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1DISTRIBUTION A: Approved for public release; distribution is unlimited.26 February 2013
Integrity  Service  Excellence
Dr. David Stargel
Division Chief
AFOSR/RTA
Air Force Research Laboratory
Multi-Scale Structural
Mechanics and
Prognosis
04 MAR 2013
2DISTRIBUTION A: Approved for public release; distribution is unlimited.
2013 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
3DISTRIBUTION A: Approved for public release; distribution is unlimited.
Thrust Areas
4DISTRIBUTION A: Approved for public release; distribution is unlimited.
Challenges
5DISTRIBUTION A: Approved for public release; distribution is unlimited.
Structural Mechanics Vision of
Future Weapon Systems
6DISTRIBUTION A: Approved for public release; distribution is unlimited.
Exploratory & Anticipated Research
New solutions to the direct projection of
today’s problems
Seldom occurs as a result of addressing
today’s problems
7DISTRIBUTION A: Approved for public release; distribution is unlimited.
Digital Twin Vision
8DISTRIBUTION A: Approved for public release; distribution is unlimited.
Anticipated Digital Twin Research
Physics-based Multi-
scale, Multi-Discipline
Models
Applied Loads &
Environments
(Probabilistic)
Range of Structural
Response & Reliability
(Probabilistic)
Airframe Digital Twin
Geometry &
Material Data
(Probabilistic)
9DISTRIBUTION A: Approved for public release; distribution is unlimited.
AFRL-VT-WSU-UM Collaborative Center for Multidisciplinary Sciences
Sciences
Christopher Corey Fischer (WSU)
MSTC-CCMS TAC Review
14-15 November 2012
Quantification of Model
Form Uncertainty in
Physics-Based
Simulations
10DISTRIBUTION A: Approved for public release; distribution is unlimited.
Uncertainty in ESAV Design
11DISTRIBUTION A: Approved for public release; distribution is unlimited.
 Y g X  
11
• Adjustment Factor Approach
• Bayesian Model Averaging
• Probabilistic Adjustment
Factors Approach
Model Form
Uncertainty
Present in having different
models that represent the same
system response, but not
positive as to which one of
these models is most accurate
Parametric
Uncertainty
Inherent in input
parameters within a model
• Natural variability in input
parameters
• Inconsistency in
manufacturing processes
• Imprecise statistical data
• Evidence Theory
• Probabilistic Analysis
• Sampling Approaches
Predictive
Uncertainty
Indicates variations in
errors of a model’s
predictions
• Differences exist between
observed experimental data
and model predictions
• Bayesian Approach
• Regression Analysis
Mathematical Model to
Predict System Response
Types of Uncertainty
12DISTRIBUTION A: Approved for public release; distribution is unlimited.
Combination of Model-Form and
Other Uncertainties
Model
Combination
• • •
13DISTRIBUTION A: Approved for public release; distribution is unlimited.
• Bayes’ theorem can be used to update prior model probability into posterior
model probability given experimental data
Bayes’ Theorem
 
   
   
1
D
D
j j
j K
i i
i
P M P M
P M D
P M P M



   D Dj jL M P M 
 
2
1
ˆ
i
N
j
i
j mle N

 


