The article presents research on solid particle erosive wear resistance of ductile cast iron after laser surface melting. This surface treatment technology enables improvement of wear resistance of ductile cast iron surface. For the test ductile cast iron EN GJS-350-22 surface was processed by high power diode laser HPDL Rofin Sinar DL020. For the research single pass and multi pass laser melted surface layers were made. The macrostructure and microstructure of multi pass surface layers were analysed. The Vickers microhardness tests were proceeded for single pass and multi pass surface layers. The solid particle erosive test according to standard ASTM G76 – 04 with 30°, 60° and 90° impact angle was made for each multi pass surface layer. As a reference material in erosive test, base material EN GJS-350-22 was used. After the erosive test, worn surfaces observations were carried out on the Scanning Electron Microscope. Laser surface melting process of tested ductile cast iron resulted in maximum 3.7 times hardness increase caused by microstructure change. This caused the increase of erosive resistance in comparison to the base material.
The purpose of the paper is to analyze the spatial variability of precipitation in Poland in the years 1981–2010. The av-erage annual rainfall was 607 mm. Precipitation in Poland is characterized by high spatial and temporal variability. The lowest annual precipitation was recorded in the central part of the country, where they equaled 500 mm. The highest annual precipitation totals were determined in the south, equaling 970 mm. The average precipitation in the summer half-year is 382 mm (63% of the annual total). On the basis of data from 53 climate stations, maps were made of the spatial distribution of precipitation for the period of the year and winter and summer half-year. The kriging method was used to map rainfall distribution in Poland. In the case study, cross-validation was used to compare the prediction performances of three periods. Kriging, with exponential type of semivariogram, gave the best performance in the statistical sense. Their application is justices especially in areas where landform is very complex. In accordance with the assumptions, the mean prediction error (ME), mean standardized prediction error (MSE), and root mean-square standardized prediction error (RMSSE) values are approximately zero, and root-mean-square prediction error (RMSE) and average standard error (ASE) reach values well below 100.