aerospace education & research in the area of design diamond jubilee lectures 2003-04 department...

Aerospace Education & Research in the Area of Design

Diamond Jubilee Lectures 2003-04Department of Aerospace EngineeringIndian Institute of Science, Bangalore

K. SudhakarCentre for Aerospace Systems Design &

EngineeringIndian Institute of Technology

Mumbai 400 076October 30, 2003

Year 1997

“Technology Perspective – The Next Decade”Aeronautics Research & Development BoardAR&DB/TC/001, May 1997

Suggested centres of excellence to be supported by AR&DB are;

– CFD – Advanced Composites – Systems Design & Engineering ? ?

Years 1990 -1997

• Aerospace Design as a discipline at IITB

– Specialization dropped

– Courses had tapered off

– Design, Build Or Open ended problems shunned

– No research interest among faculty

• March 1998 : AR&DB Sanction arrives

CASDE : July 1998

Mission

CASDE shall strive to develop and retain strong links with

Indian Aerospace Industry and shall engage in

R&D activities with worldwide visibility

http://www.casde.iitb.ac.in/

Objectives of CASDE

• M. Tech Programme in Systems Design & Engineering

• Modeling & Simulation Laboratory

• System Design Methodologies

• Awareness Creation

M. Tech in Systems Design & Engineering

• What do others teach?

• What can draw / retain student interest?

• What will faculty want to teach?

• What will industry want?

What all should be taught?

Form a composite team •

Brain-storming session •

http://www.casde.iitb.ac.in/History/PastEvents/lonavla/odw-see.pdf

M. Tech in Systems Design & Engineering

• Courses of study– System Modeling & Simulation$

– Optimization for Engineering Design$

– Systems Engineering Principles$

– Statistical Methods for Analysis & Design– Multi-disciplinary Design Optimization# (MDO)– Applied Mechatronics$ (hands on course)

• System Level Studies – RC Model Aircraft

$ Also available as short courses

# Coordinates a Special Interest Group on MDO (SIG-MDO)

http://www.casde.iitb.ac.in/edu/batch_2003/curriculum.htm

Laboratory and Other Infrastructure

• Wind tunnel balance

• Propulsion system test facilities• IM&S Laboratory http://www.casde.iitb.ac.in/IMSL/

– COTS sensors, actuators, . . . .

– R/C Model construction facilities, training

– Data acquisition cards

– Software

Propeller test facility50 gm force.

IM&S Laboratory

http://www.casde.iitb.ac.in/IMSL/resources.html

Launch Vehicle Simulator from VSSC

http://www.casde.iitb.ac.in/IMSL/vssc.html

Applied Mechatronics

Hands on course

• 2 hrs lecture + 3 hrs lab per week

• 2 projects

http://www.casde.iitb.ac.in/Mechatronics/

Student Projects

Instrumented. 2.5 kg, 1.6 m.

2000

Solar. 0.13 kg, 0.25 m.

2002

Videography. 0.9 kg, 0.6 m.

2001

http://www.casde.iitb.ac.in/IMSL/student-projects.html

Appreciated

ME Dual Degree Project : HILS

• Flight Dynamics & sensor models

• RTLinux + Comedi

• Real time simulation

• Choose WP NGC

• On-board Computer?

• Use hobby grade actuators

• Out of window display

68332 @16 MHzRAM 1 MB, FLASH 256 kB8 x 12 bit ADC @ 100 kHz15 PWM / 25 DIO30 gm; 50 x 75 x 12 mm

4 RC servo actuators

Aileron, elevator, rudder, throttle Overflying Mumbai

Autonomous Flight : 4 Way Points

http://www.casde.iitb.ac.in/Publications/pdfdoc/vishisht-DDP-2003.pdf

Flapping Wing Flight

Dual-Degree Project in Aero: Flapping wing

• Unsteady aerodynamics for prescribed motion

• Aero elastic analysis for prescribed actuation

• Wing construction - Polyurethane foam. (IDC)

• Actuation mechanism for testing. (Robotics)

B. Tech Project in Robotics(Robotics group)

• Mechanism design

• Kinematics prescribed

• Loads prescribed

Awareness Creation - 2003

• January - CEP in Applied Mechatronics

• February - 3rd Meeting of SIG-MDO

• April - Workshop on MDO @DRDL

• August - Brainstorming on System Analysis

• September - Int. Conf. MSO-DMES

We also!

