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241-250 of 265 results

  • Self-sustaining Wind Energy Extraction Technique (SWEET) Using Multi-Level Control Design Methods



    This international collaboration project supported by NSF-BSF grant involves ERAU Departments of Aerospace Engineering (co-PIs: Dr. Vladimir Golubev and Dr. Reda Mankbadi) and Physical Sciences (PI: Dr. William MacKunis), and Israeli Technion University (co-PI: Dr. Oksana Stalnov). The primary scientific objective of the proposed research is to investigate and experimentally validate new physics-based closed-loop active flow control methods that can be utilized to enhance the fluid kinetic energy harvesting capability of oscillating foil-based wind energy harvesting systems. Specifically, some of the challenges addressed in the conducted research stem from the conventional inability to sustain limit cycle oscillations (i.e., plunging and pitching foil displacements) and achieve continual power generation in realistic, time-varying operating conditions. The scientific objective is achieved using a ground-up multidisciplinary approach, which synergistically combines the international collaborative efforts in (1) physics-based mathematical modeling and closed-loop control design and analysis; (2) development of high-fidelity computational fluid dynamics simulations to optimize foil geometry and to test closed-loop flow control methods; and (3) experimental wind tunnel testing and validation of new closed-loop oscillating foil-based fluid kinetic energy harvesting systems under realistic conditions that foils will encounter under atmospheric boundary layer.

    Categories: Faculty-Staff

  • Development of a Dynamic Soaring Capable UAV Using Reinforcement Learning



    Dynamic soaring (DS) is a bio-inspired flight maneuver in which energy can be gained by flying through regions of vertical wind gradient such as the wind shear layer. With reinforcement learning (RL), a fixed wing unmanned aerial vehicle (UAV) can be trained to perform DS maneuvers optimally for a variety of wind shear conditions. To accomplish this task a 6-degrees-of-freedom (6DoF) flight simulation environment in MATLAB and Simulink has been developed which is based upon an off-the-shelf unmanned aerobatic glider. A combination of high-fidelity Reynolds-Averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) in ANSYS Fluent and low-fidelity vortex lattice (VLM) method in Surfaces was employed to build a complete aerodynamic model of the UAV. Deep Deterministic Policy Gradient (DDPG), an actor-critic RL algorithm, was used to train a closed-loop path following (PF) agent and an Unguided Energy-Seeking (UES) agent. The PF agent controls the climb and turn rate of the UAV to follow a closed-loop waypoint path with variable altitude. This must be paired with a waypoint optimizing agent to perform loitering DS. The UES agent was designed to perform traveling DS in a fixed wind shear condition. It was proven to extract energy from the wind shear to extend flight time during training and further development is underway for both agents .

    Categories: Graduate

  • ). The Engagement of Non-Traditional Students in Online Engineering Pathways.

    This project aims to serve the national interest by identifying best practices for improving the persistence and advancement of adult and veteran students pursuing online engineering degrees. Through the introduction of peer leaders and synchronous recitation sessions, students will receive additional support beyond what is traditionally offered in online modalities. Moreover, peer-led team learning environments create safe havens where foundational math and engineering principles may be explored outside the instructor-student hierarchical structure. Learning from fellow students who recently completed the course can provide motivation, context, and example for undergraduate students, especially those from adult and veteran populations who may not be comfortable with online learning or perhaps have been out of the formal academic environment for some time. 




    The intent of the study is to inform instructional practice that other institutions can leverage to better support non-traditional students in online programs. The project will produce a peer leader training curriculum and peer-led team learning activities for introductory engineering courses including statics, aerodynamics, and digital circuits. In identifying social and academic factors under which students’ experiences in peer-led team learning produce better academic outcomes, this project hopes to advance pedagogical approaches for additional underrepresented populations and contribute to the increasing breadth of knowledge for the online education community.

    Peer-led team learning has proven to be effective in face-to-face classroom settings. The scope of the current project is to implement similar structural and pedagogical practices through development of a sustainable online model that is transferable to other institutions. Goals for this project include increasing commitment to online engineering pathways, improving student persistence and advancement in online engineering programs, and identifying and mitigating cultural and structural barriers associated with non-traditional student populations. Evidence from the study will be collected from students enrolled across multiple sections of introductory engineering courses and evaluated against control sections in developing a comprehensive set of best practices. Results will advance our understanding of peer-led team learning activities’ ability to produce both statistically significant and substantially greater gains in non-traditional students’ academic performance and identity development as part of the engineering community. The EHR program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.

    This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

    Categories: Faculty-Staff

  • OPTIMIS: Optimizing Human Performance in the Air Transportation Sector by Integrating Human Factors into Homeland Security Deterrence and Detection Procedures and Training: System Interfaces and Behavioral Screening at Security Checkpoints (Embry‑Riddle Aeronautical University Undergraduate Research Collaborative Grants Program 2023)

    This project addresses human performance optimization in commercial air transportation by integrating human factors principles into homeland security deterrence and detection tasks, procedures, training, and technology interfaces at airport security checkpoints.

    9/11 occurred as terrorists overcame security screening procedures. Subsequently, the Transportation Security Administration (TSA) was created as a component of the U.S. Department of Homeland Security founded 20 years ago. In today’s persistent threat environment, strengthening the airport security screening checkpoint with its holistic human, social, and technological ecology in mind is an ongoing challenge. This project addresses human performance optimization in commercial air transportation by integrating human factors principles into homeland security deterrence and detection tasks, procedures, training, and technology interfaces at security checkpoints. The project takes a systemic approach in identifying behavioral risk vulnerabilities of airport security screening checkpoints associated with human error in order to: (a) close effectiveness and efficiency gaps in user interaction with systemic elements and (b) enhance human reliability as a measure to improve overall system performance and hence air transportation security. The focus is on how well system components are designed to interface with human physiological and cognitive abilities and limitations. System components include equipment and technology, tasks, environment, and organizational elements. Organizational elements include scheduling/shiftwork, training, culture, communication, procedures, etc. Expected outcomes include focused controls associated with fatigue/circadian dysrhythmia and development of training materials for improved recognition of behavioral threat risks indicators. 

