Airpower plays a key role in neutralizing military threats and securing victory in wars. This study analyzes newly introduced fighter forces by considering factors like performance, power index, operational environment, airbase capacity, survivability, and sustainment capability to devise an optimal deployment strategy that enhances operational efficiency and effectiveness. Using optimization methods like mixed integer programming (MIP), the study incorporates constraints such as survivability and mission criticality. The focus is on major Air Force operations, including air interdiction, defensive counter-air, close air support, and maritime operations. Experimental results show the proposed model outperforms current deployment plans in both wartime and peacetime in terms of operations and sustainment.

North Korea has repeatedly provoked using unmanned aerial vehicles (UAVs), and the threat posed by UAVs continues to escalate, as evidenced by recent directives involving the use of waste-laden balloons and the development of suicide drones. North Korea’s small UAVs are difficult to detect due to their low radar cross-section (RCS) values, necessitating the efficient deployment and operation of assets for effective response. Against this backdrop, this study aims to predict the infiltration routes of enemy UAVs by considering their perspective, avoiding key facilities and obstacles, and propose deployment strategies to enable rapid detection and response during provocations. Utilizing the Markov Decision Process (MDP) based on previous studies, this research presents a model that reflects both UAV flight characteristics and regional environments. Unlike previous models that designate a single starting point, this study addresses the practical challenge of uncertainty in initial infiltration points by incorporating multiple starting points into the scenarios. By aggregating and integrating the probability maps derived from these variations into a unified map, the model predicts areas with a high likelihood of UAV infiltration over time. Furthermore, based on case studies in the capital region, this research proposes deployment strategies tailored to the specifications of currently known anti-drone integrated systems. These strategies are expected to support military decision-making by enabling the efficient operation of assets in areas with a high probability of UAV infiltration.

This study proposes a mathematical model to optimize the fighter aircraft-weapon combinations for the Republic of Korea Air Force. With the recent emergence of the population cliff issue due to declining birth rates in Korea, there is an urgent need for efficient weapon system operations in light of decreasing military personnel. This study aims to enhance operational environments and mission efficiency within the military. The objective is to reduce the workload of pilots and maintenance personnel by operating an optimal number of weapons instead of deploying all possible armaments for each aircraft type. To achieve this, various factors for optimizing the fighter-weapon combinations were identified and quantified. A model was then constructed using goal programming, with the objective functions based on the compatibility, Circular Error Probable (CEP), and fire range of the weapons, along with the planned wartime mission-specific weapon ratios for each aircraft type. Experimental analysis of the proposed model indicated a significant increase in mission performance efficiency compared to the existing system in both operational and maintenance aspects. It is hoped that this model will be applied in military settings.

This study presents an optimization model for the Tactical Information Communication Network (TICN), which is crucial for military operations, focusing on the efficient deployment of communication nodes to create a rapid and robust network while minimizing both distances and the number of nodes required. By integrating mixed integer programming (MIP) with minimum spanning tree (MST) and Steiner Tree algorithms, the model ensures that nodes are connected through the shortest, most efficient routes. Simulations demonstrate the model’s ability to form cohesive networks under constrained resources and time, reducing transmission distances and maintaining network stability. Case studies in a grid environment confirm the system's efficiency, with the model able to redeploy nodes if damaged to preserve network integrity. By utilizing both high- and low-capacity transmission systems, the model ensures reliable communication in challenging terrains like Korea’s mountainous landscape. The findings have critical implications for military communication strategies, especially for multi-domain operations involving air, land, and sea forces, and support decision-making for rapid and efficient deployment of communication networks in unpredictable conditions.

The feeder pipes of the primary cooling system in a pressurized heavy water reactor (PHWR) are composed of carbon steel SA 106 GR.B. On the surface of this structural material, corrosion oxide layers including radionuclides are formed due to the presence of active species from water decomposition products caused by radiation, as well as the high temperature and high-pressure environment. These oxide layers decrease the heat transfer efficiency of the primary cooling system and pose a risk of radiation exposure to workers and the environment during maintenance and decommissioning, making effective decontamination essential. In this study, we simulated the formation of the corrosion oxide layer on the surface of carbon steel SA 106 GR.B, characterized the formed corrosion oxide layer, and investigated the dissolution characteristics of the corrosion oxide layer using oxalic acid (OA), a commercial chemical decontamination agent. The corrosion oxide layer formed has a thickness of approximately 4 μm and consists of hematite ( Fe2O3) and magnetite ( Fe3O4). The carbon steel coupons with formed oxide layers were dissolved in 10 mM and 20 mM OA solutions, resulting in iron ion concentrations of 220 ppm and 276 ppm in the OA respectively. In 10 mM and 20 mM OA, the corrosion depths of the coupons were 8.93 μm and 10.22 μm, with corrosion rates of 0.39 mg/cm2·h and 0.45 mg/cm2·h, respectively. Thus, this demonstrates that higher OA concentrations lead to increased dissolution and corrosion of steel.

A substantial quantity of discarded tires has inflicted harm on the environment. Microwave pyrolysis of discarded tires emerges as an efficient and environmentally friendly method for their recycling. This research innovatively utilizes the characteristics of microwave rapid and selective heating to pyrolyze waste tires into porous graphene under the catalysis of KOH etching. Moreover, this study comprehensively investigates the dielectric characteristics and heating behavior of waste tires and different proportions of waste tire–KOH mixtures. It validates the preparation of graphene through KOH-catalyzed microwave pyrolysis of waste tires, tracking morphological and structural changes under varying temperature conditions. The results indicate that optimal dielectric performance of the material is achieved at an apparent density of 0.68 g/cm3 at room temperature. As the temperature increases, the dielectric constant gradually rises, particularly reaching a notable increase around 700 °C, and then stabilizes around 750 °C. Additionally, the study investigates the penetration depth and reflection loss of mixtures with different proportions, revealing the waste tire–KOH mass ratio of 1:2 demonstrates favorable dielectric properties. This research highlights the impressive microwave responsiveness of the waste tire–KOH mixture, Upon the addition of KOH, the mixed material exhibits an augmented dielectric constant and relative dielectric constant, supporting the viability of KOH-catalyzed microwave pyrolysis for producing porous graphene from waste tires. This method is expected to provide a new method for the valuable reuse of waste tires and a technology for large-scale, efficient and environmentally friendly production of graphene.