Wind turbines operate mostly in yaw conditions that give rise to cyclic variations in aerodynamic forces applied on the blade. This induced load fluctuation is closely related to the upstream velocity field of the rotor and can be a significant source of fatigue and vibration. An accurate prediction of blade loading is considered the key in designing reliable and efficient wind turbines. The related calculation remains a complicated task to perform and requires enormous computing time. In this context, a numerical method is presented, aimed at evaluating the azimuthal fluctuation of the normal force. This method is obtained by coupling the Beddoes near-Wake model and the free-Wake method: the near-Wake-induced velocities are calculated using Beddoes near-Wake model with the far-Wake contribution evaluated using the free-Wake method. In addition, the unsteady effects on the aerodynamic coefficients are taken into account using the Beddoes-Leishman dynamic stall model. A computer code was developed, and numerical values were obtained in acceptable computational time. Results are compared with measurements performed in the NASA Ames wind tunnel.

The small microwave skin depth of sea water as well as the small penetration depth of laser signal in water impose limitations on the application of SAR and Lidar in sea surveillance systems. On the other hand, vessels travelling at sea bring about hydrodynamic anomalies in the sea water called as Wake. These hydrodynamic disturbances can be detected by using some techniques such as airborne radio imaging and Extremely Low Frequency (ELF) electromagnetic signal processing. In practice, the motion of conductive sea water anomalies in the natural earth's magnetic field induces ELF magnetic Wakes which can be measured via accurate magnetic sensors and detected through signal processing schemes. The physical properties of the hydrodynamic Wake as well as those relating to the corresponding magnetic Wake are directly related to the vessel parameters such as hull shape, speed and heading. In this work, we firstly derive and formulate the mathematical expressions relating to the aforementioned hydrodynamic and magnetic Wakes. By employing derived expressions, a novel detection scheme is proposed based on constructing the 2-dimentional image of the vessel’, s magnetic Wake through the magnetic signals captured from an array of magnetic sensors, and finally, the relation between the spectral image of the magnetic Wake and the vessel heading is studied. We will show that our proposed scheme can detect the existence of a remote vessel as well as its heading from the constructed image with high accuracy, and moreover, it does not have common limitations of existing single-sensor based heading detection schemes.

Field of sleep medicine has evolved significantly and undergone tremendous growth during last three decades. Early case reports and case series discussed the typical hypoventilation in sleepy, red-faced, morbidly obese individuals known as Pickwickian Syndrome after Charles Dickens’s fictional character “Joe, the fat boy”. Symptomatic obstructive sleep apnea (OSA) afflicts an estimated 4 percent of men and 2 percent of women aged 30-70 years….