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From Nature to Performance: Sustainable Nanoengineered Composites Using Natural Bast Fibers
No full textThe urgent need to reduce reliance on non-renewable, non-biodegradable materials has driven research into sustainable structural materials. This study develops high-performance, eco-friendly composites reinforced with natural bast fibers, jute and ramie, balancing mechanical strength and sustainability. Fiber–matrix adhesion is enhanced using nanoscale zinc oxide (ZnO) coatings via hydrothermal synthesis. These bio-inspired coatings improve interfacial bonding, moisture resistance, and durability. The composites employ a biodegradable, bio-based epoxy matrix (EcoPoxy), minimizing carbon footprint throughout production and disposal. Mechanical tests demonstrate that nanomodified fibers show significant improvements in strength and hardness. SEM confirms uniform nanoparticle coatings that enhance load transfer. This work establishes a scalable framework for sustainable composites applicable in automotive, aerospace, and biomedical sectors, advancing this material design with enhanced mechanical and environmental performance
The Grad Duck Observes the Worldwide Commencement on the U.S.S. Midway in San Diego, CA
Get PDFThe Embry-Riddle Worldwide | College of Arts & Sciences Grad Duck is seen observing the Embry-Riddle Worldwide Commencement this past August 2025 on the deck of the U.S.S. Midway in San Diego, CA
Gaseous Ethanol Rocket Engine Cooling
Get PDFIn a standard rocket engine, the exhaust gas reaches a very high temperature; thus, the engine walls must be cooled to ensure safe handling. Many cooling methods have been tried and these all have their benefits and uses, such as regenerative seeing more use in larger rocket nozzles and ablative cooling allowing for modularity. Central to this study is film cooling, the process of injecting a thin layer of liquid fuel onto the nozzle walls to provide insulation from the exhaust gas. Ethanol has been used as fuel and coolant, due to the physical properties of ethanol that allow for relatively clean propulsion and ease of storage and handling in a physical, experimental setting, with liquid oxygen as an oxidizer. In Star-CCM+, a rocket engine model has been subjected to typical ethanol-lox engine exhaust flow. The injection temperature and blowing ratio of the ethanol coolant around the exhaust gas have been varied from low to high values to ensure a wide range of input conditions. It was found that there were negligible differences between the blowing ratio and temperature combinations under incompressible, gaseous, low-blowing ratio conditions. However, it was determined that including the gaseous coolant insulation can prevent 16.35% more heat flux than not using it. Moving forward, research will strive to achieve compressible, supersonic, and liquid coolant conditions and record the relevant data
Overcoming Drone Noise for Effective Human Detection in Emergency Response
Get PDFIn disaster scenarios where visibility can be compromised, and conventional detection methods are ineffective, acoustic detection offers a critical means of localizing victims in search and rescue operations. However, the inherent noise generated by uncrewed aerial rotorcraft systems poses significant challenges to the effective use of acoustic sensing equipment. This research investigates the feasibility of utilizing drones equipped with high-sensitivity microphones to detect and locate humans in such environments. Key questions address the microphone sensitivity required for reliable identification of human sounds and the technologies available to mitigate propeller noise. Through a fusion of aeroacoustic improvements to be made to an uncrewed aircraft’s propulsion system with high-sensitivity acoustic microphones, the feasibility of creating an uncrewed aerial system- based acoustic detection system for disaster victim localization will be explored. A preliminary conceptual design, including all existing and attainable technologies, will be outlined in this study. The research will include a thorough evaluation of the system\u27s feasibility, identification of necessary advancements in sound classification algorithms, and a comprehensive analysis of the integration challenges faced by various acoustic sensors. Ultimately, this research seeks to contribute to enhancing search and rescue technologies through merging feasible leading-edge technologies.
Keywords: uncrewed Aerial Systems, propeller noise, noise mitigation and control, search and rescue, aeroacoustic
An Efficient and Data-driven Learning Algorithm to Evaluate Facial Recognition
Get PDFFacial recognition technology plays a crucial role in numerous fields, from national security to social media platforms. Convolutional Neural Networks (CNNs) stand out as the most prevalent technique for facial recognition due to their impressive accuracy and adaptability in various scenarios. However, CNN-based learning faces considerable challenges, including high computational demands, a dependence on large volumes of labeled data, and significant storage requirements, which all impede its overall efficiency.
