Design and Application of Structural Optimization Algorithm for Free-Form Surface Shell Structure

The purpose of this article is to explore the creative optimization method of free-form surface shell structure in order to improve the innovation and structural performance of architectural design. Aiming at the problems existing in traditional optimization methods, such as insufficient modeling precision and low computational efficiency, an intelligent optimization algorithm combined with convolutional neural network (CNN) technology is proposed. The algorithm adopts intelligent optimization strategy to update the surface shape iteratively, so as to gradually approach the optimal solution. With the help of comparative experiments, the obvious advantages of the proposed algorithm in modeling precision and computational efficiency are verified. Compared with the traditional ant colony optimization (ACO) algorithm, this algorithm greatly shortens the calculation time and improves the optimization efficiency while maintaining a high modeling precision. In practical project application, the algorithm has also achieved remarkable optimization effect, effectively improving the performance of free-form surface shell structure. The optimization algorithm of free-form surface shell structure proposed in this article opens a new field of vision for architectural design. The research results are of great significance for promoting the intelligent development of the construction industry.