61-70 of 85 results

  • Expanding the Nation’s STEM Talent Pool by Accelerating Graduate Degree Completion in Computer, Software, and Cybersecurity Engineering

    PI Omar Ochoa

    CO-I Massood Towhidnejad

    CO-I Debarati Basu

    ​The project will increase student persistence in STEM fields by linking scholarships with a newly created effective ecosystem that combines evidence-based practices such as faculty mentoring, academic advising, participation in the learning community, professional development activities, guidance in acquiring internships and research opportunities.

    This project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by fostering student success and supporting the retention and graduation of domestic, high-achieving, low-income students with demonstrated financial need at the Embry-Riddle Aeronautical University, a non-profit private institution. Over its six-year duration, this project will fund scholarships to 25 undergraduate students to pursue four-year bachelor’s degrees in Computer Science, Software Engineering, or Computer Engineering. Subsequently the scholars will pursue a one-year accelerated master’s degree in one of the following areas: Software Engineering, Electrical, and Computer Engineering, or Cybersecurity Engineering. First-year students will receive up to five years of scholarship support. The project will increase student persistence in STEM fields by linking scholarships with a newly created effective ecosystem that combines evidence-based practices such as faculty mentoring, academic advising, participation in the learning community, professional development activities, guidance in acquiring internships and research opportunities. With the help of mentors, the scholars will create individual development plans outlining their career goals and steps toward achieving those goals. The project will also include the evaluation of the impact of the ecosystem on supporting the academic success of scholars and the identification of best practices and lessons learned. This project will significantly contribute towards creating a model that actively engages students from groups underrepresented in STEM fields of study, broadens participation in STEM, and infuses 25 talented and diverse engineers with advanced degrees in engineering into the American workforce.

    The overall goal of this project is to increase undergraduate and graduate STEM degree completion of domestic, low-income, high-achieving undergraduates with demonstrated financial need in STEM field. Three specific aims guide the project. First is to deliver financial support to domestic, low-income, high-achieving students who will pursue an undergraduate and accelerated master’s degree in engineering. Second is to leverage evidence-based practices to foster student success, increase retention and degree attainment. Third, and finally, is to evaluate the impact of the newly created ecosystem in supporting the academic success of scholars in engineering, and disseminate best practices and lessons learned. Little is known about the factors that affect the academic success of domestic, low-income, high-achieving undergraduate students in engineering fields at a private institution, and how factors such as gender, ethnic background and discipline impact their success, which is the focus of this project. Two research questions will be investigated in this project: (a) Does the academic success of scholars improve across the years by being part of this project? (b) What were the factors effecting the academic success of the scholars, and what are the accomplishments, best practices, and lessons learned from implementing the ecosystem for the scholars? This project is funded by NSF’s Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income academically talented students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students.

    Categories: Faculty-Staff

  • Machine Learning Engineering: Infusing Software Engineering through the Semantic Web

    PI Omar Ochoa

    ​The Semantic Web provides a wealth of high-quality, structured, and contextual data, which can be used to train machine learning models.

    The Semantic Web provides a wealth of high-quality, structured, and contextual data, which can be used to train machine learning models. This can lead to the creation of models, i.e., the engineering of Machine Learning, that adhere to non-functional requirements, which include considerations such as safety, security, and reliability, which are key elements of Software Engineering. These requirements do not concern a system's functionality, but rather its quality attributes. By incorporating these concepts into the engineering of machine learning models, one can strive to create models that are secure, reliable, and exhibit the desired quality attributes. Furthermore, Verification and Validation, or V&V, is integral to successful software engineering, by ensuring that a system is implemented correctly and meets specified requirements. In engineering Machine Learning, it's equally important to define processes and methods to thoroughly test and validate models to ensure they're performing as expected and providing accurate results. Together, the fusion of Software Engineering principles into Machine Learning Engineering, aided by the Semantic Web's capabilities, can bolster trustworthiness in machine learning systems. This trustworthiness ensures that the systems can be relied upon to behave as expected. In essence, by combining these fields, one can develop machine learning systems that are reliable, secure, interpretable, and trustworthy, upholding the core principles of Software Engineering. Our research group focuses on the most recent developments in these areas, i.e., Knowledge Graphs and Large Language Models, to accomplish these goals.

