The term “digital twin” had circulated in NASA roadmapping work, but this paper by Edward Glaessgen (NASA Langley Research Center) and David Stargel (Air Force Office of Scientific Research), presented in April 2012 at the AIAA Structures, Structural Dynamics and Materials Conference, gave it the definition most cited since. It frames the digital twin as a vehicle’s living virtual counterpart used to predict structural health and extend safe service life.
The paper defines the digital twin as a system that integrates ultra-high fidelity simulation with the vehicle’s onboard health-management system, maintenance history, and all available historical and fleet data to “mirror the life of its flying twin and enable unprecedented levels of safety and reliability.” The motivation was that conventional certification and fleet management - based on physical testing and statistical averages across a fleet - could not keep up with the demands placed on next-generation aircraft and spacecraft, which fly closer to their limits and need individualised life predictions.
For a business reader, this paper is the reference point for a concept that has since spread far beyond aerospace into manufacturing, energy, and infrastructure: keeping a continuously updated virtual model of a real asset so you can predict failures and optimise operations before problems occur.