Data-Centric Engineering in Aero-Engines - Pranay Seshadri, Cambridge

Explore data-centric engineering in aero-engines through this 45-minute conference talk by Dr. Pranay Seshadri from the University of Cambridge. Gain insights into the fascinating world of aero-engine design, operation, and research. Discover three key themes at the intersection of turbomachinery aero-thermodynamics and data-centric engineering: efficient blade design and manufacturing using subspace-based dimension reduction, experimental uncertainty estimation in engine performance, and computational fluid dynamics for simulating aero-engine performance. Learn about innovative approaches to address challenges in each area, including the Delta method for aggregating measurements, polynomial chaos for aleatory uncertainties, and machine learning for epistemic uncertainties in RANS models. Understand how these advancements can lead to more accurate simulations, reduced costs, and improved engine performance while adhering to strict emission and safety regulations.

Intro
Understanding efficiency
On temperature measurements
Individual temperature measurements
The road ahead for data-centric temperature measurements
Abstraction
Computational strategy
Geometry, parameterization and meshing
Flow physics simulations
Dimension reduction
Zonotopes
The inverse map
Flow capacity
Pressure ratio
Putting the pieces together
Different blades
Different operating points
Pedigree rules for manufacturing
Trusting computational simulations: aleatory perspective
Nasa Rotor 37
The challenges & strategies
Collaborators