Brian A. Fleck’s research while affiliated with University of Alberta and other places

We study the impact of a novel wingtip modification on the wake dynamics of a 10-MW horizontal axis wind turbine using delayed detached eddy simulation. We considered a baseline turbine without wingtip modifications and a turbine equipped with winglets. The results reveal that the winglet significantly alters the near and mid wake regions, increasing the velocity deficit and reducing turbulence intensity in the near wake while minimally affecting the far wake beyond the distance of nine rotor diameters. The vortex rings from the blade tips decay faster in the wake of the modified turbine, reducing the wake energy and vorticity. The budget of mean kinetic energy transport shows that the winglet reduces the turbulence production in the near wake while increasing the turbulence convection and production in the far wake region. To study the meandering in the far wake of two turbine configurations, the dominant Strouhal number and the standard deviation of the wake center were studied. The results indicated that the winglet does not notably affect the amplitude of the wake meandering. Furthermore, the winglet increased turbine power production by 4.5% and thrust by 1.5% while reducing power and torque fluctuations by 10%. Although the winglet affected near wake dynamics, its influence on the far wake is minimal, suggesting potential benefits for wind farm design where turbines are not closely spaced.

This study evaluates the effects of a novel winglet design on the aerodynamics of the 10 MW Denmark Technical University wind turbine. The unsteady Reynolds-averaged Navier–Stokes (URANS) and the detached eddy simulation (DES) are used to numerically simulate the physics of both the baseline turbine (i.e., no winglet included) and a wingletted turbine under the rated operating condition. The results show that the addition of the winglet alters both the structure of the wing-tip vortex and the vorticity distribution in the wake, leading to lower levels of average vorticity. Moreover, the wingletted wind turbine increases the torque of the turbine by 6.3% while only increasing the drag by 2.5%. Although the URANS formulation performs well at calculating the power and force distribution at the turbine, it falls short of providing an accurate description of the flow field of the wake, failing to calculate the unsteady scales captured by the DES model.

To improve the reliability of the computational fluid dynamics (CFD) models of wind-driven pollutant dispersion within urban settings, a re-calibration study is conducted to optimize the standard k−ε model. A modified optimization framework based on the genetic algorithm is adapted to alleviate the computational expenses and to further identify ranges for each empirical coefficient to achieve the most reliable and accurate predictions. A robust objective function is defined, incorporating both the flow parameters and pollutant concentration through several linear and logarithmic measures. The coefficients are trained using high-quality and full-scale tracer experiments in a mock urban arrangement simulating a building array. The proposed ranges are 0.14≤Cμ≤0.15, 1.30≤Cε1≤1.46, 1.68≤Cε2≤1.80, 1.12≤σε≤1.20, and 0.87≤σk≤1.00. A thorough evaluation of the predicted flow and concentration fields indicates the modified closure is effective. The fraction of predictions within the acceptable ranges from measurements has increased by 8% for pollutant concentration and 27% for turbulence kinetic energy. The generality of the calibrated model is further tested by modeling additional cases with different meteorological conditions, in which the calculated validation metrics attest to the noteworthy improvements in predictions.

Historically, viruses have demonstrated airborne transmission. Emerging evidence suggests the novel coronavirus (SARS-CoV-2) that causes COVID-19 also spreads by airborne transmission. This is more likely in indoor environments, particularly with poor ventilation. In the context of airborne transmission, a vital mitigation strategy for the built environment is heating, ventilation, and air conditioning (HVAC) systems. HVAC features could modify virus transmission potential. A systematic review was conducted to identify and synthesize research examining the effectiveness of filters within HVAC systems in reducing virus transmission. A comprehensive search of OVID MEDLINE, Compendex, and Web of Science Core was conducted to January 2021. Two authors were involved in study selection, data extraction, and risk of bias assessments. Study characteristics and results were displayed in evidence tables and findings were synthesized narratively. Twenty-three relevant studies showed that: filtration was associated with decreased transmission; filters removed viruses from the air; increasing filter efficiency (efficiency of particle removal) was associated with decreased transmission, decreased infection risk, and increased viral filtration efficiency (efficiency of virus removal); increasing filter efficiency above MERV 13 was associated with limited benefit in further reduction of virus concentration and infection risk; and filters with the same efficiency rating from different companies showed variable performance. Adapting HVAC systems to mitigate virus transmission requires a multi-factorial approach and filtration is one factor offering demonstrated potential for decreased transmission. For filtration to be effective, proper installation is required. Of note, similarly rated filters from different companies may offer different virus reduction results. While increasing filtration efficiency (i.e., increasing MERV rating or moving from MERV to HEPA) is associated with virus mitigation, there are diminishing returns for filters rated MERV 13 or higher. Although costs increase with filtration efficiency, they are lower than the cost of ventilation options with the equivalent reduction in transmission. Systematic review registration: PROSPERO 2020 CRD42020193968.