Testing and application of a two-dimensional hydrothermal/transport model for a long, deep, and narrow lake with moderate Burger number

Setup, testing, and application of a 2-dimensional longitudinal–vertical hydrothermal/transport model (the transport submodel of CE-QUAL-W2) was documented for Cayuga Lake, New York, where the Rossby radius is on the order of the lake’s width. The model was supported by long-term monitoring of meteorological and hydrologic drivers and calibrated and validated using in-lake temperature measurements made at multiple temporal and spatial scales over 16 years. Measurements included (1) temperature profiles at multiple lake sites for 10 years, (2) near-surface temperatures at one end of the lake for 16 years, (3) high frequency temperature at multiple depths for 2 years, and (4) seasonal measurements of a conservative passive tracer. Seiche activity imparted prominent signatures within these measurements. The model demonstrated excellent temporal stability, maintaining good performance in uninterrupted simulations over a period of 15 years. Performance was improved when modeling was supported by on-lake versus land-based meteorological measurements. The validated model was applied through numeric tracer experiments to evaluate various features of transport of interest to water quality issues for the lake, including (1) residence times of stream inputs within the entire lake and a smaller region defined bathymetrically as a shallow shelf, (2) transport and fate of negatively buoyant streams, and (3) the extent of transport from the hypolimnion to the epilimnion. This hydrothermal/transport model is appropriate to serve as the transport submodel for a forthcoming water quality model for this lake and for other high aspect (length to width) ratio lacustrine systems for which the internal Burger number is order one or greater

The information content of a scalar plume - a plume tracing perspective. Environmental Fluid Mechanics

Abstract. The ability of many animals and insects to track a plume to its source is a particularly impressive feat when the fluid dynamics is considered. Inspired by this observation this research seeks to identify the information in a passive scalar plume suitable for developing robust and efficient plume tracing algorithms. The subject of this study is a scalar plume emanating from a point source in a turbulent boundary layer which has been modeled in a laboratory facility built specifically for this purpose. A coupled PIV-LIF technique is used to measure the velocity and scalar field in a time resolved fashion. This data set is analyzed and the convergence rates of five single-point statistics, suitable as kernels of plume tracing algorithms, are investigated. The experimental data shows that the scalar fluctuations over long downstream distances from the source are characterized by filamentary structures that lead to relatively slow convergence rates for any statistic that is based on mean concentrations. The scalar intermittency, however, converges rapidly toward its true value, in fact converging to a testable hypothesis for source location direction faster than the time scale of the larger scale plume meander

Power and Flow Analysis of Axial Induction Control in an Array of Model-Scale Wind Turbines

As research on wind energy has progressed, it has broadened from a focus on the wind turbine to include the entire wind farm. In particular, methods to mitigate the negative effects of upstream wakes on downstream turbines have received significant attention. One such mitigation method is axial induction control (AIC) in which upstream turbines are derated to reduce the momentum deficits in their wakes, leaving higher speed flow for downstream turbines. If performed correctly, it is theorized that the power production gains in downstream turbines can compensate for the power sacrificed by derating upstream turbines. Previous work has indicated that the “excess” energy left in the wake of the derated turbine is along the edges of the wake such that a turbine placed directly downstream will see little to no increase in power. To address this hypothesis, we performed a control and treatment experiment with model-scale turbines in a wide flume. Five turbines were arranged in three successive streamwise rows, with the first two rows consisting of two aligned turbines, while three turbines with small transverse spacing were placed in the third row, the central of which was also streamwise-aligned with the upstream two turbines. This arrangement was used to evaluate the difference in power production primarily among the turbines in the third row when the upstream turbines were derated. Particle image velocimetry (PIV) was used to measure the wake in the streamwise-vertical planes along the centerline of the array and along the rotor tips of the centerline turbines between all rows, and high accuracy power measurements were recorded from each turbine. The results show that the total power of the array was decreased while implementing AIC but that individual turbine performance differed from predictions. PIV results show that mean kinetic energy (MKE) is redistributed to the edges of the wakes as has been previously hypothesized. We provide an analysis of the results that connects both the power and flow measurements and that highlights several of the aspects of wind turbine wake flows that make them so complex and challenging to study

Power and Flow Analysis of Axial Induction Control in an Array of Model-Scale Wind Turbines

