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Copyright © 2007, SAS Institute Inc. All rights reserved.

Dimitri MavrisAerospace Systems Design Laboratory (ASDL)

Georgia Institute of Technology

22Prof. Dimitri Mavris

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Dr. Dimitri Mavris

Boeing Endowed Professor for Advanced Aerospace Systems AnalysisDirector, Aerospace Systems Design Laboratory (ASDL)

Guggenheim School of Aerospace Engineering Georgia Institute of Technology

Atlanta, GA, 30332-0150

A Visual Analytics Approach for the Design and Technology Assessment

of Innovative Aerospace Concepts


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Presentation Outline

• Vantage point• Innovation and Critical Thinking• Critical elements needed for Innovation• Barriers and enablers for Innovation to occur• What is Visual Analytics?• Means to enable technology and new methods

transition• A sample example of the current state of the art in the

aerospace community• Closing remarks


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ASDL: A Unique Education and Research Mission

• Produce well-trained System Analysts, System Engineers and Technologists for immediate deployment in academia, industry, and government

• Develop strong strategic partnerships with counterparts in Industry and Government

• Use these relationships to study problems of fundamental interest to both

• Promote student participation in IPT and IPPD teams, internships with industry/government, and national design competitions

• Provide leadership and innovation in the field of Advanced Design Methods (probabilistic and robust design simulations)


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ASDL Research Program

Formulation, development, and implementation ofcomprehensive approaches to the design of affordableand high quality complex systems, emphasizing:

• Disciplinary breadth and depth while accounting for uncertainty and risk

• Multi-disciplinary analysis, optimization and design• Reduction of analysis, design process cycle time• Physics-based analysis and design of complex systems• Systems-of-systems, architecture-based systems engineering• Interdisciplinary research, both within the schools at Georgia

Tech and through the formation of alliances with other universities, industry, and government


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The System Design Academy• The ASDL at Georgia Tech provides a unique opportunity for graduate

students to be developed. Emphasis is given on innovation and creativity skills to be developed.

• Well-rounded, multidisciplinary education provides breadth and depth• A wealth of activities are available to cultivate the variety of interests in our

diverse student body• ASDL education revolves/centers on the development of its students, not

overloading them with information• Technology-focused education allows students to succeed in any industry• Incorporation of policy, economics and philosophy courses into the

curriculum gives the students a different perspective and makes them better rounded

• Undergraduate and Graduate students work together in a team-centric environment

• Weaknesses are exposed and turned into strengths– Peers work to develop each other– Opportunities are provided for all students to excel

• Immense freedom contributes to unprecedented student satisfaction


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Motivating Factor for our ResearchN

umbe

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ngin

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hang

es P

roce

ssed

20-2

4M

onth

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1-3

Mon

ths

Job

#1

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U.S. CompanyJapanese Company

90%Total Japanese

Changes Complete

Be Creative. Innovate or Else.


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So What is Creativity? Where can I get it?

• Define creative.• Consider these questions:

– How do you know if something is creative?– How do you measure it?– Why do we even need it?


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Some words for creative?

• Original• Unique• Unusual• Different• Deep meaning• Imaginative• Practical/Impractical• Smart


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A Definition of “Creative”

• According to Merriam-Webster’s Collegiate Dictionary, 10th ed.– When used as an adjective . . .

• 1. marked by the ability or power to create : given to creating

• 2. having the quality of something created rather than imitated : IMAGINATIVE

• 3. managed so as to get around legal or conventional limits : deceptively arranged so as to conceal or defraud


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Creative Thinking Defined

• “Creative thinking is generally thought of as putting together information to come up with a whole new understanding, concept, or idea.”

• Kenneth D. Moore (2005)

• Phase I: Preparation• Phase II: Incubation• Phase III: Illumination• Phase IV: Verification

• Kenneth D. Moore (2005)


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So why is it important?

• The thinking process is what counts. A solid process will produce a solid product.

• They have the “information,” now let them apply it in a unique and possibly unconventional way.

• In the context of educating and empowering the next generation of scientists and engineers one has to ponder. If this group of people will be the future leaders of the world? Do you want them to effectively solve the problems of the world or keep trying what’s been done in the past and failed?


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Why don’t we use creative thinking more?

• Ambiguity scares both students and teachers• Cannot be measured by numbers

– How can standardized tests measure creative thinking?

