Since the surface operation of hub airports was facing severe congestion and aircraft delay under the de-icing mode, some practical problems of improving aircraft operation and support efficiency are put forward. A two-phase model is constructed to coordinate the scheduling of aircraft surface operation (ASO) and de-icing support resources operation (DSRO). An optimized method is used to schedule the aircraft surface operation. On the basis of the scheduling results of surface operation, an aircraft and de-icing resource collaborative scheduling (ADCS) mechanism is established to optimize the assignment of aircraft and de-icing resources. The algorithm combining receding horizon control strategy and CPLEX solver (RHC-CPLEX) is designed to solve the model. Computational experiments performed on case studies of Beijing DaXing airport show some potential improvements: Firstly, for the ASO model, the RHC-CPLEX algorithm can reduce the objective function value by more than 20% compared with the FCFS algorithm. And the results shows that not only the delay distributions under different snow conditions are reasonable, but the spatial distributions of the de-icing zones of aircraft are closer to the location of their apron and allocated runway. Secondly, for the DSRO model, the RHC-CPLEX algorithm can reduce the objective function value by more than 6% compared with the algorithm based on the principle of proximity and availability. The de-icing vehicles are used efficiently and the number of refilling de-icing fluid and the free time of the de-icing vehicles can be significantly reduced.INDEX TERMS Air traffic management, aircraft de-icing operation, collaborative mechanism, de-icing support resources operation, integrated optimization, receding horizon control.
In this research, an efficient thermal-stress coupling design method for a Chiplet-based system with a coaxial through silicon via (CTSV) array is developed by combining the support vector machine (SVM) model and particle swarm optimization algorithm with linear decreasing inertia weight (PSO-LDIW). The complex and irregular relationship between the structural parameters and critical indexes is analyzed by finite element simulation. According to the simulation data, the SVM model is adopted to characterize the relationship between structural parameters and critical indexes of the CTSV array. Based on the desired critical indexes of the CTSV array, the multi-objective evaluation function is established. Afterwards, the structural parameters of the CTSV array are optimized through the PSO-LDIW algorithm. Finally, the effectiveness of the developed method is verified by the finite element simulation. The simulated peak temperature, peak stress of the Chiplet-based system, and peak stress of the copper column (306.16 K, 28.48 MPa, and 25.76 MPa) well agree with the desired targets (310 K, 30 MPa, and 25 MPa). Therefore, the developed thermal-stress coupling design method can effectively design CTSV arrays for manufacturing high-performance interconnect structures applied in Chiplet-based systems.
In view of the common U-shaped apron structure of large- and medium-sized airports at home and abroad, this study considered the optimization design and performance evaluation of the U-shaped apron operation procedure. First, by analyzing the physical structure characteristics and traffic operation characteristics of the U-shaped area, exclusive, partition-shared, and global-shared operation procedures of the U-shaped area were designed, and differentiated apron-operation rules and traffic models were constructed for different types of operation procedures. Then, from the perspectives of safety, efficiency, and environmental protection, a multi-dimensional evaluation index system of U-shaped area operation performance is established, and a classification measurement and comprehensive evaluation method based on critique is proposed. Finally, a traffic simulation model was established based on airport network topology modeling. We used Monte Carlo methods for the simulation in Python 3.6, and the experimental results show that, in the scenario of high-density traffic operation, compared with exclusive and partition-shared procedures, the implementation effect of the global shared procedure is very significant, and the apron operation capacity increased by 14.8% and 5.0%, respectively. The probability of aircraft conflict decreased by 32.2% and 11.8%, respectively, and the time of single conflict relief decreased by 16.1 s and 10.6 s, respectively. The average resource utilization in each U-shaped area increased by 66% and 25%, respectively, while the average daily carbon emissions of a single aircraft were reduced by 16.7 kg and 11.0 kg and the average daily fuel consumption of a single aircraft were reduced by 3.6 kg and 2.4 kg, respectively. The proposed method is scientific and effective and can provide theoretical and methodological support for optimizing the configuration of the scene operation mode of complex airports and for improving flight operation efficiency.
The runway system is more likely to be a bottleneck area for airport operations because it serves as a link between the air routes and airport ground traffic. As a key problem of air traffic flow management, the aircraft runway scheduling problem (ARSP) is of great significance to improve the utilization of runways and reduce aircraft delays. This paper proposes a large neighborhood search algorithm combined with simulated annealing and the receding horizon control strategy (RHC-SALNS) which is used to solve the ARSP. In the framework of simulated annealing, the large neighborhood search process is embedded, including the breaking, reorganization and local search processes. The large neighborhood search process could expand the range of the neighborhood building in the solution space. A receding horizon control strategy is used to divide the original problem into several subproblems to further improve the solving efficiency. The proposed RHC-SALNS algorithm solves the ARSP instances taken from the actual operation data of Wuhan Tianhe Airport. The key parameters of the algorithm were determined by parametric sensitivity analysis. Moreover, the proposed RHC-SALNS is compared with existing algorithms with excellent performance in solving large-scale ARSP, showing that the proposed model and algorithm are correct and efficient. The algorithm achieves better optimization results in solving large-scale problems.
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