stargel - multi-scale structural mechanics and prognosis - spring review 2012

1 DISTRIBUTION A: Approved for public release; distribution is unlimited. 9 March 2012

Integrity Service Excellence

Dr. David Stargel

Program Manager

AFOSR/RSA

Air Force Research Laboratory

Multi-Scale Structural

Mechanics and

Prognosis

09 MAR 2012

2 DISTRIBUTION A: Approved for public release; distribution is unlimited.

2012 AFOSR SPRING REVIEW

NAME: David Stargel

BRIEF DESCRIPTION OF PORTFOLIO:

FLIGHT STRUCTURES: Fundamental basic research into

structural mechanics problems relevant to the US Air Force

LIST SUB-AREAS IN PORTFOLIO:

Novel flight structures

Multi-scale modeling and prognosis

Structural dynamics

Structural mechanics or Mechanics of structures is the computation of

deformations, deflections, and internal forces or stresses (stress equivalents)

within structures, either for design or for performance evaluation of existing

structures*

* From Wikipedia

Focus w/in sub-areas

Enabling

Computing

Predicting

http://en.wikipedia.org/wiki/Deformation_(engineering)

http://en.wikipedia.org/wiki/Deflection_(engineering)

http://en.wikipedia.org/wiki/Force

http://en.wikipedia.org/wiki/Stress_(physics)


Thrust Areas


Challenges


• NASA - Ed Glaessgen/Steve Smith

• ARO/ARL - David Stepp/Jim Chang

• ONR - Ignacio Perez/Liming Salvino/David Shifler

• NSF – Christina Bloebaum

• DTRA – Su Peiris

• MURI on Uncertainty – Fariba Fahroo

• Mathematics for Multi-Scale Modeling – Fariba Fahroo

• AOARD/EOARD/SOARD

• Transformational Computing – John Luginsland/Tatjana Curcic

• MURI on Hybrid Structures –Joycelyn

Harrison/Ali Sayir

Collaborations


Structural Mechanics Vision of Future Weapon Systems


Digital Twin Vision


Key Workshop Recommendations

1. Material Scale Modeling – Develop high fidelity 3D microstructures of heterogeneous materials

– Need better representation of mechanics in homogenization-derived

reduced order models

2. Deterministic Multiscale Modeling – Develop a computational environment with flexibility to accommodate

different methodologies in conjunction with actual physics and

mathematics of the different domains

– Explore new up-scaling and down-scaling strategies along with advances

in multiple-temporal-scale modeling

3. Uncertainty Quantification – Explore holistic combination of deterministic and probabilistic modeling

– Enhance probabilistically-based sensitivity methods to identify important

variables


AFRL Notional Digital Twin Roadmap


A Common Vision of Future

Capabilities Planned Capabilities

Hypersonic Strategic

Bombers

Long-Duration

Reconnaissance Vehicles

Shared Technical Challenges

Computational Damage Mechanics

Experimental Damage Mechanics

Structural Health Management

Materials Engineering & Processing

Autonomous Space

Vehicles

Risk-Based Design


National Multi Scale Foundational

Research Plan Process

The “Plan for the Plan”

• Phase 1- 2011: Education

• Inform damage mechanics community of the plan and ensure

participation

• Develop framework for plan organization

• Phase 2 – early 2012: Organization

• Further refine thrust area plan details

• Establish database of current funded efforts

• Estimate funding requirements and shortfalls to achieve

stated plan goals

• Phase 3 – late 2012: Utilization

• Use identified funding requirements and proof of collaboration

between agencies to advocate for increased resources for

multi-scale damage mechanics research

Each Agency will continue to utilize existing funding instruments


Comprehensive Technical Objectives

– Computational Damage Mechanics


Challenging and exciting scientific opportunities


Future, 2025…

Tomorrow, 2015 Today, 2011

AFOSR PMs: Douglas Smith & David Stargel

In consultation with Curcic, Fahroo, & Luginsland

(T–CASE)

• To create transformational approaches in computing for aerospace science and engineering

• Multi-disciplinary approach including novel computer architectures, system software, and mathematical algorithms

• Emphasis on • Multi-scale modeling & structural

mechanics • Complex flow physics modeling &

control

Novel micro-

architectures?

Hybrid/complementary

photonic methods?

Quantum-based

systems?

Bio-computing?

Neuro-morphic

computing?

