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21-30 of 263 results

  • Gravitation

    PI Quentin Bailey

    CO-I Andri Gretarsson

    CO-I Brennan Hughey

    CO-I Michele Zanolin

    CO-I Preston Jones

    Einstein’s theory of General Relativity offers a remarkable description of gravity as curved space and time. Many of the consequences of this theory have been confirmed, and some are used daily, such as the gravitational redshift effect on GPS satellite atomic clocks. In 2015, the first observation of a gravitational wave from two inspiraling black holes occurred using the gravitational wave observatories as part of the worldwide LIGO-VIRGO collaboration. This discovery won the Nobel prize, and the observations of these events have continued, including a multi-messenger event of two colliding neutron stars.



    Embry‑Riddle Prescott faculty and student researchers are part of the LIGO-VIRGO collaboration and work on aspects of detecting and studying gravitational waves. Faculty and students also study more broadly tests of the foundational principles of General Relativity, such as spacetime symmetries like Lorentz symmetry. These tests include gravitational wave observation but also solar system tests like short-range gravity and lunar laser ranging.  One of the long-standing problems in gravity research is the connection between gravity and quantum field theory. Our faculty is actively working on this problem and, in particular, the relation between gravity and electromagnetism.  There are both theorists and experimentalists among the faculty at ERAU Prescott. Most faculty receive funding from the National Science Foundation and regularly publish articles in to journals, many with students involved.

    Categories: Faculty-Staff

  • Incorporating ANSYS Simulation Tools Into Engineering Programs at Embry‑Riddle Aeronautical University

    PI Fady Barsoum

    CO-I Arka Das

    CO-I Heidi Steinhauer

    CO-I William Engblom

    CO-I Chad Rohrbacher

    This project aims to introduce and implement ANSYS computer modeling and simulation tools into the Engineering Programs at Embry‑Riddle.

    This project aims to introduce and implement ANSYS computer modeling and simulation tools into the Engineering Programs at Embry‑Riddle. Utilizing ANSYS in the undergraduate curriculum significantly enhances learning outcomes. It allows students to visualize complex physical phenomena, providing clarity on theoretical concepts. Additionally, hands-on experience with the software aligns students with industry standards, preparing them for future careers. Project-based learning fosters essential problem-solving skills. Finally, interactive simulations boost student engagement, making engineering topics more appealing.

    Categories: Faculty-Staff

  • Predicting General Aviation Accidents Using Machine Learning Algorithms

    PI Bradley Baugh

    CO-I Bruce Conway

    Aviation safety management is implemented through reactive, proactive, and predictive methodologies. Unlike reactive and proactive safety, predictive safety can predict the next accident and enable prevention before an actual occurrence. The study outlined here promotes predictive safety management through machine learning technologies using large amounts of data to facilitate predictive modeling.



    The study addresses efforts to reduce General Aviation accidents, an effort that was renewed in earnest with the Federal Aviation Administration’s 1998 Safer Skies Initiative. Over the past 22 years, the General Aviation fatality rate has decreased. However, accidents still happen, and there is some evidence showing the number of accidents, representing hazard exposure, is increasing. The accident data suggest that the aviation community still has more to learn about the variables involved in an accident sequence.

    The purpose of the study was to conduct an exploratory data-driven examination of General Aviation accidents in the United States from January 1, 1998, to December 31, 2018, using machine learning and data mining techniques. The goal was to determine what model best predicts fatal and severe injury aviation accidents and further, what variables were most important in the prediction model.

    The study sample comprised 26,387 fixed-wing general aviation accidents accessed through the publicly accessible National Transportation Safety Board Aviation Accident Database and Synopses archive. Using a mixed-methods approach, the study employed both unstructured narrative text and structured tabular data within the predictive modeling. First, the accident narratives were culled using text mining algorithms to develop text-based quantitative variables. Next, data mining algorithms were used to develop models based on both text- and data-based variables derived from the accident reports.

    Five types of machine learning models were created using SAS® Enterprise Miner™, including the Decision Tree, Gradient Boosting, Logistic Regression, Neural Network, and Random Forest. Additionally, three broad sets of variables were used in modeling, including text-only, data-only, and a combination of text and data variables. Three models, Logistic Regression (text-only variables), Random Forest (text-only variables), and Gradient Boosting (text and data variables), emerged with a similar prediction capability. The top six variables within the models were all text-based covering Medical, Slow-flight and stalls, Flight control, IMC flight, Weather factors, and Flight hours topics. The Logistic Regression (Text) model was selected as the champion model: Misclassification Rate = 0.098, ROC Index = 0.945, and Cumulative Lift = 3.46.

    The results of the study provide insights to the entire General Aviation community, including government, industry, flight training, and the operational pilot. Specific recommendations include the following areas: 1) improve the quality and usefulness of accident reports for machine learning applications, 2) investigate ways to capture and publish more open-source flight data for use in safety modeling, 3) invest in additional medical education and find ways to address impairing medications and high risk medical conditions, 4) renew efforts on improving flight skills and combatting decision-based errors, 5) emphasize the importance of weather briefings, pre-flight planning, and weather-based risk management, and 6) create an aviation-specific corpus for text mining to improve text analysis and transformation.

