uncertainty driven engineering for heterogeneous media ......examples of why tech was dropped:...

1 Distribution A: Approved for Public Release. Case #: 88ABW-2012-1871

Integrity Service Excellence

Uncertainty Driven Engineering for Heterogeneous

Media & Structures

SIAM Annual Meeting 09-13 July 2012

Dr. Timothy D. Breitzman Composite Materials Branch

Air Force Research Laboratory Wright-Patterson AFB OH

2 Distribution A: Approved for Public Release. Case #: 88ABW-2012-1871

Air Force Research Laboratory Materials & Manufacturing Directorate

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Outline

• Motivation • State-of-the-Art Checkup

– Integrated Computational Materials Science & Engineering (ICMSE)

• Discussion on Probabilistics & Uncertainty • Concluding Remarks

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The Widespread Need

“Since the 1980s, technological change and economic progress have grown ever more dependent on new materials developments.” – White House Office of Science & Technology Policy;

Materials Genome Initiative for Global Competitiveness, 2011

Materials can enable new performance, missions and platforms

Zero-CTE laminates >> dimensional stability Directional conductivity >> thermal management

…and the limitations of materials can translate into limitations of a platform

Melting/softening point >> use temperature & mission envelope Specific properties >> weight margins

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Representative Technology Selection Criteria

Initial R&D Lab Scale

Performance Evaluation Production Scale-Up

Design Properties

Testing

Examples of Why Tech Was Dropped: •Concept Not Valid •Deficiency Found •Not Amenable to Scale-Up •Program Need Goes Away •Niche Material •Missed Implementation Timing •High Cost

Technology Succeeds: •Valid Concept •Scale-Up Success •Funding Available •Real Problem Exists •Customer Acceptance •ROI Acceptable

Production & Implementation

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Why is Material Development the Rate-Limiting Step?

“Modern computational engineering tools generally have radically reduced the time required to optimize new products. However, analogous computational tools do not exist for materials engineering.” – National Materials Advisory Board;

Integrated Computational Materials Engineering, 2008

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Time from Material Invention to Widespread Use

Materials Technology Invention Widespread Commercialization

Vulcanized Rubber 1839 Late 1850s Low-Cost Aluminum 1886 Early 1900s Teflon 1938 Early 1960s Titanium (Structural Uses) Mid 1940s Early 1960s Velcro Early 1950s Early 1970s Polycarbonate (Bullet Proof Glass) 1953 Early 1970s Lithium Ion Battery Mid 1970s Late 1990s AFR-PE-4 High Temp Composite Early 1990s Early 2010s

Little improvement in the last 175 years!

8 Distribution A: Approved for Public Release. Case #: 88ABW-2012-1871

State of the Art Checkup

• DoD structures certification – Building block approach – Certification by analysis – Lots of supporting tests

• Risk reduction (uncertainty)

•Risk averse aerospace industry – Favors use of previously

qualified materials – Stifles materials innovation

Design the structure based on limitations

of the material

ELEMENTS

DETAILS

COMPONENTS

SUB-COMPONENTS

COUPONS

Current Practice

9 Distribution A: Approved for Public Release. Case #: 88ABW-2012-1871

How AFRL is Approaching the Problem

• What is it not? – Just more computer modeling

• What is it? – Systems engineering on the

materials development process

– Digitization of the development process

– Backbone architecture – Standards & protocols for

simulations, data, testing, etc. – Metadata

Component Testing

Qualification Certification

Manufacturing

Sustainment

M&P Research

M&P Development

Component Design

Digital DATA

Integrated Computational Materials Science & Engineering (ICMSE)

10 Distribution A: Approved for Public Release. Case #: 88ABW-2012-1871

Integrated Computational Materials Science & Engineering (ICMSE)

• Risk averse aerospace industry • Favors use of

previously qualified materials

• Stifles materials innovation

Design the structure based on limitations of

the material

• Reduce risk early in acquisition process via virtual composite design, manufacturing & qualification • Expand material

design/selection options

• Early resolution of mfg scaling issues

Design the material based on structural

requirements

COUPONS

ELEMENTS

DETAILS

COMPONENTS

SUB-COMPONENTS

Current Practice

DoD Certification of Composite Structures Based on Building Block Approach

Opportunity

ICMSE = Computationally based materials discovery, design, development & sustainment

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Probabilistics & Uncertainty

Building Block Approach

• Recognizes structure at many scales

• Designed to quantify and mitigate risk

• What does this mean for materials?