• Traveling Course on Design, Build and Fly. (CASDE+ADA) Student Projects as Case Studies.

http://www.casde.iitb.ac.in/IMSL/des-bld-fly.html

– Naval Institute of Aeronautical Technology, Cochin. – Dept. of Aerospace Engineering, MIT, Chennai – Dept. of Aerospace Engineering, Parks College of Eng.,Coimbatore

• AeSI Wright Flyer Design Competition. (CASDE+ADA) http://www.casde.iitb.ac.in/we-also/des-comp/

We also!

• AeSI Schools Outreach Programme. (CASDE+ADA) 30 events, 103 Schools, 5,600 students (Good part of events by CASDE) http://www.casde.iitb.ac.in/we-also/school-outreach/

Arya explaining the intricacies of flight mechanics

http://www.casde.iitb.ac.in/MDO/

Systems Engineering Process

Requirements to lower level

Context

Solution from lower level

SuperSystem

System

SubSystem

Level-3Analysis

Level-2Analysis

Level-1Analysis

Focusof CASDE

• Level – 1 : Good understanding of system; knowledge base, heuristic; Computationally less expensive; Usually not available for new systems.• Level – 3 : Physics based modeling; computationally intensive, applicable to new systems (V&V?)

CASDE Activities

Research activity

– High fidelity models in design loop ( CFD, . .)

– Multi-Disciplinary Analysis (MDA) leading to Multi-disciplinary Design Optimization (MDO)

Level-3Analysis

Level-2Analysis

Level-1Analysis

Challenges!

• Human / Admin– People coming together (Design, A/D, Str,

Prop, Controls)

– Synchronizing funds (taken care of by ARDB)

• Technical– Non-availability of disciplinary codes

– Neither here nor there!

MDO Elements

• Architectures

• Sensitivity Analysis

• Surrogate Modeling

• Variable Complexity

MDO Elements

• Architectures




Optimizer

How are the couplingshandled?

System Analysis

MDO Elements

• Architectures




How are the couplingshandled?

System Analysis

X F

• dF/dX? f/X, f/Y . . . dF/dX• How to evaluate f/x?

~ Finite difference~ Continous/Discrete Adjoint ~ Automatic Differentiation

User Supplied Gradients

Complex AnalysisCode in Fortran

Manually extractsequence of mathematical

operations

Code the complex derivative evaluator

in Fortran

Manually differentiatemathematical

functions - chain rule

FORTRANsource code

that can evaluategradients

User Symbolic Maths

Manually extractsequence of mathematical

operations

Use symbolic math packages to automate derivative evaluation


in Fortran

Complex AnalysisCode in FORTARN

FORTRANsource code


Automatic Extraction of Formulae

Parse and extract the sequence

of mathematical operations

Use symbolic math packages to automate derivative evaluation


in Fortran


FORTRANsource code


Gradients by ADIFOR


FORTRANsource code


Automated Differentiation

Package

ADIFOR Ver 2.0

• First applied to VLM• Recently to 3-D Euler

– Multiblock, Structured grid

– Central difference, FVM

– JST scheme of artificial dissipation.

– Multistage Runge-Kutta schemes.

– Implicit residual smoothing and local time stepping

Original

CodeADIFORed Code

No of lines 4,090 11,889

Exec. time (min)

6.58 28.25

Codex f

ADIFORed Code

x f, df/dx

ADIFOR

ADIFOR Ver 2.0

• 3D Euler

• ONERA M6 Wing

3D Euler (L/D)

ADIFORed3D Euler

(L/D), d(L/D)/d

Error in Finite Difference Estimate of d(L/D)/d

=0.2 =0.02 =0.002 =0.0002

3.06 38.10 4.44 7.08 77.25

4.11 2.46 1.73 1.56 15.09

MDO Elements

• Architectures




• Response Surfaces?• Design of Experiments

• Design & Analysis of Computer Experiments• Designs?

