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write about one of the articles that’s attached below.you should have everything you need for the assignment done below.
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AEE 4281 Homework 1 Essay Grading Rubric
Student:
Category
3 pts
2 pts
Depth of Coverage -50%
Well chosen subject.
Thorough coverage of
research topic or field of
study. Strong technical
depth. Includes material
from numerous sources.
Mostly thorough.
Lacks detail in some
areas. Or, good
detail but chosen
subject of limited
relevance to
assignment.
Hits main points, but more
detail needed, overly broad.
OR Excessively short, but
on a good subject. OR topic
not very relevant
General description
Cursory or very poor
of topic, but little
description of topic.
depth. OR
Excessively short and No evidence of
vague, and subject of external research.
little relevance
Writing Mechanics -10%
No (or exceedingly
few) grammatical
errors.
Understandable.
Thoughts are
communicated
clearly.
Some grammatical
errors. Text is
understandable, but
maybe unclear in
spots.
Several grammatical
errors. Mostly
Understandable.
Text is disjointed and
words do not flow
naturally.
Many grammatical
errors. Text is too
disjointed or
confusing to be
understandable.
Written Presentation
Quality — 10%
Ideas presented in a
logical and coherent
fashion. Images and
text make topic very
understandable.
Good presentation
format. Requires
some restructuring to Presentation is
better present some understandable, but
ideas. OR Meets
difficult to follow.
criterion for score of
4, but lacks images.
Quality of sources -20%
Includes more than
3citations beyond the Includes several technical
source article, at least citations beyond the source
article, but not any
one of which is
journal/conference paper
journal/conference
paper
Followed format of
using [1] or
superscript numbers
to indicate citations in
body of text. 5%
Did it properly
Numbered citations in Few references given
body, but didn’t use in body, with apparent
omissions
specified format
Citation Format in list
of references 5%
Correctly followed
AIAA citation
guidelines. Few
mistakes/omissions
Several errors or
omissions in
formatting
Comments:
4 pts
2 or more citations
beyond the source,
but none with real
technical depth
1 pt
0 pts
Score
unreadable.
Poor presentation
Minimally acceptable
style. Ideas do not
format. Text is
come across and text
difficult to read and
is unclear. No logical
ideas hard to follow.
flow of thoughts.
1 citation
Information appears
complete, but format Very incomplete
deviates significantly citations
from AIAA guidelines
No citation list, and
unclear from body of
the paper what the
reference were
Didn’t do it at all
No reference list
Total:
0
Grade:
20.0
AEE 4281
Homework #1
Assigned:
Due:
Monday, 8 January
Thursday, 18 January 11:59PM (both sections): Submit soft copy only to the Turnitin drop box in Canvas.
Portions of the article “2023, The Year in Review,” from the December 2023 issue of Aerospace America (the trade magazine published by
AIAA) pertaining to recent developments in aerospace structures and materials are posted with this assignment (AIAA members should be
able to read the entirety of the article on line through their Aerospace America subscriptions).
Read the provided Year in Review article excerpt, and write an essay describing one
of the topics included in the excerpt. Your essay should describe your chosen topic and
provide additional technical detail and context using external sources on that topic.1
Essays must focus on a topic of current interest in the aerospace field that is identified in
this article, and your essays must focus on the subject of materials, structures, and/or
manufacturing 2.
•
•
•
•
Essays should be approximately two pages length, single spaced using 12 pt font. Figures should
be included with the essay, but the page count refers to the written text only.
Provide background material to put the topic in context as appropriate (e.g. Explain the underlying
problem/issue being addressed using external references to explain unfamiliar concepts. What
alternative approaches have been tried? Are other people/organizations addressing similar
problems? What do they do differently?)
You must include and cite relevant technical information not mentioned in the Aerospace America
article.
More credit will be given for essays that include greater technical depth. (Seek technical sources,
not just press releases, newspaper articles, or announcements intended for a general audience).
