A Response Surface Modelling Approach for Resonance Driven Reliability Based Optimization of Composite Shells

Abstract

IntroductionThe development of reliable composite structures in production process is always subjected to large variability due to manufacturing imperfection and uncertain operational factors. In practice, an additional factor of safety is assumed by designers due to difficulty in assessing reliability to avoid resonance in conjunction to uncertainties of stochastic natural frequencies. This existing practice of designer results in either an ultraconservative (overestimation of material cost) or an unsafe design. Hence, it is needed to overcome this current limitation wherein the design of composites are restricted to a deterministic regime despite of rapidly increasing demands of technological, economical and safety needs. Many literatures are available dealing with uncertainty quantification of composite structures [1][2][3]. Moreover, the reliability in conjunction to cost component involved in weight optimization of such composite structures are always a challenge for the designers. The common cause of employing composite structures in many applications (such as aircraft, civil structures) is weight sensitiveness wherein the objective of design optimization [4] is to lower the weight for achieving the better performance. For example, in structural design problem, the need of computation of the natural frequency is required to avoid the resonance which can vary with the uncertain geometric and material properties of the structure. In such engineering applications with complex systems, the consequences of uncertain system behaviour become severe in terms of cost and effort. The assessment of probability of failure and the need to improve the reliability of the systems have become essentially important for structural safety. Such necessities in turn raise the need for reliability based design optimization (RBDO) analysis [5]. The uncertain variation of system parameters can be mathematically coupled with optimization tools such as genetic algorithm (GA) to achieve safety as well as cost-effectiveness.Many studies are carried out by applying RBDO methods for optimal design of shallow composite structures. The random loading and material properties including manufacturing uncertainties are considered for example in [6][7][8][9][10][11]. Miki [12] and Fukunaga and Chou [13] proposed a graphical optimization method using lamination parameters for stiffened compos-

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