Srinivasan Memorial Lecture The Aeronautical Society of India, Trivandrum VSSC

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Srinivasan Memorial LectureThe Aeronautical
Society of India, TrivandrumVSSC

• K. Sudhakar
• Centre for Aerospace Systems Design Engineering
• Department of Aerospace Engineering
• Indian Institute of Technology
• Mumbai 400 076
• June 27, 2003

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• I would love to visit IIT Bombay and get
  briefed
• Dr. S Srinivasan
• May 17, 1999
• Breakfast table at SHAR Guest House

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Years 1996-1998

• ARDB Centres
• CFD
• Composites
• Systems Design Engineering ? ?
• Aerospace Design as a discipline in Universities
• Specialization dropped
• Courses had tapered off
• Design, build Or Open ended problems shunned
• No research interest among faculty
• IIT Bombay decides to take a plunge!
• What made it fail earlier?

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Aerospace Systems Design and Engineering in
Universities

• System Level Studies
• Masters Level Specialisation
• Design Optimization / MDO
• At CASDE we also . . . . .

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System Level Studies
MAV
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MAV Challenges / Preparations2 kg, 0.6 m
Autonomous Video-platform

• Low Reynolds number flows
• Wind tunnel balance
• Miniaturisation using COTS
• Construction methods
• Propulsion system (60 weight)
• Autonomous missions ? HILS

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Launch Vehicle Simulator from VSSC
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H/W In Loop Simulator for MAV

• Flight Dynamics Sensor models
• On-board Computer ?
• Hobby grade actuators
• Way Point Navigation
• ADDR
• ADDR GPS
• Out of window display
• Problem opened up for CG specialists
• INS-GPS Module, M Tech thesis in EE

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Flapping Wing Flight
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Flapping Wing Vehicle
.

• Unsteady wing aerodynamics with prescribed motion
  in flapping twisting -VLM.
• Coupled aeroelastic analysis. Arrive at
  structural definition.
• Tailoring to get desired twisting by only
  flapping actuation.
• Construction of the wing
• Design and build the flapping mechanism
• M Tech in robotics group.

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Flapping to Induce Twisting

• Wing spar to be rigid rod. Used for flapping
• Outer sleeve has low and tailored torsional
  stiffness
• Wing strips mounted on outer sleeve

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Flapping to Induce Twisting

• Wing spar flapping hinge rigid and one piece.
• Wing surface - film

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IMS Laboratory
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M Tech Specialisation inSystems Design
Engineering

• Design Optimization - I
• Optimization laboratory
• Design Optimization - II

Modeling Simulation Applied Mechatronics
Systems Engineering Principles
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Design OptimizationMDO
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Design Optimization / MDO

• Airborne Early Warning System
• Complex system, simple models.
• Maneuver Load Control
• Existing system, database driven
• Hypersonic Launch Vehicle
• New system, simple models, system analysis
• Aero-elastic Wing Design
• Simple models
• Intermediate level models
• FEM VLM

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MDO

• System analysis
• Ownership of disciplinary analysis?
• Integration strategy?
• Human technical issues
• Strategies that will
• Accommodate above concerns
• Allow bringing in science based, compute
  intensive analysis

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Integration Issues
System Designers Nightmare!
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MDO Frameworks
Design Optimization Course during 2003 will be
offered using CASDE MDO-Framework

• Commerical Frameworks
• iSIGHT
• Phoenix Integration
• Dakota (Sandia labs)
• CASDE MDO-Framework
• http//www.casde.iitb.ac.in/MDO/framework/

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Multi-disciplinary Design Optimization

• 3D-Duct Design
• Parametrization, meshing, simple analysis
• CFD (NS) ?
• Wing or Vehicle
• CFD (NS / Euler) ?
• Hypersonic Nozzle Design
• CFD (Euler) ?

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Optimization
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Optimization Design Space Search

• Brute force. Grid the space, evaluate function,
  sort to identify minima.
• Evolutionary. Still too many function calls.
• Genetic algorithms
• Simulated annealing
• Gradient based methods
• Local optima
• Small number of function calls if gradients good!
• Suited for compute intensive problems.

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Brute Force Search
? ? ? ? ? ? ? ? ? ?
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GA / SA Search

? ?

? ?
? ? ?

? ?

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Gradient Based
Gradient of functions Required!




?

?

?

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How to evaluate gradients?

• Consider design of wings
• Design variables, x b, C
• Objective function, f(x) CL
• Analysis is CFD
• Give values to x b, C ? Wing ? mesh
• Run a CFD code and generate pressure distribution
• Integrate pressures on body ? CL
• How to evaluate

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Methods to Evaluate Gradients?

• Finite difference method. Easy to implement, but
  problematic?
• Complex variables approach, requires source
• ADIFOR Automatic DIfferentation in FORtran
  requires source. Analytical accuracy
• Surrogate Modeling Surface fits
• Response Surface Method (RSM / DOE)
• Design Analysis of Computer Experiments

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Finite Differenced Gradients?

• Finite Difference Method
• n design variables ? (n1) CFD
  runs

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Problem with Finite Differencing?

• Only (n1) CFD runs?
  
• Correct step size for FDM is important!
• Will demand more CFD runs!

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Complex Variable Approach
subroutine func (x, f) real x, f
subroutine func(x, f) complex x, f

• Evaluate fx i e e ltlt 1
• f(x) Real Part f(x i e) -
  f(x) e2 / 2
• df/dx Imag Part f(x i e) / e - f
  (x) e2 / 6
• CPU time up by 3, RAM up by 2

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User Supplied Gradients
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User Symbolic Maths
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Automatic Extraction of Formulae
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Gradients by ADIFOR
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Surrogate Modeling

• DOE / RSM modeling in physical experiments.

Fitted model is smooth and easily
differentiable. Curse of dimensionality! 2k
function evaluations Sequential RSM.
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Design Analysis of Computer Experiments

• Regression fit Stochastic process
• Single global fit
• Variability in prediction known and exploitable

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Building Models Using DACE - An Idea!
5 predictive error
Use multi-modal GA to identify n highest
peaks. Test if they are higher than 5 Add
computer experiments at those spots
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We Also . . . .

• Travelling course on design
• Schools Outreach Programme
• Design Competition - Design, Build, Fly
• KVPY Scheme for encouraging innovators of
  tomorrow
• Practical training for other engineering college
  students

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People
Hemendra Arya Amitay Isaacs

• Ashok Joshi
• PM Mujumdar
• SK Sane

Anil Marathe K Sudhakar GR Shevare
Sivan Shyam Geethai
Kurien Isaac Prasanna Gandhi Sanjay Bhat
D Henry Umakant Shamkar
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Thank You