Additional Requirements:
•
•
While a lot of good information can be obtained from online sources, greater credit will be awarded
for the use of quality technical sources (journal or conference articles, for example) than for
nontechnical sources, or low-quality web search results. The library web site gives access to highquality technical paper search engines through the “Databases/Indexes” tab on its web site
(http://www.lib.fit.edu/, then select the “Databases” link). “Science Direct” and “Scopus” (which
link to many journals and conference papers relevant to engineering) is perhaps the best available
option for engineering topics. Many of the items identified in such searches are available full-text
through the library. Google Scholar is a viable option, too. It is an excellent idea to become familiar
with these search engines and I strongly encourage you to try them out, as they are more focused on
high-quality technical info than general Google searches, etc.
As practice of providing citations in engineering documents, you are required to give complete
citations for all references using the AIAA citation format as shown by example in the AIAA
Note: by a ‘topic,’ I mean one single item that is described on one of the pages of the handout. For example, while the
structural dynamics section on page 14 lists about a dozen different topics within the field of structural dynamics, you might
choose to write your essay on the subject of the TU-Flex aircraft concept, which is described in a single paragraph in the
Aerospace America article. Clearly, you will need to do some additional research to find out more about TU-Flex.
1
2
For example, suppose the topic of the ‘X-57 Maxwell’ aircraft concept is raised. It would not be appropriate to use your essay to primarily
discuss the propulsion system of this all-electric X-plane (though some description of this might be necessary in your essay in order to
provide context). Instead, you could focus on the structural issues of this aircraft –what materials are used? How is the structural design of
this aircraft unique due to its propulsion system?
•
•
•
publication template (following proper citation protocols will count as 10% of the grade 3):
https://www.aiaa.org/publications/journals/reference-style-and-format. You are not required to
include DOI information. Note that this citation format may be different from that which you
followed in humanities courses, and may even be different from the citation format used in the
sources that you cite. To receive full credit for proper citation, you must have at least one source
that is not a simple weblink, but is instead a technical paper from a periodical or proceedings, or is
a technical report or thesis/dissertation, thus demonstrating your ability to follow the required
format. More details are found in a separate document.
Make specific calls to your cited works within the body of the paper using a format similar to the
following example. Do not just list the references at the end in the form of a bibliography. Also,
included citation references in the captions to any figures you include in your paper. Use citation
calls to refer to the source of all information presented in your essay, not just for direct quotations.
Example citation: Jackson et al.1 describe the development of a finite element model to simulate
the drop test of the ACAP helicopter airframe. Note that in this example, the superscript 1 refers to
item number one on the reference list to be found at the end of the paper. Instead of a superscript,
an explicit notation like “Ref. 1 describes the development of a finite element model…” may also
be used. If there is no superscript number within the body of your paper pointing to a reference in
your reference list, then that reference should not appear in the reference list.
IMPORTANT: Do not plagiarize. Use your own words in your essay. Do not simply cut and paste
from web sources or transcribe directly from reference material. Changing a few words to synonyms
is not enough –what you write down must reflect your understanding of the subject. Do not use
unexplained jargon. If you don’t know what something means, don’t include it in your essay (or
better yet, learn what it means and then do include it, including a brief explanation).
Do not let AI tools write the essay for you.
Note: details such as whether the Journal title is italicized or not, the order of the Author’s first and last names/initials, the
sequence of the data, all matter here. The point of this exercise is that just simply cutting and pasting citation calls from
multiple sources is not sufficient, because they are typically formatted differently from one another. Your reference list must
have internally consistent formatting, following the specified guidelines.
3
A E R O S PAC E D E S I G N A N D S TR U C TU R E S
Active materials, adaptive structures
combine to enhance performance of
aerospace systems
BY DARREN J. HARTL AND FRANCIS R. PHILLIPS
The work of the Adaptive Structures Technical Committee
enables aircraft and spacecraft to adapt to changing environmental
conditions and mission objectives.
