Optimization of design parameters for Turkish Tirkes (war) bow

The bow and arrow is a projectile weapon system that predates recorded history and is common to most cultures. The Turkish bow is the most efficient one in its category. Despite of its superiority, Turkish bow is the one which is least documented in the literature. Technical drawings for the Turkish bow are missing. Turkish bow is a system consisting of different elements. Each element has its own distinctive feature and serves for a specific purpose. Recent interest in Turkish bow simply involves the replication of museum samples without any consideration about the performance characteristics of the replica. The present work aims at describing the Turkish bow, war bow known as Tirkes in specific. Characteristic shape parameters will be identified and the effect of each parameter on bow performance will be discussed. Parametric optimization to maximize bow efficiency will then be introduced. The bow shape will first be described. Characteristic shape parameters defining the bow geometry will be identified and the range in which they vary will be determined. The bow is drawn in the ANSYS (R) environment. Based on the design drawing a model bow is manufactured. Due to its superior flexing characteristics, E-glass fiber epoxy system is used in the composite structure. The model bow is tested to determine the characteristic draw weight - draw distance behavior of a typical bow. A mathematical model which is a simplified analysis of recurved bow types is used to compare behavior of model and manufactured bow draw weight - draw distance graph. Using ANSYS, bow is optimized over the related domain. Only geometrical parameters are considered. Bow length, width and thickness are varied over their domain of definition and their effect on the bow performance is investigated. Limb part is taken as the working element and is optimized for high deflection and low weight. The optimization process results in response charts showing the effect of the design variables on output. Sensitivity analyses of the input parameters resulted in the influence weight of each parameter and how each parameter affects the output. Using a goal-driven optimization approach, different design points were rate and the best design is identified. As compared to the effect of the other variable thickness is found to be the most influential variable affecting the draw weight. (C) 2014 Elsevier Ltd. All rights reserved.