• We have not built up the critical thinking capacity in our classrooms

• Many of us honestly think our students can’t handle it

• End effect: Engineers enter the workforce ill- prepared, without the necessary skill set


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Some Thoughts on Innovation

• "All innovation begins with creative ideas . . . We define innovation as the successful implementation of creative ideas within an organization. In this view, creativity by individuals and teams is a starting point for innovation; the first is a necessary but not sufficient condition for the second" (Amabile et al, 1996)

• "Often, in common parlance, the words creativity and innovation are used interchangeably. They shouldn't be, because while creativity implies coming up with ideas, it's the "bringing ideas to life" . . . that makes innovation the distinct undertaking it is.“ (Davila et al, 2006)

• “Generally, the true disruptive power of an innovation lies not in the technology itself but in the business model that surrounds that technology.” (Clayton Christensen, Forbes.com, 2007)


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Why Innovate?• “According to one study, 75 % of CEOs of the fastest growing

companies claim their strongest competitive advantage is unique products and services and the distinct business processes that power them to market” (Howard Smith, CTO of CSC)

• According to a study conducted by Accenture (1996-2007), leading suppliers “drive their consistent revenue increases through investing in research and development and capital expenditures at a faster rate than peers, leveraging these “growth investments” to develop more and better products continually.”

• A study published in Outlook Journal (2004), suggests that there is a small subset of automakers who are significantly better at growing revenues than their competitors. The study identifies four key drivers for their success, including product innovation.


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Disruptive Innovation

• A disruptive innovation replaces the current state of the art and creates room for further improvement than was previously possible

• According to Forbes.com, the top 10 disruptors in the last 10 years are:– NetFlix– Google– Blackberry– Minute Clinic– Apple iPod– Roomba– Skype– HeartStart– YouTube

Source: Forbes.com, Clayton Christensen and Innosight

Graphic Adapted From: The Virtual Innovator by D. Arnold


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The Evolution of the Automobile

www.co.rice.mn.us www.southlakes-uk.co.ukwww.cars-pictures-index.comwww.autosellers.org

1900 1910 1920 1930 1940 1950

1960 1970 1980 1990 2000 2007 +


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The Evolution of the Aircraft

1900 1910 1920 1930 1940 1950

1960 1970 1980 1990 2000 2007 +

1928

1916

1903

1957

1981 2007

1947

First Jet-

Powered Aircraft

1939

www.meteorflight.com

1967

19692005

www.iiptc.comwww.wikipedia.comwww.fotoimages.comwww.aerospace.org

1994


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Next Generation Innovative Concepts - Disruptors

Subsonic Transports

Supersonic Aircraft

Personal Air Vehicles

Uninhabited Air Vehicles

Rotorcraft

New Generation of Innovative Vehicles can not be modeled accurately in the absence of historical data

Extreme STOL

Motivation for Physics-based Conceptual Design


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Next Generation Concepts – From Innovation to Implementation

Some Personal Observations:

– Usually there is no shortage of new ideas, creative or not.

– When you think that you have come up with something original think again. One can say that almost everything has been attempted before.

– Cross-fertilization of ideas, solutions from different fields could provide great insights and benefits.

– New ideas have a hard time overcoming organizational barriers.


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Elements needed to overcome the organizational and technical barriers so as to ensure market penetration and Successful Transition to every day use:

– Advocacy for the proposed concepts and their associated design approach. Support to overcome organizational barriers

– Fundamentally sound systems engineering processes tailored to new systems and system of systems formulations

– Practical methods and processes that can handle “Extrapolations” beyond the realm of the historical databases. A physics based approach to design

– Exploitation of technological breakthroughs


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– System level modeling and simulation to assess the technological gaps and to provide guidance, goals, impact assessments

– Means to support electronic design reviews(A parametric, multi-variate, dynamic trade-off environment)

– Methods to account for uncertainty and risk throughout the process

– Means to support strategic decision making. Visualization of the data to enable the right level of depiction for the right audience(Multi-attribute, scenario based decision making)

– Training for the new generation of designers and system engineers


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Enablers Needed to Overcome Barriers

• New methods almost by definition go against the grain of established paradigms that are well defined and accepted by the practicing community and thus are always viewed with skepticism, criticism, or in some cases even cynicism

• To facilitate the introduction of new methods the following criteria must pre- exist before they can be adapted for use:– The underlying theories, methods, mathematics,

logic algorithms etc upon which the new


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Enablers Needed to Overcome Barriers– cont’d

– Availability of training utilizing material written on the overarching method, tutorials, etc. with relevant examples.

