Active subspaces for the preliminary fluid dynamic design of unconventional turbomachinery

Active subspaces for the preliminary fluid dynamic design of unconventional turbomachinery

Bahamonde, Juan S. (TU Delft Flight Performance and Propulsion)
Pini, M. (TU Delft Flight Performance and Propulsion)
Colonna, Piero (TU Delft Flight Performance and Propulsion)

2016

The fluid dynamic preliminary design of unconventional turbomachinery is customary done with meanline design procedures coupled with gradient-free optimizers. This method features various drawbacks, since it might become computationally expensive, and it does not provide design insights or guidelines to the designer. This work proposes a strategy to abate this disadvantages, namely, the construction of a reduced-order model by means of active sub-spaces, and the use of the surrogate combined with a gradient-based optimizer. The case study is the design optimization of a Organic Rankine Cycle radial inflow turbine. The results show that active subspaces exist for this application, and that it is possible to construct a surrogate with an approximate error of ±1% for the total-to-static efficiency. Additionally, the optimization using the surrogate leads to accurate results and a computational cost at least four times faster. Furthermore, the results reveal that the models for unconventional turbomachinery feature multiple regions containing constrained optima. Active subspace methods thus prove to be a promising alternative for optimization of unconventional turbomachinery.

Active subspaces
Organic rankine cycle
Surrogate models
Turbine design

http://resolver.tudelft.nl/uuid:d002f351-7d9e-4db4-ad09-7dfa7ed179b8

National Technical University of Athens

9786188284401

ECCOMAS Congress 2016 - Proceedings of the 7th European Congress on Computational Methods in Applied Sciences and Engineering, 4

7th European Congress on Computational Methods in Applied Sciences and Engineering, 2016-06-05 → 2016-06-10, Crete, Greece

Institutional Repository

conference paper

© 2016 Juan S. Bahamonde, M. Pini, Piero Colonna