    Categories: Faculty-Staff

  • Analyticity and kernel stabilization of unbounded derivations on C*-algebras

    We first show that a derivation studied recently by E. Christensen has a set of analytic elements which is strong operator topology-dense in the algebra of bounded operators on a Hilbert space, which strengthens a result of Christensen. Our second main result shows that this derivation has kernel stabilization, that is, no elements have derivative eventually equal to 0 unless their first derivative is 0. As applications, we (1) show that a family of derivations on C*-algebras studied by Bratteli and Robinson has kernel stabilization, and (2) we provide sufficient conditions for when two operators which satisfy the Heisenberg Commutation Relation must both be unbounded.




    Categories: Faculty-Staff

  • Predictive Analytics for Unmanned Aerial Systems Deployment

    ​This research covers unmanned systems deployment in uncertain adversarial environments. Resilient logistics operations call for a holistic and crosscutting approach to proactively address both real-time and persistent adversarial events in several operational areas to outfit mobility platforms, networks, and C2 digital twin to support continued uninterrupted operations.

    This research covers unmanned systems deployment in uncertain adversarial environments. Resilient logistics operations call for a holistic and crosscutting approach to proactively address both real-time and persistent adversarial events in several operational areas to outfit mobility platforms, networks, and C2 digital twin to support continued uninterrupted operations. The research proposes the development of robust mobility platforms for UAV deployment and remote maintenance in adversarial environments with predictive logistics guarantees, including platform reliability evaluation, and remote inspection.

    Categories: Faculty-Staff

  • Pilot Response to Cybersecurity Events

    ​The first research uses the pilot cybersecurity event and risk assessment station located in the Cybersecurity Engineering Lab (LB 131).

    The first research uses the pilot cybersecurity event and risk assessment station located in the Cybersecurity Engineering Lab (LB 131). The station includes a Force Dynamics 401CR flight simulator and a digital twin for scenario development and analysis, and it allows for human systems research on aircraft crew response to external stimuli. The research results are intended to be used to build a training module for aircraft pilots.

    Categories: Faculty-Staff

  • Design Verification of Airborne AI/ML Systems

    ​The verification process of safety-critical systems must ensure system design performs all intended functionality within the required output ranges and safety limits. It must also ensure that no intended functionality is present having a risk larger than the stated development assurance level.

    The verification process of safety-critical systems must ensure system design performs all intended functionality within the required output ranges and safety limits. It must also ensure that no intended functionality is present having a risk larger than the stated development assurance level. The objective of the AI/ML-based system is to assist with the detection of unintended behavior during operations that results in enhanced online hazard analysis and risk mitigation. Validation and verification techniques must be developed for these systems with the future goal of adopting them in airborne operations.

    Categories: Faculty-Staff

  • Simulation Based Inquiry Oriented Linear Algebra

    CO-I Ashish Amresh

    Games that teach introductory concepts in linear algebra such as vectors, span and dependence are created to be used by instructors in an undergraduate class.

    ​A well-established National workforce need and critical challenge is to recruit and train students in Science, Technology, Engineering and Mathematics (STEM) fields. Since mathematics is a fundamental part of all STEM disciplines, success of undergraduate students in mathematics is a crucial ingredient to address this challenge. Linear algebra is a vital transition course for students in the STEM disciplines because of its unifying power within mathematics and its applicability to areas outside of mathematics. Accordingly, effective instruction at this stage in students' development is paramount. The focus of this project will be to improve teaching, learning, and student success in linear algebra by incorporating a blending of technology and several learning theories and applications to lead to new research results and production of curriculum resources. This project will leverage the investigators' previous research and curriculum development in Inquiry-Oriented Linear Algebra (IOLA) and expertise in Technology Based Learning to explore the unification of curriculum design and technology design theories and practices.

    The goals of the project are to: (1) create a digital platform that will equip students with a virtual experience of a version of the IOLA curriculum; (2) document the affordances and constraints for learning using a game platform (IOLA-G) in comparison to face-to-face instruction by experienced IOLA instructors; (3) compare different digital gaming formats to determine which are most conducive to inquiry-oriented learning; and (4) use the knowledge gained from (1), (2), and (3) to improve student learning through the developed technology, and, reflexively, to enhance the existing IOLA curriculum and teacher support resources. The project team will investigate students' mathematical activity and learning while the students are engaged with the digital platform and will use this insight to inform further refinement of design. Building on prior research efforts in the learning and teaching of linear algebra and expertise in Game Based Learning (GBL), the team will design IOLA-G to mimic the problem-centered approach of the existing IOLA curriculum and will iteratively refine this platform through teaching experiments with students throughout the project. The project also will explore the extent to which GBL can provide a dynamic approach to addressing the constraints that larger class sizes place on instructors' implementation of inquiry-oriented curricula. In addition to, and as part of the process of, creating the resource technology, the investigators will incorporate a mixed methods approach with a blending of game-based learning design, curriculum design theory, and research from inquiry-based learning to explore the following research questions: What are the mathematical practices that students engage in and the conceptual understandings students develop using IOLA-G compared to when using only the face-to-face IOLA curriculum? What are the affordances and constraints of different game environments in terms of enacting an inquiry-oriented curriculum? The impact of the project will include the positive effects on STEM discipline student learning, knowledge, abilities, and overall success, which will lead to strengthening United States workforce needs in STEM areas.

    Categories: Faculty-Staff

241-250 of 265 results