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1Corresponding Author 1 Copyright © 2010 by ASME
Proceedings of the ASME 2010 International Design Engineering Technical Conferences &
Computers and Information in Engineering Conference
IDETC/CIE 2010
August 15-18, 2010, Montreal, Quebec, Canada
DETC2010-28817
THE INCREDIBLE EGG: INVESTIGATING THE DESIGN EDUCATION CHALLENGES
AND COMPLEXITY OF THE EGG DROP PROJECT
Scott Ferguson1
Assistant Professor North Carolina State University, Raleigh, NC
scott_ferguson@ncsu.edu (919) 515-5231
Heidi Klumpe Undergraduate Research Assistant
North Carolina State University keklumpe@ncsu.edu
John Turner Undergraduate Research Assistant
North Carolina State University jmturne2@ncsu.edu
ABSTRACT Designing a system that will protect an egg dropped from a
predefined height is a common experience for many K-12
students and undergraduates in engineering. Often presented in
the context of the scientific method, results from these
experiments are used to teach concepts of impulse, acceleration,
and impact modeling. When done in the classroom, students
are usually given a box of pre-defined supplies and a small time
frame with which to complete the design. But what educational
challenges and outcomes can be gathered from this experience
when the problem is tackled using the systematic design
process? In this paper, outcomes from the various steps of the
design process conducted over a six-week research project by
two high school students are presented. Results include the
generation of a requirements list, the creation of a functional
model, results of brainstorming sessions, concept analysis,
model validation through experimentation, optimization, and
final design testing. Challenges faced during each step of the
design process, and the surprising complexity of the problem,
are also discussed. Additionally, the challenges associated with
teaching design principles to high school students for a
multidisciplinary and multiobjective problem are addressed.
1. INTRODUCTION The egg drop project is an experience shared by almost all
K-12 and engineering students. Results from this experiment
are often used to teach concepts of gravity, impulse,
acceleration, and rudimentary impact modeling. Motivation for
using this project in K-12 education is the desire to help
promote better differentiation between science and technology.
By using concepts already familiar to students – everyone has
dropped and broken something, at least once – and
incorporating concepts associated with problem solving and
design, a better understanding for the role of technology in
society is developed. For students in grades 5-8, it is suggested
that activities be constructed such that “only a few well-defined
ways to solve the problem” are involved. To accomplish this,
multiple constraints are often imbedded into the problem.
However, these constraints can be relaxed for students in grades
9-12. The following outcomes and assessment criteria are
suggested by the National Science Education Standards these
students in the area of technical design [1, p. 192]:
Identify a product or design an opportunity: Students
should be able to identify new problems or needs and
to change and improve current technological design.
Propose designs and choose between alternative
solutions: Students should demonstrate thoughtful
planning for a piece of technology or technique.
Students should be introduced to the roles of models
and simulations in these processes.
Implement a proposed solution: A variety of skills can
be needed in proposing a solution depending on the
type of technology that is involved. The construction
of artifacts can require the skills of cutting, shaping,
treating, and joining common materials - such as
wood, metal, plastics, and textiles. Solutions can also
be implemented using computer software.
Evaluate the solution and its consequences: Students
should test any solution against the needs and criteria it
was designed to meet. At this stage, new criteria not
originally considered may be reviewed.
Communicate the problem, process, and solution:
Students should present their results to students,
teachers, and others in a variety of ways, such as
2 Copyright © 2010 by ASME
orally, in writing, and in other forms – including
models, diagrams, and demonstrations.
These outcomes are in addition to those originally defined for
students in grades 5-8. One item of note from this category is
specifically discussed in the context of the egg drop: [1, p.164]
Assessment activity: Following the egg drop activity,
students each prepare a report on one thing they
propose in order to improve their team's container and
how they would test the effectiveness of their
improvement.
To maintain a limited number of solutions, and minimize
budgetary impacts, the egg drop problem is typically
constrained by limiting students to a set of pre-specified
materials with which to complete their design. When conducted
in a classroom setting, time constraints also play a significant
role in shaping the outcomes associated with this experience.
But what happens when material and time constraints are
removed, or at least relaxed?
In this paper, the outcomes from two high school seniors
(now freshman undergraduates) following a systematic design
process conducted over a six-week research project are
presented. Results from this approach include the generation of
a requirements list, the creation of a functional model, results of
brainstorming sessions, concept analysis, model creation
through experimentation, optimization, and final design testing.
For each step of the design process, the challenges faced – from
both an education and application perspective – are discussed.
Additionally, insights into the additional problem complexity
when material and time constraints are relaxed are presented.
The outline of this paper is as follows. Section 2 describes
the motivation for introducing the students to a systematic
approach to engineering design, and discusses the major steps
of the design process. The results generated from the planning
stage of the design process are presented in Section 3, along
with student reflections and an assessment of the result with
respect to the National Science Education Standards. Similar
outcomes are then discussed with respect to the conceptual,
embodiment, and detailed design phases in Sections 4-6.
Finally, conclusions are presented in Section 7.