– Proposed methods which are grounded on or which are complimentary to established practices have a better chance of succeeding.

– Tools automating the proposed method and making it practical for every day use. Without them the method resembles a topic of academic curiosity

– Relevant examples and applications within a given field of study.


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Advanced Methods DevelopmentIn a breakdown analogous to NASA/DoD’s Technology Readiness Levels (TRLs), the

following Advanced Methods Readiness Levels (AMRLs) hierarchical approach to research has emerged as a useful construct at ASDL:

ONR/NASABasic Research

MethodsDevelopment andProof-of-Concept

(NASA, NAVAIR, AFRL, NSWC)

IndustryApplications

• Formulation Phase• Basic Principles, Fundamentals• Analytical Formulation• Cross-Fertilization of Elements• Method Initial Formation• Initial Testing

• Method Development • Application Formulation• Proof-of-Concept Implementation• Unification of Theory• Automation, Tool Development• Creation of Tutorial Material

• Method Implementation• Full System Prototype• Actual System in Application Domain• Real World, Industrial Applications• Stakeholder Involvement• Utilization, Integration and

Automation of Actual Tools and Processes

http://www.lockheedmartin.com/wms

http://infosite.sas.com/C10/Presentations/default.aspx/../../jack/My Documents/PACE Conference/ASDL Demos/DEMOS/gordonj/sarmiegh/Local Settings/Temporary Internet Files/OLK8/JV2020_Continuity_vBppt.ppt


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Enabling Models and Techniques

Established TechniquesResponse Surface Methodology (Biology, Ops Research)Neural Networks (Artificial Intelligence, Image Processing)Design of Experiments (Agriculture, Manufacturing)Design for Computer Simulation (Geostatistics, Physics, Nuclear)Quality Function Deployment, Pugh Diagram (Automotive)Morphological Matrix or Matrix of Alternatives (Forecasting)Multi-attribute decision making (MADM) techniques (U.S Army, DoD)Uncertainty/Risk Analysis (Control Theory, Finance, Mathematics)Technology Readiness Levels (NASA, DoD)

Customized Methods Synthesized from Established TechniquesFeasibility/Viability IdentificationRobust Design Simulation (RDS)Technology Identification, Evaluation, Selection (TIES)Joint Probabilistic Decision Making (JPDM)Unified Trade-off Environment (UTE)Inverse Design using Filtered Monte Carlo Simulation

Mathematical techniques have emerged that are suitable to enable the average engineer to speed up the analysis process, do requirements flow-down, and conduct multivariate trade-off analyses.


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Motivation for Physics-based Conceptual Design

Subsonic Transports

Supersonic Aircraft

Personal Air Vehicles

Uninhabited Air Vehicles

Rotorcraft

New Generation of Vehicles can not be modeled accurately in the absence of historical data

Extreme STOL


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Structures

Performance

Propulsion

Aerodynamics

Weights & Sizing

Stability &Control

Manufacturing

Cost& Economics

Safety

Operations

Avionics

Trajectory/Mission

Physics-based Multidisciplinary Design


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Cross Fertilization Example

Number of Measurements

13

125

15

a) One at a time

b) Matrix

c) Central Composite

Experimental Design in Biotechnology


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What is needed for the Paradigm Shift to occur?

• Transition from single-discipline to multi-disciplinary analysis, design and optimization

• Easy to use integrative environments• Automation of the resultant integrated design process• Transition from a reliance on historical data to physics-based formulations,

especially true for unconventional concepts• Means to perform requirements exploration, technology infusion trade-offs

and concept down selections during the early design phases (conceptual design) using physics-based methods

• Methods which will allow us to move from deterministic, serial, single-point designs to dynamic parametric trade environments

• Incorporation of probabilistic methods to quantify, assess risk • Transition from single-objective to multi-objective optimization• Need to speed up computation to allow for the inclusion of variable fidelity

tools so as to improve accuracy• Means to facilitate data and knowledge creation, storage, versioning,

retrieval and mining• An integrated knowledge based engineering and management framework


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Data Integration and Visualization is Needed

• “An ideal environment for analysis would have a seamless integration of computational and visual techniques*”– Maturation of statistical methods and data mining

techniques– Development of visualization that uses these techniques– Synthesis of enabling techniques into a suite of application-

based methods• Extending the reach of analytics requires these three

foundational concepts

*From Illuminating the Path: the R&D Agenda for Visual Analytics, National Visualization


