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Computational Modeling of

Complex Systems using

Integrated

Computational Materials

Engineering (ICME)

September 27, 2017

Ibrahim Awad, Nick French

Robert Tryon, Animesh Dey

Sanjeev Kulkarni

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Outline

• Traditional fatigue analysis

– Safe life

– Damage tolerance

• ICME

– Total life analysis

• Probabilistic

• Microstructural

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Traditional Safe Life Fatigue AnalysisEmpirical Methods

Fatigue Life 𝑁 = 𝑓 𝜎, ε

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Fatigue Modifying Factors “Fatigue Strength” is not a material property

fatigue strength of component

fatigue strength of test coupon

e a b c d e f g h i j k e

e

e

S k k k k k k k k k k k S

S

S

= residual stress factor

= texture factor

= corrosion factor

= plating factor

= multi-axial stress factor

g

h

i

j

k

k

k

k

k

k

= surface factor

= size factor

= mean stress factor

= reliability factor

= temperature factor

= notch factor

a

b

c

d

e

f

k

k

k

k

k

k

J. E. Shigley, Mechanical Engineering Design, McGraw-Hill, 1977, pp. 188

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Complex Behavior: Notch effectJIS Steel Data

• S-N curve for

notched specimen

(Kt = 3) plotted with

local notch root

stress

– Fatigue notch

factors (Neuber and

Glinka) are available

but they require

experimentally

determine notch

sensitive factors.

Nishijima et al.

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Size Effect

• IN100 laboratory test data

• Smooth round bars cut from the same block with the same

microstructure

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0 50000 100000 150000 200000

Cycles to failure

Sta

nda

rd N

orm

al

2X bar

1X bar

1/2Xbar

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Fatigue Analysis

Why are there so many

modifying factors?

Fatigue response is

much more complex

than

Fatigue is a process, not

an event

A lot is going on from

the first cycle to the last

𝑁 = 𝑓 𝜎

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Random field of intense slip bands of

plastic deformation

Prof. Christ and co-workers, 13th International

Conference on Fracture, 2013, Beijing, China

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Random field of micro-cracks

• Fatigue is dominated by the growth and coalesce of very

small cracks.

• Fatigue is always governed by very localized damage

DARPA SIPS program

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Random field of crack growth

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Computational Material Model

• Model the material at a fundamental level

• Explicitly model the materials damage tolerance

• Must account for random nature or the important

size scale

• Loading and environment become extrinsic

factors to the material model

• This allows simple test coupon data to be used

directly in fatigue analysis of complex

components

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Traditional Damage Tolerance

• Computationally fracture mechanics modeled fatigue crack growth rate by

calculating the stress intensity factor (SIF) and knowing empirically-derived

material parameters

• SIF similitude is achieved for

– Different loads

– Different crack sizes

– Complex spatial stress gradient

– Varying residual stress gradients

• The downside are the simplifying assumptions

– Damage is a single, well-defined crack of relatively-large size

– Common initial crack size in linear elastic fracture mechanics is 1/32 inch (0.03”).

– No credit given to cycles to initiation

– In high strength materials, initiation can be more than 90% of Total Life

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Damage Tolerance for “Total Life”

Fatigue damage growth analysis using 3-D random

field of microstructural material properties

+

Dislocation Theory

Crystal Plasticity

Small Flaw Fracture

Mechanics (SFFM)

Linear Elastic

Fracture Mechanics

(LEFM)

=

Crack

Nucleation

Small Crack

Growth

Long Crack

Growth

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Microstructurally Short Crack

Top view of real

crack

Top view of

idealized crack

Side view of

idealized crack

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VLM: Grain – FEA – Component – Fleet

Tooth Life: 15,932 cycles

Failure Cause: Defects

VLM Integration for

Entire Component

1st Virtual Twin

Gear Simulated

Component Life:

14,334 cycles

17,561 24,793

27,943

22,229

25,34218,961

22,113

Repeat Sequence

for Each Tooth

Integrate VLM

Results with FEA

Run 1,000 SimulationsVT1, VT2, VT3 … VT1,000

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Output- SN Curve

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Output- Detailed Results

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Simulated Failure Surface MicrostructureGrain Orientation for Bar 1 at 75 Ksi

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Simulated Failure Surface MicrostructureFrictional Strength and Crack Growth Rate

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Load Ratio (R Ratio) Effects

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Vibration Mode Dependent Fatigue

1st Torsion Mode

(Mode 2)

1st Bending Mode

(Mode 1)

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Same material model used for various geometry/loads

Spectrum Loading Fatigue

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Engine Block Example

Images:

https://commons.wikimedia.org/w/index.php?curid=7896227

Technische Universität Wien, e307, für Laborübung/Vorlesung

Microstructural variation

within gray iron casting

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Who is VEXTEC? Founded in 2000: Over $25 million from the

United States Department of Defense

Innovative Research programs for

Technology Development

Proprietary Software and Seven Patents:

Virtual Life Management® (VLM®) is the

basis for VPS-MICRO® software

Customers: Federal Government and

Industries (Aerospace, Automotive,

Electronics, Energy, Medical Devices)

Value Proposition: Help companies

improve products and reduce cost

• New products to market quickly

• Improve reliability of existing products

• Reduce physical and prototype testing

requirements

• Forecast product durability and

manage product life cycle risk

Business Model: Hybrid – Consulting

Services, Software Licensing and Training

VEXTEC accepted into FDA’s

Medical Device Development

Tool (MDDT) pilot Program

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VPS-MICRO Value Proposition

• Our software and support services have generated

superior results for our clients:

– 75% decrease in product development time

– 90% decrease in testing and design costs

• VPS-MICRO is the advanced ICME tool that addresses

fatigue and allows manufacturers to more accurately

identify and gauge potential liabilities.

• VPS-MICRO uses physics to predict the uncertainty and

scatter in material fatigue performance to cost effectively

manage risk.

• By running as many simulations as desired, the user can

optimize resources to create data required for testing

and design.

Replace or

supplement physical

testing for increased

confidence

Forecast product

durability and

manage product life

cycle risk

Bring new products

to market quickly

Assure product

reliability and reduce

cost

Used by Leading Companies in Multiple Industries

Aerospace

& Defense

Automotive &

Transportation

Medical

ImplantsIndustrial

Equipment

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VEXTEC Demonstrated SuccessesIndustry & Client Type Project Description

Application

Aerospace Airline -Simulated lubrication changes & identified fix

Repair (American) -FAA Approved

Engineering -$4M/year saved on bearings

Automotive Engine Maker -Simulated 150 designs & identified top 3

New Product (Cummins) -$5M saved on engine block development

Development program

Industrial Specialty -Forecast maintenance schedule based on current

Equipment Manufacturer usage

Computational -$3M saved on reducing manufacturing line downtime

Framework

Healthcare Medical Devices -Evaluated material suppliers for different markets

Second (Boston -Avoided expensive developmental test program

Source Scientific)

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Simulated Fatigue Tests

Software: VPS-MICRO

Windows desktop tool

Wide range of applications

• Stand-alone tool for simple specimen

geometry models

• Integrate FEA models for complex

geometry of full-scale components

Output

• Simulated S-N Curve

• Virtual fracture surface

• Detailed statistical analysis

Customizable Software Product

• Interface with Standard FEA

software

• Predict risk of failure from complex

in-service loading spectrums Simulated S-N Curve

Software Partners

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Robert Tryon, rtryon@vextec.com

Animesh Dey, adey@vextec.com

Sanjeev Kulkarni, skulkarni@vextec.com

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