Embry‑Riddle partners with private and public entities to assist in developing solutions to today's and tomorrow's aeronautical and aerospace problems. Here at the world's largest aviation-oriented university, our focus on applied research is unique.
Filter by

161-170 of 206 results

  • Unmanned Aircraft Systems (UAS) Application to Support Aircraft Rescue and Fire Fighting (ARFF)

    PI Brent Terwilliger

    CO-I David Ison

    CO-I Dennis Vincenzi

    CO-I Dahai Liu

    This continuing research project features refinement of UAS application methods to support of ARFF responses. Previously, modeling and simulation, in combination with UAS attribute performance models, was implemented to better understand challenges, limitations, and potential benefits of UAS support. However, based on the findings and recommendations of the original inquiry, the research will be expanded to include examination of operator knowledge, skills, and abilities (KSAs), performance rating standards, and appropriate training requirements and delivery approaches.



    Our team of researchers from Embry‑Riddle Aeronautical University-Worldwide has been actively compiling published performance data associated with commercially-off-the-shelf (COTS) group 1 to 3 fixed-wing and vertical takeoff and landing (VTOL) unmanned aircraft systems (UAS) in an effort to develop statistical models of each category. The captured data, which includes maximum speed, cruise speed, endurance, weights, wind limitations, and costs, is used to calculate capabilities including range (one-way and return), time to objective, station keeping duration, and maneuver requirements. The benefit from assembling such a unified collection of information and the calculation of associated derived capabilities is that these models are anticipated to accurately reflect the capabilities, limitations, and considerations necessary in the assessment of such platforms for various applications and operating environments. These models will be available for combination with simulation or analysis frameworks to better assess end usability of these categories of aircraft for a significant number of applications including, emergency response, disaster relief, precision agriculture, security, tactical, communications, environmental study, infrastructure inspection, cargo delivery, and mapping/surveying.

    Publications:

    Terwilliger, B., Vincenzi, D., Ison, D., & Smith, T. (2015). Assessment of unmanned aircraft platform performance using modeling and simulation (paper no. 15006). In Volume 2015: Proceedings of the 2015 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC). Arlington, VA: National Training and Simulation Association.

    Terwilliger, B., Vincenzi, D., Ison, D., Herron, R., & Smith, T. (2015). UAS capabilities and performance modeling for application analysis.  In Proceedings of the Association for Unmanned Vehicle Systems International 42nd Annual Symposium. Arlington, VA: Association of Unmanned Vehicle Systems International.

    Ison, D., Terwilliger, B., Vincenzi, D., & Kleinke, S. (2015). Airport bird activity - monitoring and mitigation: The unmanned aerial system (UAS) approach.Presented at the 2015 North American Bird Strike Conference, Montreal, QC.

    Categories: Faculty-Staff

  • A Curriculum Wide Software Development Case Study

    PI Massood Towhidnejad

    CO-I Thomas Hilburn

    This NSF funded research develops case studies of software development for use in software engineering and computing instruction.

    Products include realistic projects, complete artifacts throughout the software development life cycle, case studies decoupled from a particular textbook, and case modules designed with varying complexity allowing for use in multiple classes throughout undergraduate and graduate curricula. 

    Categories: Faculty-Staff

  • Encouraging Students to Pursue an Engineering Education and Career

    PI Massood Towhidnejad

    This NSF-sponsored project provides scholarship for engineering students pursuing degrees in computer science, computer engineering, electrical engineering, mechanical engineering and software engineering.

    Working closely with faculty and student mentors, scholarship recipients are involved in multi-disciplinary projects involving unmanned and autonomous systems throughout their four years of undergraduate study.

    Categories: Faculty-Staff

  • From Middle School to Industry Vertical Integration to Inspire Interest in Computational Thinking

    PI Massood Towhidnejad

    CO-I Thomas Hilburn

    While students typically do not see immediate advantages of the topics being studies, top down integration exposes students to larger, more complex projects, giving them better appreciation for topics as they realize the “big picture.”

    Funded by the National Science Foundation, this research seeks to vertically integrate software development best practices from industry to graduate, undergraduate, high school, and middle school academic programs, with the intention of increasing student interest in computing and computational thinking.

    Categories: Faculty-Staff

  • Big Data Analytics for Injury Data

    PI Dothang Truong

    This project leverages big data analytics tools for the exploration and transformation of injury data for a major Part 121 carrier with the goal of predictive modeling. This project offers graduate students an opportunity to work with a substantial airline dataset under the supervision of a faculty member. The outcomes have the potential to lead to more extensive future projects in the realm of big data analytics. (This project is under strict NDA).


