ABSTRACT
In modern air combat, collaborative detection and engagement among multiple aircraft have gradually become a predominant combat approach. In response to the challenges posed by modern stealth aircraft, although their external factors such as coatings significantly reduce the chances of enemy detection, once these stealth aircraft activate their radar systems, they become susceptible to detection. Therefore, an application model has been proposed to mitigate enemy detection of our stealth aircraft through a collaborative approach. The underlying principle involves employing the concept of multi-aircraft collaboration, where the aircraft are divided into transmitters and receivers. The transmitters emit radar waves while the receivers are responsible for receiving these waves. This approach effectively mitigates the increased probability of enemy detection resulting from the activation of our receivers' radar systems. The optimization problem we aim to address is determining the optimal formation configuration for cooperative flight, specifically a formation with a specific configuration that maximizes the detectable range. This optimization problem is known as the configuration optimization problem for Airborne Radar Network with Separate Transmitting and Receiving (ARN-STAR). Existing methods for this problem typically suffer from limitations in either effectiveness or efficiency. To overcome these limitations, we propose an optimized configuration method based on an improved Artificial Fish Swarm Algorithm (IFSA) for ARN-STAR. Firstly, leveraging the distribution characteristics of the target radar wave's spatial scattering and the concept of dual-radar spatial diversity, we establish a mathematical model and an optimization objective function for ARN-STAR. Secondly, to address efficiency concerns, we optimize the computational process using the IAFS, successfully improving the speed of computation. To address the issue of effectiveness, we introduce adaptive adjustments to the movement step size of the artificial fish and improve the implementation of the three behavioral modes, thereby avoiding local optima and enhancing the accuracy of finding the optimal configuration. Finally, using our self-developed multi-aircraft collaborative simulation platform, we apply the improved AFSA to obtain the optimal formation configuration scheme and compare it with other methods. Simulation results demonstrate that our proposed method effectively solves the problem of finding the optimal formation configuration in multi-aircraft collaborative detection scenarios with "one transmission and multiple receptions." It overcomes the low computational efficiency associated with traditional methods while maintaining good accuracy. This approach enables the enhancement of overall combat capabilities while ensuring the safety of our aircraft to the greatest extent possible. It should be noted that the scenarios discussed in this study are at the configurational configuration level between UAVs, rather than involving the design of the UAVs combat control system itself.
ABSTRACT
CO2 miscible flooding in low permeability reservoirs is conducive to significantly improving oil recovery. At present, the microscopic displacement simulation of CO2 miscible flooding is mainly reflected in the simulation of the seepage process, but the pressure control of the seepage process is lacking, and the simulation of the characterization of CO2 concentration diffusion is less studied. In view of the above problems, a numerical model of CO2 miscible flooding is established, and the microscopic seepage characteristics of interphase mass transfer in CO2 miscible flooding are analyzed by multiphysics field coupling simulations at the two-dimensional pore scale. The injection velocity, contact angle, diffusion coefficient, and initial injection concentration are selected to analyze their effects on the microscopic seepage characteristics of CO2 miscible flooding and the concentration distribution in the process of CO2 diffusion. The research shows that after injection into the model, CO2 preferentially diffuses into the large pore space and forms a miscible area with crude oil through interphase mass transfer, and the miscible area expands continuously and is pushed to the outlet by the high CO2 concentration area. The increase in injection velocity will accelerate the seepage process of CO2 miscible displacement, which will increase the sweep area at the same time. The increase in contact angle increases the seepage resistance of CO2 and weakens the interphase mass transfer with crude oil, resulting in a gradual decrease in the final recovery efficiency. When the diffusion coefficient increases, the CO2 concentration in the small pores and the parts that are difficult to reach at the model edge will gradually increase. The larger the initial injection concentration is, the larger the CO2 concentration in the large pore and miscible areas in the sweep region at the same time. This study has guiding significance for the field to further understand the microscopic seepage characteristics of CO2 miscible flooding under the effect of interphase mass transfer.
