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Cyberaero - A Capture-The-Flag-Competition
Get PDFThe global shortage of cybersecurity professionals is projected to reach millions in the coming years, leaving critical industries, such as aerospace, vulnerable to cyber threats. To bridge this gap, early exposure to cybersecurity education is vital. Yet, K-12 computer education often falls short of preparing students for the demands of cybersecurity careers, highlighting the need for more hands-on learning opportunities. CyberAero is a one-of-a-kind Capture-The-Flag (CTF) competition designed as an immersive cybersecurity experience for high school students. Unlike traditional CTFs, participants are challenged to tackle hands-on scenarios inspired by real world aerospace cybersecurity threats. With guidance from Embry-Riddle cybersecurity students actively working in the field, participants will experience how cybersecurity plays a vital role in protecting critical systems. This competition gamifies cybersecurity concepts, making learning engaging and inspirational-no prior experience required. Participants will explore key cybersecurity topics, including computer forensics, open-source intelligence (OSINT), web exploitation, digital forensics, terminal navigation, networking, and programming in individual and team-based formats. Throughout the event, Embry-Riddle cybersecurity students will be present to mentor and assist high school participants, ensuring an engaging and supportive learning experience. Beyond technical skills, CyberAero introduces students to incident response techniques, preparing them for potential future roles in cybersecurity. Our goal is for CyberAero to ignite a passion for cybersecurity among high school students and encourage them to become the next generation of cyber defenders protecting our digital and aerospace domains. Whether students are exploring cybersecurity for the first time or already have an interest, this competition provides a fun, hands-on, and immersive experience to develop essential skills in a rapidly growing field
Strategic Model Based Systems Engineering (MBSE)
No full textAs modern systems grow in complexity, effective management of system architectures requires advanced methodologies. Model-Based Systems Engineering (MBSE), particularly through the Systems Modeling Language (SysML), provides a structured approach to handling large-scale system models. However, manual SysML processes remain time-intensive and error-prone. With rapid advancements in artificial intelligence (AI), there is growing interest in leveraging AI to automate SysML model generation and management, enhancing efficiency and scalability. This project explores the feasibility of integrating AI into MBSE, focusing on existing AI tools, techniques, and methodologies that support system engineering processes. Through a comprehensive review of AI advancements relevant to MBSE, the study examines AI’s potential in automating SysML tasks such as model generation, validation, and data handling. Additionally, a conceptual framework is proposed for an AI-integrated SysML tool, outlining its architecture and functionalities. The findings highlight AI’s transformative potential in MBSE by streamlining workflows, reducing human error, and improving scalability. This research contributes to the growing body of knowledge on AI-driven systems engineering, offering a foundation for future development and integration of AI tools in MBSE practices
Aerocare - Unmanned Aerial Delivery Vehicle
No full textCertain remote areas have limited access to life saving medical supplies. Currently medical delivery efforts are reliant on ground transportation, which consumes both valuable time and resources. Studies show that aerial transport of supplies significantly decreases delivery time in both urban and rural environments. An unmanned aerial transport has the potential of reducing cost and delivery time while filling this need for medical supplies. The AeroCare project aims to pursue the development of an unmanned medical delivery aircraft capable of dropping a payload midflight. The aircraft will fly for at least 100 miles in under an hour while carrying 4 pounds of medical supplies. A normal mission will start with a short take-off (less than 56 feet), followed by a 1000 ft/min climb to the cruising altitude of 1000 feet above ground level. A descent to 400 feet will be performed before delivery where the medical package will be deployed from the internal payload bay. The aircraft will then climb back to its cruising altitude to return for recovery and resupply. Preliminary analysis has been completed on multiple design concepts, which were compared to pick a singular aircraft shape. A high-wing, conventional-tail aircraft was selected after analysis into the cruise efficiency, stability, and manufacturability of each design. The plane will be powered by a 2-stroke gas engine since gasoline has high energy density and low cost. A 2-stroke is also lighter than a 4-stroke and more reliable than a turbine at this scale
AIAA Design Build Fly Team Coppertails - A Glider Launching Projec
No full textThe DBF club team Coppertails built HALO (High Altitude Lifting Operations), an aircraft designed to complete three flight missions and one ground mission in accordance with the requirements stated by AIAA. To optimize all mission scores, Coppertails designed HALO to have an empty weight of 1 3. 5 lb and a maximum payload of 12 lb for a combined total of 25.5 lb. Team Coppertails adhered to an iterative design process to advance the aircraft when feasible improvements were identified. HALO is a single-motor, high wing UAV with a conventional tail. A single tractor motor configuration was chosen because it provides sufficient thrust for all flight missions, increases propulsive efficiency, and reduces weight. To enhance payload capacity, a flat- bottomed fuselage was adopted, and a boom tail was employed to give the stabilizers sufficient authority given the large inertia of the aircraft. A high wing was implemented to allow easy access to the payload and avionics. To maximize mission scores, the team conducted a scoring optimization to decipher the M2 payload and maximum cruise speed. HALO is designed to complete M2 in 1 20 s carrying 12 lb of fuel payload. It is also anticipated to fly 8 laps in M3 before releasing the X-1 glider. Through flight testing, HALO has demonstrated sustained flight at a weight of 25.5 lb and cruise speeds of roughly 85 ft/s. HALO has also proven its full controllability at a maximum velocity of 110 ft/s. HALO\u27s construction is a fiberglass and carbon fiber design, intended to utilize the advantage s of both materials to their fullest. The wing is designed to have detachable pylons with fuel tanks. The X-1 glider is a dihedral high wing with a conventional tail chosen for stability. The X-1 glider\u27s construction is mostly 3D printed parts with balsa wood components for low weight while maintaining structural rigidity. The design is optimized to have interchangeable parts that can be readily replaced for fast repairs. The electronics have been selected for their minimalist qualities to conserve weight while enabling successful completion of the mission. An onboard flight controller will activate the strobe light and help maintain stable flight and direct the glider to the bonus box landing zone
