Intelligent design and optimization system for shear wall structures based on large language models and generative artificial intelligence

Intelligent design technology for shear wall structures has great potential for enhancing design efficiency and addressing the challenges of tedious and repetitive design tasks. Recently, there has been a surge in the development of this technology. However, existing deep learning-based design methods for shear wall structures suffer from poor quality and usability issues. To address these challenges, this study proposes an intelligent design and optimization system for shear wall structures based on large language models (LLMs) and generative artificial intelligence (AI). The system employs an LLM as the core controller, which interacts with engineers to interpret their language descriptions and translate them into executable computer code. Subsequently, the system utilizes the corresponding structural generation and optimization methods to accomplish intelligent design tasks automatically. Furthermore, the system incorporates such critical factors as the empirical rules, mechanical performance, and material consumption into the structural optimization process. A unique three-level, two-stage optimization method is constructed based on topology, pattern, and size to enhance the overall design quality. Being able to complete the entire workflow of architectural drawing processing, structural scheme generation, and analysis model establishment, the proposed system enables automated and efficient design of shear wall structures. Through the analysis and validation of multiple cases, it was demonstrated that this system can significantly speed up the design by approximately 30 times compared to that of traditional methods whilst ensuring the safety and cost-effectiveness of the design schemes. Consequently, this study provides valuable insights for the advancement of automated structural design undertakings.