Enhancing Flow Field Measurements Through Adaptive Multidimensional Data Sampling

Abstract

A way to gain insight into the flow field conditions in turbomachinery is by carrying out a series of point measurements in a cross section of the flow, for example, with a miniature multihole pressure probe. A problem commonly encountered in situations like these is the selection of a suitable measurement grid layout and density for obtaining all essential information in a cost-effective and timely manner. In order to achieve the latter, a novel adaptive multidimensional data sampling technique has been developed at Cranfield University. This paper describes the underlying principles of this technique, the algorithms utilized, and the results obtained during its successful application to data sets of two different flow fields in a high-speed research compressor.