T
his year, multiple efforts across the community addressed shape-memory materials. A
team at Arizona State University made significant progress in developing shapememory polymer, or SMP, composites with
self-sensing and self-healing capabilities. In July, the
team demonstrated Joule heating in an SMP glass
fiber composite by implementing a conductive
indium-tin oxide coating. In October, the team combined the ITO-enhanced glass fiber composites with
stress-responsive mechanophores to develop an SMP
composite that acted as its own sensor. Developed
with U.S. Office of Naval Research funding, this
novel material will contribute to stronger, safer and
more capable aerospace structures.
Regarding shape-memory alloys, students and
faculty at Texas A&M University continued their
collaboration with NASA’s Langley Research Center
in Virginia. In November, the team began construction
of a wind tunnel model of a structural component
formed from shape-memory alloys designed to significantly reduce noise generated by the slat-wing
interface. The planned testing will involve acoustic
wind tunnel facilities and a custom-built scanning
beamforming array to allow researchers to “see”
noise reductions from these
adaptive structures.
Structural adaptivity without
the use of shape-memory materials also showed new promise
early in the year. In January, researchers from the U.S. Army
Research Laboratory in Maryland flight tested a novel wingstrike alleviation mechanism
that combined classical components with a buckling strip, enabling both wings to sweep back
symmetrically when either wing
impacted an object. For the flight
test, a small drone was flown into
fixed poles, resulting in catastrophic failure of unmodified
wings. When the wing strike alleviation mechanism was incorporated, both wings rotated to
Johns Hopkins University
and the U.S. Army Research
Laboratory conducted
wind tunnel testing of this
bistable actuating wing
mechanism. Visible in this
cross section are the internal
rotary components that drive
leading-edge and trailingedge adaption in changing
flight conditions.
U.S. Army Research Laboratory and
Johns Hopkins University
mitigate impact effects and then returned to their
original position after clearing the obstacle, enabling
recovery and continued flight.
In March, a patent was granted to researchers
from Delft University of Technology in the Netherlands for a system that passively changed the camber
of helicopter blades based on the magnitude of the
centrifugal force, which changes with rotor speed.
The system allows blades to assume the best possible
shape for various fl ight conditions without requiring
additional energy.
In April, the Army Research Laboratory supported researchers from Texas A&M University, the University of Michigan and NextGen Aeronautics of
California in demonstrating a novel automated and
multidisciplinary design framework for the first time.
Given a set of mission-level requirements — such as
mission segments and vehicle speeds — the framework
explored the design space of morphing unoccupied
aerial vehicles with computational fluid dynamics data
to quantify the aerodynamic performance, vehicle
maneuverability and agility capabilities, design space
decomposition to rank adaptivity schemes, and finite
element analyses incorporating pressure fields from
the CFD to quantify the weight penalties of morphing.
The framework was effective in enabling designers to
answer two specific questions: “Does morphing provide
a significant enhancement in performance?” and “What
morphing scheme is most advantageous?”
In October, the Army Research Laboratory hosted researchers from Johns Hopkins University for
wind tunnel testing of a new bistable mechanism for
airfoil leading- and trailing-edge morphing. The
mechanism consists of rotary elements that rotate a
central element by up to 40 degrees. Such a mechanism
enabled the deployment and retraction of both leading-edge slats and trailing-edge flaps for changing
wing performance across diverse fl ight conditions.
aerospaceamerica.aiaa.org
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DECEMBER 2023
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9
A E R O S PAC E D E S I G N A N D S TR U C TU R E S
Computation and AI unlock detailed studies of materials
BY TERRISA DUENAS
The Materials Technical Committee promotes interest, understanding and use of advanced materials in aerospace products
where aerospace systems have a critical dependency on material weight, multifunctionality and lifecycle performance.
Penn State University
researchers created a
machine learning model
to analyze and re-create
the microstructure of a
sample of tricalcium silicate
cement (top left) that was
mixed on the International
Space Station. The cubes
on the bottom row are
3D representations of the
different components of the
cement.