    Categories: Graduate

  • Aircraft Boarding Strategies

    PI Massoud Bazargan

    Airlines today employ various strategies to cut costs and become lean and efficient.

    One of the ways that this can be achieved is by improving the boarding process since airplanes only make money while they are in the air. This paper uses simulation approach to deal specifically with the boarding strategies in use today by the major airlines. To properly simulate the boarding process, the simulation model accounts for passenger interferences (aisle & seat), the time it takes to stow away baggage, and the passenger arrival rate through the main cabin door. We applied our simulation model to study the AirTran Boeing 737-700 short haul aircraft. We looked at five major boarding strategies from random to the customary back to front and the results are very encouraging. Our analyses identifies that the arrival rate has an effect on the total boarding time and that the Reverse Pyramid and Window middle Aisle (WilMA) were among the efficient boarding strategies.

    Categories: Faculty-Staff

  • Aircraft Replacement Strategy

    PI Massoud Bazargan



    The analyses of this study attempts to address:
    • How the cost data relevant to this study, such as aircraft market values, lease prices, operations and maintenance costs were compiled and analyzed as the airlines do not or cannot provide them.
    • Identify aircraft replacement strategies for the airlines and explore their differences according to their business models.
    • Compare and contrast the recommended and current aircraft replacement strategies for the airlines.
    • Identify decisions with respect to lease and/or buy for the airlines and how sensitive these strategies are to changes to aircraft values and lease prices.
    • Explore future fleet diversity for the airlines and how sensitive these strategies are to their existing and on-order fleet.
    • How the fixed costs pertaining to aircraft buy and/or lease compare and contrast with variable costs such as operations and maintenance over the planning horizon.

    Categories: Faculty-Staff

  • A Database Management System for General Aviation Safety

    PI Massoud Bazargan

    CO-I Michael Williams

    CO-I Alan Stolzer

    The research team at Embry‑Riddle proposes to conduct a series of analyses to find patterns and associations among general aviation (GA) accidents and incidents.

    This research work is intended to provide the FAA with analyses of fatal and non-fatal accidents by examining the NTSB database and recommending strategies to mitigate risks associated with such events.Some of the potential studies that the team proposes to conduct include: analysis of primary ten causes leading to fatal and non-fatal accidents for each region by aircraft complexity and pilot demographics, statistical analyses on existing General Aviation accidents and incidents NTSB database on a national and regional basis to identify associations and patterns between flight elements and risk factors. This study will address multiple factors including pilots' demographics, light conditions, weather conditions and equipment used.

    Categories: Faculty-Staff

  • A Simulation Approach to Manpower Planning at Continental Airlines

    PI Massoud Bazargan

    This research relates to the development of a computerized line maintenance simulation model for strategic manpower planning at Continental Airlines for one of their major maintenance stations at Newark airport.

    The simulation model provides guidelines to the development of enhanced staffing models and a better understanding of resource requirements on a daily basis. The proposed simulation model could be used as a tool to support the management of the line maintenance department in solving various capacity planning issues related to the manpower requirement and scheduling. The recent capabilities of simulation modeling, namely optimization modeling is adopted in search of enhanced shift schedule of technicians that would improve the efficiency of the existing system.

    Categories: Faculty-Staff

  • A Simulation Study to Determine Optimal Shipping Strategy

    PI Massoud Bazargan

    The purpose of the project is to develop a simulation that can serve as means for choosing the optimal shipping option based on given criteria.

    This project comes from AAR Airlift, a maintenance supply chain organization that frequently sends packages overseas. The ultimate goal is to develop two separate deliverables for AAR Airlift airline efficient use of available resources and reduce flight delays. The project uses simulation for one full day of an airline's operations. The simulation model developed can identify the number of delays as well as the total time of delays that may occur throughout the system due to shortage of maintenance workforce.

    Categories: Faculty-Staff

  • Development of an Aviation Weather Database Highlighting Weather Encounters

    PI Massoud Bazargan

    The project team, which includes the FAA's Civil Aerospace Medical Institute, Clemson University, and Embry‑Riddle Aeronautical University, interviewed 26 General Aviation (GA) pilots over a 25-month period.

    The hope is that a list of items and/or data points that investigators can use to gain a better understanding of what happened within a particular weather incident/accident can be generated.

    Categories: Faculty-Staff

  • GA Airport funding strategies

    PI Massoud Bazargan

    The purpose of this study was to investigate the current financial environment of publicly owned and operated general aviation airports, and to develop an outlook for future potential.

    The study focused on basic airport demographic data and the views of airport managers of GA airports regarding their facility's current financial situation, access to finding resources, state, local, and private sector, current fuel handling activity, T-hangar vacancies, other concepts for enhancing revenue, and attitudes toward attaining financial self-sufficiency.

    Categories: Faculty-Staff

21-30 of 263 results