Innovations in Aeronautics, Różne lotnicze
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42
nd
AIAA Aerospace Sciences Meeting, January 5-8, 2004, Reno, NV
AIAA 2004-0001
Innovations in Aeronautics
2004 AIAA Dryden Lecture
Ilan Kroo
∗
Stanford University, Stanford, California
Abstract
The first fifty years of aviation were punctuated with
frequent innovations, transforming what were once
daring stunts into an engine of our modern economy.
The second fifty years seems to many, just a tuning of
this engine, with significant, but evolutionary
improvements. This paper considers possible
innovations in aeronautics over the next fifty years and
examines some of the technologies and requirements
that may drive them. Focusing on three examples of
fields in which future innovation appears likely, the
paper suggests that many opportunities exist for
innovation in aeronautics over the next few decades.
Figure 1. Boeing 707 (1954) and A340 (1991)
Introduction
For hundreds of years prior to the advent of human
flight, people dreamed about aeronautics. Numerous
innovative attempts at flight showcased the
participants’ creativity, determination, and lack of
knowledge [1]. With the first truly successful gliders
by Lilienthal [2] in the 1890’s and the first powered
flights by the Wright brothers about 10 years later, the
combination of new technologies, improved
understanding of aerodynamics, and a passion for flight
led to a revolution that changed our world in many
respects. Innovations in aeronautics were numerous
over the subsequent fifty years, from the Wright Flyer
to passenger-carrying aircraft in just a few years, to the
Boeing 367-80, 707 prototype, which flew in 1954.
Figure 2. Product of Mach number and maximum
lift/drag for several commercial aircraft (1960 – 1990).
This apparent lack of innovation has caused some to
suggest that aeronautics is a mature field. One might
attribute the current interest in aeronautical innovation
to the apparent lack of it in recent history, and
irrespective of whether this judgment is correct, many
have raised concerns about the future of the industry and
its ability to attract tomorrow’s innovators [4].
Despite the dramatic innovations over the first fifty
years of air transportation, or perhaps because of them,
modern aircraft appear almost unchanged from their
ancestors (Figure 1). And although the similar
appearance belies a dramatic reduction in fuel usage and
costs, other measures of performance have shown little
change in decades. Figure 2 (data from [3]) illustrates
how the product of Mach number and lift-to-drag ratio
has changed little in the past 40 years. Ref. [4] reports
that door-to-door travel times for flights of 500 miles
or less are 35-80 miles per hour.
The cause of the apparent stagnation in this field has
been attributed to several factors. Some argue that all
of the important breakthroughs were made in the first
50 years of aviation and that the A340 looks like the
707 because the engineers got it right in 1954. Others
argue that the tremendous cost and risk associated with
kroo@stanford.edu
,
Fellow AIAA.
Copyright © 2004 by Ilan Kroo. Published by the American Institute of Aeronautics and Astronautics, Inc., with
permission.
1
American Institute of Aeronautics and Astronautics
∗
Professor, Dept. of Aeronautics and Astronautics, Stanford University,
42
nd
AIAA Aerospace Sciences Meeting, January 5-8, 2004, Reno, NV
AIAA 2004-0001
a new technology makes it difficult to make a business
case for innovation, especially in the field of large
transport aircraft. Christensen [5] notes that “The
highest-performing companies, in fact, are those that…
have well-developed systems for killing off ideas that
their customers don’t want.” And until new ideas are
well-proven, most customers prefer low-risk
incremental improvements.
These three areas include:
1.
Exploiting computational advances for high-
fidelity simulation and multidisciplinary design.
2.
Removing the constraint that aircraft must be
designed around pilots or passengers.
3.
Designing the system rather than the vehicle:
collectives and systems of systems.
The solution to this dilemma – that innovation is too
risky, but its absence may eventually destroy the
industry – may lie in two factors. First, as necessity
motivates invention, the need for significant changes in
air transportation over the next decades may well
inspire innovation. These changes will most likely be
associated with environmental requirements for
dramatically lower noise and emissions or with issues
related to air transport system capacity. Second, the
introduction of new technologies, even in indirectly
related fields, can enable new concepts that may
revolutionize aeronautics.
High Fidelity Simulation and Design
The revolution in computing has, over the past few
decades eclipsed progress in aeronautics. Yet this
revolution has, itself, only begun and has only begun
to be exploited in aeronautics. Researchers in this field
sometimes bemoan the idea that there is no equivalent
of Moore’s Law for aeronautics. Yet, it is precisely
Moore’s Law that may lead to some of the greatest
advances in aeronautics through the use of almost
unimaginable computational capabilities projected in
the next few decades. Bill Joy [7] argues that molecular
electronics may well extend the applicability of
Moore’s observation to 2030 or beyond, leading to
computational capabilities some 10
6
times more
powerful than those of today. Simulations that would
require 1000 years with today’s computers could be
completed in 8 hours.