    Categories: Faculty-Staff

  • Investigation of Bio-Inspired Cylinders for Enhanced Heat Transfer

    PI Anish Prasad

    CO-I Yogesh Pai

    CO-I Royce Fernandes

    CO-I Mark Ricklick

    This project investigates a novel cylinder design inspired from the Harbor Seal whisker, with the goal of reducing coolant pumping power requirements while maintaining heat transfer rates in pin-fin arrays. 

    ​

    Arrays of constant cross-section cylinders have been employed in many heat exchange applications. Increases in heat transfer rates characteristically result in an increase in the coolant pumping power requirements, which can be quite high for a circular cylinder array. Pin fin channels are often used at the trailing edge of the blades where they also serve an additional purpose of providing structural support. It has been found that the behavior of the flow around a wall-mounted cylinder significantly impacts the heat transfer. The boundary layer becomes broken up by the presence of the pin, creating a horseshoe vortex. This horseshoe vortex produces high wall shear stress beneath it, resulting in high heat transfer from the wall in this region. The resulting flow separation around the pin, however, results in large pressure losses. The pin fin channel has been heavily studied in the literature, in an effort to describe the heat transfer and flow behavior and improve prediction abilities. The circular cylindrical pins are relatively easy to manufacture and hence, this configuration is often found in commercial applications. However, the need to reduce pressure drop and maintain the heat transfer rates are a much needed requirement for a variety of industries to improve the cooling efficiency.

    One such prominent line of research is conducted on optimizing the design of the circular cylindrical pins to increase their cooling performance. In this line of research, it was found that bio-mimicked harbor seal whisker geometry leads to the reduction in the cooling system pumping power requirements, while maintaining or improving heat transfer rates. The seal whisker geometry consists of stream-wise and span-wise undulations which reduce the size of the wake and coherent structures shed from the body as a result of an added component of stream-wise vorticity along the pin surface. Also, the vortex shedding frequency becomes less pronounced, leading to significantly reduced lateral loading on the modified cylinder. Preliminary computational studies have shown that the modified wake and vortex shedding structures resulting from the geometry tend to reduce the total pressure loss throughout the system without degrading the cooling levels.

    Seal whisker and proposed bio-inspired cylinder:

    Three different cross-section types, one elliptical, one of circular cross section and a 0.25X axially scaled type of the bio inspired pin were created for further investigation along with two baseline circular cylindrical and elliptical pins. Computational analysis for an array of the above three shapes and a standard elliptical cross-section pin array was undertaken. The results obtained were compared with the baseline circular cylindrical pin array. The main purpose of this research is to describe the heat transfer and flow characteristics of 3 novel bio inspired pin designs using steady and unsteady Reynolds-Averaged-Navier-Stokes (RANS) based simulations, in an effort to better understand their performance. These findings are important to the gas turbine community as reduced penalties associated with cooling flows directly translate to improved thermodynamic and propulsive efficiencies.

    Pin-fin geometries analyzed:

    Further computational research is being conducted in these geometries, and later will be compared with the experimental results, which will be carried out in Embry-Riddle's Gas Turbine Laboratory.

