In the terminal area, the integration of new aircraft (such as electric vertical takeoff and landing aircraft and unmanned aerial vehicle systems) with traditional manned aircraft poses a significant challenge to modern air traffic management systems. To overcome the limitations of traditional macro-delay indicators in identifying local sector risks, this paper constructs a dual-constraint mechanism for sector capacity assessment based on the AirTop simulation platform. This mechanism integrates key factors such as flight conflicts, average aircraft congestion rate, and controller workload to construct a comprehensive performance index. Based on this comprehensive index, this paper constructs a dual-constraint mechanism: on the one hand, it identifies physical abrupt changes in the sector flow efficiency evolution curve; on the other hand, it uses historical safety thresholds from traditional manned aircraft operations for benchmark anchoring. Through these two dual constraints, the safe saturation level of the sector is ultimately determined. Experimental results show that as the UAV integration rate increases from 0% to 30%, the terminal area capacity decreases non-linearly, from 79 flights/hour to 65 flights/hour. When the UAV integration rate is 10%, the mechanism successfully identifies a latent saturation flow of 5 flights/hour and corrects the hourly saturation capacity of the terminal area to 71 flights/hour. Furthermore, this paper applies a multi-sectoral collaborative flow reduction strategy based on set theory to deduplicate flight data, successfully eliminating 22.09% of redundant calculations and effectively avoiding excessive system adjustments caused by spatiotemporal coupling. This fusion method meets the stringent requirements of microscopic security and macroscopic efficiency, providing a solid theoretical foundation and practical technical support for refined capacity management of heterogeneous hybrid airspace in the future.