MDO Elements

• Architectures



• Variable ComplexityMix high & low fidelity methods

• VLM & Euler• thumb rules + analysis

Design / MDO Studies

– WingOpt

– 3D Duct

– Hypersonic Vehicle

Design under uncertainty +

MDO of Transport Aircraft Wing

Analysis Block

AeroelasticityIteratorOptimizer

FSQP

I

N

T

E

R

F

A

C

E

History Block

Input Processor

Output Processor

Aerodynamics(VLM)

Structures MSC/

NASTRANNASTRANI

nterface

3-D Duct Design

Entry Exit Location and shape known

Geometry of duct from Entry to Exit ?

• Pressure Recovery?• Distortion?• Swirl?

3D-Duct Design Using High Fidelity Analysis

Low Fidelity Design Criteria- Wall angle < 6°- Diffusion angle < 3°- 6 * REQ < ROC

Fluent for CFD RSM / DOE DACE

X1-MINX1-MAX

X2-MAX

X2-MIN

Parameterization of HSTDV Body

Design variables

XD: {1, 2, 3 , n_plan , wc , wfac_pl, tfac_pl,, Hcruise }

z

x

l l

h h

l l

wcanth

l

r

l

noz

cowl

noz

1 2 3

1 32 mid noz

1

h intake

r

n-pl

r2

a

b

t

Hypersonic Vehicle – Discipline Interactions

Ext. CompressionModel : AM1

Ext. ConfigurationModel : AM2

Aero Model : AM3

Trim Model : AM4

Thrust Model : AM5

Performance Model : AM6

Y1: l1, l2, l3, h1, h2, h3

Y2: ma , MI, , pst

Y3: (X,Y,Z)Y4: TOGW , C.G., Vol, Fuel mass

Y5: CN, Cm, CA

Y6: TOGW_up, T , T , D

Y7: Th_deliv, Lp, Mp

Y8: Cruise Range

1

2

3

n_pl

w_c

SW

ST

Hcr

Input variable Analysis Model Output

n_pl, SW

1…, Hcr

Variables not sharedShared variables

Y1

Y1… Response from AM1 required as input in AM2

MDO-Framework

Database

ConfigurationServer

ExecutionManager

MDOController

NameServer

DataServer

OPT1

Optimizer Manager

OPT2 OPT3

AM1

AnalysisManager

AM2 AM3

GUI

Control

Data

http://www.casde.iitb.ac.in/MDO/

Publications

2000 2001 2002 2003

Journal 0 1 3+2 1+1

InternationalConferences

0 1 6 5

Core faculty = 4

Analysis for Design

Design

z = design variablesf = objectiveh = equality constr.g = inequality constr.R = residue

Interface

AnalysisR(z,p)=0

Optimizer

z f, h, g

z p

Optimization

Analysis

Optimizer

z f, h, g

z = design variablesf = objectiveh = equality constr.g = inequality constr

MDO


Analysis-1R1(z,p1)=0

Interface

Optimizer

z f, h, g

z p


Y12

Y21

MDO-ArchitecturesMDO


Interface

Optimizer

z f, h, g

z p



Y12

Y21



Y12

Y21

z p

MDO-Architectures



Y12

Y21

z p

p



Y12, Y21z 1 = Y12 - Y12* 2 = Y21 - Y21*

Analysis

Evaluator

Y12*

Y21*

MDO-ArchitecturesMDO


Interface

Optimizer

z f, h, g

z p



Y12

Y21

MDO


Interface

Optimizer

z, y12, y21

f, h, g1, 2

p1, 2



z, y12, y21


X1-MINX1-MAX

X2-MAX

X2-MIN




X1-MINX1-MAX

X2-MAX

X2-MIN

http://www.casde.iitb.ac.in/MDO/3d-duct/



MDA - System Analysis

• Performance• -ilities?• life cycle?• Cost, etc.?

Parameters

A-2

A-4

A-1

A-5

A-3

Design & Analysis of Computer Experiments

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

xx

xx

x

Estimates of Predictive error

x Computer exp DACE Fit

Building Models Using DACE

xx

xx

x

5% predictive error

x = Computer exp DACE Fit

xx

x

Use multi-modal GA to identify ‘n’ highest peaks.Test if they are higher than 5%Add computer experiments at those spots

Design - Publications

Journal of Aircraft Volume 40 Number 4

July 2003

• Total number of papers - 22• Number of papers addressing design - 4

aerospace education & research in the area of design diamond jubilee lectures 2003-04 department...

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