2. ADOPTING A SYSTEMATIC APPROACH TO
ENGINEERING DESIGN Conducting a Google search for references to the „egg drop
project‟ reveals 6.58 million results, with multiple high school
and university websites that discuss concept ideas, materials
lists, rules, and assessment criteria [2-4]. It is interesting to
note, however, that design assessment is almost always binary:
did the egg break – yes or no? While students are typically
evaluated on multiple criteria like weight, cost and success,
rarely does it seem that a true understanding of how close a
system was to success or failure is ever attained. Instead, it
often seems that students are making design decisions with
regards to performance criteria without comprehensive or
accurate predictions of system performance. Such decisions, or
conclusions on product architecture, appear to be more inquiry-
based in nature. That is, the students do not always know how
the system will perform until after the final result is observed.
One approach to gathering information that students are
introduced to early in their education is the scientific method.
The scientific method, as an approach, focuses on rigorous data
collection, with information being the resultant outcome.
However, when the desired output is more than information, a
design process is required. As defined by the Accreditation
Board for Engineering and Technology, engineering design is:
“. . . a decision-making process (often iterative), in
which the basic sciences, mathematics, and the
engineering sciences are applied to convert resources
optimally to meet these stated needs. [5]”
Thus, a design process focuses on rigorous information
synthesis as a means of developing a final product.
Regardless of the design process model followed [6-10] it
is well established that successful process navigation
necessitates the understanding of the interconnected (although
sometimes unexpected) relationships between subsystems and
components. According to the systematic design approach
proposed by Pahl et al. [6], the fundamental elements of design
include: planning and task clarification, conceptual design,
embodiment design, and detailed design. In conceptual design,
a designer searches for working principles and develops
concept variants. After these variant designs have been
evaluated against technical and economic criteria, a principle
solution is established. Embodiment design then builds upon
this principle solution through the selection of material and
form, validating the performance of the product through a series
of calculations and simulations. The form of this procedure is
similar to approaches proposed by Dewey [11], who suggested
that the problem-solving process consists of defining the
problem, identifying the alternatives, and selecting the best
alternative. Osborn [12] has further enforced this notion,
stating that problem solving involves fact finding, idea finding,
and solution finding.
For this project, two students were instructed to follow the
systematic approach to engineering design as described by Pahl
et al. [6]. This design process was chosen in particular because
of its wide acceptance within the engineering design community
and because the inputs and outputs associated with each step are
clearly defined. This was viewed as particularly important for
students who were getting their first exposure to regimented
instruction on engineering design principles. Additionally, this
design approach embraces the idea of establishing function
structure before establishing the physical form and layout of the
design. Given the motivation of exploring the consequence of
removing material and time constraints from the egg drop
problem, creating a functional model was considered a useful
endeavor to prevent user-implied constraints associated with
form and function.
3 Copyright © 2010 by ASME
The next section introduces the results obtained from the
first step of the design process: planning and clarifying the task.
For each step of the design process, this paper will discuss the
results generated for each task, student reflections and
assessment of results with respect to the National Science
Education Standards introduced in Section 1.
3. PLANNING AND CLARIFYING THE TASK The first task of the design process is to identify the design
objectives, and specify the properties that the design must have
or not have. The objective, inputs and outputs of this task are:
Task objective: Collect information about requirements
and identify constraints
Task input(s): Customer needs
Marketing information
Task output(s): Requirements list (demands and wishes)
Product proposal
For this project, the supervisor served as the customer. The
background supplied to the students was that they were required
to design a system that could protect one-dozen eggs being
dropped from a height somewhere between 25 and 40 feet.
They were told that the eggs were symbolic of medical supplies
being dropped from a hovering helicopter, and as such would
have a negligible initial horizontal velocity. Modifications to
the eggs were not permitted, nor could the system be a danger
to the user or anyone on the ground (unless they were standing
directly under the system at the point of impact). Remaining
demands and wants that needed to be defined were left to the
students to extrapolate from conversations with the customer
over the six-week period, or set to ensure “market
competitiveness”. The finalized product demands established
by the students are shown in Table 1.
Product demands
No egg modification allowed
System must carry 12 eggs
System cannot be volatile or hazardous
Survive falls between 25 and 40 feet
90% survival rate of cargo
Reusable
Straight drop (i.e. from hovering helicopter)
Table 1. List of product demands
Many of the product demands established by the students
came directly from the foundational story they were given as
motivation for the project. While mostly straightforward, one
interesting result was that they specifically defined a 90%
survival rate of the cargo. When asked about this, they
explained that a decision had been made to quantify
acceptability as 11 out of 12 eggs surviving on average. They
noted that improper packaging, manufacturing defects, and
other uncertain variables could prevent a 100% success rate
from being achieved across multiple drops.
„Wishes‟, or requirements that are taken into account
whenever possible, were also developed. As shown in Table 2,
these requirements were arranged from greatest to least
importance. The students felt that given the vagueness of the
problem statement supplied, there was not enough evidence to
make them absolute demands. Instead, they developed this list
as targets and criteria that they would like to achieve so long as
it did not affect mission success.