W
Peter Collins, Vishnu Saseendran,
Aleksandra Radlińska and Namiko
Yamamoto
10
|
DECEMBER 2023
hen it comes to researching and developing materials for space travel and
exploration, artificial intelligence is
fast becoming not a luxury but a required
tool. In January, research teams from
the University of Utah and Virginia Commonwealth
University designed a complex carbon nanostructure,
via a machine learning algorithm, with properties
that could match those of desired bulk mechanical
properties. Th is has implications for how machine
learning can assist in the exquisite design of materials that are both structural and can survive in deep
space. To train their algorithm, the researchers started with a convolutional neural network and showed
it various configurations of bundle microstructures.
Th is taught the algorithm to recognize patterns of
material structures suitable for spacecraft construction. They then incorporated this network into a
genetic algorithm that now has the ability t o search
the bundle microstructure “design space” for configurations that optimally achieve target bulk properties.
Finally, they performed three-dimensional finite
element micromechanics analyses of the nanotube
microstructures to yield desirable bulk properties for
operation in space.
Another area where computation is required is
simulating the hy personic speeds and adverse
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aerospaceamerica.aiaa.org
weather conditions that vehicles,
including military aircraft and future
hypersonic craft, will encounter. In
May, research teams from Virginia
Commonwealth University and the
University of Maryland led by Ibrahim Guven and Christoph Brehm
devised a computational approach
to study how rain droplets damage
vehicle surfaces and degrade aerot her mody na m ic per for ma nce.
Their met hod coupled solid mechanics and computational f luid
dynamics to quantify how the material of a vehicle reacts to striking
raindrops, as well as how the shape
of droplets changes when they pass
through a vehicle’s bow shock, depending on the velocity, angle and
ot her cond it ions. T h is met hod,
Peridynamic-CFD Coupling for
Adverse Weather Encounters, could
help builders of hypersonic vehicles assess how
different materials hold up under extreme thermodynamic states without actually having to be in
hypersonic flight.
Elsewhere in materials research, AI helped researchers populate sparse experimental datasets
from tiny samples returned from the International
Space Station. In June, researchers from Pennsylvania State University created a machine learning
model to reconstruct the microstructure of a piece
of hydrated tricalcium silicate cement that was mixed
and cured aboard ISS in 2018. Led by Vishnu Saseendran and Namiko Yamamoto, this AI-assisted reconstruction could help material scientists on Earth
see firsthand how cement cures in zero gravity, which
could influence plans to construct future space habitats and shape future research on properties of
space-made materials. Th is method could also be
applied to any experimental samples returning from
ISS or the study of other materials, including polycrystalline. When used in conjunction with micromechanics-based tools — such as the NASA Multiscale
Analysis Tool, as was the case in this experiment
— materials scientists could study microstructural
characteristics with a much higher resolution than
without these in combination.
Contributors: Ibrahim Guven and Vishnu Saseendran
A E R O S PAC E D E S I G N A N D S TR U C TU R E S
New software and frameworks for optimizing design and development
BY GIUSEPPE CATALDO
The Multidisciplinary Design Optimization Technical Committee provides a forum for those active in development,
application and teaching of a formal design methodology based on the integration of disciplinary analyses and sensitivity
analyses, optimization and artificial intelligence.
T
his year, several areas in the field of multidisciplinary design optimization saw progress both in aeronautical and space applications.
In March, the Multiscale Multiphysics
Design Optimization Laboratory at the University
of California San Diego released ParaLeSTO. Short
for Parallel Level Set Topology Optimization, this code
parallelizes OpenLSTO, both of which are based on
the level set topology optimization method developed
in the lab. It utilizes discrete adjoint sensitivities,
allowing automatic differentiation libraries for complex multifunctional design via topology optimization
with coupled physics. Multiscale topology optimization was extended to consider electrochemistry and
to design the thermal and mechanical load-managing
battery system integration for electrical aircraft. In
addition, multifidelity modeling allowed researchers
to consider material property uncertainties to obtain
a robust topology optimization design within a reasonable computational cost.
In July, Brigham Young University’s Flight, Optimization, and Wind Laboratory released major
updates to the ImplicitAD.jl software package for
automating steady and unsteady adjoints leveraging
forward- and reverse-mode algorithmic differentiation.
