ARRID: ANN-based Rotordynamics for Robust and Integrated Design
This provides a fast tool for designers to optimize rotordynamics early in the process, addressing a domain-specific problem in engineering design.
The study tackled the slow evaluation of rotordynamics in design by introducing ARRID, an ANN-based software using surrogate models, which sped up computation by three orders of magnitude compared to current models.
The purpose of this study is to introduce ANN-based software for the fast evaluation of rotordynamics in the context of robust and integrated design. It is based on a surrogate model made of ensembles of artificial neural networks running in a Bokeh web application. The use of a surrogate model has sped up the computation by three orders of magnitude compared to the current models. ARRID offers fast performance information, including the effect of manufacturing deviations. As such, it helps the designer to make optimal design choices early in the design process. The designer can manipulate the parameters of the design and the operating conditions to obtain performance information in a matter of seconds.