Product wants (most to least)
Cheap (minimum cost)
Able to withstand non-flat landing
Biodegradable / green materials
Waterproof / ability to float
Common components
Redundancy
Able to withstand initial horizontal velocity
Table 2. List of product wants
The desire to minimize cost and withstand a non-flat
landing both appeared as obvious „wants‟ for the designed
system. An unexpected outcome was the appearance of
biodegradability or the use of green materials. When asked for
insight into their thought process, it was revealed that Ms.
Klumpe was a proponent of, and interested in, green and
sustainable systems. Furthermore, the „want‟ related to
„common components‟ was an artifact of a discussion with the
students regarding research into product platforming [13-14].
Throughout the course of the project, the original
requirements list was slightly refined. A significant change to
product demands came in the form of more detailed definitions
of product failure. Under this new definition, failure of an egg
was now considered across three criteria:
1. More than one crack (includes "spider web" cracks)
2. Lengthwise crack longer than half egg length, or
width-wise crack one quarter the circumference
3. Leaked fluid/damaged yolk sac
In assessing the requirements list, and discussing the
process with the students, it was clear that a major hurdle they
faced was assigning the different requirements to an individual
designer. They felt that they did not know enough about the
structure of the system to make that determination at this phase
of the design process. Pahl et al. [6, p.157] also note that it is
common for factors like low-cost production and reusability to
be accidently left off a requirements list because it is an
assumed requirement. While these factors were included in
Table 1 and 2, it is significant to note that ease of assembly and
quick turn-around time did not make these lists. In discussing
the end product with the students, both strongly felt that these
factors were important elements of their design, but were not
explicitly incorporated into the requirements list.
4 Copyright © 2010 by ASME
Overall, the students successfully completed the assessment
criteria of „identifying a product or designing an opportunity‟.
No major product demands were ignored, and sufficient insight
was developed to progress to the conceptual design phase.
Student feedback about this phase of the design process
commented on how when first making the requirements list, it is
easy to define what you think needs to happen, but in reality the
process is much more complex. Additionally, it was felt that the
least important „wishes‟ were too hard to incorporate into the
system for the first generation of the design. They believed that
with additional redesigns, it would be possible to account for
these additional criteria.
Having identified the requirements of the product, the next
step in the design process is arriving at a conceptual design.
This is the focus of the next section.
4. CONCEPTUAL DESIGN Understanding the requirements that the system must meet
allows a designer to begin the search for a working concept.
This is completed by translating consumer demands into the
engineer‟s language of potential problem and solutions.
Research and brainstorming are used to establish system
functionality and define principles that meet this function. The
objective, inputs and outputs of the conceptual design phase
are:
Task objective: Arrive at a principle solution
Task input(s): Requirements list
Task output(s): Function structures
Working principles
Concept variants
The first challenge the students faced in the conceptual
design process was extracting generalized functional
requirements from the requirements list. To help the students
arrive at a generalized functional mode, two afternoons were
spent discussing the notion of functional modeling [9, 15].
Functional modeling is a technique that uses a common design
language to model the functionality of a product or process. A
black box model of the system is created using verb-noun pairs
to yield functional chains. These functional chains present a
designer with information regarding where system interactions
exist and what inputs and outputs are required of each
functional block.
Three principle functions of the system were defined:
1. Slow down fall (decrease Vf)
2. Cushion/support eggs (energy-absorbing insulation)
3. Extend impact time/absorb impact (crush zones,
airbags, etc.)
4.1 ESTABLISHING FUNCTION STRUCTURES Attempts at constructing functional models by both
students are shown in Appendix A in Figures A.1 and A.2.
Examining Figure A.1, the upper level functionality that was
defined includes:
Dissipate kinetic energy (KE)
Minimize impact force
Hit target accurately
Load / remove cargo easily
Maintain reusability
Stabilize system (in flight)
Withstand dynamic conditions
The number of higher-order functions associated with this
system speaks toward the complexity inherent in egg drop
projects when constraints are relaxed. Impact problems like
this require concepts associated with energy, linear momentum
and constitutive models. Students must dissipate the kinetic
energy of the egg at impact by using principles of work to exert
a force on the “insulating materials” over some distance. From
a momentum perspective, the velocity at impact must be
dissipated to remove all momentum, requiring a larger impact
time to reduce the magnitude of the force.
At the K-12 level, many teachers will establish constraints
that prevent parachute-like items from being used to reduce the
size of the solution space. However, from a functionality
standpoint, this would not remove the higher-order functions of
„Withstand dynamic conditions‟ and „Dissipate KE‟, as other
feasible solutions could be generated to achieve the same
functionality. The complexity of the problem is also seen when
investigating „Minimize impact force‟. Here, the student
defined two lower level functions, „Maximize t‟ and
„Minimize F‟ from the impact equation of:
t
mvF
(1)
In Figure A.1, basic solution principles are defined for each
lower-level function. In trying to maximize the impact time, the
student suggests attaching a malleable surface or collapsing a
section of the system. To minimize the force at impact, the
student suggests adding insulation, a large base, modifying the
orientation of the egg, and adding a suspension system.
