The following are highlights of my research at ERAU. Please see my CV for a complete list of research projects and publications.

ASSURE FAA Center of Excellence for Unmanned Aircraft Systems

Funding Agency: Federal Aviation Administration

I am the ERAU site director and principal investigator for the FAA’s Center of Excellence for Unmanned Aircraft Systems as a core member for the Alliance for System Safety of Unmanned Aircraft Through Research Excellence (ASSURE). You can learn more about the Center of Excellence on the ASSURE@ERAU website. In addition to managing ERAU’s portfolio of FAA sponsored research under ASSURE, I have served or am serving as a research performer on several FAA sponsored projects under the COE including projects addressing:

  • Automation requirements and risk analysis for Urban Air Mobility

  • Flight data recorder requirements for small UAS

  • Impact of Urban Air Mobility on Air Traffic Control

  • Concepts of operations for Urban Air Mobility

  • Criticality of surveillance sensors for detect-and-avoid operations.

  • Impact of maintenance induced failures on the safety of the national airspace system.

  • Human Factors Considerations & Pilot and Crew Procedures for larger-than-small UAS systems integration.

  • Data analysis of existing aviation data sets to determine the existing impact and trends associated with FAA UAS integration efforts.

Aviation Big Data / Physics-informed Machine Learning for Aviation Weather Prediction

Funding Agency: ERAU Internal, NextGen Embry-Riddle Applied Research Laboratory

I am currently leading a team of graduate and undergraduate research students in exploring the integration of big data practices into aviation data analytics and machine learning. To date, the team has produced a Hadoop/Hive framework to integrate and facilitate queries upon flight track data from collected and stored Traffic Flow Management System (TFMS) XML messages. This data set is being utilized to identify instances in which safe separation between manned aircraft and detected unmanned air traffic is violated.

A major trial program under this initiative with PhD student, Gurvir Bawa, and colleague Dr. Christopher Herbster (ERAU Meteorology Program faculty) focuses on the development of a flight weather prediction tool for predicting weather future weather conditions and the likelihood of delay at airports using Physics-Informed Machine Learning techniques. The research integrates from the TFMS data information including flight information, delays reported for historical flight plans, airport traffic flow conditions, and weather data from NWS including METAR, local weather conditions, and GFS forecast data, among several others.

ADS-B for Commercial Space Applications

Funding Agency: FAA Commercial Space Office and Terminal Velocity Aerospace, Inc

Near space Corporation Nano Balloon System Launch

For this project, the MITRE UBR-TX ADS-B receiver has been modified to produce an advanced ADS-B receiver capable of supporting operation onboard reusable launch vehicles and sounding rockets.  The payload has flown onboard a number of platforms courtesy of NASA's Flight Opportunities Program.  

The goal of the UBR-ERAU, the payload, is demonstrate the viability of ADS-B as a mechanism for tracking commercial spacecraft. By broadcasting out the vehicle's location, velocity vector, and altitude once per second, equipped aircraft and air traffic controllers can track the spacecraft.  Ultimately, a greater awareness of the spacecraft's location during launch and descent can help mitigate the requirements for airspace sterilization (i.e. diverting air traffic) and improve their integration into the national airspace system.

Flight Tests To Date:

Student Dominic Tournour at SL-8 Launch

  • Near Space Corporation's Nano Balloon System, achieved an altitude greater than 95,000 ft.

  • Near Space Corporation's High Altitude Shuttle System, achieved an altitude near 105,000 ft.

  • Up Aerospace, Inc's SpaceLoft-8 Sounding Rocket, achieving an altitude near 380,000 ft.

Boeing HireU Job App

Funding Agency:  Embry-Riddle Aeronautical University

Sponsoring Organization:  The Boeing Company

This product is the direct result of a course that I taught Fall 2013.  For the Mobile Application Development course students were required to implement a fully functional (though not release ready) mobile application.  
I was approached by personnel of Boeing to invite students to produce a new application to assist in campus recruiting.  The application presents the current internship and entry-level opportunities.  After positive feedback in December 2013, the team was approved for continued effort in spring 2014 with corporate branding, beta testing, and moving the product toward eventual release.

Students: Jeffrey De Kort, Aaron Kersch, Umar Idris, Nicholas Victor, and Ryan Gauthier.

Disclaimer:  The final product has not been officially endorsed or released by The Boeing Company.  Implemented under a memorandum of understanding (MOU) between Boeing and ERAU to develop this application as part of a student project with the intent to possibly transition it to a corporate branded product. Regrettably, the project discontinued following personnel change at Boeing.

NOAA Gale UAS

Funding Agency: NOAA UAS Program

The Gale UAS was commissioned by NOAA for deployment from the WP-3D Orion Hurricane Hunter through its free-fall chute.  The aircraft features collapsed wings, which deploy dynamically after release.  It utilizes a MIST Sonde meteorological sensor package to receive real-time sensor data from the environment.  It is designed for deployment into a tropical cycle.

My role as co-PI has been to guide requirements, preliminary design, and test plans for the aircraft.

The next series of flight tests is anticipated in summer 2014.

Alternative Classification Schemes for Unmanned Aircraft Categorization

Funding Agency: NASA UAS NAS Integration Program

The goal of this project was to analyze through a literature survey the current approaches taken by various agencies/organizations to classify unmanned aircraft, which are needed as a basis for UAS regulations.  Additionally, UAS concepts of operations were analyzed to determine the various ways unmanned aircraft may be used.  The team contends that there are two approaches for classifying unmanned aircraft to guide regulations:  first, beginning with the aircraft's characteristics and capabilities to derive the set of missions for which the aircraft can be utilized; and second, begin with the UAS mission parameters to derive the aircraft capabilities and characteristics required to ensure safety.