Probabilistic Structural Optimization Under Reliability, Manufacturability, and Cost Constraints

A methodology is presented for probabilistic design optimization of aircraft structures subject to a set of multidisciplinary constraints including reliability, manufacturability, and manufacturing cost. Using the advanced firstorder second-moment method, reliability of each structural component is evaluated by considering its primary static failure mode. Metrics-based analytical models are used in manufacturability analysis, and semi-empirical models are used for manufacturing cost estimation. The described design methodology is developed into a software tool and applied to probabilistic sizing optimization of a moderately loaded built-up wing spar. Using two alternative web design concepts, one limited by buckling and the other by diagonal semitension field action, the spar model is optimized for weight considering uncertainties in the material properties, structural sizing, and loading parameters. The optimization problem is solved using the method of sequential quadratic programming for different values of target reliability, with or without any limit on manufacturing cost. The optimization results are used to highlight the interactions between reliability, weight, and cost, whereas the probabilistic sensitivities are used to examine the influence of each random variable on structural reliability.