The functional model created in Figure A.2 doesn‟t follow
standard convention of verb-noun pairs, instead attempting to
define independent variables, considered attributes, and
potential attribute groupings in as generalized a manner as
possible. This model acts as more of a combination of
functional model and requirements list, in that it accounts for
the cost of the eggs and environmental friendliness. However,
there are some aspects of this model that do establish
generalized functionality, providing some value.
Discussing the functional modeling process with the
students after the project was completed revealed that they were
generally happy with the outcome of the process. They
believed that creating a generalized functional model helped
decompose the problem into smaller, more manageable
5 Copyright © 2010 by ASME
components. Feedback was provided that functional modeling
helped with the brainstorming process, as it was easier to tie
product components together to achieve desired results.
Creating a functional model for a product can be a
significant challenge, even for a designer with prior experience.
A main challenge that often arises is when the size and
complexity of the model becomes overwhelming even for the
most rudimentary product. However, the feedback from this
project tended to look favorably upon the experience, even if
the model was not generated correctly. The information and
understanding gained from this process proved to be something
that the students would refer to throughout their six-week
project as they considered possible configuration changes.
4.2 SEARCHING FOR WORKING PRINCIPLES Having developed a generalized function structure, the next
step of the process was to search for working principles that
provided desired functionality. To facilitate idea generation, the
6-3-5 method of brainstorming [6, p.85] was used in a weekly
lab meeting. The two students worked in conjunction with 4
graduate students who are part of the System Design
Optimization Laboratory at NC State. To complete the 6-3-5
method, each student created 3 unique concepts, using
sketching, labels, and phrases to illustrate their idea. After a
pre-determined amount of time, each student passed the sheet of
paper in front of them clockwise. Each student then added
additional details to the three new concepts in front of them,
with the restriction that nothing could be removed from the
design. This process resulted in 18 designs, with a subset of
those results shown in Figure 1.
Many of the results from the brainstorming session
provided concepts that were realistically infeasible. All
students involved in the brainstorming process, however, had
positive comments about the experience. Ms. Klumpe also
recently mentioned that she taught her group members this
brainstorming process for a project in E101 at NC State. It was
also considered beneficial to set aside a specific block of time
for the sole purpose of brainstorming. Comments were made
that while students often have the intention to go through a
brainstorming procedure, it is commonly overlooked or pushed
aside in the interest of “getting to building more quickly”.
While the results of the brainstorming session did provide
mostly infeasible or impractical concepts, the overall trend
provided insight into the final principle solution. This is
discussed in the next section.
Figure 1. Results of 6-3-5 method of brainstorming
4.3 PRINCIPLE SOLUTION AND ASSESSMENT After analyzing the trends in the result obtained from the
brainstorming session, the students defined a principle solution
as shown in Figure 2. Arriving at this decision in the conceptual
design process was aided by analyzing the results of the
brainstorming session using rudimentary technical and
economic criteria. The requirement of using these criteria at
each phase of the design process is another reason why the Pahl
et al. [6] approach to engineering design was selected.
After considering the technological need and economic
impact of the different variant solutions, the students worked
together to establish a principle solution that took the strongest
elements from the possible solution set. It is interesting to note
that while the principle solution is by no means a unique or
Insulation
Crush Zone
Egg
Parachute
or
Accelerometer
Figure 2. Resultant principle concept
6 Copyright © 2010 by ASME
novel solution, the procedure by which they arrived here was
well documented and allowed them to validate their decision-
making process.
By this stage of the design process, the students had begun
to consolidate their ideas and choose between alternative
solutions. While these decisions were made at the very highest
level of product form, they were facilitated by evaluating
possible functionalities against technical and economic criteria.
This approach is significantly different than a “tinker-toy”
approach to product design. Now that a principle solution has
been developed, attention turned to giving it physical form.
This is the focus of the next section.
5. EMBODIMENT DESIGN The goal in embodiment design is to develop the solution
principle to a point where it can be prototyped, tested, and
manufactured. This is also the most difficult part of the
engineering design process for students because it requires a
culmination of their engineering education. It is at this step that
students must combine abilities in architecture determination /
component selection, model building, engineering analysis,
prototyping, and experimentation to arrive at a definitive layout.
This layout develops the system to a point where “a clear
check of function, durability, production, assembly, operation,
and costs can be carried out [6, p. 227]”. The objective, inputs
and outputs of the conceptual design phase are:
Task objective: Arrive at a definitive layout
Task input(s): Principle concept
Task output(s): Preliminary layouts
Analysis of proposed concepts
Optimization of design
Final layout
To successfully arrive at a definitive layout, the next step of
the project was to define the arrangement of the system from a
spatial perspective and determine component shape and
material. However, to validate the final configuration it was
necessary to iterate between periods of analysis and synthesis.
The first phase of this approach involved specifying the design
variables, constraints, and objective functions associated with
the problem.
The design variables associated with the proposed solution
principle are shown in Table 3. For each major component
(egg, insulation, etc.) there are multiple design variables that
must be defined. For example, while the students were told that
large eggs would be supplied for experimentation and testing,
no comment was made about the color of the supplied egg.