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Key Enablers

• An integrated knowledge based engineering and management framework based on the concept of meta-models or surrogate models

• A multi-attribute Decision Making and Support Environment based on the concept of Visual Analytics that finally allows the Decision Makers to Visualize, understand/comprehend and query their data in real time

• These two enablers combined will provide a means to :- speed up processes, - protect proprietary nature of codes used, overcome organizational barriers (protectionism of tools and data), - allow for the framework to be tool independent (no need for direct integrations of codes), this also enables our desire for variable tool fidelity formulations, - enable the designer to perform requirements exploration, technology infusion trade-offs and concept down selections during the early design phases (conceptual design) using physics-based methods- finally move from a deterministic, serial, single-point design mind frame to a dynamic parametric and interactive trade-off environment


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Introducing the Concept of Visual Analytics• Grand Challenge: How to analyze overwhelming, disparate, dynamic

information• Analytics is the “science of analysis” to discover and understand patterns

– Uses statistical tools and methods– Primary goal is to understand the past to predict the future

• Visual Analytics is “the science of analytical reasoning facilitated by interactive visual interfaces”

– Provides a mechanism for a user to see and understand large volumes of information at once

– The brain can best process information received through visual channels– Facilitates discovery of unexpected trends and highlights transparency of

underlying physical phenomena• Applications include Homeland Security, marketing, design and

optimization, disaster management, and othersVisualization aids decision making on otherwise insurmountable problems


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Creation of Modeling and Simulation Environment

WATEWeight Analysis of

Turbine Engines Code

FLOPSFlight Optimization

Code

NPSSNumerical Propulsion

Simulation

ALCCAAircraft Life CycleCost Analysis Code

Multi-Disciplinary DOEMission

Requirements

MarketRequirements

TechnologySetting

FidelityMultipliersEconomic

Assumptions

Vehicle Size

VehiclePerformance

VehicleEconomics

NOx CO2 NOISE

EmissionsModules

Airframe Fixed Given Engine Architecture

ThrustRequired

ThrustAvailable

A B

Engine Engine ArchitecturesArchitectures

Aircraft NeedsAircraft Needs


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Parametric Technology Space: Family of Designs


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Pareto Analysis of Significant Technology Metrics


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Parametric Interactive Technology Assessments

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Emissions

Engine Performance

NoiseCost

(More) Emissions

NOx

CO2

SFC

T/W

FON

SLN

DOC

HC

Soot


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• A Gap Analysis can be used at the conceptual design stage to:– Determine the minimum technology attributes that

are necessary in order to meet the desired objective– Identify where investment in technology

development will yield the best payoffs– Assess where design tradeoffs need to be made

• By obtaining this information earlier in the design process, Gap Analysis can reduce design costs and time

The Gap Analysis answers the question: What do I need to do today to get to where I

want to be in the future?

Gap Analysis


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Probabilistic Requirements Analysis

• Using surrogate models, the constellations of points can be viewed in multiple dimensions

• The green area indicates the desirable region• Using probabilistic techniques and surrogate

models, 10,000 discrete designs were created and graphically displayed

Zoomed In Version

% NOx Reduction

% C

O2

Red

uctio

n

% Engine Thrust/Weight

% F

uel C

onsu

mpt

ion

Red

uctio

n

Flyo

ver N

oise

Red

uctio

n (d

b)

Sideline Noise Reduction (db)


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Technology Space Constellations

% NOx Reduction % NOx Reduction

% C

O2

Red

uctio

n

% C

O2

Red

uctio

n

% Engine Thrust/Weight

% F

uel C

onsu

mpt

ion

Red

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n

Flyo

ver N

oise

Red

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n (d

b)

Sideline Noise Reduction (db)

Zoomed In Version

• Clicking on any point of interest brings up the associated flowpath diagram

Case 1156

Research Lead: Dr. Michelle Kirby


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Multivariate Analysis: Joint Probability Contours

• Using the joint probability technique, the trends in each dimension can be viewed

• For positive correlations, both variables can be changed in the same direction

• For negative correlations, a compromised design will result

• The blue highlighted point of interest is also shown in each dimension

• The highlighted point can be compared to the pareto optimum

• Where is the “Needle in the haystack?”

