The airside is a principal subsystem in the intricate airport systems. This study focuses on introducing a digital twin framework for analyzing delays and capacity at airports. This framework encompasses a diverse array of authentic features related to civil airports, accommodating a mixture of both landing and departing flights. Serving as a decision support tool for the management of international airports, the framework considers all sizes and weight categories of aircraft, each with unique service time and speed requirements in accordance with global aviation regulations.

The proposed discrete event simulation digital twin provides a real-time demonstration of system performance and predicts future outcomes of managerial decisions. Additionally, this twin is equipped with advanced and realistic 3D visualization, facilitating a more comprehensive understanding of ongoing operations. To assess its efficiency in practice, the framework was implemented at an international airport. Statistical tests revealed a high degree of similarity between the proposed twin and the real system. Utilizing this twin, the researchers further optimized the studied system by analyzing its projected future performance under various scenarios. This optimization resulted in nearly a 30% increase in the airport's capacity while reducing expected delays by over 18% annually.