English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Compressor map interpolation is usually performed through the introduction of auxiliary coordinates ( β ). In this paper, a new analytical bivariate  β  function definition to be used in compressor map interpolation is studied. The function has user-defined parameters that must be adjusted to properly fit to a single map. The analytical nature of  β  allows for rapid calculations of the interpolation error estimation, which can be used as a quantitative measure of interpolation accuracy and also as a valid tool to compare traditional  β  function interpolation with new approaches (artificial neural networks, genetic algorithms, etc.). The quality of the method is analyzed by comparing the error output to the one of a well-known state-of-the-art methodology. This comparison is carried out for two different types of compressor and, in both cases, the error output using the method presented in this paper is found to be consistently lower. Moreover, an optimization routine able to locally minimize the interpolation error by shape variation of the  β  function is implemented. Further optimization introducing other important criteria is discussed.

Improvements in Off Design Aeroengine Performance Prediction Using Analytic Compressor Map Interpolation