The purpose of this paper is therefore not to recount a
history of aeronautical innovation, nor to describe the
concept of technology S-curves, how managers might
deal with the innovator’s dilemma, or how a specific
technology, such as nano-scale engineered materials
might affect aircraft performance. Instead it will focus
on three promising and fundamental areas of research
that may drive future innovation. Such innovation will
still depend on future market demand, continued
development of sustaining technologies, and a longer
term vision from industry, government, and academia,
but the next fifty years of aviation may well be as
innovative as the first.
Although researchers at NASA, industry, and academia
succeeded in developing algorithms for solving the
nonlinear equations of fluid flow in the 1970’s and 80’s
and it is sometimes suggested that CFD is no longer a
research field, the use of computational simulation in
many areas is just beginning and promises to
revolutionize the way new aerospace products are
developed. Skeptics note that even rather modern
aircraft benefited little from extensive computational
simulation (although Johnson, et al. [8] cites several
compelling examples of its use in the development of
several commercial aircraft). Examples of current CFD
capabilities include Reynolds-Averaged Navier Stokes
simulations of a Boeing 777 in high-lift configuration,
with detailed geometry including flap tracks and some
30 million nodes in the computational mesh. This
calculation is currently completed in as little as a week
[9]. Current capabilities permit drag computation of
wing/body/nacelle/pylon configurations to within +/-
2% to 4% [10]. Evolving capabilities under
development as part of the ASCII program [11] will
soon permit complete unsteady modeling of internal
engine flows, including compressor, combustor, and
turbine stages with fuel spray modeling and
subproduction, utilizing LES in the combustor
simulation.
Three Technology Areas that May Drive
Future Aeronautics Innovation
Just as a history of aeronautical innovation would
require volumes, not pages, a prediction of possible
future aeronautical ideas would be hopelessly ambitious
and most surely wrong -- as Wired [6] declares in its
Dec. 2003 edition, ‘Futurism Is Dead.’ Rather, three
general areas that may lead to new concepts of use in
aeronautics are described as examples to motivate the
idea that aeronautics is hardly a mature endeavor.
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42
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AIAA Aerospace Sciences Meeting, January 5-8, 2004, Reno, NV
AIAA 2004-0001
The next few decades will bring even higher fidelity
simulations for cases involving unsteady flows, fluid-
structures-controls coupling, large scale separation, and
laminar-turbulent transition. Dynamic simulations of
complete vehicles, including nonlinear, time-domain,
6+ DOF may include much-improved aerodynamic,
propulsion, and structural models and the impact of
these systems on the environment may be evaluated
with a level of detail that is impossible with current
tools.
application is especially difficult because of the need to
capture accurate pressures some distance from the
vehicle and taxes current CFD capabilities.
The quest for efficient supersonic flight utilizing
extensive laminar flow is similarly challenging, relying
on nonlinear CFD computations, boundary layer
modeling, and transition estimation, again taxing the
capabilities of simulation tools and requiring flight
confirmation.
The development of such a capability may have a direct
effect on future innovation by reducing the risk
associated with new ideas that exploit complex
phenomena. This is especially important when
experiments that might provide new insight or
validation would be very expensive. Two recent
examples of this, which have utilized newly developed
computational simulation tools and which would
benefit greatly from further simulation capabilities, are
DARPA’s Shaped-Supersonic Boom Demonstration
[12], and recent designs exploiting supersonic natural
laminar flow [13].
In the SSBD program, a modified F-5 was used to
demonstrate the idea that a supersonic airplane ground
signature might be to significantly reduce its loudness.
This concept was suggested by Seabass and George
[14] early in the development of supersonic
aerodynamics and propagation theory, but the role of
certain nonlinear effects on signature development and
the influence of real atmospheric characteristics on this
type of signature were uncertain.
Figure 4. Computed amplification factors on
supersonic test wing (left). Infrared image of test wing
showing turbulent areas in white (right). F-15B with
test wing mounted below (top).
Figure 3. Pressure fields associated with baseline F5
and version modified to produce desired signature.
(From [12]).