Therefore, one decision the students had to make was whether
they should choose a brown egg or a white egg – a binary
choice. In addition to egg color, the students also had to make
an integer-based decision regarding the orientation of the egg
(pointed side down, pointed side up, egg sideways), and the
location of the egg in the container (x, y coordinates as
continuous variables).
Similar decisions had to be made for other components as
well. For instance, when determining insulation the design
variables include: material, material thickness, volume of the
material in total, and whether insulation should be included in
the design. When considering 12 eggs, there are technically 72
different design variables that must be accounted for. If only
one egg was to be placed in the system, 28 design variables
would still be needed to define the problem. Additionally, for
the manner in which the problem was described there are 2
specific constraints, as shown in Table 4.
Component Design variable Type
Egg (x12) Color (brown or white) Binary
Orientation Integer
Location in container (x, y) Continuous
Insulation Material Integer
Material thickness Discrete
Volume (x, y, z) Continuous
On / Off Binary
Parachute Shape Integer
Volume (x, y, z) Continuous
Material Integer
Material thickness Discrete
On / Off Binary
Crush zone Number of components Integer
Material Integer
Material thickness Discrete
Area (x, y) Continuous
On / Off Binary
Container Length Discrete
Width Discrete
Height Discrete
Material Integer
Material thickness Discrete
Table 3. Component design variables and variable type
Constraint
11 of 12 eggs must survive each drop
Eggs and insulation must fit within container
Table 4. Problem constraints
From an optimization standpoint, there are six design
objectives that can represent the problem. These objectives are
shown in Table 5. Here, three objectives are to be minimized
(cost, weight, size) while three objectives are to be maximized
(survivability of eggs, repeatability, reusability). Furthermore,
this is a mixed-variable optimization problem whose solution
requires an understanding of multiobjective optimization.
7 Copyright © 2010 by ASME
Objective function Goal
Cost Minimize
Weight Minimize
Size Minimize
Survivability of eggs Maximize
Repeatability Maximize
Reusability of system Maximize
Table 5. Objective functions
5.1 INITIAL MODEL DEVELOPMENT FOR INSULATION Understanding the design variables associated with the
problem, however, is only one element of the overall puzzle.
Without models to evaluate the performance of different
configurations, ensuring product success is nearly impossible.
To begin the process of model development, the students first
turned their attention to the primary component of this project –
the egg. The first question to answer about the egg was how
much impact force was required to produce egg failure as
defined in Section 3.
An experimental study was performed to determine the
significance of two design variables associated with the egg:
color and orientation. Eggs were dropped from various heights
onto a paved parking lot (similar in texture to the ground used
for final product testing) using a full factorial experiment. As
shown in the results in Table 6, the pointed end of an egg is
most able to withstand the greatest force before failing.
Additionally, brown eggs were found to be slightly stronger
than white eggs. Not shown in this table is that an egg turned
on its side was found to crack at significantly smaller heights,
which was an expected result.
Egg color Orientation Average height of
failure (cm)
Brown Pointed end 3.75
Brown Rounded end 2
White Pointed end 3.6
White Rounded end 2
Table 6. Average failure height of unprotected egg
In addition to determining the average height of failure for
an unprotected egg, this experiment also allowed for the
estimation of impact time. References were found that the
pointed end of an egg was able to withstand 50 Newtons of
force, on average [16-17]. Using the mass of an unprotected
egg with energy and momentum equations resulted in an impact
time of 0.002 seconds to be calculated. This result was then
used as an estimated starting point for prototype system testing.
Developing an analytical or experimental model to predict
the performance of different insulations proved to be a greater
challenge. Despite numerous research attempts it was
concluded that material and performance properties for
household items – such as bubble wrap, Cheerios, and
Styrofoam – were not readily available. Insulation materials
studied during the course of this experiment included:
Jell-o
Cornstarch and water
Styrofoam
Cheerios
Bubble-wrap
Shredded paper
The objective of these tests was to quantify the energy / work
absorbed by different thicknesses of each material.
The first experiment designed to capture these properties
used a three-egg container dropped at 1-foot intervals. The
maximum drop height of the apparatus was 17 feet. In setting
up this experiment, insulation was placed only on the bottom of
the container, an assumption that worked well for drops from
low heights. As the drop distance increased, the container had a
tendency to tumble on impact, making it difficult to determine
which forces caused egg breakage.
To reduce the error associated with testing, the students
developed a guide-wire system to control the motion of the
container during free-fall in an effort to reduce the uncertainty
associated with force direction on impact. As shown in Figure
3, the system was constructed out of two wooden boards,
fishing line (low friction), and eyelet screws. The line length
was designed to be adaptable to reduce the overhead associated
with testing at various heights, and was secured to provide
consistent tension. The bottom board was later secured to the
ground as initial tests saw this board bouncing on impact.
Reel of
Fishing Line
Egg
Insulation
Rubber mat to increase ? t (improve
accelerometer readings)
Figure 3. Initial test rig for insulation property
determination
Student feedback regarding their testing system noted the
fixed height of the system sometimes prevented egg breakage.
To solve this issue, very thin metal plates, weighing 216 and
244 grams respectively, were added to the container with the
hope of increasing impact force. Also, when resetting the
system, thin plastic straws that were added to the container to
guide the system would get damaged by the taut fishing wire.