Applications include derivatives for a 3D panel code,
an unsteady vortex particle method and an unsteady
geometrically exact beam analysis, conducted with
the U.S. Department of Energy. Starting in September, NASA funding supported additional methodology development, aerospace applications and OpenMDAO integration.
At NASA’s Goddard Space Flight Center in Maryland, a group of researchers in September completed
QUAnT, the Quantification of Uncertainty Analysis
Toolkit. This set of computational tools was designed
to efficiently quantify uncertainty as needed to inform
and guide the design process of complex, large-scale,
multidisciplinary systems throughout their lifecycles.
Based on multifidelity modeling and efficient sampling
techniques, QUAnT demonstrated two-orders-of-magnitude improvements in computational cost for problems related to NASA’s Mars Sample Return program.
In Europe, Airbus continued its work on digital
integration for the European Union’s Horizon 2020
initiative. The company and its partners in February
completed the AGILE 4.0 research project, implementing its digital framework into an Operational
Collaborative Environment. Combining model-based
systems engineering and MDO in a heavily automated workflow, AGILE 4.0 allows for rapid, complex
development with reduced design costs, especially
for aeronautical systems. For instance, Airbus Defence
and Space used the framework to model complex
coupled issues including lightning strikes on a medium-altitude, long-endurance drone.
Throughout the year, Airbus entered research
partnerships on the following projects: The U.K.
Aerospace Technology Institute-funded ONEHeart,
which is studying overall aircraft design and sustainable aviation; the European Union Horizon-funded
Ultra Performance Wing, or UPWing; and the U.K.
government-funded NextWing, which looks at the
design and manufacturing of the next generation of
high-performance transonic wings, with a focus on
structural design, materials and manufacturing. The
aim is by including high-fidelity and contextual operational effects in the early stages of product design,
the companies will develop complementary technology bricks such as semantics and simulation data
management and incorporate real-world event simulation. The research intent is to demonstrate probable concept maturity far earlier in the product design
process. Total funding for the projects exceeds €120
million ($127 million) over the next four years.
Contributors: Nathalie Bartoli, Alicia Kim, Martin
Muir and Andrew Ning
Airbus Defence and Space applied the AGILE 4.0 framework
to model issues including lightning strikes on this design for
a medium-altitude, long-endurance unoccupied aircraft. Blue
represents a low-strength internal electromagnetic field, with
green to orange tones representing higher strengths.
Airbus
aerospaceamerica.aiaa.org
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DECEMBER 2023
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11
A E R O S PAC E D E S I G N A N D S TR U C TU R E S
Rapid aeroelastic testing, metamaterials, and
design and analysis headline the year’s activities
The Non-Deterministic Approaches Technical Committee advances
the art, science and cross-cutting technologies required to advance
aerospace systems with non-deterministic approaches.
BY DANIEL L. CL ARK
Scaled-down models of
aircraft components, such
as the semi-span wing in
this photo, were placed on
a rotary table at WrightPatterson Air Force Base
in Ohio to measure flexing
under various aerodynamic
loads. The researchers
tested models comprised
of different materials and
built via different additive
manufacturing processes to
quantify repeatability and
reduce risk to future test
articles.
I
Air Force Research Laboratory’s
Aerospace Systems Directorate
12
|
DECEMBER 2023
n January, the U.S. Air Force Research Laboratory conducted a risk reduction test in the Parker
Subsonic Research Facility wind tunnel at
Wright-Patterson Air Force Base in Ohio. The test
was part of investigations into rapid vehicle configuration design-to-test aeroelastic phenomena,
such as flutter. The test was also among a series of
fi rsts at AFRL: the fi rst wind tunnel test with both
statically and dynamically aeroelastically scaled
models and the first wind tunnel test using both
noncontact measurement and optimized additively
manufacture models to show rapid-cycle and low-cost
configuration measurement.
