Abstract

The present work considers the possibility of using river currents to generate electric power in order to supplement existing power units. A physical system consisting of a flowing river/canal with rectangular cross section, an open channel nozzle, and an impact turbine is modelled mathematically. The model is simulated using MATLAB for varying slopes and two nozzle-turbine sequences. It is found that the usage of nozzles demonstrably increases the velocity, and therefore, the kinetic energy of the flow. A total power ranging from 0.34 to 10.79 MW for the lowest and highest value of slope, respectively, is predicted by the model. Possible applications are discussed.

Multiphase flow induced vibrations are difficult to calculate. This is in part the prediction of the force frequency spectrum at a single bend, part the influence of bends on the multiphase flow behavior and therefore the prediction of the multiphase flow characteristics between bends. In this paper, the evolution of the forces between subsequent bends are discussed including the phase relations of the forces on the different bends. For annular flow, the forces between the different bends are incoherent and are more or less random. However, for stratified and especially slug flow, the forces remain coherent up to high frequencies. This means in a frequency response analysis of a piping structure, the transport velocity of the multiphase structures must be taken into account.

No abstract

The presence of offshore wind farms causes downstream regions of reduced wind velocity, i.e. wind farm (cluster) wakes, which can affect the power of wind farms downstream. Engineering models are now being used to simulate the effects of these wakes, and an important requirement for model validation is a comparison with full-field measurements. Our objective in this paper is to parametrize and validate two engineering wake models with long-range lidar measurements. We use a long-range scanning Doppler lidar to scan the near wake region of a 400 MW offshore wind farm and compare the wind velocities in the wake to the outputs of two engineering models: FarmFlow and flappy. We adapt FarmFlow to solve the flow in highly unstable atmospheres by modifying the boundary conditions, which enables the comparison of velocity profiles behind the farm. The models perform qualitatively well in predicting the wake deficit and shape close to the farm and at lower heights. They predict higher wake losses within the farm when compared to production power data in a strongly unstable atmospheric case. However, the current analysis is limited due to the lack of inflow measurements for model initialization, compounded by limited data availability. We discuss the possibilities and limitations of long-range scanning lidar data for cluster wake model validation and the need for inflow measurements for model initialization. We conclude that with detailed inflow measurements, scanning long-range lidars could serve as a good tool for the validation of wind farm wake models.