AE Brown Bag Seminar
Friday, February 27
11:00 a.m. - 1:20 p.m.
Guggenheim 442
Irene Abraham
Devindi Ambawatta
Davis Lee
Cayden Perry
Illiyan Tajani
Dominic Santa Lucia
Irene Abraham
Title:
Ice Accretion in Aviation Jet Fuel
Abstract:
Ice formation in jet fuel presents an aircraft engine performance and safety issue, particularly when operating at high altitudes where temperatures can fall below -40 degrees Celsius. Although above the freezing point of jet fuel, dissolved water can precipitate as ice crystals when temperature decreases. These ice particles can accumulate within fuel lines, lessening flow rate and causing engine performance loss.
Ice formation begins when dissolved water in jet fuel exists in a supercooled liquid phase under water’s freezing temperature. In its supercooled state, the water molecules are unstable and will rapidly nucleate around any solids it encounters. The water molecules become less soluble in jet fuel with a temperature decrease, increasing the nucleation tendency.
Having encountered this issue for the first time in their testing rig, the team tried various methods to target various hypotheses about the causes of this phenomenon. This presentation summarizes an investigation into the causes of ice formation in aviation jet fuel, including proposed mitigation methods, particularly in relation to research regarding high-altitude ignition at the Ben T. Zinn Combustion Lab.
Faculty Advisor:
Prof. Adam Steinberg
Devindi Ambawatta
Title:
CAN-Bus Communication Network Development for eVTOL Aircraft
Abstract:
This research presentation summarizes the design, implementation, and validation of CAN-Bus communication networks for both a small scale “Copper Bird” platform as well as a full-scale “Iron-Bird” test rig. The work focused on understanding the software and hardware requirements of CAN-Bus networks, proving the scalability and reliability of the two way communication, and exploring the vulnerabilities of CAN-Bus communication networks to electrically noisy aerospace environments (such as in an eVTOL aircraft).
A small scale “Copper Bird” was developed as an initial testbed for the CAN Bus Communication system. A modular network was created to integrated motor control, control surface actuation, RPM, voltage, and current sensing. This testbed proved the viability of CAN Bus communication for both control and monitoring, and provided useful insight into how Simulink software can be used to run CAN-Bus networks. The results of this testbed were then expanded onto the larger “Iron-Bird” test rig, for instrumentation purposes. Load cells attached to the feet of the rig provide crucial safety measurements during propeller-driven testing, and so the research focused on developing an instrumentation CAN-Bus with live monitoring of loads on the rig. Additional challenges were encountered with the large scale implementation, including higher electromagnetic interference environments and more complex integration into a flight computer system.
Across both platforms, the research has demonstrated the advantages of CAN-Bus networks for eVTOL aircraft, as well as discover unexpected vulnerabilities of the system when in full-scale environments. Further work is being done to continue to scale up the communication networks, and to fully integrate the entirety of the aircraft communications system into CAN-Bus networks for the Iron-Bird test rig.
Faculty Advisor:
Prof. Brian German
Davis Lee
Title:
Bi-modular Sandwich Panels Under Pure Bending
Abstract:
Many theories assume the core of sandwich panels have similar compressional and tensional moduli, but polymeric foams, such as PVC foam, commonly used in shipbuilding, have vastly different compressional and tensional moduli. This theory hopes to accurately predict the bending behavior of materials exhibiting this behavior and provide a benchmark for four-point bending tests or pure bending cases. The formulation is an extension of simple bending theory, taking into account a bi-modular core sandwich structure with differing tensional and compressional moduli and two isotropic face sheets. First, the neutral axis is found by summing the stresses on a cross section and setting the result to zero, and then, the moments for the core and two face sheets are solved using pure bending theory in terms of the neutral axis. The sensitivity of the neutral axis location to core bi-modularity is then explored by analyzing sandwich panels across different industries. Results show that the face-to-core stiffness ratio and face thickness-to-total thickness ratio govern the sensitivity of the neutral axis to core bi-modularity, where a high face-to-core stiffness ratio and high face thickness-to-total thickness ratio lead to the lowest sensitivity to core bi-modularity.