    ​


    Categories: Graduate

  • Investigate Detect and Avoid Track Classification and Filtering

    PI Richard Prazenica

    CO-I Troy Henderson

    CO-I Morad Nazari

    CO-I Tyler Spence

    This research will identify key sources of uncertainty in representative detect and avoid architectures and assess the downstream risks and effects of spurious information on downstream system performance

    In this project, which is funded by the FAA ASSURE program, the research team consisting of The Ohio State University, Embry‑Riddle Aeronautical University, Mississippi State University, University of North Dakota and Cal Analytics will work together to:

    • Identify the key sources of misleading surveillance information produced by airborne and ground-based detect and avoid (DAA) systems. Develop risk modeling and analysis tools to assess the system-wide effects of false or misleading information on alerting and separation, as well as impacts on pilots in command (PIC) and air traffic operators.
    • Provide guidance and recommendations for track classification and filter performance and safety requirements to standards bodies, including Radio Technical Commission for Aeronautics (RTCA) and American Society for Testing and Materials (ASTM) DAA working groups, and inform Federal Aviation Administration (FAA) rulemaking on DAA operations.

    Current guidance provided by the Federal Aviation Administration has made beyond visual line of sight (BVLOS) missions an executive priority. Key to the success of these missions is the development of DAA systems capable of providing accurate pilot in the loop, or autonomous deconfliction guidance. Current standards for DAA services provided by RTCA and ASTM do not address the requirements for system performance with respect to generation of false or misleading information to the PIC or autonomous response services of the unmanned aircraft system. This research will identify key sources of uncertainty in representative DAA architectures and assess the downstream risks and effects of spurious information on downstream system performance. Additionally, recommendations will be developed for track classification accuracy requirements that provide sufficient safety margins for enabling DAA services in support of BVLOS missions.

    Categories: Faculty-Staff

  • Researching How You Teach Holistic Modeling (RHYTHM)

    PI Kelsey Rodgers

    CO-I Matthew Verleger

    CO-I Lisa Davids

    "Models are a critical part of the analysis and design of engineered systems. The purpose of multiple types of models (physical, mathematical, computational, and financial) is to provide a simplified representation of reality that mimics the features of the engineered system, and that predicts the behavior of the system. This project, a collaboration between Embry-Riddle Aeronautical University, San Jose State University, and the University of Louisville, aims to improve engineering students' modeling competence. The project plans to achieve this goal by transforming first-year engineering courses to teach modeling as an engineering tool. The project will change existing course materials, pedagogy, and assessment methods across the three institutions. Each institution will implement its own specific strategy to teach mathematical, physical, computational, and financial modeling, thus providing three different approaches. By comparing student's modeling abilities across the institutions and approaches, the project aims to identify the most impactful approaches for teaching multiple modeling in introductory undergraduate engineering courses.

    The project is guided by a "holistic modeling perspective" theoretical framework, that builds on the successful "Models and Modeling Perspective" and "Computational Adaptive Expertise" frameworks. The objectives of the project are to: (1) implement, test, and refine holistic modeling environments for institutions that have flexibility in changing curriculum and for instructors that have different degrees of interest in changing their course(s); (2) implement, test, and refine methods to assess students' modeling abilities; and (3) evaluate and present the results of modeling abilities attained by students at three different universities. A unified language and discussion around modeling will be adopted in all revised courses. An assessment tool to measure students' modeling competence will be developed and implemented at each university. This work builds upon existing research in the development of more easily adaptable and adoptable modeling pedagogies and modeling languages. The following broad research question guides the research: How do students' definitional knowledge, ability to apply, and ability to create models change based on different degrees of modeling integration in the classroom?

    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

  • CAREER: Additively Manufactured 3D Reconfigurable Antennas

    PI Eduardo Rojas

    ​The focus of this CARRER development project is on an emerging antenna fabrication technique that combines additive manufacturing (AM) and pulsed laser machining that has the potentials to fundamentally alter the existing state of the art. 