Research Lead: Dr. Michelle Kirby

CO2 Reduction

NOx Reduction

% Thrust/ Weight

% TSFC

FlyoverNoise

SidelineNoise


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Three-Dimensional Pareto Frontier (Propulsion)

• Red = Architecture A• Green = Architect. B• Blue = Architecture C• Surrogate model

allows rapid evaluation of SFC and Specific Thrust as a function of several input parameters

• Clicking on any point brings up a flowpath of that engine and links to other information

Notional


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High Dimensionality Analysis Using Multivariate Plot

• Multivariate = Simultaneous view of all x vs. y plots

– “Slices” of the 3-D profiler

• All points linked across hierarchy

• Validation: Multiple trends can be easily confirmed

• Error checking: Failed cases (negative TSFC) can be highlighted and the reason for failure can be graphically identified very quickly

• Traceability: Engine architectures for specific design regimes can be justified using physics- based modeling

1

32

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TSFC

SpecificThrust

Mach

Altitude

TurbineTemp.

EngineType

Turbojet

Turbofan

Ramjet

1

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11

3322

11 2233

TSFC

SpecificThrust

Mach

Altitude

TurbineTemp.

EngineType

Turbojet

Turbofan

Ramjet3

1

2


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Filtered Monte Carlo Technique0 20 40 60 80

PlatformsLost

100 400 700

Enemy Range

0.1 0.6 1 1.4Enemy

Dwell Time

0 200 500FriendlyRange

500 1100 1600FriendlySpeed

10 20 30 40Missile-

Wing Area

3 4 5 6Missile-

Aspect Ratio

0.25 0.34 0.42Missile-

Fuel Volume

0.2 0.3 0.4Engine-

Inlet

4 5 6 7Engine-

Pressure Ratio

1000 3000Engine-

Turbine Temp

03060

Targ

ets

Kill

ed

03060

Pla

tform

sLo

st

100400

700

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my

Ran

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0.10.71.3

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ime

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Select Show Include

0 ≤Targets Killed≤100

0 ≤Platforms Lost ≤100

100.28 ≤Enemy Range≤899.97

0.10019 ≤Enemy Dwell Time≤2

-58.257036 ≤Friendly Range≤904.230311

532.322798 ≤Friendly Speed≤1978.78995

Data Filter


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Filtered Monte Carlo Technique

0 20 40 60 80Platforms

Lost

100 400 700

Enemy Range

0.1 0.6 1 1.4Enemy

Dwell Time

0 200 500FriendlyRange

500 1100 1600FriendlySpeed

10 20 30 40Missile-

Wing Area

3 4 5 6Missile-

Aspect Ratio

0.25 0.34 0.42Missile-

Fuel Volume

0.2 0.3 0.4Engine-

Inlet

4 5 6 7Engine-

Pressure Ratio

1000 3000Engine-

Turbine Temp

03060

Targ

ets

Kill

ed

03060

Pla

tform

sLo

st

100400

700

Ene

my

Ran

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0.10.71.3

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804 matching rows

Select Show Include

0 =Targets Killed=100

0 =Platforms Lost =10

100.28 =Enemy Range=899.97

0.10019 =Enemy Dwell Time=0.30017

-58.257036=Friendly Range=904.230311

532.322798=Friendly Speed=1978.78995

Data Filter


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T3

off

on

off

T7

off

on

off

T5

off on

off

T8

off

on

off

T10

off

on

off

T4

off

on

off

T11a

off

on

off

T11b

off

on

off

T12

off

on

off

T13

off

on

off

T14

off

on

off

T15a

off

on

off

T16

off

on

off

T9

off

on

off

% CO2 /ASM

% Below LTO NOx

% DOC+I

+26.70%

-88.18%-31.50%

-17.35%

0%+5.85%

0%-23.40%

+3.49%%

Cha

nge

From

Bas

elin

e

This is the baseline configuration.

Dynamic Technology Environment

Baseline +T3 +T5 +T7 +T8 +T9 +T10 +T11a/b+T13 +T14 +T15a +T16

0.00%

-31.50%

-30%

-24%

-18%

-12%

-6%

0%

% R

educ

tion

in C

O2

-100%-90%-80%-70%-60%-50%-40%-30%-20%-10%0%

% R

educ

tion

in N

OX


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T3

off

on

on

T7

off

on

off

T5

off on

off

T8

off

on

off

T10

off

on

off

T4

off

on

off

T11a

off

on

off

T11b

off

on

off

T12

off

on

off

T13

off

on

off

T14

off

on

off

T15a

off

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off

T16

off

on

off

T9

off

on

off

% CO2 /ASM

% Below LTO NOx

% DOC+I

+26.70%

-88.18%-82.76%

-17.35%

0%+5.85%

0%-23.40%

+3.49%%

Cha

nge

From

Bas

elin

e

Addition of the TAPS advanced combustor (T3) does not change the flowpath, but results in a significant reduction in the LTO NOx characteristics.