Implementing & Evaluating a Limited Legal Guardianship in Yavapai County
No full textEvery community faces challenges helping individuals who are less capable of taking care of themselves. This challenge is more evident in Yavapai County, popular for retirement and rehab. However, this jurisdiction does not have standard procedures in place to ensure maximal autonomy while still creating supports needed for those who are legally incapacitated. Frequently, incapacitation occurs as a result of cognitive decline or substance use among individuals without close family ties. Stakeholder meetings continually suggested a gap in services in the legal sector putting strain on financial (public fiduciary) and social work (e.g. Adult Protective Services) fields. In efforts to alleviate county level struggles, we first set out to show the quantitative need for limited legal guardianship via survey to health providers and secondly implemented a pilot program. Initial surveys indicated there would be potentially 3 referrals per week to a limited legal guardianship program. After implementing this system in Yavapai County, the first 3 months had 12 referrals resulting in numerous success stories. Stakeholder reflections revealed several barriers that can be overcome as we move into 2025 with the limited legal guardianship program
Additive Manufacturing Reliability Based on Microscope Analysis
No full textAdditive manufacturing (AM) has revolutionized the production of aerodynamic components by enabling the rapid prototyping of complex geometries. However, the reliability of these components remains an active area of research. This study investigates: How do varying 3D printer parameters affect the reliability of additively manufactured aerospace components? Three objectives were defined: first, to identify optimal printing temperatures; second, to determine optimal thickness and velocity for the 3D printer settings; and third, to integrate the results using global optimization to determine the ideal set of parameters. Nozzle and bed temperatures were varied independently, and the results were compared using microscopic analysis. Nozzle speed and layer height were also tested independently to determine optimal settings. Systematic variations were applied to temperature, speed, and layer height, following a statistical approach. Wing test sections were 3D printed to test the reliability of varying AM parameters. Polyethylene terephthalate glycol (PETG) was selected as the AM material due to its ease of printing and impact resistance. Microscopic analysis was then conducted to examine the reliability of the external surface of each print, capturing variations due to the different parameters. Next, the wing models were cut and analyzed internally using microscopic analysis to determine the characteristics of the internal structures. Finally, a global optimization was performed in order to determine the ideal set of AM printing parameters. This work bridged the gap between the reliability of AM and its applications in aerodynamics
Probing the Multiplicity of Dusty Wolf-Rayet Stars with Multi-Wavelength Techniques: Survey of Infrared Spectrometry
No full textWolf-Rayet (WR) stars, emblematic of massive celestial entities in advanced evolutionary phases, wield significant influence over the cosmic background. Carbon-rich WR stars emerge prominently among their ranks, distinguished by their expansive infrared emissions, which foster unique conditions conducive to producing cosmic dust. Exploring galactic systems that create dust necessitates a detailed and thorough analysis spanning multiple wavelengths aimed at discerning potential influencers, such as the presence of companion stars. Present endeavors are concentrated on refining data through meticulous telluric line corrections, laying the foundation for subsequent investigations. This iterative process unfolds gradually and methodically, ensuring the maximum smoothness in each graph corresponding to the respective order. Future endeavors aspire to juxtapose observational data with theoretical constructs, emphasizing O stars, thereby enabling more profound insights into the mechanisms governing dust production within these stellar configurations. Ongoing research efforts to clarify the underlying dynamics governing dust production in WR stars, thereby contributing to the comprehension of stellar evolution and interstellar environments
Acoustic Drone Detection Sensor Network
No full textThe proliferation of drones has created a challenge for places like borders, where drones are being used for smuggling, and airports, where drones infringe on controlled airspace . Finding as many ways to detect drones as possible is important for border and airport security. Typical ways to detect drones are to listen for the RF signature of a control signal or to use optical means of recognizing drones in images. However, for situations like smuggling, a drone can be run completely autonomously, leaving no RF control signal to listen for, and at night without lights or in fog the optical methods also fail. Therefore, a different modality for detecting the drones is needed. We propose to use sound (acoustics) to detect drones traveling nearby. Acoustic detection is not meant to replace RF and optical methods, but instead to add to the suite of drone detection capabilities. We expect to be able to detect drones out to at least fifty feet even with background aircraft noise using small, low-cost microcontrollers and microphones. Our sensors will be both recording their data locally and reporting it live to Amazon Web Services Internet of Things (AWS loT) where it can be monitored in real time. This project entails not only acoustic detection, but the creation of a reporting infrastructure using long distance LoRa radios bridged to Wi Fi and sent to AWS loT with end-to-end encryption. We will also develop weather resistant, solar powered nodes
