the current setup
Emulation of the simulation model by meta-modeling allow parameter studies of variability such as POD
Calculation time ~1:10000
Complicated physical simulation models may need emulation by computer experiments, including Gaussian Process emulators, for example:
Signal amplitude – multi-parameter regression sufficient (shown)
Signal response angle – require higher level stochastic modeling (not shown since no POD relevance)

22. Deliverables Publication:
G. Persson and H. Wirdelius, “Recent survey and application of the simSUNDT software”, Proc. Review of Progress in Quantitative Nondestructive Evaluation, Kingston, 2009.
H. Wirdelius and G. Persson, ”Simulation based validation of the detection capacity of an ultrasonic inspection procedure”, accepted abstract, International Symposium On Fatigue Design & Material Defects, Trondheim, 2011.
H. Wirdelius, P. Hammersberg and G. Persson, ”Predictive modeling of POD curves”.
Integrity and quality assessment by NDE (IqNDE).
The PICASSO project (EU) - imProved reliabIlity inspeCtion of Aeronautic structure through Simulation Supported POD (6M€)

23. Future plans
Experimental validation of a more realistic situation with artificial fatigue cracks (EDM notches).
Compare experimentally based POD curves with corresponding emulated from synthetic data.
Include higher level stochastic modeling into the emulator.