PICASSO - TRIMIS · PICASSO Consortium is in contact with this MAPOD WG in order to present and...

PICASSOA new and original concept of « simulation supported Probability of Detection »

AERODAYS 2011

March 31th, 2011 – Madrid

Nancy MALEOSnecma (Safran Group)Villaroche site, Francee-mail : [email protected]

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AERODAYS 2011 – Madrid – March 31th, 2011

This document and the information contained are Snecma property and shall not be copied or disclosed to any third party without Snecma prior written authorization.

Oultines

Introduction / Overall viewTechnical and Innovative contextObjectives of PICASSOPartners involved / Overall startegyPreparation of the project results exploitationConclusions


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Introduction / Overall viewPICASSO is a research collaborative project registered in the Seventh Framework Programme of the European Commission

Start date : July 1rst, 2009

Duration : 36 months

Project Cost ≈ 7,3M€

Project EC Funding ≈ 5M€

14 european partners – Coordinator = Snecma

AimAim :: build a new and original concept of “simulation supported Probability of Detection (POD) curves based on Non Destructive Testing (NDT) simulation in addition

to existing experimental data base”.

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Technical context (1/4)

AeronauticalAeronautical criticalcritical parts parts designdesign

Damage toleranceconcept

Aeronautical structures contain flaws due to :§ inherent material structure§ material processing§ component design§ manufacturing§ usage

“Damage tolerance is the ability of the engine to resist failure due to the presence of flaws, cracks,

or other damage, for a specified period of unrepaired usage.” (MIL-HDBK-1783)

Critical Part : component whose failure will result in probable loss of the aircraft.

Damage Tolerance requirements are developped through the Engine Structural Integrity Program (ENSIP) in 1984 (normative

document MIL-HDBK-1783).

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Example scheme of damage tolerance rule :

Cycles

Size of fatigue crack

Break

Fatigue crack size which is not detected

Predictive life span of the part (D)

Crack propagationIn-service inspection of the part

Autorisation to use the part è D / 2

Maintenance intervals are driven by NDT capability

Probability of Detection (POD) estimation is one way of quantifyingthe reliability of NDT

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NDT are defined by procedures and performed by qualifiedinspectors

BUTBUTThe results of NDT remain subjected to « uncertainties » which

appear as scattering in the result dataset.

Why talking about Probability of Detection ?

Possible sources of uncertainty :üDefect (geometry, …)üProcedure (fine tuning, …)üTesting equipment (one instrument & an equivalent one)üMaterial of the part (structural noise and conductivity variability, …)üMechanical repeatability (positionning of the probe, …)üHuman appreciation (diagnosis)ü…

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WhatWhat isis the the minimum sizeminimum size of indication of indication thatthat cancan bebe reliablyreliably detecteddetected duringduring

inspections inspections ??((not the smallest flaw that can be found))

DemonstrationDemonstration of the of the capabilitycapability of of NDTNDT

Probabilityof Detection

100%

0%

90%

a90-95 Size of defect :a

POD(a) 95%

POD(a) 50%

a90-50


100%

0%

90%


POD(a) 95%

POD(a) 50%

a90-50

POD estimation

=

MIL-HDBK-1823 : general guidance for assessing the capability of an NDE system in terms of the probability of detection (POD).

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Innovative context (1/2)

Simulation supported POD concept

Fully experimental data

§ often technically impossible to realize

§ cost and time consuming

§ configurations equivalence not available

PICASSO

NDT simulation tools (UT, ET, RT)

Simulated data

Experimental campaign+


100%

0%

90%


POD(a) 95%

POD(a) 50%

a90-50


100%

0%

90%


POD(a) 95%

POD(a) 50%

a90-50

“simulation supported Probability of Detection (POD) curves based on Non Destructive Testing (NDT) simulation in addition to existing experimental

data base”

cost and time

reliability

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Innovative context (2/2)Main advantages of the «Main advantages of the « simulation supported PODsimulation supported POD » »

concept :concept :Experimental POD Simulation supported POD

- Difficult to manufacture real defects - simulation of complex defect geometries, easy positioning by modelling

- Limited number of samples - Large number of samples

- Limited number of defects - Large number of defects

- Several operators needed - NDT procedure is respected

- Respect of the NDT procedure (sometimes operators change parameters for a better detection)

- Find equivalence between artificial and real defects by modelling (in order to manufacture only “easy” defects)

- Human factor will not be treated in the framework of this project

POD data exploitation - Data collection - Automatic data exploitation can be implemented with

simulation tools

- Use simulation to find transfer function to find equivalence between POD configurations

- Reduced POD campaign sufficient for a new configuration

Sample manufacturing

NDT inspection campaign

New POD configuration - Need to do a new POD campaign

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Objectives

To overcome cost issue of the Probability of Detection campaign with Non Destructive Testing simulation techniques.

Validation of the concept of “simulation supported POD” by initial realistic results, implementation and methodologies.

Main result expected :Main result expected :

More accurate and reliable POD curves

More appropriate damage tolerance assessments for

critical parts

Approved life of the partApproved life of the part

Potential risk of failure from induced

anomalies ?

