Damage precursor detection to outsmarting fatigue

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UNCLASSIFIED The Nation’s Premier Laboratory for Land Forces UNCLASSIFIED The Nation’s Premier Laboratory for Land Forces

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Damage Precursor Index Methodology for Aviation Structures

Ed Habtour1, Daniel Cole1, Christopher Kube1, Adam Svensken1, Mark Robeson2, and Abhijit Dasgupta3

1 U. S. Army Research Laboratory, APG, MD 21005 USA 2US Army Aviation and Missile Research, Development, and Engineering Center, Ft. Eustis, VA 23604 USA

3Center for Advanced Life Cycle Engineering, University of Maryland, MD 20742 USA

Ed Habtour, Ph.D., P.E., Team Lead Prognostics & Diagnostics, Vehicle Technology Directorate at ARL [email protected]

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UNCLASSIFIED The Nation’s Premier Laboratory for Land Forces

Objective 1)  Understand materials evolution 2)  Incorporate precursors into models 3)  Track changes in nonlinear dynamics

Damage Precursor: Aviation

Challenges 1)  Characterize Precursors:

i.  classes of materials ii.  loading profiles iii.  environmental Conditions

2)  Nonlinearity: i.  manifestation of health ii.  parameters sensitivity iii.  multiaxial loading

Army Impact

1)  Prolong the life of critical components to achieve “Fatigue-Free”

2)  Provide fast, relevant health information

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The Why: FY16 Army Budget

1 FY2016 Army Budget Overview, Deputy Assistant Secretary of the Army (DASA) for Budget , 2015 2 Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2014-15 Edition, Military Career

Operations and Maintenance $45B, 36%

Military Personnel $56B, 44%

Other, $2B, 2%

Procurement & RDTE,

$23B, 18%

Battle Damage Assessment and Repair is not a driving

maintenance factor

OCO Request1 O&M $12B (55%)

FY16 Army Request1

Base: $126B OCO: $ 22B

~ 27% of Army personnel2 are in sustainment functions

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Current State: Data Collection

Materiel Instrumentation Data Collection Systemic

Issues RootCauses Mi1ga1ng Correc1veMeasures

Deploy field analysts

Increase number of field data collectors world wide

Analyze field data

Utilize Physics of Failure capabilities

Increase LSS Green & Black Belt

Update training, manuals and requirements and integrate solutions

“… none are connected and provide a coherent description of what failed and why,…. Hence, there is no realistic, formal way to track successes, analyze failures… from past acquisition programs.” Final Report of the 2011 Army Acquisition Review

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Shigley, Mechanical Engineering Design (2001)

Fatigue Loading in Shafts and Axles:

!!!32 = ! !!

!! + !!!!!!

!+ !!

!! +!!"!!!!

!!!

d = diameter !! = alternating moment !! = mean moment

!!= alternating torque !! = mean torque !! = yield strength ! = safety factor !! = fatigue strength reduction factor !!" = fatigue strength reduction factor for shear !! = fatigue limit !! = !!!!!!!!!!!!! !! = Surface Factor !! = ! !!"! !! = Load Factor (Bending, Torsion, …) !! = Size Factor !! = Temperature Factor !! = Miscellaneous Effects Factor

Current State: Design

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Detect Precursors

Structural Mechanics

Micro- mechanics

Nonlinear Dynamics

Damage Sensors Repair

Open-loop Monitoring Integrated State Awareness & Control

Current State of the Art ARL

ARL: Future State of the Art

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Approach

Project 1: Metal Alloys •  Steel 1095 •  Al 7075

Project 2: Composite • Glass/epoxy •  IM7/8552 •  IM10 Project 3: Composite Constituents •  Individual IM7 •  8552 •  Fiber/Matrix

Future Materials •  3-D Printed •  Hybrid Alloys Select Aviation

Materials

Local Materials Characterization (e.g. SEM, AFM, EBSD, Nanoindentation)

Identify Precursors

Create State Awareness Models

Global Sensing (e.g. UT, Electrical, Optic, IR, EMI)

Detect Precursors – COTS sensors

Conventional & Multifunctional Sensors:

Performance, Sustainment & Survivability

Engineering Models

•  Connect Micro to Macro-Mechanics

•  Apply Nonlinear Dynamics

0

1

2

3

4

5

6

46.4 46.6 46.8 47 47.2 47.4 47.6 47.8 48

Res

pons

e (m

m)

Freq. (Hz)

Translation Base Excitation 0.3g, Ramp up 30s, Dwell 20s, 5in beam, AR=8

Test 1

Test 2

Test 3

Test 4

Test 5

Model 1

Model 2

Model 3

Model 4

Model 5

Dynamic Loading •  Structural •  Rotating •  Tension-Tension •  3- Point Bend

Environmental Loading

•  Thermal Cycling

Excite Structure – Laboratory testing

Mechanical Properties

•  Tension •  Bending •  Shear

Control Loads

20 µm

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Damage Precursor in Alloys: Identification