    Antennas are key components of ubiquitous wireless communication, radar, and navigation systems that affect widespread societal needs, such as aerospace systems, healthcare, and space exploration. Most of the antennas used in a variety of applications including cellular phones to unmanned aircraft systems (UAS) are based on flat planar structures or wire geometries that are developed using traditional manufacturing technique. This approach does not allow designers the opportunity to fully leverage the geometry, space, and materials available to design better performing antennas. The focus of this CARRER development project is on an emerging antenna fabrication technique that combines additive manufacturing (AM) and pulsed laser machining that has the potentials to fundamentally alter the existing state of the art. The proposed research will allow engineers to implement smaller, efficient, lighter, and reconfigurable antenna embodiments in three-dimensions (3D) for future applications with increasing complexity. The research proposed in this project is fully integrated with an education and outreach plan. The educational plan will impact the next generation of professionals by exposing high school students to hands-on activities and videos to explain basic antenna engineering concepts. The videos will be made by accomplished engineers in the engineering field to have a strong role-model-based motivational component to stimulate them to pursue STEM careers. An advanced cellular phone-based teaching tool that allows engineering undergraduate students to visualize complex 3D concepts in electromagnetics and antenna engineering is also proposed.

    The overall goal of this project is to pursue the discovery of the next generation of antennas with reconfigurable performance while conserving size, weight and cost. Research initiatives include: (a) the investigation of novel additive manufacturing processes for the fabrication of conformal 3D multiple curved antennas based on laser-enhanced direct print AM (LE-DPAM) with femtosecond laser machining and 5-axis kinematics, (b) the study of bio-inspired 3D superior antenna geometries that are not possible to manufacture using traditional methods but are conceivable using LE-DPAM, (c) the development of design methods based on a novel 3D to 2D conformal mapping technique, (d) the study of embedded material- and IC-based reconfigurability mechanisms including the use of electrically tunable inks that can be deposited on conformal surfaces, as well as IC-based switches for reconfiguration of antenna feeds and loads, and (e) the investigation of the structure-property relationships of commercially available and custom-formulated inks that provide excellent electromagnetic performance while addressing the needs for aviation and space environments.

    Categories: Faculty-Staff

  • FAA ASSURE Center of Excellence for Unmanned Aircraft Systems

    PI Richard Stansbury

    ERAU has completed or is conducting research tasks addressing the impact of maintenance induced failures on UAS safety; the function allocation of systems operations between automated systems, remote pilots, and support crew, surveillance criticality for detect, and avoid systems; impact of UAM air traffic on air traffic controllers; data analysis to determine the impact of UAS on the NAS, UAS flight data recorder requirements, etc.



    ASSURE or the Alliance of System Safety for UAS through Research Excellence is a multi-university center designated by the Federal Aviation Administration (FAA) as its Center of Excellence for Unmanned Aircraft Systems established in 2015. As a core and founding member of ASSURE, ERAU sponsorship to conduct research enabling the integration of unmanned aircraft systems (UAS), advanced air mobility (AAM), and urban air mobility (UAM) in the National Airspace System (NAS). New funding opportunities come available 1-3 times per year.

    ERAU has completed or is conducting research tasks addressing the impact of maintenance induced failures on UAS safety; the function allocation of systems operations between automated systems, remote pilots, and support crew, surveillance criticality for detect, and avoid systems; impact of UAM air traffic on air traffic controllers; data analysis to determine the impact of UAS on the NAS, UAS flight data recorder requirements, etc.

    Categories: Faculty-Staff

  • ASSURE A55

    PI Richard Stansbury

    PI Christopher Herbster

    The aviation industry uses flight data recorders (FDR) and cockpit voice recorders (CVR) to investigate accidents and incidents. FDRs record sensor data to provide information about an aircraft’s technical status, while CVRs record sounds from the cockpit to draw conclusions through crew communications and environmental sounds.

    The aviation industry uses flight data recorders (FDR) and cockpit voice recorders (CVR) to investigate accidents and incidents. FDRs record sensor data to provide information about an aircraft’s technical status, while CVRs record sounds from the cockpit to draw conclusions through crew communications and environmental sounds. The American National Standards Institute (ANSI) Unmanned Aircraft Systems Standardization Collaborative (UASSC) standardization roadmap v2.0 indicates that there are significant gaps regarding these flight recorders for UAS. Therefore, the purpose of this project is to close these gaps and define appropriate requirements for FDR and CVR for UAS in the national airspace.

