20.500.12556/RUL-134398 Statistical modelling of the fatigue bending strength of Norway spruce wood When wood is used as a structural material, the fact that it is a highly inhomogeneous material, which significantly affects its static and fatigue properties, presents a major challenge to engineers. In this paper, a novel approach to modelling the fatigue-life properties of wood is presented. In the model, the common inverse-power-law relationship between the structural amplitude loads and the corresponding number of load cycles to failure is augmented with the influence of the wood’s mass density, the loading direction and the processing lot. The model is based on the two-parametric conditional Weibull’s probability density function with a constant shape parameter and a scale parameter that is a function of the previously mentioned parameters. The proposed approach was validated using the example of experimental static and fatigue-strength data from spruce beams. It turned out that the newly presented model is capable of adequately replicating the spruce’s S-N curves with a scatter, despite the relatively scarce amount of experimental data, which came from different production lots that were loaded in different directions and had a significant variation in density. Based on the experimental data, the statistical model predicts that the lower density wood has better fatigue strength. spruce wood wood density static material characteristics fatigue strength Weibull’s probability density function augmented inverse power law smrekovina gostota lesa statične lastnosti materiala dinamična trdnost Weibullova gostota porazdelitve verjetnosti razširjeni inverzni potenčni zakon true false true Angleški jezik Slovenski jezik Članek v reviji 2022-01-13 08:57:06 2022-01-13 08:57:09 2022-09-13 03:54:54 0000-00-00 00:00:00 2022 0 0 15 str. iss. 2, art. 536 Vol. 15 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 630*8 1996-1944 10.3390/ma15020536 93092867 RAZ_Klemenc_Jernej_2022.pdf RAZ_Klemenc_Jernej_2022.pdf 1 744BE4F1D8B5F869A77239CCFACF7B2A 2079d50e504febebd502d1f1dbcceebce357afc8c74fdf4a3cb5662e8973cbb4 16d2c49e-7447-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=152826 https://www.mdpi.com/1996-1944/15/2/536 1 39f53b49-7446-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=152825 Fakulteta za strojništvo Biotehniška fakulteta 0 0 0