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14 partners

H T SHoch Technologie Systeme

World Centre for Materials Joining Technology

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Overall strategy

Influent parameters description

WP5

–M

anag

emen

t and

coo

rdin

atio

n

WP6

–Ex

ploi

tatio

n an

d di

ssem

inat

ion

WP1 – Initial input

Validation cases used to validate the simulation

supported POD methodology

Description of material properties, defect geometries

and equipment for the development of models

WP3 – Simulation supported POD

WP2 – Modelling

WP4 – Assessment of new POD

methodology

Accurate, reliable and numerically efficient

simulation tools.

Common prototype software for simulated

supported POD determination

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Overall strategy – WP2NDT simulation softwares

Ultrasonic TestingElastodynamic Finite Elastodynamic Finite Integration Technique Integration Technique

(EFIT)(EFIT)Owner : IZFP-D

Numerical 1-D, 2-D, and 3-D simulation modules for elastic wave propagation problems

CIVA UTCIVA UTOwner : CEA List

NDT simulation software which offers the user physics based models for UT technic.

X-Ray TestingCIVA RTCIVA RT

Owner : CEA List

NDT simulation software which offers the user physics based models for the X-Ray technic.

Analytical RT inspection Analytical RT inspection simulation tool (simulation tool (aRTist) aRTist)

Owner : BAM

Simulation of radiographic imaging. Modeling of the real inspection scenario by defining a virtual setup.

Eddy Current TestingVICVIC--3D3D

Owner : HTS

NDT technic concerned : EC

Simulation of EC technique

VACVACOwner : Chalmers / Volvo

Simulation software of EC technique to build simulated data base.

CIVA ECCIVA ECOwner : CEA List

NDT simulation software which offers the user physics based models for EC technic.

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Oultines

Introduction / Overall viewTechnical and Innovative contextObjectives of PICASSOPartners involved / Overall startegyPreparation of the project results exploitation

Conclusions

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Preparation of project resultsexploitation (1/2)

Approval of the concept at regulation Authorities level :

RISC group : Composition : engine manufacturers and the FAA, EASA and Transport Canada authorities. Missions : propose to FAA authority recommended practices to guarantee the tolerance to damage (metallurgical and surfaces defects) for the critical parts of turbojets (rotors).

The NDT and especially their POD curves are animportant tool of proposed probabilistic methodsin order to contain the risk of breakdown ondefects.

PICASSO Consortium in contact with the RISCGroup and present a progress each year duringtheir European meeting.

The RISC Group is very interested in PICASSOproject.

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Contact with Model-Assisted POD (MAPOD) Working Group :MAPOD WG Composition : American organization which gathers representatives of Aeronautic industries, regulation authorities, Defense Government, Navy and universities.Objectives : promote theincreased understanding, development and implementation of model-assisted POD methodologies.Very influent organization in POD domain.

PICASSO Consortium is in contact with thisMAPOD WG in order to present and explain theEuropean “Simulation Supported POD” approach.

Some PICASSO partners have met the leader ofthe MAPOD Working Group during theQuantitative Nondestructive Evaluation (QNDE)Conference in San Diego in July 2010.

Preparation of project resultsexploitation (2/2)

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Conclusion

The “simulation supported POD” concept improves the reliability of POD calculations by :ü increasing the population of POD samples with defects üby enabling the simulation of sub-components

configurations.

The main result of the project will be the validation of the concept of “simulation supported POD” by first realistic results, implementation and methodologies.

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PICASSO

AcknowledgmentsMany thanks the members of the consortium of PICASSO project for the work performed and the participation to this presentation.Thank you for your attention !

www.picasso-ndt.eu

For more informations …

Questions ?

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BACK-UP

Quick overview of the current status

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WP1 – Initial Input

ü Description of the some equipments available : eddy current probes, …

ü Description of some material properties available : ultrasonic noise in Titanium alloy /

X-ray diffraction in single Ni crystal

ü Validation cases selected by the industrial partners available

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WP2 - Modelling

ü Parameters fluctuation scenary implemented in the NDT softwares

ü Developments of material models in progress and adaptation to simulate NDT

techniques more reliable

ü 3D tools implemented in the NDT softwares

3D-2D conversion tool : Description of the principle

3D CAD data 2.5D CAD specimenNotchNotch no more no more detecteddetected

Input determination

Analysis

POD determination

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WP3 – Simulation supported POD

ü Studies concerning the combinaison of experimental measurements and

modelling data in progress.

ü Methods and tools selected for the POD application

ü Uncertainties modelling strategy defined

ü Improvement of the POD estimation model in progress

Deterministic Deterministic

DeterministicNDT

simulation software

Input parameters Output Values

X Y

Uncertainty propagation

With uncertainties With variability

Challenge :Challenge : how to generate data with uncertainty with fully deterministic how to generate data with uncertainty with fully deterministic simulation tools?simulation tools?

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WP4 –Assessment of the new POD methodology

ü Preliminary simulation runs on the validation cases performed

ü Experimental measurements on the validation cases started

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