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In recent times, traditional metals such as iron and steel are being replaced by polymer composites because of its advanced physical characteristics. In this physical study, e-glass fiber is used as reinforcement agent along with IPN blend (Vinylester + polyurethane) under two categories of filler material, with and without alumina (5% wt), since e-Glass fiber has widespread merits such as lighter weight, higher strength to weight ratio, good chemical resistance and low cost. Besides that, the study also mainly concentrates on analyzing of the mechanical and wear behavior of coated and uncoated e-glass fiber reinforced IPN composites with varying proportions of e-glass fiber (0%, 5%, 10%, 15%, and 20 wt%) and adding 5 wt% of Alumina, with help of the pin-on disc apparatus. Additionally, mechanical properties such as hardness, tensile strength, impact strength and flexural strength are observed under various proportionate of fiber and filler embodiments.

For the past few decades, aluminum based hybrid composites have been widely used in many industries, with multiple reinforcements embedded to enhance the wear resistance properties. The wear performances of hybrid composites were prepared by stir casting method and wear performances were evaluated by pin on disc method at dry condition with varying applied load of 40N to 80N and sliding velocity of 1.5 m/s to 4.5 m/s. The wear worn surfaces were analyzed by scanning electron microscope and wear rates were calculated. The experimental results show that wear rate increases in either increasing applied load or sliding velocity and also the applied load and sliding velocity significantly influenced the wear volume loss in hybrid composites. The presence of multiple reinforcements in the matrix enhance the wear performances compared to the 6061 Al alloy.

Species-specific allometric models were developed to predict aboveground biomass (AGB) of eight woody species in the Borana rangelands, Ethiopia. The 23 equations developed (8 species; three biomass components: total aboveground, stem and branches) fit the data well to predict total AGB and by components for each of the species ( r 2 > 0.70; p Acacia bussei and Acacia etabaica ) were significantly predicted from a single predictor (circumference of the stem at ankle height), with a high coefficient of determination ( r 2 > 0.95; p Acacia oerfota ) was more effectively predicted by using the canopy volume ( r 2 = 0.84; p Acacia mellifera ) were most accurately predicted by a combination of both circumference of the stem at ankle height and canopy volume ( r 2 = 0.95; p 2 emission concerns and mitigation strategies.