In January, researchers from Pennsylvania State
University, the Argonne National Laboratory in Illinois
and Florida State University published their method
of estimating the reliability of complex systems at reduced
costs in the Journal of Computational Physics. Previously, gas turbine blade reliability was estimated via an
expensive high-fidelity model. The researchers applied
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aerospaceamerica.aiaa.org
a multifidelity Gaussian process-based approach to
show that a combination of low- and high-fidelity models can estimate system reliability more accurately and
with up to 50 times reduced computational cost, compared to the high-fidelity model alone.
In February and May, researchers from the University of California, San Diego introduced two
methods to compute risk for structures including
riveted silicon carbide composite plates for highdimensional dependent random inputs (up to 30). Via
surrogate models, they estimated the risk of damage
to a fiber-reinforced composite laminate 20 times
faster than conventional methods.
Also in May, Northrop Grumman air vehicle designers demonstrated the trades of analyzing two Air
Force-relevant configurations with the uncertainty
quantification, or UQ, method. The work was conducted under AFRL’s Enabling Quantification of Uncertainty in Aerospace Technology Evaluation program.
The integration of UQ into multidisciplinary design,
analysis and optimization framework for mission effectiveness highlighted the relationship between
design decisions, uncertainty and design margin.
In July, a computational materials design team at
Virginia Tech’s ASTRO Lab proposed a methodology
to quantify the variations of the structural properties
of cellular mechanical metamaterials as a result of
manufacturing defects. The uncertainty in the resulting mechanical performance was predicted accurately by a surrogate model trained with physics-based
simulation data. The proposed method estimated the
uncertainty affecting a combination of multiple
structural properties. The propagation of this manufacturing-related uncertainty was mathematically
modeled as t he variat ions capt ured by an Ndimensional material properties space.
In September, researchers from NASA’s Langley
Research Center in Virginia completed Technical
Challenge 1 under the agency’s Hypersonic Technology Project. The System-Level Uncertainty Quantification and Validation challenge spanned six years
and had two primary objectives: develop tools and
techniques for assessing uncertainty of complex
hypersonic systems and develop a workforce versed
in UQ practices. Key achievements included development of multiple approaches for efficient UQ, a
novel validation metric for mixed uncertainty, initial
development of a new UQ tool suite and the application of UQ to multiple complex problems related to
hypersonic systems. Members of the challenge team
received a NASA group achievement award, and the
work has generated interest and engagement from
academia and other U.S. government agencies.
Contributors: Pinar Acar, Edwin Forster, Boris
Kramer, Alex Pankonien, Ashwin Renganathan, Tom
West and Laura White
A E R O S PAC E D E S I G N A N D S TR U C TU R E S
Groundbreaking structural dynamics and
aeroelastic tests
BY CRISTINA RISO AND RAFAEL PAL ACIOS
The Structural Dynamics Technical Committee focuses on the interactions
among a host of forces on aircraft, rocket and spacecraft structures.
Researchers from
Politecnico di Milano and the
University of Washington in
February tested this X-DIA
model in a wind tunnel in
Italy to investigate active
flutter suppression.
I
Sergio Ricci/Politecnico di Milano
14
|
DECEMBER 2023
n January, researchers at Sapienza University
of Rome completed the experimental validation
of sloshing nonlinear reduced-order models
for integration into full-scale structural and
aeroelastic analysis tools. The combined effects
of rotation and vertical tank motion on the dissipative behavior of sloshing were characterized for the
fi rst time with Sapienza’s closed-loop control environmental testing device.
Also in January, the Delft University of Technology in the Netherlands and the Israel Institute
of Technolog y conducted the first parametric
flutter margin, or PFM, wind tunnel test on a highly flexible wing. PFM is a novel method for safe experimental identification of f lutter behavior and
prediction of flutter margins via a self-contained
measuring wind-mounted device called a fl utter
pod. The method captured the nonlinear evolution
of the flutter boundary as a function of angle of attack
of a highly flexible high-aspect ratio wing.
