Understanding the heat transfer phenomenon during interior ballistics and consequently presenting a realistic model is very important to predict the temperature distribution inside the cannon barrel, which influences the gun wear and the cook-off. The objective of this work is to present a new detailed numerical model for the prediction of thermal behaviour of a cannon barrel by combining PRODAS interior ballistics simulation with COMSOL simulation. In this study, a numerical model has been proposed for the heating behaviour of a 120 mm smoothbore cannon barrel, taking into account the combustion equation of the JA-2 propellant. Temperature dependent thermophysical properties of product gases were used for the calculation of the convective heat transfer coefficient inside the barrel. Projectile position, velocity of the projectile, gas temperature inside the barrel, volume behind the projectile and mass fraction during interior ballistics have been obtained by PRODAS software and used in the numerical model performed by COMSOL multiphysics finite element modelling and simulation software. Temperature simulations show that maximum wall temperature inside the cannon barrel is observed after 3 ms from fire, when maximum value of the convective heat transfer coefficient inside the barrel is observed. The results reveal that the convective heat transfer coefficient of burned gases inside the gun has major effect than the burned gas temperature on the heat transfer phenomenon.

In the first part of this study, the drying behavior of wool-acrylic yarn bobbins was investigated by a theoretical model and genetic algorithm method. Each candidate solution for Do, D1 and D2 was presented on a single chromosome. The values of Do, D1 and D2 yielding the best fit between the experimental and predicted moisture contents were obtained using the genetic algorithm. In the second part of this study, the suitability of various empirical and semiempirical models in the modeling of the drying process was investigated by the genetic algorithm. The population number was taken as 30 and the tournament selection method was used. The calculations were performed until the 20th generation for the theoretical model and 100th generation for the empirical and semiempirical models. The results show that the genetic algorithm can be successfully used in the modeling of the drying process of yarn bobbins. The results also show that the Verma et al. and Diffusion Approach models yield the best fit with experimental data.

In this study, intermittent drying process of corn was studied numerically for various intermittent periods and drying air temperatures. An Arrhenius type diffusicoefficient D = e (-b/T) ⋅ 10-9 m 2 /s was proposed for the moisture diffusion inside the corn. Numerical simulations were performed by choosing the suitable value for drying constant, b, that yields the best agreement with experimental drying rates. The experimental results were obtained via an experimental setup for intermittent periods of 30 minute and 60 minute, and drying air temperatures of 40 °C, 50 °C, 60 °C, and 70 °C. The results show that overall agreement between the experimental and theoretical prediction is good. On the other hand, the theoretical results overestimate the moisture ratio at the initial stage and underestimate it at the later stage of drying.

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