Abrasion resistance of surface-modified steels used for artillery weapon barrels
A barrel is one of the most tribologically and thermally loaded parts of artillery weapons. The influence of the salt bath nitrocarburizing and hard-chrome plating of three steels used for artillery barrels on their abrasion resistance is studied in this paper. The tested steels are 42CrMo4, 30CrNiMo8, and 36CrNiMo4 in the initial quenched and tempered state. The test results from the ''dry sand/rubber wheel'' method, after 700 m of wear path, showed that the hard-chrome plating of 42CrMo4 and 30CrNiMo8 steels improved their abrasion resistance. In addition, reduced abrasive wear of 42CrMo4 steel samples was also achieved by nitrocarburizing. Hard chrome-plated samples exhibited good wear resistance due to their greater hardness and bigger thickness of the compound zone in comparison with that obtained on nitrocarburized samples.
Thermo-chemical erosion in gun barrels
Abstract When a gun fires the metal temperatures at the bore may reach 1100°C in a few milliseconds and decline to half this value by the time the projectile reaches the muzzle. Although the temperature fluctuation does not penetrate very far from the surface it does create a hard and brittle surface layer commonly referred to as the heat-affected zone . The diffusion of chemical species such as CO, CO 2 , H 2 , H 2 O and N 2 into the hot surface forms a chemically-affected zone . Wear rate in guns is related to the thickness of this chemically-affected zone. From the equation of mass diffusion a simple equation of the Arrhenius type is derived relating the wear per round to the initial temperature, the maximum surface temperature, and the erosivity of the propellant. This equation is verified by trials on a vented vessel, which simulate gunfire, and also by data on the wear rates of numerous gun and propellant combinations. The erosivity of service propellants is correlated with their chemical composition and demonstrates that CO and H 2 are very erosive whereas CO 2 , H 2 O and N 2 are much less erosive.
Modelling and simulation of surface roughness in face milling
The paper presents a research on machined surface roughness in face milling of aluminium alloy on a low power cutting machine. Based on the results of the central-composite plan of experiment with varying machining parameters (number of revolutions - spindle speed n, feed rate f and depth of cut a) and the roughness observed as output variable, two models have been developed: a regression model and a model based on the application of neural networks (NN model). The regression model (coefficient of determination of 0.965 or 0.952 adjusted) with insignificant lack of fit, provides a very good fit and can be used to predict roughness throughout the region of experimentation. Likewise, the model based on the application of neural networks approximates well the experimental results with the level of RMS (Root Mean Square) error in the phase of validation of 4.01%.