21-30 of 73 results

  • Self-Sustained Flow-Acoustic Interactions in Airfoil Transitional Boundary Layers

    PI Vladimir Golubev

    CO-I Reda Mankbadi

    This work carries out collaborative theoretical, experimental and numerical investigations of flow-acoustic resonant interactions in transitional airfoils which are responsible for sudden appearance of prominent acoustic tones and unsteady aerodynamic fluctuations in low-Reynolds-number airfoils.

    The experimental part of the efforts is implemented in France at anechoic wind tunnel facility of Ecole Centrale de Lyon, while numerical and theoretical studies are conducted at Embry-Riddle using DOD HPC facilities. The project involves several PhD and MSAE students both in U.S. and France.

    Categories: Faculty-Staff

  • Synthetic Jet-Based Robust MAV Flight Controller

    PI Vladimir Golubev

    This project conducts theoretical and high-fidelity numerical analyses of UAV robust flight controller employing synthetic-jet actuators (SJAs). The technology-demonstration feasibility study focuses on SJA-based suppression of gust-induced airfoil flutter.

    It joins AE and Engineering Physics faculty and students (including undergraduate) in preparation for Phase 2 effort that will include experimental validation and further development and commercialization of the novel flight control technology

    Categories: Faculty-Staff

  • Wake Vortex Safety Analysis in the Context of UAS Integration in the NAS

    PI Vladimir Golubev

    ​This project is a collaboration with several research organizations under the supervision of FAA. The focus  of the current research efforts is on developing and employing variable-fidelity prediction approaches to examine safety implications of the future integration of variable-size UAS systems in the National Aerospace System (UAS). 



    In particular, variable-fidelity prediction methods to accurately resolve all aspects of aircraft wake generation, evolution, interaction and control are developed. The results of this research will be incorporated in the FAA Integrated Safety Assessment Model developed for analysis of risk implications of UAS operations in the terminal zones and beyond.

    Categories: Faculty-Staff

  • Demonstration of an Electrostatic Dust Shield on the Lunar Surface

    PI Troy Henderson

    This project will demonstrate the capability of an electrostatic dust shield, developed by NASA/KSC engineers, to remove dust from the lens of a camera after impact on the lunar surface.



    This project, which is funded by NASA Kennedy Space Center, will demonstrate the capability of an electrostatic dust shield, developed by NASA/KSC engineers, to remove dust from the lens of a camera after impact on the lunar surface. Laboratory tests will confirm the experiment design, followed by a flight to the lunar surface in early 2022

    Categories: Faculty-Staff

  • Hazard Detection and Avoidance for Lunar Landing

    PI Troy Henderson

    This project develops and demonstrates algorithms for detecting and avoiding areas of large rocks and high slopes for a lunar lander

    This project, funded by Intuitive Machines, develops and demonstrates algorithms for detecting and avoiding areas of large rocks and high slopes for a lunar lander. Preliminary work uses an optical camera and future work will include a lidar sensor. These algorithms will be tested in simulation, tested in laboratory experiments and demonstrated on a lunar lander flight mission.

    Categories: Faculty-Staff

  • Improved Image Processing for Orbit Estimation

    PI Troy Henderson

    This project seeks to improve orbit estimation methods using advanced image processing techniques applied to images from ground and space-based telescopes.

    This project, funded by Air Force Research Laboratory, seeks to improve orbit estimation methods using advanced image processing techniques applied to images from ground and space-based telescopes. Additional work uses RF signals to estimate orbits of transmitting spacecraft.

    Categories: Faculty-Staff

  • Multiscale Computational and Experimental Framework to Elucidate the Biomechanics of Infant Growth

    PI Victor Huayamave

    There is currently a lack of biomechanical quantification of growth and development because: (1) there is no generic musculoskeletal infant model, and (2) the lack of infant data in the literature.