Baseline +T3 +T5 +T7 +T8 +T9 +T10 +T11a/b +T13 +T14 +T15a +T16

0.00%

-82.76%

-30%

-24%

-18%

-12%

-6%

0%

% R

educ

tion

in C

O2

-100%-90%-80%-70%-60%-50%-40%-30%-20%-10%0%

% R

educ

tion

in N

OX


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T3

off

on

on

T7

off

on

off

T5

off on

on

T8

off

on

off

T10

off

on

off

T4

off

on

off

T11a

off

on

off

T11b

off

on

off

T12

off

on

off

T13

off

on

off

T14

off

on

off

T15a

off

on

off

T16

off

on

off

T9

off

on

off

% CO2 /ASM

% Below LTO NOx

% DOC+I

+26.70%

-88.18%-83.54%

-17.35%

-2.99%+5.85%

-3.91%-23.40%

+3.49%%

Cha

nge

From

Bas

elin

e

The highly loaded compressor system (T5) improves the efficiency of the HPC, thus reducing vehicle fuel burn and CO2 production.



-3.91%

-83.54%

-30%

-24%

-18%

-12%

-6%

0%%

Red

uctio

n in

CO

2

-100%-90%-80%-70%-60%-50%-40%-30%-20%-10%0%

% R

educ

tion

in N

OX


[email protected]

T3

off

on

on

T7

off

on

on

T5

off on

on

T8

off

on

on

T10

off

on

on

T4

off

on

off

T11a

off

on

on

T11b

off

on

on

T12

off

on

off

T13

off

on

on

T14

off

on

on

T15a

off

on

off

T16

off

on

off

T9

off

on

on

% CO2 /ASM

% Below LTO NOx

% DOC+I

+26.70%

-88.18%-78.73%

-17.35%

-15.35%+5.85%

-21.56%-23.40%

+3.49%%

Cha

nge

From

Bas

elin

e

The turbine tip clearance control (T14) influences the adiabatic efficiency, which improves fuel burn and reduces the CO2 /ASM.



-21.55%-78.73%

-30%

-24%

-18%

-12%

-6%

0%%

Red

uctio

n in

CO

2

-100%-90%-80%-70%-60%-50%-40%-30%-20%-10%0%

% R

educ

tion

in N

OX


[email protected]

T3

off

on

on

T7

off

on

on

T5

off on

on

T8

off

on

on

T10

off

on

on

T4

off

on

off

T11a

off

on

on

T11b

off

on

on

T12

off

on

off

T13

off

on

on

T14

off

on

on

T15a

off

on

on

T16

off

on

on

T9

off

on

on

% CO2 /ASM

% Below LTO NOx

% DOC+I

+26.70%

-88.18%-78.91%

-17.35%

-16.45%+5.85%

-22.27%-23.40%

+3.49%%

Cha

nge

From

Bas

elin

e

The aspirated seal for the turbine (T16) influences the adiabatic efficiency, which reduces the fuel burn, decreasing the amount of CO2 /ASM produced.



-22.27%-78.91%

-30%

-24%

-18%

-12%

-6%

0%

% R

educ

tion

in C

O2

-100%-90%-80%-70%-60%-50%-40%-30%-20%-10%0%

% R

educ

tion

in N

OX


[email protected]

The Collaborative Visualization Environment (CoVE) A Means to Enable Visual Analytics


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CoVE During a Design Review


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Concluding Remarks

In Summary Elements Needed for the Successful Transition of the Next Generation Aerospace Vehicles:

– Advocacy for the proposed concepts and their associated design approaches. Support to overcome organizational barriers

– Fundamentally sound systems engineering processes tailored to new systems and system of systems formulations

– Practical methods and processes that can handle “Extrapolations” beyond the realm of the historical databases. A physics based approach to design.

– Exploitation of innovative technological breakthroughs

– System level modeling and simulation to assess the technological gaps and to provide guidance, goals, i t t


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Thank you!

For inviting me to speak to you today