Region-Based Convolutional Neural Network for Wind Turbine Wake Characterization in Complex Terrain

We present a proof of concept of wind turbine wake identification and characterization using a region-based convolutional neural network (CNN) applied to lidar arc scan images taken at a wind farm in complex terrain. We show that the CNN successfully identifies and characterizes wakes in scans with varying resolutions and geometries, and can capture wake characteristics in spatially heterogeneous fields resulting from data quality control procedures and complex background flow fields. The geometry, spatial extent and locations of wakes and wake fragments exhibit close accord with results from visual inspection. The model exhibits a 95% success rate in identifying wakes when they are present in scans and characterizing their shape. To test model robustness to varying image quality, we reduced the scan density to half the original resolution through down-sampling range gates. This causes a reduction in skill, yet 92% of wakes are still successfully identified. When grouping scans by meteorological conditions and utilizing the CNN for wake characterization under full and half resolution, wake characteristics are consistent with a priori expectations for wake behavior in different inflow and stability conditions.

Variations in Sleep Characteristics and Glucose Regulation in Young Adults with Type 1 Diabetes

Context Short sleep duration and sleep disruptions are associated with impaired glucoregulation in type 1 diabetes (T1D). However, the mechanistic pathways between sleep and glucose variability remain unclear. Objective To determine within-and between-person associations between objective sleep-wake characteristics and glucose variability indices. Design/Setting Multilevel models (MLMs) were used to analyze concurrent sleep and glucose patterns over seven days in 42 young adults with T1D in their natural home environment. Patients or Other Participants Young adults with T1D (mean age of 22.2 ± 3.0 years, HbA1C 7.2%, 32.6% male) for at least 6 months with no other medical or major psychiatric comorbidity were included. Main Outcome Measure(s) Sleep-wake characteristics via wrist actigraphy and glucose variability indices via a continuous glucose monitor (CGM). Results Lower sleep efficiency predicted higher glucose variability (less time in range β= .011 and more time in hyperglycemia β= -.011) within-person. A longer wake after sleep onset and more sleep disruptions were associated with higher glucose variability between persons (β= .28 - .31). Higher glucose variability predicted poorer sleep within-person (delayed bedtime, waketime, mid-sleep time, and lower sleep efficiency), while higher glucose variability was associated with poorer sleep and more sleep disruptions between persons (lower sleep efficiency, longer wake after sleep onset, and a higher sleep fragmentation index). Conclusions Clinicians can address the reciprocal nature of the sleep-glucose relationship by optimizing sleep and targeting efforts towards a euglycemic range overnight. Sleep habits are a modifiable personal target in diabetes care.

Dynamic Analysis of Wake Characteristics of the Circular Cylinder with a Dimpled Surface

In order to understand the wake characteristics for the circular cylinder with the dimpled structure, particle image velocimetry (PIV) and proper orthogonal decomposition (POD) method are used to measure and analyze the flow field velocity and the flow characteristic of the wake flow of the circular cylinder with the dimpled surface. This study focuses on the distribution of Reynolds stress and turbulent kinetic energy, the velocity profiles and recirculation zones, and the velocity fluctuating characteristics of flow field with POD technology. It is found that the equivalent high-intensity Reynolds stress and turbulent kinetic energy regions of the circular cylinder with the dimpled surface are smaller, and the peak values are lower, and the velocity gradient in the wake region of the circular cylinder with the dimpled surface is larger. Otherwise, the energy contained by the dominant modes of the smooth cylinder is larger than that contained by the dominant modes of the circular cylinders with the dimpled surface, which means the energy of the dimpled cylinder is more distributed. At the same time, it is observed that the dimpled structure will decrease the vortex shedding intensity, but may increase the vortex shedding frequency, and destroy the inherent flow mode of the flow field around the cylinder.

Aerodynamic Performance and Wake Characteristics of a Wind Turbine Model Subjected to Surge and Sway Motions

A wind-tunnel experimental study was performed to investigate the impact of the surge and sway motions of a wind turbine model on the power output, rotor thrust and wake characteristics. A wind turbine model was mounted on a translation platform to simulate the surge and sway motions under given amplitude and frequency. The power output and rotor thrust of the turbine model subjected to surge and sway motions were measured by using a DC variable electronic load and a six-component force sensor, respectively. For comparison, these measurements were also performed in a bottom-fixed wind turbine. The results show that the mean power output and mean rotor thrust of the turbine model under surge and sway motions are almost the same as those of the bottom-fixed turbine. However, the thrust fluctuation amplitude of the turbine model under surge motion is significantly higher than those of the turbine model under sway motion and the bottom-fixed turbine. In addition, the wake characteristics of the turbine model were also investigated by using a particle image velocimetry system. The results show that the surge and sway motions have slight effect on the near and intermediate wake of the turbine model in the horizontal plane at the rotor hub height.