This made the straws more susceptible to catching, resulting in
increased friction. Finally, a major complaint was the time-
8 Copyright © 2010 by ASME
consuming nature of set-up, especially after an egg broke within
the container.
5.2 INSULATION MODEL USING AN IMPACT
ACCELEROMETER The lengthy set-up time associated with cleaning up and
replacing eggs that broke during testing led to a desire for a
more robust solution. The USB Impact X250-1 data logger was
purchased from Gulf Coast Data Concepts [18] to measure the
acceleration of the system for various insulation materials and
thicknesses. This system was capable of measuring +/- 250g in
all 3-axes, had an internal battery, and interfaced with a
standard PC using a USB port.
Given the size of the accelerometer (4” x 1” x 1”), the egg
was removed from the test rig and the accelerometer was
secured in the container‟s egg cavity. The height of the
accelerometer left room for insulation only on the container‟s
bottom and sides. Data collection was now more efficient, but
some technical issues needed to be addressed before the data
could be validated. Some of these issues included that:
the amplitude of the noise could be one or two g‟s
the accelerometer had to be zeroed correctly before
each run
the device needed to be secured to ensure readings
along a single axis to prevent confounding
During accelerometer testing, the sensor occasionally
reached its upper limit for certain design configurations. A
rubber mat was added to extend the impact time. Plans were
then made to establish the quantitative effect of the mat on the
observed acceleration. However, the mat failed to significantly
alter the results and was removed to ensure consistency.
Experimental results using the impact accelerometer when
0.25”-thick Bubble wrap was used as the insulating material is
shown in Figure 4.
Figure 4. Accelerometer data for
0.25”-thick Bubble wrap as insulation
Results from the accelerometer provided insight into the
number of g‟s experienced by the sensor for different material
types and thicknesses. Future model development will include
modeling the sensor as a point mass that is connected to
insulating materials modeled as springs and dashpots. The
acceleration data collected will then be used to determine the
effective spring coefficient and energy dissipating element for
each material at a given thickness.
5.3 INSIGHTS FROM INSULATION MATERIAL
TESTING Many insights about the practicality of different insulation
materials were drawn from the experimental testing. Jell-o,
although relatively successful at protecting an egg from large
falls, was considered too messy and difficult to replace.
Cornstarch and water were removed from consideration due to
the increased weight when compared to other insulation
options. Styrofoam was found to be effective and reusable, with
the biggest complaint being the mess made during construction.
To ensure continuity between test runs, it was necessary to
rotate and replace the Cheerios, equally distributing the broken
and unbroken bits. This life-cycle failure contributed to
Cheerios not being used in the final design. The students also
struggled with reliably calculating the thickness of the shredded
paper, due to variations in packing. Additionally, knowing
when to replace this material was a concern.
As time constraints prevented determining the effective
spring coefficient and energy dissipation elements of the various
materials, experimental data was used along with energy and
impulse equations. Here, the students made the simplifying
assumption of an impulse time of 0.002 seconds to calculate the
amount of force absorbed by a specified thickness of insulating
material, as shown in Figure 5. Overall, the following results
were collected for a given material at a given thickness:
average break height in meters
force absorbed per gram of material
force absorbed per dollar of material
Figure 5. Results from experimental testing
5.4 PARACHUTE AND CRUSH-ZONE TESTING Despite severe time limitations at this point in the six-week
project, the students attempted parachute and crush-zone
testing. The conclusion drawn about parachute testing was that
no substantial, quantifiable results could be obtained in the
allotted time. The best result from limited experimentation was
an upside-down, plastic grocery bag attached to the container.
For crush-zone testing, four concepts were tested, two of
which are shown in Figure 6: airbag, angled accordion, spiral
accordion, and cardboard tubes. Between tests, the airbag was
replaced if damaged, and the different accordions were
9 Copyright © 2010 by ASME
“fluffed” between trials. From testing, it was revealed that the
greatest failure of the angled accordion was the system‟s
inability to fall straight, causing alignment issues at impact.
5.5 OPTIMIZATION OF PROPOSED CONCEPTS Despite weeks of experimental testing, there was not nearly
enough data generated to create a full-fledged optimization
model for this problem. However, there was enough material
test data to facilitate informed and improved decision-making
with regards to the insulation material. To aid this decision-
making process, background material on optimal alternative
selection when considering multiple attributes was introduced
[19]. This experience allowed the students to learn about the
potential pitfalls associated with ranking, scaling, and
normalizing attributes. During these discussions they were also
introduced to the concept of optimization, Pareto optimality
[20], and use of utility theory in engineering design [21].
The idea that attributes can be weighted was leveraged to
create an interactive optimization algorithm for insulating
materials that required replacement (bubble wrap, Cheerios,
etc.). For a given insulation thickness, the amount of material
replaced per drop can be varied. The amount of material
replaced directly influences the overall cost of the insulating
material per average drop. However, replacing larger amounts
of material also increases the probability of system success. By
assigning weights to the attributes of cost and system reliability
(not breaking an egg), the utility of the proposed scheme was
calculated. An example of this approach is shown in Figure 7.