    The project is divided into subtasks. The first major step is the literature review of current data recorder standards, technologies, and their requirements for UAS and UAM aircraft. The requirements of various government organizations and institutions are analyzed in this step. The next step is to examine the requirements found. Within this task, it is investigated how applicable the existing requirements are to various categories of UAS. If there are problems adapting these requirements, the corresponding standards will be adjusted. The research will especially focus on test procedures for crash survival, methods for data recording, and the minimum data required.

    Categories: Faculty-Staff

  • Mixing of a supercritical jet in a supercritical cross-flow

    PI Neil Sullivan

    CO-I Mark Ricklick

    This project is focused on the exploration and validation of numerical modeling techniques, for the simulation of supercritical jets in crossflow. 

    ​The injection of fuels and oxidizers into combustion chambers is often performed at near-critical or supercritical (SC) temperatures and pressures. At the critical point, the surface tension and enthalpy of vaporization of a fluid approach zero. This means there is no droplet formation in a jet, and also no density change between phases. The fluid has in effect only one supercritical phase, and has both liquid-like and gas-like properties. Physical and thermodynamic properties of the fluid have large gradients near the critical point, and this has led to complications in numerical simulation of even simple flow phenomena at this condition.

    It is desired to simulate the mixing and subsequent combustion of certain supercritical fluids for application to the design of SC-CO2­ combustion power generation. SC methane and oxygen will be burned in an atmosphere of SC carbon dioxide, allowing highly efficient power extraction using smaller turbomachinery than in traditional Brayton or Rankine cycles. The study of SC methane jets also has applications to liquid rocket propellant injection and jet impingement rocket nozzle cooling.

    Reynolds-Averaged Navier Stokes (RANS) and Large Eddy Simulation (LES) numerical studies are conducted to investigate the diffusion-driven mixing of one or more species in a SC jet, with another species in a SC cross-flow. Real-gas effects will be captured using the Peng-Robinson cubic equation of state. Benchmarking is performed against previous experimental and LES studies performed on near-critical and SC jets in quiescent fluids. The commercial code STAR-CCM+ is used for the simulation.

    Improved prediction of jet behavior at near-critical and SC pressures and temperatures will better inform combustor design, combustion efficiency and thermodynamic efficiency.

    Ideal gas axisymmetric simulation of a sub-critical nitrogen jet

    Categories: Graduate

  • Secret Sharing Over a Gaussian Broadcast Channel: Optimal Coding Scheme Design and Deep Learning Approach at Short Blocklength

    PI Rumia Sultana

    ​We consider a secret sharing model where a dealer shares a secret with several participants through a Gaussian broadcast channel such that predefined subsets of participants can reconstruct the secret and all other subsets of participants cannot learn any information about the secret.

    We consider a secret sharing model where a dealer shares a secret with several participants through a Gaussian broadcast channel such that predefined subsets of participants can reconstruct the secret and all other subsets of participants cannot learn any information about the secret. Our first contribution is to show that, in the asymptotic blocklength regime, it is optimal to consider coding schemes that rely on two coding layers, namely, a reliability layer and a secrecy layer, where the reliability layer is a channel code for a compound channel without any security constraint. Our second contribution is to design such a two-layer coding scheme at short blocklength. Specifically, we design the reliability layer via an autoencoder, and implement the secrecy layer with hash functions. To evaluate the performance of our coding scheme, we evaluate the probability of error and information leakage, which is defined as the mutual information between the secret and the unauthorized sets of users channel outputs. We empirically evaluate this information leakage via a neural network-based mutual information estimator. Our simulation results demonstrate a precise control of the probability of error and leakage thanks to the two-layer coding design.

    Categories: Faculty-Staff

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