Online Archive of University of Virginia Scholarship
Computational Modeling of Helical Groove Seals432 views
Author
Watson, Cori, Mechanical and Aerospace Engineering - School of Engineering and Applied Science, University of Virginia
Advisors
Wood, Houston, Department of Mechanical and Aerospace Engineering, University of Virginia
Abstract
Helical groove seals are non-contacting annular seals used in turbomachinery to reduce the leakage of working fluid. These seals have continuously cut grooves, like the threads of a screw, across the surface of the rotor, the surface of the stator, or both surfaces. Despite usually being more stable and having lower leakage than other types of non-contacting annular seals such as smooth or labyrinth seals, helical groove seals are less widely used. This is due in part to the complexities that exist in designing and predicting the performance of helical groove seals. Previous methods for analyzing these seals either do not capture enough characteristics of the flow pattern to provide an accurate analysis or are too computationally expensive and time consuming to be practical. This work proposes the methodology of a three control volume bulk flow based code to analyze helical groove seals with grooves on either the surface of the rotor or the surface of the stator. This is the first simplified helical groove seal code to model the flow within the groove which a critical characteristic of the flow for a component that functions as a screw pump. Analysis of helical groove seals using this bulk flow method and a commercial computational fluid dynamics software are then performed. These results are validated against prior experimental work. The result of these numerical experiments is a new understanding of the flow mechanisms of helical groove seals that will help future engineers design helical groove seals for their applications.
Watson, Cori. Computational Modeling of Helical Groove Seals. University of Virginia, Mechanical and Aerospace Engineering - School of Engineering and Applied Science, PHD (Doctor of Philosophy), 2018-04-25, https://doi.org/10.18130/V3PV6B65N.
