UTRGV
/ COLLEGE
OF ENGINEERING AND COMPUTER SCIENCE / MECHANICAL
ENGINEERING DEPARTMENT
TEAM
9: Design of a Morphing Winged Agriculture Surveillance Drone
|
SDI Students (L-R) |
·
Justin Mares ·
Rene Perez ·
Mario Barrera ·
Brandon Lira ·
Vanessa Gamboa |
|
Faculty Advisor(s) |
·
Dr. Isaac Choutapalli ·
Dr. Nadim Zgheib |
|
Course Instructors |
·
Dr. Noe Vargas
Hernandez ·
Mr. Greg Potter |
WHAT
IS THE PROBLEM WE ARE TRYING TO SOLVE?
WHY
IS THIS PROBLEM IMPORTANT?
LEARN
MORE ABOUT OUR DESIGN PROCESS
Welcome! We are Team #9, known as "Doritos Locos Tacos".
Throughout the Spring and Fall of 2024, our dedicated team members - Mario, Justin,
Rene, Vanessa and Brandon - collaborated on an innovative project titled "Design
of Morphing Wing Agricultural Surveillance Drone". Our objective was to tackle
the challenge of creating a drone equipped with morphing wing capabilities. Through
meticulous design and engineering, we developed a device that not only boasts
lightweight construction but also excels in energy efficiency. We are thrilled
to present our project in hopes that you will find it as engaging and inspiring
as we did throughout its development.
We are
striving to create an agricultural surveillance drone to aid farmers in
effectively surveying their land for any factors hindering crop growth ranging
from pests to disease that affects plants. This drone will be a fixed-wing
model with morphing capabilities, utilizing memory shape material to switch
between airfoils and enhance its aerodynamic capabilities. By providing
comprehensive property surveys through use of a FPV modular camera, this
technology aims to significantly improve productivity and agricultural
efficiency.
To better understand the problem between 20% to 40% of
global crop production is lost annually to pests, resulting in staggering
economic impacts. Plant diseases alone cost the global economy around $220
billion (about $680 per person in the US) annually, while invasive insects
incur losses of approximately $70 billion (about $220 per person in the US),
according to the Food and Agriculture Organization of the United Nations [1]. Weed’s
also pose a significant threat to global food production. Given these
challenges, innovative solutions are urgently needed. Our forthcoming
technology aims to revolutionize crop protection, offering a proactive approach
to mitigate the impact of pests on agriculture and enhance global food production.
Agricultural Threats (Leaf diseases (Top L- Leaf Streaks Top R- Tar spots) & Pests)
Implementing innovative solutions to combat crop loss caused
by pests and plant disease can yield significant economical and societal
benefits. By reducing crop losses, farmers can increase their yields and
revenue while stabilizing prices for consumers. Enhanced food security leads to
stronger rural communities and improved public health outcomes. The Figure on
the bottom shows a statistic collected by The Crop Protection Network that we lose
116.8 million bushels of Corn to tar spots and a bushel of corn costs 4.36 $
USD.
Our solution is to use drone
technology to identify and monitor pest infestations, potential crooks and
agricultural diseases. The drone is to be equipped with an on-board camera for live
viewing and photography. The camera is also modular and can be swapped to an infrared.
Early detection creates an opportunity to stop the spread of infestations or
potential predators, thus increasing crop yields. The drone is meant to be small and efficient,
to fly at least 45 min of flight time, and have a range of 5 km. We are trying
to match our competitors which is the DJI mini 3 pro and Crop X.
L- Crop-x R- DJI Mini 3 Pro
It has been difficult bringing this
project to life but what we have been able to achieve has been purely
theoretical. We’ve also 3-D printed designs for fuselage and airfoils as proof
of concept and what we plan to bring to reality next is to achieve sustainable
flight and reliably morph our wings. The wings morphing capabilities will be
done through the use of Nitinol, a Shape memory alloy that will be reliably
trained to change shape when heated above 45 degrees Celsius. When implementing
the metal only the bottom half of the airfoil will be made of the shape memory
material and will be heated through a direct current and nichrome wire. Another
specification of note is that this drone will be a fixed wing micro aerial
vehicle so it will have an aspect ratio no greater than 2.5.
Preliminary Prototype & camber diagram
The preliminary prototype was developed to understand how the chamber of the airfoil will change.
