I went from being a student to a professional at Honeywell Aerospace.
Eager to make an impact, I soon realized that I was in the deep end of a highly specialized technical field. At a large aerospace organization, I continually initiated my own learning and actions to survive. This meant going above and beyond my day to day tasks by seeking out people and resources to become competent. I couldn’t let the same distractions I had in school hinder my work flow. I developed a new respect for discipline. The habits I cultivated led to my effectiveness. The familiar feedback was not always there so I needed to self-validate much of my progress. It was only after I gained experience that I was able to use skepticism and creativity to push back and refine on some of the already pre-existing processes the company had in place. The laid-out and highly acknowledged path of my academic career did not prepare me for the dynamic uncertainty of the “real world” that I encountered at Honeywell Aerospace.
I was hired as a System Modeling Engineer to build thermodynamic jet engine models to ensure safe operation by developing controls strategies. From this close work with the controls group, I soon switched roles to a Controls Systems Engineer to stretch my responsibilities by designing and validating the embedded software that governs the engine and communicates with the aircraft. This multi-disciplinary experience gave me a broader perspective across the product and enabled me to become a liaison between technical groups to ensure successful software design and implementation.
While working across both the System Modeling and Controls Systems teams, I supported several projects:
Designed, tested, and implemented engine controls software for a commercial turbo fan engine to improve acceleration times while preventing compressor surge.
Lead controls systems team in a rapid controls prototyping method to validate software before design reviews. New process implemented an automated tool that reduced rework by 60% and to help meet DO-178 requirements.
Develop fault detection and accommodation algorithm for a low-pressure turbine over-speed due to a severed shaft.
Implement pressure leak and surge indication control algorithm. Solution eliminates 9 loss of thrust field events.
Generate APU engine model with Simulink controller to size an electric starter 18% larger than its predecessor.
Program stability assessment GUI that freely evaluates engine operation through cross platform simulations. Improves simulation speed by 83% and gives new abilities to analyze the engine in the PC environment.