COUPONS

ELEMENTS

DETAILS

COMPONENTS

SUB-COMPONENTS

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How a Designer Sees a Material

•Material allowable – Distribution-based – Environment-specific

• A-Basis Allowable – At least 99% of material values

meet or exceed with 95% confidence

– Single point catastrophic failure with no load redistribution

• B-Basis Allowable – At least 90% of material values

meet or exceed with 95% confidence

– Redundant load path with load redistribution

1. R. Rice, R. Randall, J. Bakuckas, S. Thompson., "Development of MMPDS Handbook Aircraft Design Allowables". Prepared for the 7th Joint DOD/FAA/NASA Conference on Aging Aircraft, September 8-11, 2003, New Orleans, LA.

2. DOT/FAA/AR-03/19, Final Report, "Material Qualification and Equivalency for Polymer Matrix Composite Material System: Updated Procedure" Office of Aviation Research, Washington, D.C. 20591, U.S. Department of Transportation Federal Aviation Administration, September, 2003.

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How a Materials Scientist Sees a Material

Dis

cipl

ine

Mat

eria

ls S

cien

ce

Phy

sics

C

hem

istry

Eng

inee

ring

pm nm µm mm m Length Scale

Electronic

Atomistic

Micro

Macro

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The Disconnect

• Material allowable

• Probability distribution function of responses

• Variability – Many batches – All environments

• Mean response

• Deterministic simulations

• Laboratory-scale – Often single batch &

few test specimens – Often single

environment

Designer Needs: Materials Scientist Provides:

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Task at Hand

• To decrease the materials development timeline, materials scientists must start delivering the information designers require. – This task requires quantifying the uncertainty at

all levels (Verification & Validation across scales) • Experimental uncertainty • Computational uncertainty • Material state uncertainty

– Polymer (or other) chemistry – Microstructure (functional definitions of RVEs & SVEs) – Outlier statistics – Statistical distributions of properties

» Efficient sampling » Generation of outlier realizations

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Statistical Variation

Molecular Micro / Meso Coupon Subcomponent

•Part Dimensions •Coupon Props.

•Free Volume •Porosity •Chemical Structure

•Micro Geometry •Fiber Diameter •Constituent Props.

•Lamina Props.

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Uncertainty in Microstructure

• How do we quantify the statistical nature of the microstructure? – What details are

important? • Volume fraction • Fiber spacing(?) • Correlation functions(?)

– How does “importance” depend on properties of concern?

– NEED functional definitions for RVE & SVE

Vf = 0.527

Vf = 0.526

Vf = 0.535

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• Sample Size • Dense Sampling • Scale effects • Incorporation of

experimental data – Bayesian

Methods(?) – Markov Chain

Monte Carlo(?)

Population Sampling Strategies

actual damage pattern

statistical realization

Case 1

statistical realization

Case 4

Experimental Load-POD Curves

Simulation Load-POD Curves

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Concluding Remarks

•Lightweight, efficient structures & materials are critical for current & future air & space assets

•Future assets are both enabled & held back by new materials development

• We can utilize current simulation capabilities to guide experiments today for new materials development and for better understanding of today’s materials – 2D Laminates – Carbon Fiber, Epoxy, Bismaleimide, Cyanate Ester, etc.

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Concluding Remarks

Technical hurdles for complete utilization… •The robust computational framework being developed must address critical issues – Materials maturation timeline – Multifunctionality and blending of materials &

structures – Optimal design in high dimensional spaces with

sparse data (curse of dimensionality) – Uncertainty due to phenomena occurring

simultaneously at many scales

ICMSE – systems engineering on materials design and development for a streamlined, digitized process

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Questions?