Study of experimental design and response surface method for surrogate model of computational simulation

While the high-precision simulation is widely used in science and technology, Design of Experiment (DOE) based on Response Surface (RS) method can be employed in surrogate model to reduce the cost and error. In order to illustrate the relationship between parameters and response features , several DOE methods and Response Surface (RS) method are studied. The author used polynomial regression and RBF neural network based on orthogonal array to build a rocket aerodynamic discipline surrogate model respectively which proved their feasibility. From the results of the test case, conclusion is drawn that characteristic as well as acclimatization of DOE methods and different approximation should be considered for different issues, so the factors of cost and accuracy could reach a balance synthetically.