
David Alvord
Georgia Insitute of Technology, GTRI
pmx
digital twin
ai/ml
predictive maitenance
mbse
virtual sensing
predictive maintenance
aiml
logistics
analytics
data science
machine learning
mission readiness
4
presentations
4
number of views
SHORT BIO
Mr. Alvord is a Senior Research Engineer at GTRI in the ATAS laboratory and serves as the Rocketry and Flight Instrumentation Branch (RFIB) Chief. His primary research areas include aeroacoustician, propulsion engineer, and Predictive Maintenance/Analytics (PMx/PMA). He is seen as a GTRI SME in rocketry and launch vehicle Test and Evaluation (T&E) and Modeling and Simulation (M&S), UAS acoustic T&E and analysis, and data pipeline improvements using AI/ML for PMx/PMA for improved aircraft readiness. He holds one patent in onboard UAS acoustic sensing, is an invited ASA conference presenter, and has multiple peer-reviewed publications. Mr. Alvord’s technical expertise has been recognized by his technical peers by being awarded the AIAA’s Advancements in Aerospace Engineering award, speaking as an invited AIAA Atlanta Chapter Distinguished Lecturer on rocketry propulsion systems and UAVs, receiving the ATAS Outstanding Technical Achievement Award, a MDA Certificate of Appreciation and a NASA Group Achievement Award. He was a PHM Society invited panelist for the “Perspective on Predictive Maintenance from the Joint AI Center’s Joint Logistics Mission Initiative Panel” November virtual Prognostics and Health Management Society Society Conference. He also represents GTRI as an AIAA Senior Member, an AIAA Aeroacoustics Technical Committee (TC) member, as an elected official on the Georgia Tech Faculty Senate as well as the GTRI Awards Council, serving as an AIAA conference paper reviewer, is Chairman of the GTRI/GT PMx/PMA Community of Interest, and mentoring GT Rocket Club students.
Presentations

Improving Mission Readiness using AI/ML Enabled Predictive Analytics
AnnMarie Spexet and 1 other author

Navy Applications Q&A Session
David Alvord and 6 other authors

Requirements Considerations for AI/ML Digital Twin Model Transition
David Alvord and 1 other author

Digital Twin Virtual Sensor Development for H-60 Accelerometer Data Reconstruction
David Alvord and 1 other author