No abstract

Introduction:Large Eddy Simulation (LES) modelers must begin to answer the question of how to better incorporate large datasets into simulations. This question is important because, at a given location, the diurnal, seasonal, and day-to-day variations of atmospheric stability have significant consequences for the power generated by wind turbines. The following study provides a methodology to obtain discrete values of surface flux, inversion height and geostrophic wind for LES using field data over multiple diurnal cycles (averaged over a month) at 12 Local Time (LT) (during the convective ABL). The methodology will allow the discrete LES to quantify the day-to-day variations over multiple diurnal cycles.Methods:The study tests the hypothesis that LES can capture the mean velocity and TKE profiles from the averaged variations in surface heat flux at 12 LT measured in the field (mean, +1 standard deviation, and -1 standard deviation). The discrete LES from the mean, +1 standard deviation, and -1 standard deviation surface heat flux represent the variations in the ABL due to the day-to-day variations in surface heat flux. The method calculates the surface heat flux for the NREL NWTC M5 dataset. The field data were used to generate Probability Density Functions (PDFs) of surface heat flux for the January and July 12 LT. The PDFs are used to select the surface heat fluxes as inputs into the discrete LES.Results / Conclusion:A correlation function between the surface heat flux and the boundary layer height was determined to select the initial inversion height, and the geostrophic departure function was used to determine the geostrophic wind for each surface heat flux. The LES profiles matched the averaged velocity profiles from the field data to 4% and the averaged TKE profiles to 6% and, therefore, validated the methodology. The method allows for further quantification of day-to-day stability variations using LES.

Sliding seals play a critical role in the dynamic sealing of a wide-variety of machinery applications. There are many type of sliding seals, such as segmented carbon ring, O-ring, or bellows; and are used as sealing elements in hydraulic rod and piston seals, as well as secondary sealing elements in mechanical and dry-gas seals. Motion between the dynamic and static parts of the machine is most often lubricated by the process fluid, and therefore has leakage. This paper presents a new test rig capable of measuring leakage and friction force of annular sliding seals for a range of sealing pressures (0–24.8 MPa), temperatures (20–700 C), gasses, and motion. The rig is capable of large linear motions and high frequency dynamic motion. The large linear motion replicates piston movement or shaft thermal growth and the dynamic excitation matches the typical vibration response from a spinning shaft. Currently, there is little available information in the literature on the leakage performance of dynamic O-rings at high pressures, especially for gas sealing. The paper presents experimental results from two different material, 150 mm diameter, O-rings at sealing pressures up to 70 bar (1,000 psi) in CO2. The rings were tested for large ranges of motion, up to 4 mm. Two different durometer FKM O-rings (70 and 90) were compared to a 70 durometer BUNA O-ring. The softer rings exhibited superior leakage performance, and similar friction forces. The BUNA O-ring performed slightly better at sealing (10–20%) then the similar hardness Viton ring.

No abstract

A novel and a robust high-fidelity numerical methodology has been developed to realistically estimate the net energy production of full-scale horizontal axis wind turbines in a convective atmospheric boundary layer, for both isolated and multiple wind turbine arrays by accounting for the wake effects between them. Large eddy simulation has been used to understand the role of atmospheric stability in net energy production (annual energy production) of full-scale horizontal axis wind turbines placed in the convective atmospheric boundary layer. The simulations are performed during the convective conditions corresponding to the National Renewable Energy Laboratory field campaign of July 2015. A mathematical framework was developed to incorporate the field-based measurements as boundary conditions for the large eddy simulation by averaging the surface flux over multiple diurnal cycles. The objective of the study is to quantify the role of surface flux in the calculation of energy production for an isolated, two and three wind turbine configuration. The study compares the mean value, +1 standard deviation, and −1 standard deviation from the measured surface flux to demonstrate the role of surface heat flux. The uniqueness of the study is that power deficits from large eddy simulation were used to determine wake losses and obtain a net energy production that accounts for the wake losses. The frequency of stability events, from field measurements, is input into the calculation of an ensemble energy production prediction with wake losses for different wind turbine arrays. The increased surface heat flux increases the atmospheric turbulence into the wind turbines. Higher turbulence results in faster wake recovery by a factor of two. The faster wake recovery rates result in lowering the power deficits from 46% to 28% for the two-turbine array. The difference in net energy production between the +1 and −1 standard deviation (with respect to surface heat flux) simulations was 10% for the two-turbine array and 8% for the three-turbine array. An ensemble net energy production by accounting for the wake losses indicated the overestimation of annual energy production from current practices could be corrected by accounting for variation of surface flux from the mean value.