Parametric Studies for Vertical Axis Wind Turbine Simulations
Efficiency of the vertical axis wind turbine depends on turbine design. Wind tunnel experiments, usually performed for evaluation of turbine design, are expensive in comparison with CFD simulations. Although purely numeric, CFD models critically depend on a large set of parameters, which varies from mesh size to numerical schemes and models of turbulence. The aim of the presented research is to evaluate the critical ranges of these parameters for a practically applicable turbine design.
Geometrical accuracy of remote sensing data often is ensured by geometrical transforms based on Ground Control Points (GCPs). Manual selection of GCP is a time-consuming process, which requires some sort of automation. Therefore, the aim of this study is to present and evaluate methodology for easier, semi-automatic selection of ground control points for urban areas. Custom line scanning algorithm was implemented and applied to data in order to extract potential GCPs for an image analyst. The proposed method was tested for classical orthorectification and special object polygon transform. Results are convincing and show that in the test case semi-automatic methodology is able to correct locations of 70 % (thermal data) – 80 % (orthophoto images) of buildings. Geometrical transform for subimages of approximately 3 hectares with approximately 12 automatically found GCPs resulted in RSME approximately 1 meter with standard deviation of 1.2 meters.
The space-borne Moderate Resolution Imaging Spectroradiometer (MODIS) data based net primary production (NPP) product from Numerical Terradynamic Simulation Group (NTSG) was tested in the Kurzeme region, Latvia using a stand-wise forest inventory database. The NPP product has been validated globally and found to have no overall bias. In this study the NPP product was compared with stem biomass increment and soil fertility in respect to distance from the Baltic Sea coast. For each MODIS NPP product pixel we calculated forest cover, share of coniferous trees, average stem biomass increment and average site fertility (growth potential estimate). Then, 2432 pixels with a forest cover over 75% were selected for analysis. The results indicated that MODIS NPP decreased with distance from Baltic Sea coast but stem biomass increment and site fertility indicated a trend of increase. There was no functional relationship between MODIS NPP and stem biomass increment. Analysis of the landcover map used by NTSG for MODIS NPP product showed that the classes “Evergreen needleleaf” and “Mixed forests” differentiated only 10% by mode value of coniferous proportions in species composition. A non-natural jump was detected in the MODIS NPP values at a longitude of 22.5 degrees east corresponding to the border of the coarse scale meteorological dataset (NCEP Reanalysis (R2)) data representation unit. According to the results the MODIS NPP product is not applicable for regional level planning but can probably provide only rough average estimates of NPP for the Baltic region