Implementation of an Efficient RMS Algorithm for Random Analysis in Vibrata™

When analyzing forced dynamic response to random excitation, obtaining root-mean-square (RMS) results without having to compute the underlying power spectral density (PSD) functions can significantly reduce solution time and memory usage. An algorithm for such calculations published by de la Fuente [1, 2] has been incorporated in ATA Engineering’s Vibrata™ program, a GUI- and text-file-driven modal dynamic analysis tool that works with Femap™ and MATLAB® to provide random, transient, harmonic, and response spectrum analysis. This paper describes some of the difficulties encountered in implementing this random response method and how they were overcome. It then shows two examples of the algorithm’s use in Vibrata and compares those computation times and solutions to standard PSD-based computations.