Figure 7. Optimizing the amount of
material replaced per drop
5.6 FINAL LAYOUT Arriving at a definitive layout for the system occurred
during the last week of the six-week project. While multiple
experiments had been run in an attempt to model the effect of
different design variables on system performance, the amount
and fidelity of the information gathered was not comprehensive
enough to develop equations that described the entire system.
Instead, decisions on the final design were based on two types
of student experience: 1) experience gained from working with
different materials during the experimentation phase, and 2)
past experience with egg drop projects, discussions with other
students, and a mental model of what the system should look
like gathered from outside research.
In addition to performance criteria, ease of use was
specifically targeted. When discussing this decision with the
students, it was determined that they were interested in running
multiple tests as quickly and easily as possible. This decision
was motivated by the need for final test results to be used in a
poster symposium that occurred at the end of the six-week
research experience. The final design is shown in Figure 8.
Figure 8. Final design layout
This design primarily used Styrofoam as the insulating
material. Shredded paper was used to cover the top of the eggs,
as it was concluded that minimal forces would be seen at this
location. Instead, the paper was used to securely fasten the eggs
in their defined slots during free-fall and to allow for ease of
access during testing set-up. Airbags were placed at the corners
of the container, and a plastic grocery bag served as the
parachute. Additionally, holes were cut in the container in an
effort to minimize weight
Final testing showed that the final design successfully
completed the defined requirements listed in Table 1. During
multiple tests from 40 feet, an average of 95% of the eggs
survived free fall. To test the “optimality” of the system, the
free fall height was increased in increments of 10 feet. At a
Figure 6. Experimental designs for crush-zone testing
10 Copyright © 2010 by ASME
height of 50 feet, 2-3 eggs on average would fail, indicating that
the thickness of the material selected was correctly chosen for
the mission. Complete system failure occurred when dropped
from 80 feet. Here, a gust of wind added horizontal velocity to
the system, causing it to collide with the fire escape used to test
the system at the 60 foot mark. This collision caused the system
to tip, and half of the eggs were ejected to experience
unprotected free-fall. The system landed upside-down,
breaking the remaining eggs at impact.
5.7 ASSESSMENT OF EMBODIMENT DESIGN TASKS The embodiment design phase was by far the most difficult
task for the students to complete. The assessment criteria
defined in Section 1 state that when choosing between
alternative solutions, students should be introduced to the roles
of models and simulations. As part of this task, students had to
generate models for multiple components: the egg, insulation,
parachute, and crush zone. Data for these models came from
experiments created by the students to extract this data. While
the information gathered provided useful insight into the
problem, the six-week period was not enough time to plan,
develop, and run the necessary experiments needed to create a
comprehensive model.
In reality, the students ended up with two design projects.
In addition to designing the system to protect the eggs, the
students were also required to design and validate their testing
mechanisms. Interviews with the students revealed that they
enjoyed the process of gathering data for the problem, as they
felt it gave them a better understanding of how the different
components of the system worked. Much like the design
process, they felt that successfully developing a testing scheme
was iterative in nature. While the functional model gave them
suggestions for component layout, failures in testing provided
insight into what did or did not work. They were also surprised
by how much information they gained from failures in the
testing approach itself. Often, they were able to gather data on
system phenomena that they did not intend to capture because
of a failure in the testing mechanism or a poorly designed
experiment.
In achieving the final design, the students believed that they
gravitated toward focusing on two objectives: reusability and
survivability. A non-specified system requirement that received
much attention was reset time. Also, despite the limitations of
gathering data for model development, listing and exploring the
design variables associated with this problem showed the
students how much control they had over system performance.
They felt that in many high school projects they never
completely understood of all the design variables associated
with a problem, which often led to a disconnect in
understanding performance changes.
Finally, the students were surprised at how well the
“simple” final design performed. When compared to their
brainstorming session, which resulted in many infeasible or
impractical designs, they felt their final design lacked a degree
of novelty. However, by creating system models and analyzing
the data, they were able to predict the performance of their
design against the criteria that it needed to meet. By comparing
this design against other concepts, they felt that they had made
the best-informed decision possible. Implementation of the
proposed solution was also achieved by constructing a final
version of the system and conducting drop tests from multiple
heights. It was also interesting to note that Styrofoam was
chosen by the student who originally was a proponent of using
green materials – a listed „want‟ in Table 2.
6. “DETAILED” DESIGN The end result of the detailed design phase is product
documentation. In this light, the assessment criteria of
communicating the problem, process, and solution will be
addressed. As part of this six-week research experience, the
two students were required to present their work at a poster
symposium on NC State‟s campus. Their individual posters
discussed the culmination of their research efforts and allowed
them to discuss their experience with other student researchers
and university faculty. Procedure logs, documentation, and
reports were also collected by the advisor to document the
experimental efforts and lessons learned. They also contributed
to the writing of this paper.
Additionally, the students performed a self-assessment
activity on the work that they completed. As stated in Section
1, students must also prepare a report on an aspect of the system
they would improve. This activity was completed by develop
four alternative solutions to the testing apparatus originally
presented in Section 5.1. Two of these proposed alternatives
are shown in Figure 9 and outlined below.
