A combined finite element-multiple criteria optimization approach for materials selection of gas turbine components

A Shanian, AS Milani, N Vermaak, K Bertoldi… - 2012 - asmedigitalcollection.asme.org
A Shanian, AS Milani, N Vermaak, K Bertoldi, T Scarinci, M Gerendas
2012asmedigitalcollection.asme.org
The design of critical components for aerospace applications involves a number of
conflicting functional requirements: reducing fuel consumption, cost, and weight, while
enhancing performance, operability and robustness. As several materials systems and
concepts remain competitive, a new approach that couples finite element analysis (FEA) and
established multicriteria optimization protocols is developed in this paper. To demonstrate
the approach, a prototypical materials selection problem for gas turbine combustor liners is …
The design of critical components for aerospace applications involves a number of conflicting functional requirements: reducing fuel consumption, cost, and weight, while enhancing performance, operability and robustness. As several materials systems and concepts remain competitive, a new approach that couples finite element analysis (FEA) and established multicriteria optimization protocols is developed in this paper. To demonstrate the approach, a prototypical materials selection problem for gas turbine combustor liners is chosen. A set of high temperature materials systems consisting of superalloys and thermal barrier coatings is considered as candidates. A thermo-mechanical FEA model of the combustor liner is used to numerically predict the response of each material system candidate. The performance of each case is then characterized by considering the material cost, manufacturability, oxidation resistance, damping behavior, thermomechanical properties, and the FEA postprocessed parameters relating to fatigue and creep. Using the obtained performance values as design criteria, an ELECTRE multiple attribute decision-making (MADM) model is employed to rank and classify the alternatives. The optimization model is enhanced by incorporating the relative importance (weighting factors) of the selection criteria, which is determined by multiple designers via a group decision-making process.
The American Society of Mechanical Engineers
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