As research on wind energy has progressed, it has broadened from a focus on the wind turbine to include the entire wind farm. In particular, methods to mitigate the negative effects of upstream wakes on downstream turbines have received significant attention. One such mitigation method is axial induction control (AIC) in which upstream turbines are derated to reduce the momentum deficits in their wakes, leaving higher speed flow for downstream turbines. If performed correctly, it is theorized that the power production gains in downstream turbines can compensate for the power sacrificed by derating upstream turbines. Previous work has indicated that the “excess” energy left in the wake of the derated turbine is along the edges of the wake such that a turbine placed directly downstream will see little to no increase in power. To address this hypothesis, we performed a control and treatment experiment with model-scale turbines in a wide flume. Five turbines were arranged in three successive streamwise rows, with the first two rows consisting of two aligned turbines, while three turbines with small transverse spacing were placed in the third row, the central of which was also streamwise-aligned with the upstream two turbines. This arrangement was used to evaluate the difference in power production primarily among the turbines in the third row when the upstream turbines were derated. Particle image velocimetry (PIV) was used to measure the wake in the streamwise-vertical planes along the centerline of the array and along the rotor tips of the centerline turbines between all rows, and high accuracy power measurements were recorded from each turbine. The results show that the total power of the array was decreased while implementing AIC but that individual turbine performance differed from predictions. PIV results show that mean kinetic energy (MKE) is redistributed to the edges of the wakes as has been previously hypothesized. We provide an analysis of the results that connects both the power and flow measurements and that highlights several of the aspects of wind turbine wake flows that make them so complex and challenging to study

Infrared Quantitative Imaging Velocimetry (IR-QIV) data supporting Schweitzer & Cowen, 2021, WRR

This data set contains infrared images and velocity measurements collected at two sites on the Sacramento River, and one of its tributaries, near Sacramento, California, USA, in November 2017. Details on the data collection and analysis are available in Schweitzer & Cowen, 2021, WRR. Included are infrared images of the flowing water surface, the instantaneous velocity field as calcalated from these images using Infrared Quantitative Image Velocimetry (IR-QIV), a near-field remote sensing method of surface velocimetry similar to LSPIV that is capable of measuring the instantaneous two-dimensional velocity field and extract metrics of turbulence. Also included are concurrent measurements of water velocity using traditional acoustic instruments (ADV and ADCP), and meteorological measurements made on site.This work was funded by the California Department of Water Resources (DWR) contract numbers 4600010495 and 4600012347

H1. A Surface PIV Approach for the Remote Monitoring of Mean and Turbulent Flow: Properties in an Open Channel

In an effort to develop a reliable, continuous and efficient method of remotely monitoring mean velocities, water column turbulence levels and bathymetry, a surface PIV (particle image velocimetry) experiment is conducted in a wide open channel (B/h >12) for a range of flow conditions. Mean and turbulent velocities, longitudinal power spectra and the longitudinal integral length scale have been calculated at the free-surface from the PIV data. The results reveal the presence of secondary flow within the channel, which leads to heterogeneous turbulence metrics on the surface; for example, the streamwise turbulent velocities and the Reynolds stress vary strongly as a result of the secondary motion. The results also indicate two methods by which the flow depth can be determined: 1.) the longitudinal integral length scale which varies predictably with the flow depth (L22,1 ≈ 0.3h) and 2.) the normalized longitudinal spatial spectra which exhibit a slight bump at the wave number corresponding to the flow depth. These results suggest that it is possible to determine volumetric flow rate solely from measurements of the free- surface water flow. These findings have important implications for developing new technologies for stream gauging, near-shore and estuarine monitoring

Boundary layer flow and bed shear stress under a solitary wave

Liu & Orfila (J. Fluid Mech. vol. 520, 2004, p. 83) derived analytical solutions for viscous boundary layer flows under transient long waves. Their analytical solutions were obtained with the assumption that the nonlinear inertia force was negligible in the momentum equations. In this paper, using Liu & Orfila's solution and the solutions for the nonlinear boundary layer equations, we examine the boundary layer flow characteristics under a solitary wave. It is found that while the horizontal component of the free-stream velocity outside the boundary layer always moves in the direction of wave propagation, the fluid particle velocity near the bottom inside the boundary layer reverses direction as the wave decelerates. Consequently, the bed shear stress also changes sign during the deceleration phase. Laboratory measurements, including the free-surface displacement, particle image velocimetry (PIV) resolved velocity fields of the viscous boundary layer, and the calculated bed shear stress were also collected to check the theoretical results. Excellent agreement is observed. © 2007 Cambridge University Press.N