Swinging pendulum
Variability: change in mass, or change in elevation, changes
the absorbed kinetic energy
Advantages: Small size; easier to reset; can apply a point force
Egg
Pendulum Stop
Pendulum Stop
Insula
tio
n Mass
Swinging pendulum
Egg
Sto
p
Insulation
Sto
p
Mass
Inverse drop
Figure 9. Alternative testing apparatuses
11 Copyright © 2010 by ASME
Disadvantages: (1) May require large masses to get data that
approximates high drops; (2) have to minimize egg movement
(so instead absorbs kinetic energy, rather than transfers it)
without “sandwiching” and crushing the egg, (3) does not
provide linear motion after initial impact, (4) may measure
compressibility of material more than energy absorption.
Inverse Drop
Variability: change the mass or change the initial height to
change the falling mass‟s final velocity.
Advantages: Small size; easier to reset; can apply a point
force; linear movement throughout impact; (the mass could
easily be replaced with the egg, although a larger unit may be
required to get adequate height)
Disadvantages: (1) May require large masses to get data that
approximates high drops; (2) have to minimize egg movement
(so instead absorbs kinetic energy, rather than transfers it)
without “sandwiching” and crushing the egg; (3) may measure
compressibility of material more than energy absorption; (4)
gravity‟s direction parallel to the force being applied may
increase the complexity of the math.
7. CONCLUSIONS AND FUTURE WORK The traditional egg drop project is a common experience
for many K-12 students and undergraduates in engineering. To
reduce the feasible design space, students are commonly given a
box of pre-defined supplies (material constraints) or constraints
placed on allowable components. In this paper, the true
complexity of the problem is investigated when these
constraints are removed, or at least relaxed. When a system
designed to protect 12 eggs is considered, the possibility exists
for 72 different design variables define the problem. If a
container is designed for only one egg, 28 design variables
would still be needed to define the problem. In addition to this
complex number of design variables, six unique performance
objectives must also be considered – 3 of which are to be
minimized, 3 of which are to be maximized. Therefore,
students are faced with a constrained mixed-variable
multiobjective optimization problem.
Assessment of student outcomes from this project show
that following a systematic design process satisfies the
suggested criteria defined by the National Science Education
Standards, and helps students make informed configuration
decisions by assessing against technical and economic
conditions. Discussions with the two students revealed that they
thought it was very important to go through the steps of the
design process, as they had a better understanding of how
design variables in a problem affected system performance. In
developing a requirements list, the students believed that they
had tangible goals - or things to solve for - where following a
scientific method is typically more of a binary response to
answer a hypothesis. In developing models to assess the
performance of their proposed concepts, they developed an
increased understanding of the multidisciplinary aspects of
system and how component interactions can drastically impact
system performance. Students also expressed that the
“exciting” parts of engineering design took about 20% of their
six-week window, while the remainder of the time was spent
developing, running, and analyzing experimental data.
Furthermore, they found that important information could be
learned not only when the system failed an experiment, but also
when the experiment itself failed and revealed unintended
information about system performance.
Testing of the final design showed that even without
comprehensive models of the system, the container was not
drastically over-designed. The two students associated with this
project quickly learned complex engineering design principles,
and were able to adopt them into their project. They were
excited by the multiobjective and multidisciplinary nature of the
problem, and quickly identified future challenges associated
with this project. The categories for these aspects of future
work include:
Data Analysis
What is the relationship between the accelerometer‟s
reading and the egg cracking?
How much uncertainty is associated with the readings
over a large number of drops?
How does the surface area of the container bottom
change accelerometer readings?
Is there a way to test the accelerometer from larger
heights and then scale the system? Can a metamodel
be fit to this data?
How does the performance of the system degrade over
time?
Configuration challenges
What would be the ideal characteristics for a (fictional)
material for the system?
How does the multi-egg layout alter performance
outside of increasing system weight?
How do we best measure the interactions between the
components? How about between the materials?
How do you quantify requirements like
biodegradability rather than assigning an arbitrary
value?
ACKNOWLEDGMENTS The authors would like to acknowledge the support
provided from the NC Space Grant and the NC State Reaching
Incoming Student Enrichment (RISE) Program
REFERENCES [1] National Committee on Science Education Standards and
Assessment, National Research Council, 1996, National
12 Copyright © 2010 by ASME
Science Education Standards, National Academy Press,
Washington, DC.
[2] Davis Creek Elementary, 1998, “5th
Grade Eggdrop
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[15] Stone, R. B. and K. L. Wood (2000). "Development of a
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[19] See, T. K., Gurnani, A., Lewis, K., 2004, “Multi-Attribute
Decision Making Using Hypothetical Equivalents and
Inequivalents,” Journal of Mechanical Design, 126(11):
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[20] Pareto, V., Manuale di Econòmica Polìttica, Società
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Decision Making in Engineering Design, American Society
of Mechanical Engineers, New York.
13 Copyright © 2010 by ASME
Figure A.1. Functional diagram of Ms. Klumpe
Figure A.2 Functional diagram of Mr. Turner
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