Multidisciplinary Design and Optimization (MDO) Natural Evolution of that Other Engineering Activity.

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Multidisciplinary Design and Optimization
(MDO)Natural Evolution of that Other
Engineering Activity.

• Dr. Rob McDonald
• Lockheed Martin Endowed Professor
• Cal Poly, SLO
• UT Austin AIAA

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Core Engineering Activities

• Analysis
• Given a system, how do we expect it to perform?
• Test
• Given a system, how does it perform?
• Design
• Given a desired performance, what system do we
  want?

Design is an inverse problem. Design is
inherently different from Analysis Test.
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Complex Systems

• Systems are becoming more complex
• Larger systems
• Systems of systems
• Networks, connections, interactions
• Longer life cycles longer development cycles
• Higher cost
• There are more constraints than ever before
• Emissions
• Noise
• Safety
• Systems perspective not just for the system

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Reconnaissance/Observation
Federal observation balloon Intrepid being
inflated. Battle of Fair Oaks, Va., May 1862.
National Archives.
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Multi-mission Aircraft
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Stick and Rudder?
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Communications
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US Soldiers
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Complex Systems

• Systems are becoming more complex
• Larger systems
• Systems of systems
• Networks, connections, interactions
• Longer life cycles longer development cycles
• Higher cost
• There are more constraints than ever before
• Emissions
• Noise
• Safety
• Systems perspective not just for the system

Q How do you analyze design complex
systems? A SDAO / MDAO
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NASA's Aeronautics Plan
-Lisa Porter
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NASA's Aeronautics Plan
-Bill Haller
The Systems Analysis, Design, and Optimization
team has identity at Levels 2 through 4... -
SFW Reference Document, Collier et.al.
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NASA's Aeronautics Plan
The Systems Analysis, Design, and Optimization
team has identity at Levels 2 through 4... -
SFW Reference Document, Collier et.al.
-Lisa Porter
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Not Just NASA

• DARPA
• ONR
• NAVAIR
• AFRL
• FAA
• Industry
• Lockheed
• Boeing
• Northrop Grumman
• Pratt Whitney
• General Electric
• etc.

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Core Engineering Activities

• Analysis
• Given a system, how do we expect it to perform?
• Test
• Given a system, how does it perform?
• Design
• Given a desired performance, what system do we
  want?

Design is an inverse problem. Design is
inherently different from Analysis Test.
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Analysis
Given a system, how do we expect it to perform?
Design
Given a desired performance, what system do we
want?
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Multidisciplinary Analysis (MDA)?
MDA Techniques focus on the challenges of this
problem. System Decomposition
Integration Convergence Consistency Model
Approximation Information/Data Management Parallel
ization Acceleration Error Propagation Validatio
n etc.
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Multidisciplinary Design Optimization(MDO)?
MDO Techniques focus on the challenges of this
problem. All of the challenges of MDA. Design
Exploration Optimization Constraints
Requirements Tradeoff Robust Design Decision
Making Visualization Sensitivities Growth etc.
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Familiar Challenges
Has anyone never performed an analysis?
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Familiar Challenges
Has anyone never changed an input and analyzed
multiple cases? wished it was easier?
Parametric Analysis Automation.
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Familiar Challenges
Has anyone never fit a curve to the
points? plotted the resulting curve? estimated
the curves error?
Metamodeling / Surrogates Visualization. Respons
e Surface Equation, Least Squares Regression,
Spline Interpolation, Neural Networks, Gaussian
Processes, Radial Basis Functions.
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Familiar Challenges
Has anyone never wanted to explore a space more
dimensions, but thought There must be a better
way to pick the points?
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Familiar Challenges
Has anyone never wanted to do the same in more
dimensions, but thought There must be a better
way to pick the points?
Design of Experiments. Face Centered Cubic,
Orthogonal Arrays, Latin Hypercube, Monte
Carlo. Not to mention parallelization.
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Familiar Challenges
Has anyone never estimated a derivative? used
that derivative to predict behavior?
Sensitivity Analysis. Finite Difference, Adjoint
Methods, Automatic Differentiation, System
Sensitivity Analysis.
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Familiar Challenges
Has anyone never looked for the maximum or
minimum of the curve? Subject to constraints?
Optimization. Constrained Optimization, Gradient
Based, Conjugate Gradient, Penalty Function,
Stochastic Optimization, Genetic Algorithms,
Synthetic Annealing,
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Familiar Challenges
Has anyone never been uncertain of
inputs? been uncertain of the analysis?
Robust Design, Uncertainty Error Propagation.
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Familiar Challenges
Has anyone never faced competing objectives?
Decision Making. Pareto Frontier, Non-Dominated
Solution, MADM, MODM, SAW, TOPSIS.
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Natural Evolution of Design
1. Evolution of Complex Systems 2. MDO as the
Solution to the Complexity of Systems 3. MDO
as a Core Engineering Activity 4. MDO as a
Toolbox for Familiar Challenges
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Questions?Thanks,Rob McDonald