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.
Investigation of the material chemical composition influence on artillery weapons barrel hardness
The weapon barrel is exposed to strong thermal, mechanical and chemical effect of the powder gasses and the projectile. That causes the appearance of the intensive wear process of the barrel bore. In this paper the analysis of the samples’ chemical composition is performed, the metallographic structure of the samples’ material is imaged, the possible modification of the barrel bore surface is tested and the hardness over the samples cross section was measured. The hardness of the barrel material is one of the essential factors which contribute to increased barrel’s wear resistance. Therefore, modelling of HV5 hardness as a function of the chemical composition of materials was conducted. Determined correlations should allow an easier selection of the wear resistant barrel material as well as the material of other parts of the artillery weapons, with the need to establish a small number of influential parameters, without carrying out extensive tests.
Selection of Optimum Process Parameters in High Speed CNC End-Milling of Composite Materials Using Meta Heuristic Techniques - a Comparative Study
The machining of aluminium metal matrix composites in CNC high speed conditions is significant because such composites have diverse applications in the aeronautics industry. Because that industry requires high quality outcomes, the prediction of surface roughness, which depends on input process parameters, assumes significance in the maintaining quality of products. Even though many researchers have worked in the area of conventional machining, very few of them have explored optimization techniques, such as teaching-learning-based optimization (TLBO) and gravitational search algorithms (GSA) in high speed environments. In this research, an attempt is made to determine the optimum machining conditions for the end-milling of composite materials using GSA. Input process parameters, such as cutting speed, feed, the depth of cut and the step-over ratio are taken as independent variables, and surface roughness is taken as dependent variable. Experiments were conducted on Al 2O3 + SiC metal matrix composite by considering selected variations in the input process parameters. Surface roughness is measured in each of cases, and the required data is obtained for further analysis. An empirical relationship is established between dependent and independent variables in the form of linear and non-linear regression equations, and the results are analysed. The results showed that GSA gives better results for surface roughness when compared to the genetic algorithm, simulated annealing and TLBO methods. An additional set of experiments was conducted to validate the results obtained.