Research Results

E. Habtour, D. Cole, M. Robeson et al., Str Ctrl & Health Monitoring, 2016 E. Habtour, D. Cole., Int. J. of Nonlinear Mechanics, 2016

𝑚�̈� + 𝑐�̇� + 𝑘𝑦 = 𝐹 𝑚 = inertia, 𝑐 = Damping, 𝑘 = Structural stiffness Nonlinear system:

𝑚𝑒𝑓𝑓 �̈� + 𝑐�̇� + 𝑘𝑒𝑓𝑓 𝑦 + 𝑁𝑖(𝑦2�̈� + 𝑦�̇�𝟐) + 𝑁𝑔 𝑦3 = 𝐹 𝑁𝑖 = Nonlinear inertia, 𝑁𝑔 = Nonlinear stiffness, 𝐹 = Base excitation

•  Detected precursors with COTS sensors •  Nonlinear detection models for transverse rotational Vibration

Accomplishments

a)

b) c) After

20 µm

Fatigued Beam Free Surface

Alloy Cantilever under Harmonic Oscillation

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Damage Precursor in Alloys: Verification

Research Results

Control 75K cycles 150K cycles BCC

Ferrite

Fe3C Cementite D. Cole, E. Habtour, et al., to be

submitted to Experimental Mechanics, 2016

•  Changes in local micro-mechanical properties prior to crack initiation

•  Confirmed precursors using novel techniques •  Nano-indentation •  AFM, EBSD

Accomplishments/Advancements

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Damage Precursor: Global Model

Equation of motion for nonlinear system is: !!""! + 2!!!""!!! + !!""! + !!"#$ !!! + !!! + !!"#$!! = !!!!

Nonlinear inertial coefficient including tip rotary inertia is:

!!"#$ = ! !!"!"!

!

!

!"!

!+! !!"!"

!

!

!

!!!+ !!!" !!!

Effective stiffness and nonlinear geometric stiffness coefficients:

!!"" = !" !!!"!"!

! !!"#$ = 2 !" !!!!! !!"

!

!

!! =1+ 3!

!

4!!"#$!!""

1+ !!

2!!"#$!!""

Equation of motion for linear system is: !!""! + 2!!!""!!! + !!""! = !!!!

E. Habtour, et al., to be submitted to Mech Sys & Sig Pro, 2016

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Damage Precursor: Micromechanics Model

ρ∂2ui∂t2

=∂2uk∂x j∂xl

Cijkl +∂um∂xn

Cijklmn +δkmCijnl +δikC jlmn +δimC jknl( )⎡

⎣⎢

⎤

⎦⎥

Quadratic Nonlinearity Term

u a( ) = u1 cos ka−ωt( )−u2 sin 2 ka−ωt( )+ ...

where ( )222 1

8a ku uβ= →

β ≡ Quadratic Nonlinearity Parameter

( )22

1

8ua ku

β =

Second-harmonic amplitude gives an experimental parameter

measured lattice damageβ β β+=

C. Kube and J. Turner, J. Acoust. Soc. Am., 2015

C. Kube and J. Turner, J. of Elasticity, 2015

Damage Quantification from Harmonic Generation

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Damage Precursor: bridging the scales

Example of 3-Dimensional Distribution of Material Nonlinearity for Titanium Single Crystals

•  Nonlinearity is directionally dependent •  Nonlinear response depends on dilational or shear wave displacement

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C. Kube and J. Turner, J. Acoust. Soc. Am., 2015

C. Kube and J. Turner, J. of Elasticity, 2015

Effective elastic moduli needed to define requires averaging over all orientations of the grains

β

( )2 1

0 1

1 , d d4ijkl ijklC Cw

πχ φ χ φ

π −〈〉 = ∫ ∫

( )2 1

0 1

1 , d d4ijklmn ijklmnC Cw

πχ φ χ φ

π −〈〉 = ∫ ∫

( )0 ˆ ˆ ˆ ˆ ˆ ˆˆ ˆ ˆ ˆ

ijklmn ijnl jlmn jkm ik im j l n i k m

j l i

knl

j ki kl

n n n u uC C un n u

C CC u

δ δ δβ

〈〉 + + +〈〉〈〉〈〉

〈〉= −

2z 3z4z

5z

4x

5x

2x

3x1z

1x 1y

4y 5y

2y

3y1z

1x 1y

Single Grain Elastic Modulus

Aggregate Elastic Modulus

ijklC

〈Cijkl 〉

Damage Precursor: bridging the scales

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Characterizing: Induce Damage Precursors in Composites

