Computational Optimization

Abstract

AbstractAerospace systems are often subject to challenging requirements on performance and reliability. Computational design optimization is an approach assisting design engineers in meeting these requirements. It automates the design procedure, allows for predicting the performance of a system by large, high‐fidelity numerical models, and enables consideration of a large number of design constraints and optimization variables. The formulation and solution of design optimization problems can be organized around three tasks: (i) transforming an engineering design problem into a mathematical optimization problem which is then solved by numerical algorithms, (ii) selecting the features of the systems that can be altered in the optimization process and expressing these modifications as functions of the optimization variables, and (iii) predicting the performance of the system as a function of the optimization variables. Today design optimization methods are used to optimize the material composition and the geometry of aerospace structures, considering for example structural, aerodynamic, and thermodynamic performance criteria. Optimization approaches are used to determine the conceptual layout of the system and to fine‐tune a particular feature. Computational design optimization supports design engineers in efficiently developing products. However, it requires an in‐depth understanding of the numerical models and methods used in the optimization process to obtain reliable optimization results.