| description abstract | The concept and design of high-temperature heat pumps (HTHP) including their components for specific temperature needs is a time-consuming and interdisciplinary task. Especially, the design of compressor geometries have a big impact on the overall performance and the initial costs of the system. For this reason, in this work, an automated aerodynamic gradient-free optimization including structural constraints for the geometry of a radial compressor impeller blade as well as diffusor vane geometry for water steam, that is applied in a reverse Rankine cycle-based HTHP, is presented. The objective of the optimization is the isentropic efficiency in the aerodynamic design point (ADP) of the compressor. The requirements for the cycle simulation of the whole HTHP system and structural needs are satisfied by constraints for pressure ratio, mass flowrate, and limits for stresses in the blade and disk geometry. The optimization method is based on evolutionary algorithms and stochastical surrogate models. Additionally, a highly throttled operating point is regarded to achieve an acceptable distance to the surge line. These types of optimization problems are often characterized by many unconverged iterations due to unstable computational fluid dynamic (CFD) simulations. To encounter this, a study of the optimization process with different surrogate models is presented. The results are discussed with respect to convergence history as well as objective and constraint improvement. | |
