The increasing demand for air transportation has led to congestion in many major airports all over Europe, producing the necessity of innovative solutions to optimize runway capacity and efficiency. This study develops and simulates a model for evaluating airport runway capacity, integrating trajectory-based calculations and simulation methodologies to enhance aircraft operations. The main objectives are the assessment of the impact of different separation standards-ICAO-WTC and RECAT-EU-on runway performance, evaluating their effects on operational efficiency and safety and the creation of a software able to offer basic local solutions. A functional, robust, and efficient simulation tool was developed in C# to model single-runway operations under varying traffic conditions. The model incorporates key parameters such as aircraft separation minima, runway occupancy time, and approach sequencing, providing an accurate representation of real-world airport dynamics. Designed with a simple yet effective structure, the simulator is capable of processing multiple traffic scenarios, ensuring flexibility in analysing operational conditions. The software meets its intended objectives, providing reliable and consistent results across different input conditions. The results demonstrate that the RECAT-EU separation standards significantly improve operational capacity, achieving a 15-20% increase compared to ICAO-WTC. Homogeneous traffic scenarios yielded the highest capacities, while mixed operations highlighted the advantages of optimized separation rules. Additionally, arrival-dominated sequences consistently exhibited higher efficiency than departure-heavy or balanced scenarios. The simulator successfully validated these results, confirming its reliability in estimating runway capacity under different operational settings. This study highlights the importance of simulation-based decision-making tools in modern airport management. The developed simulator is functional, adaptable, and efficient, allowing users to evaluate and optimize runway capacity with ease and accuracy. Future research could expand the model by integrating multi-runway configurations, environmental factors, and real-time traffic flow adjustments to enhance its applicability in dynamic air traffic environment.
