Digital Twins – An Emerging Technology for Aero Engines

Ashok K Koul

ABSTRACT

Similitude, experience and heuristics play vital role over the entire life cycle management of aero-

engine, starting from design and manufacturing to certification, maintenance and sustainment. Effect of

the associated uncertainties in every step are mitigated with large factors-of-safety that are ultimately

borne by engine owners. Emergence of Digital Twin capability is a paradigm shift, where multi-scale and

multi-physics model-based simulation and data analysis is replacing the requirement of numerous

iterations and trials, expensive testing, restrictive heuristics and limited experience. Digital Twins for

aero-engines directly translate to deeper understanding of the asset under actual usage, reduced

development cycle, quantified certification, reduced maintenance cost and higher sustainability.

Digital Twin is providing unprecedented insight into the behavior of the physical engine at both system-

level performance and component-level structural health under operative loads, beyond the realm of

any sensor. It utilises material-physics modeling, simulation and AI driven data analytics to provide

detailed quantitative information about the engine. Capability to handle variability in design,

manufacturing, in-service degradation in the engine health and performance is included to ensure high

predictive accuracy and upfront quantify reliability of the Digital Twin.

This talk shall illustrate the proven applications of Digital Twins for design, certification and predictive

maintenance of aero-engine components.