technical programs in place in eddy current mapod march/technical programs in...

3/9/2006 MAPOD WG Mtg, Atlanta 1CENTER

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Technical Programs in Place in Eddy Current MAPOD

Norio Nakagawa, CNDE/ISUJay Amos, Cessna/Textron

Kevin Smith & Dave Raulerson,Pratt & Whitney/UT


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Outline

Overviews of• Background• Two On-Going Projects

– Air Force project, with Pratt & Whitney– FAA project, with Cessna

• Partner Perspectives

• Technical Activities– Selected Technical Topics


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Overview ofBackground


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Long Range Goal of MAPOD Demonstration Plan

Empirical POD vs. MAPOD demonstrations• Full MAPOD methodology demonstration

– Identifications of• Empirically tractable controlling factors• Empirically intractable controlling factors Model

• By case studies– Cracks in blocks– Cracks in geometry


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Plan for POD/MAPOD Comparison• Perform full 1823 determination of POD in a designed experiment in which

all controlling factors are treated empirically– This may require significant time and cost.

• Determine a subset of the controlling factors (to be called empirical factors) that can more readily be treated in an empirical experiments and perform an 1823-like study to determine mean flaw response, and its variability, as a function of size.

– These empirical factors will include human factors and other effects not amenable to treatment by physics-based models but would likely not include both the effects of naturally occurring flaw morphology and component geometry.

• Use physics-based models to extend the results obtained in step 2 to the full set of controlling factors.

– This means determining the changes in mean flaw response and its variability as a function of size due to the additional controlling factors not addressed in step 2.

• Predict the POD of the original problem based on the results of steps 2 & 3.• Compare that POD to the value obtained in step 1.


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Required Starting Point

• Validated physics-based models for flaw response as a function of controlling factors

• Strategy for building in effects of variabilities to enable predictions of distributions


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Subset of MAPOD Work Elements

• Model Development & Validation– #1 Priority in Austin Meeting Report

• Input parameters – how to determine– Input parameters in average– Variability

• Output - where to use– Average-value predictions

• e.g. “shift of â-vs-a lines”– Estimation of certain variability

• Of mechanical origin by Monte Carlo simulation• Converting input variability to output variability


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CNDE EC Modeling• Modeling Algorithms

– Analytical methods• Dodd-Deeds Solution

– Numerical methods• Finite Difference• Finite Element• Volume Integral

Boundary Element• Hybrids

Physics-based models– Idealize the system

of an EC probe and parts

[ ]( ) ( )[ ]HHiEEdV

I

HEHESdI

Z

v

S

′⋅Δ+′⋅Δ−

=

×′−′×⋅=Δ

∫

∫rrrr

rrrrr

μωσ2

2

1

1Auld’s reciprocity formula

ferrite corecoil

part surface crack

Probe

Part

edge


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Modeling ProcedureElement-rendition of

probe/part/crack

• Complex probe configuration• Complex part geometry

BEM-basedcomputational model


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C-Scan Images of Fatigue Crack

@700kHz

TH

EXPT

R X


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Experience in MAPOD

Monte Carlo

Empirical

ROC

POD

N. Nakagawa and R. E. Beissner, Rev. QNDE 9A, 893-899, 1990; N. Nakagawa, M. W. Kubovich, and J. C. Moulder, op. cit., 1065-1072.

1mm 0.5mm

(1) Noise PDF(2) Signal PDF(3) Signal⊗Noise


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Overview ofTwo On-Going Projects

Air Force project, with Pratt & Whitney

FAA project, with Cessna


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AF Project• Participants

– N. Nakagawa, R. B. Thompson, W. Meeker, L. Brasche, Z. Chen (ISU)

– D. Raulerson, K. Smith (P&W)

• Long-term objectives– To develop a model-

assisted EC POD methodology.

– To develop a fully validated EC model code, being applicable to the model-assisted POD methodology.

• Project Objectives– To validate the EC models,

while assessing accuracy and capability limits.

– To develop the next-generation EC model code, with needed capabilities (crack, notch, and geometry responses)

– To search for practical methods for probe characterization

– To demonstrate MAPOD by case studies


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Planned Activities• Critical examination of modeling capabilities with

validation studies.• Necessary model capability developments

and/or improvements.– Development of the next-generation EC models– Needed capabilities (crack response, notch response,

and geometry response in a single software tool).• Characterization methods of model input

parameters– E.g. probe parameters, noise distributions

• POD vs MAPOD demonstration


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Task Schedule

Task 1 – EC Model validationTask 2 – EC Model development and

probe characterizationTask 3 – Noise Characterization

Measurement and AnalysisTask 4 – Crack vs. Notch Studies

0-24months

Task 5 – Model-Assisted POD Demonstration

24-42months


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Planned Test Matrix

ProbesSolenoid, 30,60/1000” dia.Split-D diff. ref., 30,60/1000”(Elongated) ECP, 120/1000”

Specimens IN-100:3x6, 15x30 notches, cracks

Instrument-ation

Scanner (XY) benchUS-454

probe element model

part model

probe element model

0.06” thick

Modeling Example

0.064” nominal core diameterDrive coil: 2 layers; inner=20 turns, outer=5 turnsD-half coils: 20 turns each

Coil split run perpendicular to flaw and scan direction.