Transformational Computing in Aerospace

Science & Engineering


Future …

Tomorrow

Today

Transformational Computing in

Aerospace Science & Engineering To create transformational approaches in computing for aerospace

science and engineering. “How can we exploit quantum computing architectures specifically to

advance aerospace computing?” University of California San Diego Team Lead PI: Dr. David Meyer Project Title: Applications of Quantum Computing in Aerospace Science and Engineering Team Disciplines: Mathematics, Computational Science, Structural Eng., Mechanical and Aerospace Eng., Chemistry, Physics Approaches: (1) Combine four quantum subroutines

into quantum algorithm for efficiently solving systems of linear equations

(2) Application of quantum search algorithms for use in optimization problems

University of Pittsburgh Team Lead PI: Dr. Peyman Givi Project Title: Quantum Speedup for Turbulent Combustion Simulations Team Disciplines: Mechanical Eng., Materials Science, Physics, Quantum Theory, Simulation and Modeling Approaches: (1) Quantum algorithms that operate on

general purpose quantum computers (2) Avenues for quantum simulation on

quantum devices


Forecasting Aircraft Usage for Prognosis LRIR PIs: Ben Smarslok, Eric Tuegel, and Ravi Penmetsa

Background & Motivation

• Material state evolution is nonlinear & history dependent

• Reliable structural prognosis requires the generation of realistic loading and environmental sequences

• Existing techniques focus on a single structural load parameter history

• Used ABAQUS Solver

– Developed scripts to translate CFD pressures

onto the FE mesh

• ~1 Million DOF

• 2.5 hrs of run time using 2 cores of a single

CPU

– 30 Min for actual static analysis

– 2 hrs processing input file


A Bayesian Experimental Design Approach for Optimization and

Uncertainty Quantification in Aerospace Structural Modeling and

Analysis

PI: Dr. Michael Todd, UCSD

Objective

Develop a framework for “optimal” model

selection, performance assessment, updating,

and uncertainty assessment in aerospace

structural modeling

Some Fundamental Basic Science Issues

• Logical accounting of relevant uncertainty

sources

• Consistent transition probability model that

propagates uncertainty through the decision-

making process

• Optimization strategy of complex, likely non-

smooth decision surfaces

• Determination of the cost function

form(s)…application-specificity

The ideal future…

• Completely known physics with no (or negligibly little) uncertainty

• A much Much MUCH greater computational capacity

Physical

Variability

Information

Uncertainty

Model

Uncertainty

Uncertainty

Modeling

FEM and

Dynamic

Analysis

Damage

Mechanism

Analysis

Probabilistic

Fatigue

Prognosis

Usage

monitoring

Model

update

Bayesian

Updating

Inspection

SHM

RUL

update

Verification &

Validation

A sound uncertainty management methodology

- Mechanism Model

- Uncertainty Quantification and Propagation

- Uncertainty Updating

- Verification and Validation

Yongming Liu, Clarkson University Concurrent structural fatigue

damage prognosis under uncertainties


Enabling Methodologies


Accordion Rib Stitch

Arching Seed Stitch

Twisting I-Cord

Rolled Furling Stockinette Stitch

Contraction Garter Stitch

Backward

Loop

Rear

Ridge

Backward

Loop

Connecting

wire

A

A

Forward

Loop

Backward

Loop Forward

Loop

Backward

Loop

Forward

Loop

Backward

Loop

Active Knits for Radical Change Air Force Structures

PI: Dr. Diann Brei, University of Michigan GRANT # FA9550-09-1-0217


Novelty of approach: includes operational transitions, friction, load path, and active materials

Analytical Model


Flow Control Applications

Bumps and Spars Roughness Elements

Technological Needs: Large Displacements, High Pressure, Distributed Actuation

(Bein et al., 2000)

Synthetic Jet

• Constant disturbance delays boundary layer separation

• Traditional jet mechanisms increase design complexity

• Piezoelectric active jets are promising but debond at high frequencies

Contour Bump

(Holman et al., 2005)

Flap and VGS

(http://www.aerospaceweb.org)

Synthetic Jets Flaps, Spoilers, Vortex Generators

• Change effective shape of wing midflight

• Effective at leading and trailing edge of the wing

• Large size and weight prohibit full integration of distributed actuators over wing

Leading Edge Distributed

Roughness Elements

• Contour bumps theoretically reduce transonic drag ~15%

• Spars theoretically reduce shear stresses by 9.9%

• Actively varying height mid-flight and creating large deformations difficult

• Distributed surface texturing

• Reduce turbulent skin friction drag up to 30%

• Difficult to create distributed actuation across surface of wing

(Stanewsky, 2001)

Benefits •Reduce Drag

•Enhance Lift

• Improve Maneuverability

• Increase Fuel Economy

•Expand Mission Variety

(Collis, 2004) (Smith, 1998; Cattafesta, 2001, Crook 1999)

(Milholen, 2004; Stanewsky, 2001) (Dearing, 2007; Lambert, 2006)


Rib Stitch Architecture and

Operation

Rib Stitch Architecture

SMA Wire Schematic

Rib Stitch Operational Mechanism

• Martensite Compressed State - Applied load flattens ridges

- Leg connecting knit to purl loops bends horizontally in the less stiff state

• Austenite Expanded State - Material stiffens and straightens, recovering plastic

deformation from Martensite State

- Increased stiffness and unbalanced force couples cause the forward ribs to lift and backward ribs to depress

