Method for using spectral flow data to predict vortex-induced vibration onset of static structures

Abstract. Spectral representations of vortex shedding behavior, such as airfoil data derived from computational fluid dynamics or experiment, can support the efficient identification of potential vortex-induced vibration onset. However, use of such data is hindered by the myriad of practical considerations required to scale, filter, and rank the risk of overlap between natural frequencies and shedding frequencies. This problem spans across Reynolds number, local angle of attack, and local skew angle, in addition to frequency harmonics, interpolation, and multi-body multi-element structures. The combinatorial scale of the problem additionally necessitates efficient numerical methods. This paper presents a reproducible, open-source framework with accompanying source code and a graphical user interface. With the improvements here, these problems can be addressed to enable the straightforward use of existing spectral datasets for arbitrary beam-type structures. We describe the methods, present a simple verification case, and exercise the method on a sample structure using a spectral airfoil dataset. The framework enables designers to readily navigate the complex space to identify, avoid, and include (via one-way coupling) the onset of vortex-induced vibration in their design workflows. Code, example datasets, and reproduction assets are openly released.