Eric Trevisan
Study of a methodology to optimize preliminary design of aero engines.
Rel. Stefano Zucca. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Aerospaziale, 2026
Abstract
The current industrial context, characterized by high performance requirements, strong competitiveness and reduction of development times, makes it necessary to search for optimal solutions. In this context, this thesis aims at analyzing techniques of explorations and optimization, with focus on evaluating the architectural design of the engine and its rotating parts. The aim is to show how, even for these applications, it is possible to propose the use of optimization software with particular emphasis on process automation, to reduce the manual workload to the user. The use of the tool is then described: parameterization of models files, definition of a DOE, construction of meta-models (Fit) and mono and multi-objective optimization studies, highlighting critical issues such as choice of the number of runs, management of outliners and quality of Fits, as well as a series of emerging obstacles typical of the world of rotor dynamics.
The main contribution is the development of an automated workflow, based on Python script, where it is possible to insert Data Sources/Responses/Goals, launch DOE–Fit–Optimization in sequence and organize the outputs
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