Rib Stitch Actuation Mechanism

Forward Rib(Knit Loops)

F

F

F

F

F

F

Balanced Force Couples

Backward Rib(Purl Loops)

F

F

Unbalanced Force Couples

http://www.spin-knit-dye.com

Traditional Fiber Textile

Knit Column

Purl Column

Rear Ridges

Forward Ridges

Backward Rib: Purl Loops

Forward Rib: Knit Loops


Rib Stitch Prototype Fabrication

and Testing

Experimental Procedure

Experimental Setup

Prototypes Prototype Testing

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20

Fo

rce

(N)

Prototype Height (mm)

Austenite Expanded

Martensite Compressed

2

3

5

1

4

6

Apply

Load

Increase Load

Heat

Heat

Cool

Cool

Heat

Stainless Steel Rods

Linear Ball Bearings

Base Plate

Slider Plate

Encoder StripRib Stitch

Knit Prototype

Rib Stitch Prototype *Area = 0.010 m2 Mass = 19.6 g

140 mm

72 m

m

16 wales

14 co

urses

2 k 2 k 2 k 1 k1 k 2 p 2 p 2 p 2 p

a) Stacked Rib Stitch Configuration

2*hMcomp

2*DAct

Applied Load

(Fapp)

Plate

Rib Knit

Plate

Rib Knit

Stacked Rib

Knit Actuator

b) Nestled Rib Stitch Configuration

Applied Load

(2*Fapp)

>hMcomp

DAct

Plate

Rib Knits

Nestled Rib Knit

Actuator


Compliant Mechanisms


Passively Morphing Ornithopter Wing for

Increased Lift and Agility PIs: Dr. James E. Hubbard Jr., U of Maryland and Dr. Mary I. Frecker, Penn State

FA9550-09-1-0632


The primary objective of this workshop is to

1. Investigate the research challenges associated with applying Compliant Mechanism

(CM) design methodology to flapping Micro Air Vehicle (MAV) designs, with a

extension to general air vehicle designs.

2. Explore past and on-going research in this application area to determine the current

state of the art and to aid in determining future feasibility.

3. Establish collaboration between compliant mechanism design and air-vehicle design

communities in order to leverage current and future research opportunities with the

goal of more affordable and reliable vehicle design.

Suggested topics

March 26th and 27th, 2012, Tec^Edge, Dayton, Ohio

Workshop Chairs: Dr. David Stargel (AFOSR) and Dr. James Joo (RBSA)

AFRL/AFOSR Workshop on Compliant

Mechanisms in Micro Air Vehicle Design

Methodology

Design synthesis

Performance definition, calculation and

measurement

Passive shape change and complex motion

generation

Multi-DOF compliant mechanism

Origami

Laminar emergent mechanism

Smart/adaptive structure & actuator

Fabrication

Softening or statically balanced compliant

mechanism

Flapping Micro Air Vehicle


ODISSEI: Origami Design for Integration of Self-

assembling Systems for Engineering Innovation Collaborative effort with NSF EFRI Program

AFOSR PMs: Fariba Fahroo, Joycelyn Harrison, Doug Smith, & David Stargel

• Four themes:

– A: Compliant Mechanisms

– B: Active Materials

– C: Bio-origami

– D: Foldable Structures and Micro-structures

• Required Elements:

– ODISSEI-1 – Development of scientific, mathematical, and/or design

theories and methods for folding/unfolding

– ODISSEI-2 – Development of theoretical foundations for self-assembly

at all scales and across scales.

– ODISSEI-3 -Computational discovery and tools to facilitate design of

complex systems through folding and unfolding mechanisms

• PIs are strongly encouraged to include community outreach and

educational opportunities for outreach

Active Materials

Design Theory

Origami

Mathematical Rigor +

Artistic Inspiration

Adaptive Morphing System (AMS)


Multi-Scale Structural Mechanics

Summary Past Present Future

Few tests represent

aircraft fleet

CAE supplements

experimental fleet models

Each aircraft has its

own virtual twin

• Three core thrusts with the integrating vision of a Virtual

Twin Concept

• Novel Flight Structures

• Multi-scale Modeling and Prognosis

• Structural Dynamics

• Focus program on core concepts of structural mechanics

• Computing

• Predicting

• Enabling

• Program is coordinated and actively collaborating with

other government agencies and within AFOSR

• Exploring new transformational capabilities

• Quantum Computing for Aerospace Sciences

• Origami Engineering

29 9 March 2012 DISTRIBUTION A: Approved for public release; distribution is unlimited.

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stargel - multi-scale structural mechanics and prognosis - spring review 2012

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