In February, researchers tested a pylon-mounted version of t he X-DIA aircraft w ind tunnel
model at the Politecnico di Milano in Italy. In this
FAA-sponsored joint project with the University
of Washington, the researchers investigated the
impact of free play on aeroelastic stabilit y and
active flutter suppression. The test configuration
with a pylon allowed researchers to accurately
cont rol i ncidence a nd sideslip a ng les, wh ich
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aerospaceamerica.aiaa.org
strongly impact limit-cycle oscillations. Due to the
elastic pylon, the model shows two flutter mechanisms — sy mmet ric and ant isy mmet ric w ing
bending and torsion. By actively suppressing the
first mechanism, it was possible to identif y the
second one. Finally, both flutter mechanisms were
controlled, and the model was safely tested at speeds
beyond the second flutter point.
In March, NASA fi nalized the data analysis and
correlation for the dynamic rollout test and wet dress
rehearsal of the Space Launch System, which in
late 2022 launched an unoccupied Orion capsule
for the Artemis I mission. In general, rolling out to
the launchpad produces relatively small structural
loads compared with those experienced during
launch and ascent, but these repeated loads can
progressively cause structural damage or failure. It
is not possible to measure rollout loads while the
rocket is at the launchpad, so NASA engineers applied
operational modal analysis techniques to identify
the modal characteristics of the rollout and wet dress
configurations.
Also in March, AIAA members Peretz Friedmann,
George Lesieutre and Daning Huang published a
graduate-level textbook on structural dynamics as
the 50th volume of the Cambridge Aerospace Series.
The book covers fundamental material in structural dynamics augmented by in-depth treatment of
damping, rotating systems and periodic systems.
In June, the Technical University of Berlin and
the German Aerospace Center’s Institute of Aeroelasticity froze the configuration of a radio-controlled
demonstrator named TU-Flex to study the coupling
among fl ight mechanics, aeroelasticity and controls
for very flexible aircraft. The demonstrator is to have
exchangeable wings, permitting tests of diff erent
levels of f lexibility: a f lexible wing with wingtip
deflections up to 10% of the wing semi-span, and a
very flexible one with wingtip deflections up to 20%,
for which nonlinear aeroelastic effects are expected.
Construction of the fi rst prototype started in July.
Ground vibration and wind tunnel tests are planned
for the end of the year, with fi rst fl ight tests targeted
for 2024.
In July, University of Michigan researchers validated their new technique for conducting ground
vibration tests for very flexible aircraft. By hanging
their flexible aircraft model from a 35-meter-tall crane
via bungee cords, they created a suspension system
with a very low frequency of 0.15 hertz, sufficiently
separated from the aircraft’s natural frequency of
0.95 hertz, to measure its modal parameters.
Contributors: James Akers, Carlos E.S. Cesnik,
Giuliano Coppotelli, Daning Huang, Dexter Johnson,
Teresa Kinney, Russel Parks, Sergio Ricci, Flávio
Silvestre, Jurij Sodja and Francesco Toffol
A E R O S PAC E D E S I G N A N D S TR U C TU R E S
Lighter-weight structures for aircraft and spacecraft continue to proliferate
The Structures Technical Committee works on the development and application of theory, experiment and operation in
the design of aerospace structures.
BY EMILY ARNOLD AND CRAIG MERRETT
I
n March, an ultra-lightweight and low-power sensor
developed by MIT, Metis Design Corp. and Analog
Devices in Massachusetts was installed on a U.S.
Navy destroyer. Comprised of polymer nanocomposites, the 10-gram sensor was designed for structural health monitoring. In August, one of the 25millimeter-long sensors was installed on a U.S. Air
Force F-15. The Air Force evaluated the sensor’s sensitivity to detecting cracks in airframes and found there
was a 90% probability that the design would detect
cracks less than 0.5 mm. An FAA evaluation of the design
for commercial aircraft yielded similar results. Plans
call for Analog Devices to develop a smaller version that
would weigh about 1 gram and be 12.5 mm long.
In June, researchers at Oklahoma State University developed a nonconformal mesh modeling
approach to determine the curved beam design that
would maximize the crit
