Uncertainty and Robustness in Aerospace Structures
Engineering is not an exact science. In fact, all engineering activity contain some degree of assumption, simplification, idealization, and abstraction. When engineered creations meet reality, every manufactured product behaves differently. This variation can be detrimental to product quality and functionality. In an aerospace context, this variation may even result in serious threats to the safety and reliability of aircraft. However, it is not the variation in and of itself that is harmful, but the effects it imposes on functionality—an important distinction to make.
Reducing sources of variation is often associated with tightening tolerances and increasing cost. Instead, it is preferable to eliminate the effects of this variation by making designs more robust. This idea is at the core of robust design methodology.
Aerospace is an industry characterized by the complexity of its products and the multidisciplinary nature of its product development. In such contexts, there are significant barriers against implementing uncertainty-based design practices.
The research presented in this thesis aims at identifying the role of robust design in general, and geometry assurance in particular, in the early phases of aerospace component design. Further, this thesis proposes a methodology by which geometry assurance practices may be implemented in this setting. The methodology consists of a modelling approach linked to a multidisciplinary simulation environment.
In a series of case studies, the methodology is tested in an industrial setting. The capability of the methodology is demonstrated through several applications, in which the effects of geometric variation on the aerodynamic, thermal, and structural performance of a load-bearing turbofan component are analysed. Investigated effects include part variation, fixture variation, part configuration and welding.
The proposed methodology overcomes many of the current barriers, making it more feasible to assess geometric variation in the early design phases. Despite some limitations, the methodology contributes to an academic understanding of how to evaluate geometric variation in multidisciplinary simulations and provides a tool for industry. Geometric variation is only one source of uncertainty amongst many others. By evaluating geometric variation against the framework of uncertainty quantification, this thesis addresses the relative importance of geometry assurance against other product development activities.