Bayes’ Theorem
Model Likelihood
1
2π(σ)2
𝑚𝑙𝑒
𝑁
2
𝑒
−𝑁
2
where
Experimental Data
Models 1 - K
14DISTRIBUTION A: Approved for public release; distribution is unlimited.
Computational Prototype Design
is part of ADT
Prototype Representation
Prototype Analysis for Design
Prototype
Experimental
Validation
Prototype Design Space Exploration
Conceptual Design Studies
Technology
Suite
10000s configurations
10s configuration
-Capture the phenomena driving the design
-Configuration & Flight Condition dependent
-Technology Suite Dependent
Dialable Fidelity
“Physics to Flight”
15DISTRIBUTION A: Approved for public release; distribution is unlimited.
• NASA - Ed Glaessgen/Steve Smith
• ARO - David Stepp
• MURI on Uncertainty – Fariba Fahroo
• Mathematics for Multi-Scale
Modeling – Fariba Fahroo
• Transformational Computing –
John Luginsland/Tatjana Curcic/Doug Smith
• MURI on Hybrid Structures –Joycelyn
Harrison/Ali Sayir
• AFRL/RX ICMSE - Chuck Ward et al.
• AFRL/RQ Airframe Digital Twin –
Eric Tuegel/Pam Kobyrn
• AFRL/RQ SSC - Ravi Chona et al.
• AFRL/RQ MSTC – Ray Kolonay et al
• ONR - Bill Nickerson
Collaborations related to Digital Twin
16DISTRIBUTION A: Approved for public release; distribution is unlimited.
Enabling Methodologies
17DISTRIBUTION A: Approved for public release; distribution is unlimited.
• Goal is to develop and characterize wirelessly
triggered stimuli-responsive polymeric materials
capable of rapidly reversible planar and flexural-
torsional shape adaptations exhibiting both shape-
restoring (muscle like) and shape-retaining (shape
memory) behavior.
– Responsive liquid crystal polymer synthesis, development, and
characterization for conventional, hierarchical (through thickness),
and spatially ordered systems
– Baseline polymer physics: correlated thermo-mechanical and
photo-mechanical analysis
– Development of spatially controlled adaptations
Photoresponsive Liquid Crystal Polymer Networks:
Future Generation Adaptive Materials
PI: Dr. Timothy White, AFRL/RX
18DISTRIBUTION A: Approved for public release; distribution is unlimited.
Liquid Crystal Polymer
Networks (LCNs)
The orientation of the nematic director can be spatially varied through the thickness.
The resulting mechanical response is an interplay between the geometry of the film, the
orientation of the liquid crystalline director (e.g. uniaxial, homeotropic, twisted, or splay)
within the film, and the input stimulus (heat, light, electric field).
Twisted nematic Splay
Broer et. al, Adv. Funct. Mater., 2005;
Eur. Phys. J. E, 2007.
Tuning the Shape – Varying Orientation
and Temperature
RH coiling
LH coiling
0° to 90°
90° to 0°
15° to -75°
-15° to 75°
30° to -60°
-30° to 60°
45° to -45°
-45° to 45°
0 3 6 9 12 15
-90
-60
-30
0
30
60
90
OrientationofNematicDirectortoLongAxisofFilm()
Thickness (m)
i
ii
iii
iv
vii
vi
v
i
ii iii iv
i
v vi vii
TN LCN at 130°C
Temperature (
o
C)
20 40 60 80 100 120 140 160
Numberofpitch
0
1
2
3
4
5
6
7
8
9
Lee/White et. al, Adv. Mater., 2012
TN DISTRIBUTION A: Approved for public release; distribution is unlimited.
20DISTRIBUTION A: Approved for public release; distribution is unlimited.
Populating material capability suite &
exploiting design
21DISTRIBUTION A: Approved for public release; distribution is unlimited.
Multi-Scale Structural Mechanics
Summary
Past Present
Few tests represent
aircraft fleet
CAE supplements
experimental fleet models
• Three core thrusts along with the integrating vision of a
Virtual Twin Concept
• Spans Exploratory and Anticipated Research for:
•Novel Flight Structures
•Multi-scale Modeling and Prognosis
•Structural Dynamics
• Program focuses on core concepts of structural mechanics
• Computing
• Predicting
• Enabling
• Program is coordinated and actively collaborating with
other government agencies and within AFOSR
DISTRIBUTION A: Approved for public release; distribution is unlimited.

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Stargel - Multi-Scale Structural Mechanics and Prognosis - Spring Review 2013

