In this study, a priori tests were performed to develop accurate and efficient implementations of autonomic closure based on particular generalized representations and parameters associated with the local system identification of the turbulence state. These included the relative number of training points and bounding box size, which impact computational cost and generalizability of coefficients in the representation from the test scale to the LES scale. The focus was on studying impacts of these factors on the resulting accuracy and efficiency of autonomic closure for the subgrid stress. Particular attention was paid to the associated subgrid production field, including its structural features in which large forward and backward energy transfer are concentrated.
More than five orders of magnitude reduction in computational cost of autonomic closure was achieved in this study with essentially no loss of accuracy, primarily by using efficient frame-invariant forms for generalized representations that greatly reduce the number of degrees of freedom. The recommended form is a 28-coefficient representation that provides subgrid stress and production fields that are far more accurate in terms of structure and statistics than are traditional prescribed closure models.
Particle Image Velocimetry (PIV) has become a cornerstone of modern experimental fluid mechanics due to its unique ability to resolve the entire instantaneous two-dimensional velocity field of an experimental flow. However, this methodology has historically been omitted from undergraduate curricula due to the significant cost of research-grade PIV systems and safety considerations stemming from the high-power Nd-YAG lasers typically implemented by PIV systems. In the following undergraduate thesis, a low-cost model of a PIV system is designed to be used within the context of an undergraduate fluid mechanics lab. The proposed system consists of a Hele-Shaw water tunnel, a high-power LED lighting source, and a modern smartphone camera. Additionally, a standalone application was developed to perform the necessary image processing as well as to perform Particle Streak Velocimetry (PSV) and PIV image analysis. Ultimately, the proposed system costs $229.33 and can replicate modern PIV techniques albeit for simple flow scenarios.