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AFOSR Grants:– FA9550-05-1-0135 (OSU)– FA9550-05-1-0100 (UofM)– FA9550-05-1-0102 (JHU)

Funding:– AFOSR to OSU $ 1,119K– AFOSR to UofM $ 285K– AFOSR to JHU $ 195K– Total $ 1,599K

Team Gov’t AFOSR Manager: Brett ConnerGov’t Technical Manager: Dennis DimidukOSU Program Manager: Michael MillsUofM Program Manager: Tresa PollockJHU Program Manager: Kevin Hemker9 Faculty & 4 AFRL Mentors (+ Students)

Duration: Feb 05 - Feb 08

MEANS2Microstructure- and Micromechanism-Sensitive PropertyModels for Advanced Turbine Disk and Blade Systems

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Objective: Develop physics-based understanding and modeling capability for deformation/damage mechanisms in Ni-base disk and blade alloys

Approach: Integrated experiments and modeling for microstructure and micromechanisms developed in collaboration between AFRL, industry partners and universities

Payoff: Improved fidelity of AIM property and microstructure evolution models

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Processing Microstructure

Microstructure Modeling

+ Calibrating

Experiments

Micromechanical Modeling

+ Calibrating

Experiments

SlowCool

FastCool

Properties

Transitions: Providing fundamental micro-mechanical insights for the AIM augmentations at Pratt and Whitney and GEAE, and for the DARPA-Prognosis and NASA-Propulsion 21 efforts.

Goal: Augment/replace costly and time-intensive empirical databases with microstructure-sensitive, mechanism-based materials models.

MEANS 2: Approach for Developing Microstructure- and Micromechanism-Sensitive Property Models

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Slipped -matrix

Unslipped -matrix

Unslipped 'Pseudo-

twin/SESF

CSF

Deformation Mechanisms

PropertiesMicrostructure

(111)

1 nm

Mechanisms

Ch

arac

teri

zati

on

/V

alid

atio

nC

om

pu

tati

on

al

Mo

del

ing

EF-TEM/SEM/3DAP

Phase Field

-100

0

100

200

300

400

500

600

0 0.5 1 1.5 2

CSF

SESF

Pseudo twinm

J/m

2

Ab-Initio& MD

&twin =Dord ⋅ρ tpbtp

x2 lnf2 ⋅(γ pt − γ tt )

(τ eff ⋅btp − f2 .γ tt )

⎡

⎣⎢⎢

⎤

⎦⎥⎥

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100 nm

20 nm

Crystal Plasticity

MEANS 2: Approach for Developing Microstructure- and Micromechanism-Sensitive Property Models