    An infant’s spontaneous movements generate forces that are constantly acting on the joints and can affect the morphology and development of soft bone. Using experimental motion capture data, statistical shape modeling, and multi-scale musculoskeletal mechanobiological models, we will be able to predict the complex adaptation of the joint to biomechanical factors, thus providing a biomechanical basis for improved prevention and treatment of developmental disorders. This project pioneers the development of solutions that improve intervention and outcomes of conditions such as scoliosis, spina bifida, clubfoot and developmental dysplasia of the hip. The model provides a non-invasive three-dimensional approach to study the dynamics of human movements using biomechanical parameters that are difficult or impossible to examine using physical experiments alone. Our proposed research will advance pediatric movement science and will uncover the underlying mechanisms involved in the maturation of the hip joint during early development. Results from the proposed research will: (1) Provide experimental data and computational models that can serve as the basis for developing innovative solutions for infant developmental disorders; (2) Develop innovative tools to aid clinicians, pediatricians and physical therapists when managing joint disorders; (3) Identify factors that drive and regulate growth early in life that may have long-term benefits for prevention of early arthritis. Each of these contributions is significant given that joint disorders such as developmental dysplasia of the hip underlie around 29% of all primary hip replacements in adults.

    Categories: Faculty-Staff

  • Integrated Structural Health Sensors for Inflatable Space Habitats

    PI Dae Won Kim

    PI Sirish Namilae

    Under this research project we will develop an innovative structural health monitoring system for inflatable space habitat structures by integrating nanocomposite piezoresistive sensors 

    Inflatable structures for space habitats are highly prone to damage caused by micrometeoroid and orbital debris impacts. Although the structures are effectively shielded against these impacts through multiple layers of impact resistant materials, there is a necessity for a health monitoring system to monitor the structural integrity and damage state within the structures. Assessment of damage is critical for the safety of personnel in the habitat, as well as predicting the repair needs and the remaining useful life of the habitat. We are developing a unique impact detection and health monitoring system based on hybrid nanocomposite sensors composed of carbon nanotube sheet and coarse graphene platelets. An array of these sensors sandwiched between soft good layers in a space habitat can act as a damage detection layer for inflatable structures. We will further develop algorithms to determine the event of impact, its severity, and location on the sensing layer for active health monitoring.  Our sensor system will be tested in the hypervelocity impact testing facility at UDRI in future.

    Categories: Faculty-Staff

  • FMSG: Cyber: Perceptual and Cognitive Additive Manufacturing (PCAM)

    PI Daewon Kim

    CO-I Eduardo Rojas

    ​This grant supports fundamental research on a radical transformation of additive manufacturing through digitally connecting machines, humans, and manufactured products.

    This grant supports fundamental research on a radical transformation of additive manufacturing through digitally connecting machines, humans, and manufactured products. Additive manufacturing has enabled a new paradigm shift from conventional design for manufacturing approaches into manufacturing for design. A fundamental change in additive manufacturing is necessary as we enter a new era of intelligent future manufacturing beyond additive manufacturing. A promising solution is the convergence of wireless embedded sensors with artificial intelligence (AI) and machine learning (ML) data processes, which can transform the way people interact with manufacturing processes, factory operations, optimizing efficiency, and anomaly system detection that could provide critical information about evaluated components and systems. This project opens a new transitional door to perceptive and cognitive additive manufacturing, enabling true internet of things and digital twin, connecting devices and machines in factories with robots, computers, and humans, and every product we manufacture in factories. The grant will also support educational activities to upskill the manufacturing workforce, K-12, undergraduate and graduate students, and the public, significantly influencing diverse populations of all ages and backgrounds.

    Transformation to cyber-physical production manufacturing demands advanced process monitoring through distributed sensing beyond the current state of digitally connected machines and robots collaborating with humans. This project seeks to enable unprecedented wireless fingerprinting and sensing of additively manufactured parts by embedding wireless sensors and performing predictive analysis and health monitoring using AI and ML techniques. This project proposes a holistic approach involving four core research tasks: 1) to study the effects of embedding sensors during additive manufacturing; 2) to design embeddable acoustic sensors and insert them during the manufacturing process to read physical parameters; 3) to prove that embedded passive sensor signals can be sensed wirelessly using millimeter-wave antennas, and 4) to quickly monitor and evaluate the state of manufactured products using ML algorithms. This project has the potential to enable next-generation cyber-physical production systems.

    Categories: Faculty-Staff

  • In Service Performance of Pipe to Structure Connections

    PI Payal Kotecha

    Dr. Kotecha was awarded a research grant for $200,000 from the Florida Department of Transportation to investigate pipe-to-structure connections.

    This two-years project will investigate the performance of installed resilient connectors and typical brick and mortar connections. This will include field inspections and documentation within District 7 for resilient connectors. Additional investigations will also be conducted in other locations for structures with brick-and-mortar connections. These results will further evaluate the potential of statewide deployment of resilient connectors.

    Categories: Faculty-Staff

21-30 of 73 results