Mathematical modeling of the elastic rolling process and optimization of its parameters to reduce the roughness of the processed surface of high-precision non-rigid thin-walled parts

The possibilities of a new technological process — elastic rolling are considered. Modeling and optimization of the process were performed to ensure the minimum surface roughness of the treated surface. Keywords elastic rolling, surface roughness, parameter, modeling, optimization, part. [email protected]

DETERMINATION OF SURFACE ROUGHNESS PARAMETER THROUGH AERIAL IMAGES IN WIND POWER PLANT INSTALLATION

The surface roughness parameter is an important parameter in the installation of a wind energy power plant and it varies depending on the dimensions and the distribution of the roughness elements on the land. Before the installation roughness maps indicate roughness of the surface has to be drawn. In today's applications, these maps are drawn approximately by WAsP software using the information obtained from the terrestrial observations belongs to experts. But this application is costly and time consuming and the assessment is based on limited land observations. In this study the surface roughness parameter is determined by digital image processing techniques from the digital images taken over aerial field. Thus it gives the opportunity to consider whole power plant surface into account with lower cost and time requirements over the traditional methods. Images used in the study are obtained from the Map General Command and MATLAB software platform is used. The study is based on the determination of the closure rates on the land by image segmentation method such as OTSU algorithm, fuzzy c-means and k-means algorithms. In order to evaluate the consistency of the results images are evaluated with ERDAS software. Obtained results showed the effectiveness of the study.

Determination of the Surface Roughness Parameter and Wind Shear Exponent of Kisii Region from the On-Site Measurement of Wind Profiles

The research sought to investigate the surface roughness parameter (Zo) and wind shear exponent (α) of Kisii region (elevation 1710m above sea level, 0.68°S, 34.79°E). A six-month experiment was set at three sites of Kisii region. Two PRO AcuRite 01036 Wireless Weather Stations with pro+ 5-in-1 Sensors were placed at different hub heights above the ground and data were sent and received by a display board set at a room through remote sensing at an interval of 12 minutes. Data was collected from the display board through the pc connect software, grouped into discrete data and then calculated to represent mean wind speed, diurnal variation, daily variation, and monthly variations. The calculated averages of wind speeds at hub heights of 10m and 13m were then used to determine the wind shear exponent and surface roughness parameter of the sites. The wind shear exponents were found to be 0.92, 0.41, and 0.54 for Nyamecheo, Kisii University, and Ikobe stations, respectively, with an average of 0.64. The roughness parameter was also calculated and found to be 3.75, 1.32, and 1.96 for Nyamecheo, Kisii University (KSU), and Ikobe, respectively, with an average of 2.35.