Multidisciplinary Design Optimization Of The Research And Application Of The Agent Model

Surrogate model is an important component of Multidiscipline Design Optimization (MDO). A surrogate model is created with experiment design methods and approximation approaches, and it can be easily integrated into a MDO Framework. This article describes the development process of surrogate models and introduces some experiment design methods and approximation approaches that can be used for a MDO surrogate model, they are Full Factorial Experiment Design, Orthogonal Experiment Design, Uniform Experiment Design, Central-Composite Experiment Design, and Polynomial Response Surface method, Kriging method, Radial Basis Function method and Artificial Neural Network. At the end of this article, a surrogate model is created to describe the lift distribution of a wing. Result shows that Kriging method and RBF method are two useful approximation approaches, especially for high dimension problem. In addition, this article created a generalized polynomial response surface model, and result shows that it can be also used to describe the lift distribution.