Thomas P. Russell

Director

Aerospace, Chemical and Material Sciences Directorate

Air Force Office of Scientific Research (AFOSR)

USAF Fundamental Research for Micro Air Vehicles (MAVs)

20 September 2007

Distribution A: Cleared for Public Release, Distribution unlimited

AFOSR

2

Presentation Outline

• Brief overview of AFOSR

• AFOSR Research relevant to Micro Air

Vehicles

• Future directions/emphasis

3

Air Force Research Laboratory (AFRL)

Materials &

Manufacturing

Sensors PropulsionHuman

Effectiveness

http://www.afrl.af.mil/

BASIC RESEARCH IS THE FOUNDATION

Directed

EnergyMunitionsInformationSpace

VehiclesAir

Vehicles

AFOSR is the Sole Manager of AF Basic Research

HQ AFRL

Technology Directorates

AFOSR

4

Vision

The U.S. Air Force dominates air, space, and cyber

through revolutionary basic research

Mission

We discover, shape, and champion basic science that

profoundly impacts the future Air Force

AFOSR Vision and Mission

Today’s breakthrough science for tomorrow’s Air Force

5

AFOSR Research Areas

Aerospace, Chemical, and

Material Sciences (NA)

Physics and Electronics

(NE)

Sub-thrusts• Physics• Electronics• Space Sciences• Applied Math

• Chemistry• Propulsion• Materials • Fluid Mechanics• Structural Mechanics

• Info Sciences• Human Cognition• Mathematics• Bio Sciences

Math, Info, andLife Sciences

(ND)

Areas of enhanced emphasis:• Information Science• Computer-Assisted Human Decision-Making• Micro Air Vehicles• Nanotechnology• Novel Energy Technology

6

Aero-Structure Interaction and Control

Hybrid and Adaptive Materials and Structures

Energy, Power and Propulsion

Space Architecture and Protection

Thermal Control

NA Basic Research Focus Areas

Vehicle Surface/

Sub-structure

Severe

Environment

Material

Response

Optimized Material w/ ultra-high and/or

anisotropic thermal conductivity

7

• Unsteady, low Reynolds number aerodynamics

– Flapping wings

– Flow control

• Materials

• New flight structures

• Flight guidance, navigation and control

• Sensor fusion

• Novel power sources

AFOSR research relevant to MAVs

8

2007 MURI: Bio-Inspired Flight for MAVs

• Integrated disciplines: Low Re# fluid mechanics,

biology, fluid structure interactions, distributed

sensing, flight control, and material science

• Focus on fundamental understanding rather than

developing flying vehicles

• Complements knowledge gained from on-going basic

research efforts funded by AF, Navy, Army, DARPA

9

University of Michigan

• Investigates science of insect and bird flapping flight

– Wing span: 4-8 cm; AR: 3-7; fflap=10-30Hz

– Re#: O(103) – O(104); V=5-10 m/s

• Will consider transition & unsteady gust effects

• Integrates theoretical, numerical & experimental studies

• Will assess fluid-structure interaction

– Link computational tools (CFD & CSD)

– Conduct aerodynamic, structural & aeroelastic experiments

• Wing shape/deformation/anisotropy

• Modal analysis & damping ratio

• Separate effects of loading, inertia & flexibility

• Will consider multiple-sensor input for flight/flow control

10

Brown University

• Characterizes aeromechanics and scalability (Re# effect) of bat flight

– Bat wing motion has many DOF, unlike insects/birds

– Highly flexible wing structure & membrane, with extreme anisotropy and non-linear elasticity

– Arrays of raised hair sensors/actuators that may provide flow sensing & influence flight control

– Embedded muscles may control wing camber

• Integrates theoretical, numerical & experimental studies

• Considers different flight regimes/characteristics:

– Level flight, maneuvering, gust tolerance, take-off, landing & hover

– Multiple body flight

• Flight control

• Modeling theory, analysis and design tools

11

Bat Morphology

Cynopterus brachiotis in Wind tunnel (Photo: Arnold Song)

Fingers

(Adv structures)

Joints

(Flapping wing)

Intrinsic muscles

(Fluid-structure interaction)

wing hair cell sensors

(Flight & flow control)

Wing membrane

(Advanced materials)

Swartz & Breuer, Brown Univ

12

Bio-inspired Flight for MAVs

13

Numerical simulations

Kinematics:

3 cameras @ 1000 Hz

Particle Image velocimetry:

stereo measurement of wake

flows @ 200 Hz

Computational mesh

generated from

experimentally measured

motion

Wake flows, computed using

high-order panel/vortex methods

Dave Willis, Jaime Peraire, Mark Drela and Jacob White, MIT

14

Cilia-based Tufts for Flow Control

• Arrays of vertically-

oriented, electrically-

addressable „tufts‟

• Strain patterns in „tufts‟

may detect flow

separation & velocity

Dense arrays Flexible substrates

Finite element simulation Individual cilium response

15

Materials for Morphing Structures(Actuation and Skin)

