Abstract: With the continuous development of launch vehicle technologies and the growing demand for high-density, diversified mission requirements, higher requirements have been placed on rapid iteration of launch vehicle development and closed-loop design parameter optimization. Based on the principles of Model-Based Systems Engineering (MBSE), this paper adopts a data-driven approach to enable collaborative design of multidisciplinary models during the overall closed-loop design process of launch vehicles, demonstrating the engineering feasibility of model-based processes over document ones. Aiming at addressing issues such as prolonged aerodynamic characteristic prediction time and multiple trajectory design constraints in traditional general loop design, the application of artificial intelligence prediction and optimization algorithms significantly enhances the design efficiency of aerodynamic characteristic models and trajectory calculation models, thereby substantially reducing the design cycle of general loop systems. Through actuator invocation, the platform enables the calling of specialized tools and data interaction between models. This ensures both free flow of design data across disciplines during the process and real-time tracking of design data iterations. These achievements reach the goals of "data homogenization" and "change synchronization" throughout the entire loop of the overall design process.

Key words: data-driven, general design, MBSE, artificial intelligence