Computer Aided Optimisation Design Of Riveted Joints In Aereonautics

Riveted joints are one of the major methods for joining airframe structural components. There are millions of rivets in a common commercial aircraft, and they play a crucial role in aircraft safety. Then, the reduction of the number of rivets can lower the cost of manufacture significantly. Moreover, riveted joints design represents a considerable cost in the design process. In sum, riveted joints design has an important influence on the mechanical strength, manufacturability and design cost of the aircraft.Nowadays, two main departments are involved in the riveted joints design: the design department and the calculation department. A lot of time is wasted during the transmission of information and possible desynchronization between these two departments. Moreover, the design has a lot of design variables and the object function is rather complex, thus an automatic algorithm is not enough to optimize the design.To solve this problem, this article proposed a computer aided optimization design method to design riveted joints in aeronautics. First, this article develops an evaluation algorithm. This algorithm transforms design variables of riveted joints design such as number, positions, and types of rivets into observation variables which are directly linked to performance of riveted joints design such as safety factors of rivets, distances between rivets, mass of structure, etc. Then, this evaluation algorithm transforms the observation variables into four evaluation indicators: mechanical strength, manufacturability, lightness and professional rules. At last, this algorithm combines these four indicators into one single value: the general performance of riveted joints design. Designer performs a preliminary optimization design with help of feedback information of the evaluation algorithm. Second, this article develops an Artificial Immune System(AIS) optimization algorithm to further optimize riveted joints design. AIS optimization algorithm is a stochastic optimization algorithm inspired by human immune system. This article puts the preliminary optimization design into initial population of candidates of AIS optimization algorithm, and through operations such as clone, mutation, selection, etc., a final optimized design solution is obtained. This method is applied to the riveted joints design of the nacelle of the turbofan engine SaM 146 and proves that this method which combines optimization by designer and optimization by algorithm is both effective and efficient.