0.02” X 0.01”crack model

0.25” X 0.055”crack model

Surface-breaking vs.Subsurface cracking

Peak amplitudeAs

Ab

%150=b

s

AA

Simulation

Shielding effects on an Absolute Solenoid

Impedance Magnitude

0

0.005

0.01

0.015

0.02

0.025

0.03

-0.060 -0.040 -0.020 0.000 0.020 0.040 0.060

X axis scan (in)

Z m

agni

tude

10 mil gap

20 mil gap

Comparison of gap effects for Absolute Semi-toroid


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MAPOD Demonstration Plan

Empirical POD vs. MAPOD demonstrations• Full MAPOD methodology demonstration

– Identifications of• Empirically tractable controlling factors• Empirically intractable controlling factors Model

• By case studies– Cracks in blocks– Cracks in geometry

Follow General Direction of UT POD Methodology Validation

Steps to validation:• Design, fabricate and

characterize sample• Generate and analyze

system/operator data • Calculate empirical POD curve• Calculate model-based POD

using validated signal and noise models

• Compare empirical POD to model-based POD

SMITH


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FAA Project

• Participants– N. Nakagawa, R. B.

Thompson, W. Meeker, L. Brasche (ISU)

• Partner– J. Amos (Cessna)

• Objectives– Next-generation EC

model software– EC model validation

• Overview of Approach– Simulated airframe

inspections– Fasteners and notches

in multi-layer structure• Overview of plans

– Multi-layer model development

– Model validation– POD curve generation


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FAA Project: Planned Tasks

Task 1Develop EC

Model

Hybrid of BEM and multi-layer Green’s function approachMulti-layer geometry with fasteners, complex probe

Task 2Validate EC

Model

Against multi-layer specimens with notches with and without fastenersDevelop validation protocol

Task 3Generate POD

curves

Both empirical POD and MAPOD curves for comparisonDetailed plan to be developed


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FAA Project: Schedule

Task 1 EC model development

Task 2 EC model validation

0-30months

Task 3 POD curve development

8-30months


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Model geometry

• Complex probe configuration• (multi-layered) plate geometry


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Sliding Probe Model


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Overview ofPartner Perspectives

Air Force project, with Pratt & Whitney

FAA project, with Cessna


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Overview ofTechnical ActivitiesSelected Technical Topics


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Probe Characterization

T. JensenCNDE


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Meshed Probe Objects


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Defect Signal Calculation

• â-vs-a curves– Median values

• Crack signal– Gap between noise

and signal PDF peakslog(Z) vs log(a)

-3

-2.5

-2

-1.5

-1

-0.5

0

-2.5 -2 -1.5 -1 -0.5

log(a), a=length [in]

log(

Z), Z

=Com

pute

d Im

peda

nce

[Ohm

]


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Signal Variabilitydue to Finite Step Size

• Example: Finite Step Size effect

-4.00 -3.00 -2.00 -1.00 0.00 1.00 2.00 3.00 4.00-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

Finite scan mesh


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Mechanically inducedImpedance Fluctuations

• Suppose that variability of an input parameter has been characterized.– Example: Lift-off fluctuation, probe wobble

• Then, the model can calculate impedance signal variability from the input variability– Use, e.g., lift-off signal calculation– Perform Monte Carlo simulation


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Empirical Noise Characterization

Data processing


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Material Noise (Ni-alloy)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0 2 4 6 8 10 12 14

Almen, A-strips

Avg

Rou

ghne

ss, u

m

IN2 Profile (um)IN6 Profile (um)

IN2-6 (8mm filters)

0

1

2

3

4

5

6

7

8

9

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

Profile Avg Roughness, um

EC

Sk V

alue

IN6 Real SkIN6 Imag SkIN2 Real SkIN2 Imag Sk

Inconel 718

• For nominally shotpeened superalloysurfaces, the EC material noise is controlled by roughness.


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Material Noise (Ti-alloy)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 20 40 60 80 100 120 140

Peen Pressure, psi

Avg

Rou

ghne

ss, u

m

Ti-8Ti-12Ti-15

Ti12 & Ti-15 (8mm filters)

0

2

4

6

8

10

12

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

Profile Avg Roughness, um

EC S

k Va

lue

Ti-8 Imag SkTi-12 Imag SkTi-15 Imag SkTi-8 RealTi-12 Real SkTi-15 Real Sk

Ti-6Al-4V

• For nominally shotpeened Ti-alloy surfaces, the EC material noise is not controlled by roughness (presumably by grain noise).


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Topics on â-vs-a Data

0

0.2

0.4

0.6

0.8

1

1.2

-1.5 -1 -0.5


log(

Mag

), M

ag=S

ig. A

mpl

. [vo

lt]

Base

150pF

50Ohm-150pF

Resonance effect

log(V) vs log(a)

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

-2 -1.5 -1 -0.5


log(

V), V

=V c

ompo

nt [v

olt]

1MHz3MHz

log(Mag) vs log(a)

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

-2 -1.5 -1 -0.5


log(

Mag

), M

ag=m

agni

tude

[vol

t]

1MHz3MHz

.120.080

.040.020

No effects on log-amplitude slope.

Some effects on log-vertical slopes.

“Bad cable” effect?

Instru-ment

Artificial cable imbalance

No effects have been found on log-amplitude slope within instrument linearity.


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Are Human Factors Modeled?

• No: Human characteristics themselves are not modeled– Hand dexterity– Cognitive capability– etc

• BUT …– If any inspector-induced mechanical variability

is empirically measured, then it can be input to Monte Carlo models.


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Summary

Presented Overviews of• Two On-Going Projects• Planned Technical Activities

– Generate model validation protocol– Validate the model– MAPOD demonstration


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Summary (cont.)

Planned MAPOD-related activities• Generate fully validated EC models• Demonstrate MAPOD methodology

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