Perhaps the most useful application of expanded
computing power is the extension of computational
simulation from analysis to design. This field,
starting with single-discipline optimization and inverse
design, has grown to include multidisciplinary
optimization as well as distributed, multiobjective,
and topological design. At the moment, most high
fidelity optimization is used to refine a configuration
that has been defined using simpler but more
comprehensive analyses or design intuition, but as
computing power increases, these tools will be used
more at the conceptual design phase, leading to the
possibility of innovative conceptual solutions that
appear from the optimization automatically. This type
of emergent innovation is suggested in some recent
Flight tests of a supersonic aircraft, even one that
represents a modification of an existing design, are very
costly and correct modeling is essential to ensure a
successful flight program. The analysis for this
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42
nd
AIAA Aerospace Sciences Meeting, January 5-8, 2004, Reno, NV
AIAA 2004-0001
examples that illustrate how unexpected fundamental
concepts can arise from robust configuration
optimization. Figure 5 shows the computational grid
defining a blended-wing-body design. This
configuration was optimized using a Navier-Stokes
simulation together with propulsion modeling to
investigate propulsion/airframe interactions [15].
minimum total drag, yet fit inside a box of fixed
height and span. Although the analysis was
simplified, interesting and somewhat surprising results
emerged and the idea was subsequently incorporated in
the design of a very large airplane concept (figure 8)
[16].
Figure 5. RANS-based Optimization of BWB
Optimization was also used to determine the maximum
allowable thickness of the wing center section. As
shown in figure 6, the center section can maintain weak
shocks and low transonic drag, despite the freestream
Mach number of 0.85 and an 18% thickness to chord
ratio. This dramatic 3-D effect was not envisioned in
the initial conceptual design of the BWB and permits
configurations that might have been overlooked if 3-D
nonlinear design tools were not available.
Figure 7. Evolution of C-Wing design from generic
nonplanar wing model.
Figure 8. C-Wing transport aircraft concept [Boeing].
Figure 6. Blended Wing Body Cp Distribution (from
[15]).
The utility of robust optimization methods, such as
simulated annealing or genetic algorithms, which are
generally much less efficient than traditional gradient-
based optimization algorithms, improves as
computational resources become more capable. By
avoiding some local minima, not requiring smooth
Another example of unexpected results appearing from
topological optimization is summarized in figure 7. In
this work, an evolutionary optimization algorithm was
used to find the wing geometry that produced
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42
nd
AIAA Aerospace Sciences Meeting, January 5-8, 2004, Reno, NV
AIAA 2004-0001
functions, and easily supporting large parallel
computing environments, such approaches may find
expanding applications in future conceptual designs.
These methods are particularly well suited to
topological and multi-objective design and have been
applied successfully for quiet supersonic aircraft design
problems using both Euler and linear analysis methods
[17, 18].
Figure 9. Artist’s concept of ARES rocket-powered
UAV for Mars exploration.
The use of autonomous aircraft for exploration of
planets such as Mars or Titan is appealing, allowing
high resolution imagery and
in situ
measurements of
atmospheric and magnetic properties over a large region
and bridging the scale and resolution measurement
gaps between global-scale orbiters and higher
resolution landers or rovers. As sensor and flight
control electronics become smaller, the cost of such
systems is dramatically reduced. In this program, the
ability to reduce the aircraft scale was also exploited in
the design and successful flight test of a subscale
aircraft, dropped from a balloon at about 100,000 ft.
The resulting data provided valuable insight on the
vehicle aerodynamics, wing folding mechanization, and
drogue chute dynamics.
Figure 8. Multiobjective (boom and drag) optimization
of a small supersonic aircraft using a genetic algorithm.
It is sometimes imagined that the revolution in digital
electronics occurred in the 1970’s and that continued
advances simply improve performance incrementally.
Yet advances in microprocessors and surface-mount
components just over the past few years have enabled
inexpensive autopilots with masses measures in grams
rather than kilograms. As an example of how this
technology is changing aircraft capabilities, students in
the aircraft design course at Stanford were challenged to
design a small, low cost, fully autonomous aircraft
using GPS navigation. Figure 10 illustrates the
successful design, which weighed less than 300 g and
was developed over the past 3 months.
Man is (No Longer) the Measure of All
Things Aeronautical
Continued advances in computation and electronics
may have a more dramatic impact on aeronautics as
automated systems replace pilots on an increasing
number of aerospace platforms. While this might, at
some time, be used to reduce the operating costs of
cargo aircraft or eventually, perhaps, other transport
aircraft, its more significant effect may be in enabling
new roles for aircraft. With the fielding of military
UAV’s, aircraft are being used for reconnaissance and
surveillance in situations, and for mission durations,
incompatible with piloted airplanes. A more extreme
example of how UAV’s may be used in the future to
expand the role of aeronautics is seen in the recent
development of the ARES aircraft (Aerial Regional-
scale Environmental Survey) for Martian exploration
[19].
Figure 10. Autonomous electric aircraft developed in a
few months using a 12g GPS unit, with airframe and
flight software designed by the students.
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