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 13

3.5

4

4.5

5

5.5

6x 10-5

N/Nf

com

plia

nce,

s

Bulk Composite – Compliance Effect Measured during 3-pt Bend Test

Microtensile Testing for Individual Microfibers

0

1000

2000

3000

4000

5000

6000

0.0

0.5

1.0

1.5

2.0

2.5

3.0

50 100 150 200

Failu

re S

tress

, MPa

Failu

re S

train

, %

Failure Displacement, µm

28 mm

12.5

mm

gage lengthadhesivefiber

gripped region

load(m

m/N

)

Elastic Modulus Map Conductivity Map

UNCLASSIFIED

UNCLASSIFIED The Nation’s Premier Laboratory for Land Forces Habtour, et al. Shock and Vibration (In Preparation)

Damage Precursor: Nonlinearity vs. Control

!!""! + 2!!!""!!! + !!"" − !!!!!! − ℎ!!!! ! + !!"#Ω!!!!+!!"#$ !!! + !!! + !!"#$ − ℎ!!!! !! = !!Ω! + !!!!


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Sense Evolution: •  Ultrasonics •  Electric Impedance •  Thermocouple •  Accelerometer •  Fiber optic

Material Evolution: •  Fibril stiffness •  Cavitation •  Deformation/Stress •  Debonding •  Compliance •  Micro-structure

Sense Precursors

Precursors Models (MRC)

Uncertainty Quantification

(ISC/CSC)

Provide Current State

Adapt Control

• Reduce damaging flight loads

• Maintain Capabilities • Optimize • Relearn

Sensor/Data Fusion

Operational Loads

Risk Assessment (ISC/CSC)

RUL Models (ISC/CSC)

Survivability Models

(ISC/CSC)

Forecast Future State

Material Degradation

Sensor Data

Current State

Projected Capabilities

Proposed Solution

Propeller System: •  Propellers •  Bearings •  Controllers

Materials System:

•  Composite •  Alloys

State Information

Integrated State-Awareness & Control

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Update Health State

Micromechanics and Structural Testing Facilities

Adaptive Controls

ARL Computational Facilities

Reliability & State Awareness Facilities

Integrated State-Awareness & Control

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Transonic Experimental Facility

Rodman Materials Research Laboratory

Rotorcraft Survivability Assessment Facility

Pulse Power Facility

Access to Partner Facilities

Zahl Physical Sciences Laboratory Shooter Performance Facility

DSRC & Scientific Visualization Facility

Robotics Research Facility

Vertical Impulse Measurement

Facility

Environment for Auditory Research

Fuel Reformation Laboratory

Novel Energetics Research Facility

Electromagnetic Vulnerability Assessment

Facility

Microsystem Indoor Testing Grounds

Specialty Electronic Materials and Sensors Cleanroom

Vehicle Research Laboratory

ARL Technical Infrastructure

Academia Industry

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C. Kube and J. Turner, J. of Aco Soc of Am, 2015 C. Kube and J. Turner, J. of Elasticity, 2015 D. Cole, E. Habtour, et al., ASME SMASIS, Colorado Springs, CO, Sept 21-23, 2015 E. Habtour, D. Cole, M. Robeson et al., Structural Control & Health Monitoring, 2016 E. Habtour, D. Cole., Int. J. of Nonlinear Mech, 2016 D. Cole, E. Habtour, et al., to be submitted to Exp Mech, 2016 E. Habtour, et al., to be submitted to Mech Sys & Sig Pro, 2016 Additional References: FY2016 Army Budget Overview, Deputy Assistant Secretary of the Army (DASA) for Budget , 2015 Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2014-15 Edition, Military Career Shigley, Mechanical Engineering Design (2001)

Publications


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US Army Research Laboratory: •  Nano- & Micromechanics Characterization: Dr. Daniel Cole, [email protected] •  Composites DP Detection: Dr. Robert Haynes, [email protected] •  Composites Micromechanics Modeling: Dr. Todd Henry: [email protected] •  NDE & Materials Constituents Modeling: Dr. Christopher Kube, [email protected] •  SHM-Based Adaptive Controls: Mr. Brent Mills, [email protected] •  System Identification & Fault Detection: Dr. Ed Habtour: [email protected] Collaborators: US Army Aviation and Missile Research, Development, and Engineering Center: Aviation Structures Durability: Mark Robeson, [email protected]

Center for Advanced Life Cycle Engineering, University of Maryland: Experimental and Computation Mechanics: Dr. Abhijit Dasgupta, [email protected]

Damage Precursor: Efforts Leads

Damage precursor detection to outsmarting fatigue

Engineering

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