Faculty Advisor:
Prof. George Kardomateas
Cayden Perry
Title:
Experimental Evaluation of Additive Manufacturing Materials and Design Strategies for UAV Airframes
Abstract:
Recent advances in additive manufacturing have created new possibilities for UAV airframe fabrication, but the structural, and mass distribution performance of new printed materials in drone applications remains poorly characterized. This research evaluated additive manufacturing techniques and materials for UAV development, with the ultimate goal of developing an initial manufacturing baseline leading to SETTER, a fully configurable subscale vehicle derived from NASA RAVEN, designed for flight controls scalability research. A Commercial Off-The-Shelf airframe was first fabricated using a baseline filament and flight-tested to identify the limitations of current additive design strategies. These shortcomings motivated a structured comparison of foaming filaments, multi-material shells, foam cores, composite layups, and surface coatings. Foaming ASA, PET-CF, and PPA-CF combined with lightweight fiberglass and epoxy coatings emerged as the most promising material solutions, offering favorable tradeoffs between printed mass, stiffness, and manufacturability. Fiberglass-epoxy coatings demonstrated the most favorable mass efficiency, adding as little as 0.014 g/cm² (approximately 11% weight increase) compared to over 0.032 g/cm² for elastomeric alternatives a significant difference that directly informs material selection for weight-sensitive airframe applications. These findings were then applied to design and fabricate a 19.75% scale BEDE-6 aircraft as a manufacturing testbed, validating the selected material strategies and related design choices at subscale. This research establishes material and fabrication guidelines for printed UAV airframe construction, directly informing the future development of SETTER.
Faculty Advisor:
Research Engineer Lee Whitcher
Illiyan Tajani
Title:
NASA Machine Learning Bots: Educational Outreach on AI & Robotics
Abstract:
NASA ML-Bots is a K-12 educational outreach program that uses small autonomous rovers and open-source tools to introduce students to engineering, coding, and machine learning in the form of NASA-inspired missions. There is a focus on creating this program for metro Atlanta high schools, where many students have limited access to STEM experiences. The work centers on a classroom sequence that includes Python basics, data collection for machine learning, and training a simple neural network for road following and obstacle avoidance of Jetson Nano robots. For a sustainable curriculum, standards and manuals were identified and created for educators to run activities after initial support. The effort also helps also helped connect CEISMC projects such as the Big Bot Challenge to create a pipeline to undergraduate autonomy to K-12 outreach. The research explores how designed machine learning activities and classroom resources can lower barriers for schools and spark students interest in STEM.
Faculty Advisor:
Prof. Kelly Griendling
Dominic Santa Lucia
Title:
Improving SLOSH-ML: GUI Tools, Documentation, and Damping Checks
Abstract:
An important aspect of spacecraft flight is that propellant slosh dynamics can introduce destabilizing forces and moments that can have a profound effect on a vehicle’s guidance, navigation, and control (GNC), especially for high propellant mass fractions. To make slosh modeling more accessible to non-specialists and more directly usable in early-stage design and controls simulation, the URO sloshing coding team within the Low-Gravity Science and Technology (LGST) Lab has developed a tool called SLOSH-ML, an open-source MATLAB GUI that implements axisymmetric, high-gravity linear slosh dynamic input parameters and maps the resulting modes to equivalent mechanical analogies (pendulum and spring–mass representations). The tool supports the creation of arbitrary tank geometries with the ability to input properties such as fill ratio, liquid density, liquid viscosity, and gravitational acceleration. The app then computes modal frequencies/shapes and enables batch (trajectory-style) parametric studies over fill ratio and acceleration, producing mechanical-analog parameters suitable for GNC modeling. In this seminar, I will give a walkthrough of the SLOSH-ML application functionality at a high level and go over its companion Contour Designer geometry tool. I’ll then focus on the practical engineering work I did while on the coding team: documentation and user-facing guides, software call-graph figures used in the conference paper, a geometry utility improvement (even spacing along elliptical segments), and verification/validation support for damping correlations (including conical and toroidal cases and cylindrical ring-baffle correction factors).
Faculty Advisor:
Prof. Alvaro Romero-Calvo