Prototype v1
Prototype v1 was created to understand the scale at which the model would be produced. The drone is targeted to have an aspect ratio of 2.5 with a wingspan of 9 in.
Prototype v2
The second prototype model was designed to be more streamlined as in prototype v1 the dent in the fuselage reduced internal space and reduced aerodynamic performance.
Prototype v3
In prototype v3, we added a removable cover for better access to the internals. The placement of the cover is not optimal, and a better solution will be needed in the future.
Airfoil Prototype
The airfoil prototype was created to understand how the nitinol was going to be placed in the airfoil.
Our initial attempt at running a heat test with nitinol
using an electrical current. Through this test, we realized that we were
getting hot spots, and the heat wasn't being dispersed evenly and in a timely
manner. So, we transitioned into using nichrome wire for assistance another
challenge with the metal creating a short circuit arise, but this was then
mitigated with a thermal heating pad electrically insulating the nichrome from
the nitinol. Giving us the results we wanted.
Test connections
Using a breadboard and a power supply we created a prototype that will be used to heat our nichrome wire on command. The final product will use an electrical current activated by a raspberry pi.
Test Fit
The test fit was created to understand how the electrical components would fit inside the fuselage.
Our final product we have created a proof-of-concept airfoil and how it will implement our shape memory alloy in order to reliably morph.
The next step to really optimize this project is to fly the drone with the morphing wing and to see where we can minimize the weight of the drone to make it within tolerance.
IN CONCLUSION
Our senior design experience was a learning experience that included aerodynamics and fluid dynamics. We learned what it will take to achieve stable flight, and we learned it’ll take more work to implement our morphing wing tech since it has never been implemented in this fashion before. This project also gave experience in problem identification, conceptual design, cost analysis, testing and data analysis
REFERENCES
[1] Nifa Authors
Lori Tyler Gula. (n.d.). Researchers helping protect crops from pests.
National Institute of Food and Agriculture. https://www.nifa.usda.gov/about-nifa/blogs/researchers-helping-protect-crops-pests#:~:text=Between%2020%25%20to%2040%25%20of,Organization%20of%20the%20United%20Nations.
[2]Corn disease loss estimates from the United
States and Ontario, Canada - 2022. Crop Protection Network. (2023, February
6). https://cropprotectionnetwork.org/publications/corn-disease-loss-estimates-from-the-united-states-and-ontario-canada-2022
[3] Jani, J.
M., Leary, M., Subic, A., and Gibson, M. A., 2013, “A review of shape memory
alloy research, applications and opportunities,” Materials & Design
(1980-2015) [Online]. Available:
https://www.sciencedirect.com/science/article/pii/S0261306913011345
[4] Taha, O.
Y., Experimental-study-on-two-way-shape-memory-effect- ... [Online]. Available:
https://www.researchgate.net/profile/Obai-Taha/publication/283807098_Experimental_study_on_two_way_shape_memory_effect_training_procedure_for_NiTiNOL_shape_memory_alloy/links/5c1f4951458515a4c7f29ba2/Experimental-study-on-two-way-shape-memory-effect-training-procedure-for-NiTiNOL-shape-memory-alloy.pdf
FIGURE 2: HEAT LOST
BY FORCED CONVECTION
(1)
By using the convection equation in (1) and plotting it over the range of the coldest to the highest temperatures in Texas [2], the linear plot in figure 2 is created. This would allow the drone to calculate how much heat is being lost due to forced convection.
FIGURE 3: HEAT LOST
BY FORCED CONVECTION
(2)
(3)
By using the using both equations (2)
and (3), the time it takes for the nitinol to reach 50°C can be found. Since forced
convection is happening to the nitinol, it decreases in temperature in the
beginning. It then proceeds to heat up due to the nitinol.
FIGURE 4: VELOCITY
VS THRUST
(4)
(5)
By
obtaining the coefficient of lift and the coefficient of drag at every stage
the thrust required can be calculated. Figure 4 visualizes the differences in
the airfoils and how the thrust required changes with increased weight.
The team received help from various people, their help was critical to our success, we would like to acknowledge.
·
Dr. Isaac Choutapalli
·
Dr. Nadim Zgheib
· Dr. Vargas
· Mr. Potter