Stefano Agradi

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PhD thesis title: Development of a simplified multi-fidelity optimization framework for high-performance blading aerodynamics design of axial turbine multistage sections

Academic Tutor: Giacomo Persico

Academic Supervisors: Paolo Gaetani and Alessandro Romei

Affiliate external company or research group: Franco Tosi Meccanica S.p.A

PhD cycle: 40° (see all student profiles of the same cycle > LINK)

BSc: Mechanical Engineering, Politecnico di Milano
MSc: Mechanical Engineering, Politecnico di Milano

Thesis abstract

I am approaching the axial turbine design workflow to evolve it beyond its dependence on internal company standards and its highly iterative nature.
The industrially widespread process allows limited room for variations in blade design and their multi-stage coupling.
The net result is an iterative workflow that does not always guarantee optimality.

Personal interest in my research theme

Working within the turbomachinery industry, I am driven to achieve the best possible design outcomes by merging industry expectations with detail-oriented research.
In the current energy landscape, characterised by the need for decarbonization and rising energy demand, I believe conventional turbines remain central enablers for the emergence of new technologies.
Exploring the capabilities of new approaches to the design workflow, building on different optimisation strategies and multi-fidelity tools, allows me to tackle my daily challenges with a fascinating mix of creativity and rigour.