Multi-Objective Aerodynamic Shape Optimization Based on Class and Shape Transformation

A parameterization technique with fewer parameters and high fidelity and appropriate optimization algorithms was applied to improve the efficiency and accuracy of aerodynamic shape optimization. The class and shape transformation (CST) method is concise and efficient. Nevertheless, it is difficult to parameterize complex vehicle configurations using a unified CST method. This article presented a multi-block CST method after analyzing the mathematical description of the method, and this method joined adjacent surfaces smoothly and retained the good properties of the CST method. Pareto strategy was employed to deal with the multi-object problems in complicate flying task. A system of aerodynamic shape optimization was developed based on the multi-block CST method, genetic algorithms and hypersonic aerodynamic engineering analysis, and the aerodynamic characteristics of a quasi-waverider wing-body vehicle were improved significantly after optimization. A novel configuration was also created using the optimization system. The optimization results indicate that the multi-block CST method, which involves fewer design variables and yields higher fidelity, and Pareto genetic algorithms are powerful tools for aerodynamic shape optimization.