We aim to implement an innovative and efficient facial recognition approach utilizing structured neural networks grounded in Discrete Cosine Transforms (DCTs), achieving accuracy comparable to conventional CNNs. Our extensive and varied facial dataset guarantees robustness against diverse features, expressions, and lighting conditions. Furthermore, we will conduct a comprehensive comparison between our proposed neural network and traditional methods such as Eigenfaces, emphasizing their performance in facial recognition applications
Working with the Immune System to Fight Infection: An Innovative Alternative to Chemical Anti fungal Treatment
Get PDFCurrent clinical treatments for blood-based fungal infections mainly rely on systemic Amphotericin B, which, despite its effectiveness, is biologically toxic and remains the sole method for infection management. To explore safer alternatives, this project aims to introduce a gene therapy strategy as a promising treatment for fungal infections caused by Candida albicans biofilms. Through genetic engineering, we intend to deliver a powerful antimycotic enzyme, endo-alpha-mannosidase, into monocytes using plasmid gene therapy, thereby enhancing immune and antifungal responses. This initiative will create an effective alternative therapy to treat systemic fungal infections. Furthermore, the methodologies developed will provide proof of concept for enhancing monocyte functions of phagocytosis, encouraging further exploration for both terrestrial and space medicine applications
Evaluating a Biologically-Inspired Multi-Agent System Consensus Algorithm for Robustness to False Negatives
Get PDFMulti-agent systems have several advantages over centralized systems of control and are becoming more heavily relied upon by systems. Consensus algorithms are a fundamental element of multi-agent systems, but current methods of consensus have a low robustness to faulted agents, endangering the integrity of the system. Biologically Inspired Design previously inspired a state-of-the-art consensus algorithm with resilience of up to 20% faulted agents within a population, called the Synchronous Hatching Consensus Algorithm. This article further tests the algorithm by implementing faulted agents reporting false negatives, rather than the original false positives, to see if the model remains robust. To test the proposed algorithm an Agent-Based, ANYLOGIC model was tested against 0, 1, 5, 10, 15, and 20 ‘false negative’ faulted agents across four varying environments. The robustness of the algorithm was measured by the time to consensus for 66% and the percentage of runs that failed to reach consensus. Three separate tests were conducted to determine if the model is robust to faulted agents reporting false positives. It was found that two of three tests deemed the model not robust. An uncertainty and sensitivity analysis was then performed to determine the uncertainty of failure to reach 66% consensus and the cause of uncertainty in the results. The total probability to not reach consensus was 59%, and the highest cause of this failure was the rate of change of the environment. The number of faulted agents had the second highest impact upon the uncertainty. Thus, we recommend this algorithm be implemented in an environment that quickly reaches its decision threshold and interacts with predominantly false positive faulted agents
Project Minerva
Get PDFWeather balloons play a crucial role in atmospheric data collection, but their vulnerability to lightning strikes remains a significant concern. This study seeks to address two primary objectives: (1) to test the hypothesis that lightning does not significantly interfere with the accuracy of data collected by weather balloon payloads, and (2) to explore the feasibility of using a lightweight Faraday cage to protect the balloon from potential lightning damage. The payload will be equipped with standard sensors for measuring temperature, pressure, and humidity, along with lightning detection equipment to monitor any strikes during the flight. Additionally, the project includes secondary objectives of testing 3D-printed components for CubeSat construction and developing a parachute deployment system for safe recovery of the payload.
As the launch is forthcoming, no results have been obtained yet; however, the study is designed to provide quantitative data on lightning interference, if any, and the protective efficacy of the Faraday cage. The results are expected to offer valuable insights into enhancing the durability of weather balloons in storm-prone environments, while contributing to advancements in CubeSat design and recovery technologies. These findings will contribute to the broader field of atmospheric data collection and space technology development, potentially improving safety and efficiency in future missions