Producing compressor maps is time consuming, costly and error prone and many data samples must be collected to give sufficient accuracy. Even then, expert input is typically required to fine tune the map to the appropriate shape. In this paper, we take some of that expertise and incorporate it in the smoothing process. The main piece of knowledge used is the cubic approximation for speed lines derived from the Moore Greitzer model. This well accepted approximation captures much of the general performance properties of compressors. But it is also widely recognized as only being very roughly true of real compressors. Nevertheless, we show that embedding this approximation, however limited, in the smoothing process results in accurate interpolation and extrapolation. The aim of this work is to substantially reduce the need for human input in the fitting process. We also anticipate a number of other benefits: less data is needed, with the commensurate time and money saved; the data collection process can be monitored for possible problems; changes in the map can be quantified and, when sufficiently small, data collection can be terminated.
Hybrid monomer design for unifying conflicting polymerizability, recyclability, and performance properties
