Abstract
Sandia National Laboratory (SNL) developed reference tidal and river turbines illustrated in Fig. 1 to develop and refine design tools, allow accurate estimates of levelized cost of energy (LCOE), and provide testing data that can be made publicly available to the MHK industry. More details on the reference modeling effort are provided in Previsic and Jepsen (2011). Scaled model studies of the reference tidal (axial-flow) turbine, and the reference river (cross-flow) turbine are needed to provide detailed flow field measurements around the device, while simultaneously collecting information on the MHK machine loading and performance. Dimensional analysis provides scaling laws that are used to upscale model test information into performance and design information for a full-scale prototype turbine. For water turbines, hydrodynamic similitude is achieved when the chord Reynolds number (Rc), Froude number (F), and the tip speed ratio (TSR) of the model and the full-scale device are the same. It is rare to achieve perfect similitude for Rc, but a threshold value should be exceeded. Boundary layer trips or long flumes should be employed to ensure the flow is fully turbulent and simulates the essential physics of flow-machine interaction. Froude number similitude in open channel testing is usually met and is particularly important for upscaling wake flow data. As indicated by Neary and Sale (2010), the inflow characteristics of natural rivers, tidal channels and open channel flumes, including vertical profiles of mean velocity, turbulence intensity and Reynolds normal stresses, are similar, and generally well represented by flat-plate boundary layer theory. This report provides details of the experimental test plan for scaled model studies in St. Anthony Falls Laboratory (SAFL) Main Channel at the University of Minnesota, including a review of study objectives, descriptions of the turbine models, the experimental set-up, instrumentation details, instrument measurement uncertainty, anticipated experimental test cases, post-processing methods, and data archiving for model developers.