Alexis Cantizano

Efficient Multi-objective Optimization for Gas Turbine Discs

An original multi-objective optimization strategy for aeronautical gas turbine discs is presented in this chapter. A sensitivity analysis together with an optimal design of experiments (DoE) are accomplished prior applying a multi-objective genetic algorithm (MOGA) based on a Kriging surrogate model. Fatigue life prediction and total geometry mass are taken as optimization objectives in this work, whose results can be validated against laboratory tests but going further experimental conditions. To begin with, (i) a first case study considers laboratory test conditions, basically centrifugal loads due to the blades and the own mass of the disc. However, (ii) a second case study considers real conditions such as the centrifugal loads, airflow forces and thermal loads as well as taking into account different typical materials for this application. Results show that the proposed methodology successfully leads to the optimal geometric parameters both for laboratory and real conditions. The main conclusions and qualitative differences are finally summarized, highlighting the suitability of A718Plus among other materials and the Cob width parameter as the most critical one.