  • 1. 1DISTRIBUTION A: Approved for public release; distribution is unlimited.26 February 2013 Integrity  Service  Excellence Dr. David Stargel Division Chief AFOSR/RTA Air Force Research Laboratory Multi-Scale Structural Mechanics and Prognosis 04 MAR 2013
  • 2. 2DISTRIBUTION A: Approved for public release; distribution is unlimited. 2013 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
  • 3. 3DISTRIBUTION A: Approved for public release; distribution is unlimited. Thrust Areas
  • 4. 4DISTRIBUTION A: Approved for public release; distribution is unlimited. Challenges
  • 5. 5DISTRIBUTION A: Approved for public release; distribution is unlimited. Structural Mechanics Vision of Future Weapon Systems
  • 6. 6DISTRIBUTION A: Approved for public release; distribution is unlimited. Exploratory & Anticipated Research New solutions to the direct projection of today’s problems Seldom occurs as a result of addressing today’s problems
  • 7. 7DISTRIBUTION A: Approved for public release; distribution is unlimited. Digital Twin Vision
  • 8. 8DISTRIBUTION A: Approved for public release; distribution is unlimited. Anticipated Digital Twin Research Physics-based Multi- scale, Multi-Discipline Models Applied Loads & Environments (Probabilistic) Range of Structural Response & Reliability (Probabilistic) Airframe Digital Twin Geometry & Material Data (Probabilistic)
  • 9. 9DISTRIBUTION A: Approved for public release; distribution is unlimited. AFRL-VT-WSU-UM Collaborative Center for Multidisciplinary Sciences Sciences Christopher Corey Fischer (WSU) MSTC-CCMS TAC Review 14-15 November 2012 Quantification of Model Form Uncertainty in Physics-Based Simulations
  • 10. 10DISTRIBUTION A: Approved for public release; distribution is unlimited. Uncertainty in ESAV Design
  • 11. 11DISTRIBUTION A: Approved for public release; distribution is unlimited.  Y g X   11 • Adjustment Factor Approach • Bayesian Model Averaging • Probabilistic Adjustment Factors Approach Model Form Uncertainty Present in having different models that represent the same system response, but not positive as to which one of these models is most accurate Parametric Uncertainty Inherent in input parameters within a model • Natural variability in input parameters • Inconsistency in manufacturing processes • Imprecise statistical data • Evidence Theory • Probabilistic Analysis • Sampling Approaches Predictive Uncertainty Indicates variations in errors of a model’s predictions • Differences exist between observed experimental data and model predictions • Bayesian Approach • Regression Analysis Mathematical Model to Predict System Response Types of Uncertainty
  • 12. 12DISTRIBUTION A: Approved for public release; distribution is unlimited. Combination of Model-Form and Other Uncertainties Model Combination • • •
  • 13. 13DISTRIBUTION A: Approved for public release; distribution is unlimited. • Bayes’ theorem can be used to update prior model probability into posterior model probability given experimental data Bayes’ Theorem           1 D D j j j K i i i P M P M P M D P M P M       D Dj jL M P M    2 1 ˆ i N j i j mle N      Bayes’ Theorem Model Likelihood 1 2π(σ)2 𝑚𝑙𝑒 𝑁 2 𝑒 −𝑁 2 where Experimental Data Models 1 - K
  • 14. 14DISTRIBUTION A: Approved for public release; distribution is unlimited. Computational Prototype Design is part of ADT Prototype Representation Prototype Analysis for Design Prototype Experimental Validation Prototype Design Space Exploration Conceptual Design Studies Technology Suite 10000s configurations 10s configuration -Capture the phenomena driving the design -Configuration & Flight Condition dependent -Technology Suite Dependent Dialable Fidelity “Physics to Flight”
  • 15. 15DISTRIBUTION A: Approved for public release; distribution is unlimited. • NASA - Ed Glaessgen/Steve Smith • ARO - David Stepp • MURI on Uncertainty – Fariba Fahroo • Mathematics for Multi-Scale Modeling – Fariba Fahroo • Transformational Computing – John Luginsland/Tatjana Curcic/Doug Smith • MURI on Hybrid Structures –Joycelyn Harrison/Ali Sayir • AFRL/RX ICMSE - Chuck Ward et al. • AFRL/RQ Airframe Digital Twin – Eric Tuegel/Pam Kobyrn • AFRL/RQ SSC - Ravi Chona et al. • AFRL/RQ MSTC – Ray Kolonay et al • ONR - Bill Nickerson Collaborations related to Digital Twin
  • 16. 16DISTRIBUTION A: Approved for public release; distribution is unlimited. Enabling Methodologies
  • 17. 17DISTRIBUTION A: Approved for public release; distribution is unlimited. • Goal is to develop and characterize wirelessly triggered stimuli-responsive polymeric materials capable of rapidly reversible planar and flexural- torsional shape adaptations exhibiting both shape- restoring (muscle like) and shape-retaining (shape memory) behavior. – Responsive liquid crystal polymer synthesis, development, and characterization for conventional, hierarchical (through thickness), and spatially ordered systems – Baseline polymer physics: correlated thermo-mechanical and photo-mechanical analysis – Development of spatially controlled adaptations Photoresponsive Liquid Crystal Polymer Networks: Future Generation Adaptive Materials PI: Dr. Timothy White, AFRL/RX
  • 18. 18DISTRIBUTION A: Approved for public release; distribution is unlimited. Liquid Crystal Polymer Networks (LCNs) The orientation of the nematic director can be spatially varied through the thickness. The resulting mechanical response is an interplay between the geometry of the film, the orientation of the liquid crystalline director (e.g. uniaxial, homeotropic, twisted, or splay) within the film, and the input stimulus (heat, light, electric field). Twisted nematic Splay Broer et. al, Adv. Funct. Mater., 2005; Eur. Phys. J. E, 2007.
  • 19. Tuning the Shape – Varying Orientation and Temperature RH coiling LH coiling 0° to 90° 90° to 0° 15° to -75° -15° to 75° 30° to -60° -30° to 60° 45° to -45° -45° to 45° 0 3 6 9 12 15 -90 -60 -30 0 30 60 90 OrientationofNematicDirectortoLongAxisofFilm() Thickness (m) i ii iii iv vii vi v i ii iii iv i v vi vii TN LCN at 130°C Temperature ( o C) 20 40 60 80 100 120 140 160 Numberofpitch 0 1 2 3 4 5 6 7 8 9 Lee/White et. al, Adv. Mater., 2012 TN DISTRIBUTION A: Approved for public release; distribution is unlimited.
  • 20. 20DISTRIBUTION A: Approved for public release; distribution is unlimited. Populating material capability suite & exploiting design
  • 21. 21DISTRIBUTION A: Approved for public release; distribution is unlimited. Multi-Scale Structural Mechanics Summary Past Present Few tests represent aircraft fleet CAE supplements experimental fleet models • Three core thrusts along with the integrating vision of a Virtual Twin Concept • Spans Exploratory and Anticipated Research for: •Novel Flight Structures •Multi-scale Modeling and Prognosis •Structural Dynamics • Program focuses on core concepts of structural mechanics • Computing • Predicting • Enabling • Program is coordinated and actively collaborating with other government agencies and within AFOSR DISTRIBUTION A: Approved for public release; distribution is unlimited.