(DARPA, ML, VA, MN)

(STTR) Air Force - Mechanically Adaptive Materials for Morphing Aircraft Skins

(STTR) Air Force - Mechanized Skins for Morphing Aircraft Structures

(STTR) DARPA - Adaptive Skin-Stiffener Interconnects for Shape-Changing

Vehicles

(STTR) DARPA - Fiber Reinforced Shape Changing Polymer Composites

6.2 BAA- Materials for Optimally Responsive Fabricated Structures (MORFS)

Atomistic/Continuum

Coupling

Fully Atomistic

Quantum Mechanics

of Reaction, Kinetics

16

Membrane

skins

Power, sensing,

communication, …

Kobayashi (U. Hawaii): algorithmic development of new flight structures

Friedmann (U. Michigan): structural dynamics

and response at the micro scale

Rahn (Penn State):

MEMS micro fabrication

active PZT

spars

New Flight Structures:Multi-scale multi-field structural science

17

• Unsteady, low Reynolds number aerodynamics

– Flapping wings

– Flow control

• New flight structures and materials

• Flight guidance, navigation and control

– Biologically-inspired sensors

– Sensor (vision) integration

– Cooperative control

• Sensor fusion

• Novel power sources

AFOSR research relevant to MAVs

18

Special Biosensory Systems

Distinctive Research Focus:

Sensory & sensorimotor systems

for navigation & flight control, not

yet developed in engineered flight.

Insect nocturnal navigation at the

lower limit of visual sensitivity via

night sky polarization

Polarization signature of the night skyT. Cronin, UMBC, E. Warrant, Lund U.

Stealth Intercept &

collision avoidance:

Theorems & neuro-

morphic VLSI models

Steering laws derived from

bat & insect flight behavior

University of MarylandAFRL/MNG, NRL

Universities

of Lund,

Canberra,

Marburg;

AFRL/MNG.

19

• Key enabling technologies for single

MAV

– Trajectory/waypoint tracking

– Target tracking

– Integrating vision sensors with

autopilot

• Active contours

• Optic flow

• Dynamic feature extraction

MAV Autonomous Control

20

Vision Control, Landing on Moving Target

MAV Autonomous Control: integrating vision with autopilot

Beard/McLain, Brigham Young Univ,

21

MAV Autonomous Cooperative Control

• Cooperative Multi-agent

Dynamics and Control

– Task Allocation

– Path Planning

– Tracking

– State Estimation

– Network

Theory/Architecture

– Information Theory

– Mixed Initiative

Decisions/

Computation

Centr

aliz

ed

De

cen

traliz

ed

Task Allocation

Path Planning

Target Tracking

1700 f

t

UAV Trajectories over Urban

Terrain

22

MAV Autonomous Cooperative Control (Cont)

How, MIT

Multi-MAV task allocation and tracking

23

• Unsteady, low Reynolds number aerodynamics

– Flapping wings

– Flow control

• New flight structures and materials

• Flight guidance, navigation and control

– Biologically-inspired sensors

– Sensor (vision) integration

– Cooperative control

• Sensor fusion

• Novel power sources

– Biofuel cells

– Solar cell and battery

– Multifunctional power components

Research relevant to MAVs

24

Sensor and Processor Integration for Improved Resolution

(reconstitute with multiple frames)

Problems• “Smart” hardware and storage buys us

higher spatial and temporal resolution “cheaply”

Progress

• Integration enhances spatial and temporalvideo fidelity

• More faithful reconstruction despite:

–Motion in the scene

–Finite aperture and sampling artifacts

•Use inexpensive imaging sensors in

quantity and fuse their information content.

•Trade off sensor complexity for advanced

post-processing.

•Analyze the trade-offs from a sound

mathematical and statistical basis.

•Seek to understand the impact of such

tradeoffs on the overall ATR process.

Infrared Sequence from AFRL/SNA

Before AfterBefore Milanfar, UC Santa Cruz

25

• Unsteady, low Reynolds number aerodynamics

– Flapping wings

– Flow control

• New flight structures and materials

• Flight guidance, navigation and control

– Biologically-inspired sensors

– Sensor (vision) integration

– Cooperative control

• Sensor fusion

• Novel power sources

– Biofuel cells

– Solar cell and battery

– Multifunctional power components

Research relevant to MAVs

26

Biofuel Cells For Compact Power

Approach

Provide compact power that can refuel itself from its

surroundings (i.e. “live of the land”) and thus enable

revolutionary mission capabilities.

Understand & control electron transfer using biological systems through both Microbial (in figure above) and Enzymatic approaches.