    Categories: Faculty-Staff

  • Developing Artifact Peer Review Assignment Methodologies to Maximize the Value of Peer Review for Students

    PI Matthew Verleger

    This engineering education research project seeks to develop a proof-of-concept peer review matching algorithm and demonstrate if it is a valuable and viable methodology for conducting peer review. Peer review is a proven method that has positive impact on student learning. The project will test the algorithm on Model Eliciting Activities in the engineering classroom, and investigate how changing peer review can affect student learning.



    ​The broader significance and importance of this project is the transformative potential of improving peer review processes, since peer review is used throughout STEM and medical fields. Thus this preliminary investigation can extend outside the realm of improving student learning. This project overlaps with NSF's strategic goals of transforming the frontiers through preparation of an engineering workforce with new capabilities and expertise. Additionally NSF's goal of innovating for society is enabled by supporting the development of innovative learning systems.

    ​


    Categories: Faculty-Staff

  • Platform for Investigating Concept Networks on the Instrumentality of Knowledge (PICNIK)

    PI Matthew Verleger

    This engineering education research project seeks to develop a concept network for engineering and a platform for helping students identify how concepts are connected across a curriculum.  The goal is to better understand and improve how students value the concepts being taught throughout their education.



    By data mining course materials (i.e., textbooks, course notes, syllabi, video transcripts, websites, etc.), a concept network can be developed for that course. With each additional resource, the network connectedness become more fully representative.  By mapping materials from courses throughout a curriculum, and then overlaying the resulting map on a degree plan of study, students will be able to better identify and value how concepts being taught today are connected and used throughout the rest of their education. For instructors, curricular redesign becomes significantly easier, as they will be able to more fully contextualize how other courses depend on their material.

    Categories: Faculty-Staff

  • Bayesian Analysis of Stellar Evolution

    PI Theodore von Hippel

    Bayesian Analysis of Stellar Evolution is an international collaboration studying stellar evolution with an emphasis on stellar ages. We also develop and support a Bayesian software suite that recovers star cluster and stellar parameters from photometry, currently called BASE-9.

    BASE-9 is useful for analyzing single-age, single-metallicity star clusters, binaries, or single stars, and for simulating such systems. BASE9 uses Markov chain Monte Carlo to estimate the posterior probability distribution for the age, metallicity, distance modulus, and line-of-sight absorption for a cluster, and for the mass, binary mass ratio, and cluster membership probability for every cluster member.

    Categories: Faculty-Staff

  • Optimizing Countermeasures for Spaceflight-Induced Deconditioning

    PI Christine Walck

    This research focuses on understanding space deconditioning and developing comprehensive systems to mitigate the adverse physiological effects of microgravity on astronauts.

    Spaceflight-induced deconditioning presents a major challenge to human health during and after long-duration missions, contributing to muscle atrophy, bone loss, cardiovascular dysfunction, and sensorimotor impairment. This research investigates the underlying mechanisms of physiological decline in microgravity and evaluates integrated mitigation strategies using a combination of ground-based analogs (e.g., head-down tilt, LBNP), biomechanical modeling, and real-time physiological monitoring. By developing a modular countermeasure system — featuring tools like the Lower Extremity Force Acquisition System (LEFAS) and personalized exercise protocols — we aim to preserve musculoskeletal and cardiovascular integrity throughout space missions. The findings contribute to NASA’s broader efforts in preparing astronauts for lunar and Mars exploration.

    Categories: Faculty-Staff

  • Small UAS (sUAS) Mid-Air Collision (MAC) Likelihood

    PI Ryan Wallace

    CO-I Dothang Truong

    CO-I Scott Winter

    CO-I David Cross

    This research focuses on sUAS MAC likelihood analysis with general aviation (GA) and commercial aircraft. Because severity research varies based on where a collision occurred on a manned aircraft, this likelihood research will not only look at the probability of a MAC, but also the likelihood of colliding with different parts of a manned aircraft.

    Complete Mid-Air Collision (MAC) risk assessments require estimates of both collision severity and collision likelihood. This research focuses on sUAS MAC likelihood analysis with General Aviation (GA) and commercial aircraft. Because severity research varies based on where a collision occurred on a manned aircraft, this likelihood research will not only look at the probability of MAC but also the likelihood of colliding with different parts of a manned aircraft.

    Categories: Faculty-Staff

161-170 of 206 results