Analysis and identification of multi-variate random pressure fields using covariance and spectral proper transformations

Abstract

This paper will present applications of the Proper Transformations based on both cross spectral matrix and covariance matrix branches to analysis and identification of multi-variate random pressure fields. The random pressure fields are determined due to the physical measurements on some typical rectangular models in the wind tunnel tests. The significant roles of the first covariance mode associated with the first principal coordinates as well as of the first spectral eigenvalue and associated spectral mode are clarified in reconstructing the random pressure fields and identifying the hidden physical phenomena inside this pressure fields.