Advantages of Bio-Powered MAVs (Micro Air Vehicles)

• Flexible, abundant fuel

• Low IR/noise signature

• Size and cost

Bio-Powered MAVs address needs for increased miniaturization, autonomy, and persistence.

Current Challenges:

• Synthesis and control of biocatalysts outside living organisms

• Understanding how to “digest” and transport fuel efficiently

• Increasing rate of reaction for more power density

• Optimizing lifetime, fuel versatility, and storage

(Shewanella oneidensis strain MR-1 cultivated on a graphite fiber electrode)

Challenges & GoalsConcept

Current technology (enzyme-

based fuel cell)

Ultimate goal

(MAV with integrated

bio-power)

27

The Potential of Biofuel Cells

Two issues for maximum power: Get the electrons out of the fuel,

and then transfer the electrons to the electrode

Fuel Energy

Density for

Complete

Oxidation

(kWhr/L)

Energy Density

for Single

Enzyme

Oxidation

(kWhr/L)

Ethanol 6200 1033

Methanol 4700 1567

Glucose 5600 467

For

Comparison

Li Primary

Battery1000

Li Secondary

Battery500

28

Nature Dye for Dye-Sensitized Solar Cell:

Pros -

1. More Stable with light and heat

2. High absorption coefficient

3. Easy to change absorption wavelength by

changing a central metal

4. Be able to absorb visible and Infrared light

TiO

2

FT

O

N

N

N

N

N

N

N

NM

Dye2N

N

N

N

N

N

N

N

HOOC COOH

COOHHOOC

M

Dye1

TiO2 nano-particles or nano-tube

Dye3

O

OH

N

N

e-

I-

I3-

Light

e- e-

Phthalocyanine NaphthalocyanineCarotenoid

Redox

Bio-inspired Design of Light-harvesting System:Absorbed Wide Wavelength (UV, Vis., IR)

New Solar Cell & Battery

0.01 0.1 1 10 100 1000

1

10

100

1000

10000

100000

1000000

1E7

Sp

ec

ific

Po

we

r (W

/kg

)

Specific Energy (Wh/kg)

Capacitor

Electrochemical

Capacitor

BatteriesFuel Cell

0.01 0.1 1 10 100 1000

1

10

100

1000

10000

100000

1000000

1E7

Sp

ec

ific

Po

we

r (W

/kg

)

Specific Energy (Wh/kg)

Capacitor

Electrochemical

Capacitor

BatteriesFuel Cell

Capacitor

Electrochemical

Capacitor

BatteriesFuel Cell

Nanostructured Battery Electrodes:

• Demonstrated that the nanostructured

vanadium pentoxide electrodes can store

significantly higher energy with much

improved kinetics.

Ideal performance:

Large storage capacity: energy

Fast transport kinetics: power

Taya/Nango/Cao

29

a. System level

c. Material level

mic

ro-s

ca

le

antenna

PBCPower amplifier

TEC

Heat spreader

Polymer solar cells

(PSC)

Thermo-electric cooling

device (TEC)

Antenna system under

the wing with TEC

Polymer matrix composite (PMC) cell

Battery package layer (BPL)

SeparatorCathode

Anode

Polymer solar cell (PSC)

PMCBPL

ma

cro

-sca

len

an

o-s

cale

d. Composite levelBinder polymerCarbon nano

tube network

Porous Cu collector

p-type TEn-type TE

TEC

TIM

Thermal interface material (TIM)

b. Component level

Polymer battery

cells (PBC)

TECAntenna

Skin

PBC

Polymer solar cells

(PSC)

ENERGY HARVESTING (U WA/U CO/UCLA/VPI: Taya et al)

PM: B. L. Lee; Co-PM’s: Joan Fuller & Victor Giurgiutiu

30

Future Directions/Emphasis

• Potential Breakthrough research areas

– Flexible wing flapping flight

– Vision-based flight control

– Sensor fusion

– Multifunctional materials and power sources

• Emphasis on multidisciplinary collaboration

– Focused reviews/workshops/conferences

– Use of university research initiatives (MURI)

– Participation in NATO RTO panels (e.g. AVT-149 Low

Re# MAV Aerodynamics)

31

AFOSR/NA: Shaping the future of Aerospace Sciences

QUESTIONS?

32

Back up charts

33

MURI Overview

• Multidisciplinary basic research (6.1) in US university

– Multiple researchers in a single university or in two or more universities

– Period of performance: 3 years + 2 years

– Funding: ~ $1.2M/year for up to 5 years

• MURI topics formulated each year by basic research offices of US Army (ARO), Navy (ONR) and Air Force (AFOSR)

– Topics coordinated with on-going and planned 6.1 research

• Approximate timeline

– MURI Broad Agency Announcement released to public in June

– White papers due in August

– Proposals due in November

– Selection notification in March

– Grant award in June