Weather is one of the main causes of aircraft accidents, and among the phenomena caused by weather, icing is a phenomenon in which an ice layer is formed when an object exposed to an atmosphere below a freezing temperature collides with supercooled water droplets. If this phenomenon occurs in the rotor blades, it causes defects such as severe vibration in the airframe and eventually leads to loss of control and an accident. Therefore, it is necessary to foresee the icing situation so that it can ascend and descend at an altitude without a freezing point. In this study, vibration data in normal and faulty conditions was acquired, data features were extracted, and vibration was predicted through deep learning-based algorithms such as CNN, LSTM, CNN-LSTM, Transformer, and TCN, and performance was compared to evaluate blade icing. A method for minimizing operating loss is suggested.

In this study, the scale of renewable photovoltaic(PV) panels and hydrogen fuel storage facilities required to achieve "net zero carbon emissions" in military facilities were predicted based on actual electricity consumption. It was set up to expect the appropriate installation size of PV panel and hydrogen fuel storage facility for achieving carbon neutrality, limited to the electricity consumption in the public sector, including national defense and social security administration in Yeongcheon. The experimental results of this paper are largely composed of two parts. First, representative meteorological factors were considered to predict solar power generation in the Yeongcheon area, and solar power generation was estimated through a multiple regression model using deep learning techniques. Second, the size of solar power generation facilities and hydrogen storage facilities in military bases was estimated with the amount of solar power generation and electricity consumption. As a result of this analysis, it was calculated that a site of 155.76×104 m² for PV panels was needed and a facility capable of storing 27,657 kg of hydrogen gas was required. Through these results, it is meaningful to demonstrated the prospect that military units can lead the achievement of "carbon net zero 2050" by using PV panels and hydrogen fuel storage facilities on idle sites of military bases.

In order to avoid the high observability due to the cavity resonance or electromagnetic wave leakages from the bridge of a battleship or the cockpit of an aircraft, this paper presents a transparent conductive oxide coated structure to prevent the incoming/outgoing electromagnetic waves. Currently, most of the RCS reduction technologies were focused on radar absorbing material such as paints based on conductive or magnetic materials in the fuselage, and there is not much research on countermeasures for achieving the low observability of materials that required optical transparency in actual weapon systems. In this study, the transmission/reflection and absorption performance of the ITO coated structure according to the change of the surface resistance of the transparent conductor were analyzed. Finally, the relationship between the electromagnetic and optical characteristics was established through fabrication and measurement.

The gas-gun test is a experimental approach employed to validate the operational or structural stability when subjected to the impact energy encountered during launch or target collision. Predicting the outcomes of the gas-gun test has traditionally relied on empirical knowledge, due to numerous factors such as the bird assembly's shape, weight, material, and flight velocity. However, due to the nonlinearity and complex interactions between these variables, numerous tests are necessary to identify the necessary requirements, resulting in significant expense and time consumption during the process. The objective of this study is to forecast the variations in impact energy in future tests by developing a numerical model and analysis that aligns with the test outcomes, utilizing the ABAQUS Explicit. The outcome of the numerical analysis produced a framework that anticipates the peak g and the duration of the actual gas-sun test results, throughout post-processing techniques using FFT and LPF filters.

In this study, the methodology of determination of base bleed motor data for base bleed projectile based on the NATO standard trajectory model, especially STANAG 4355 Method 2 were presented. Ground combustion experiments and aerodynamic performance firing tests were conducted to determine the drag reduction motor data of the base bleed projectile and this data was described based on the NATO standard ballistic model. The derived drag reduction motor data were input into the ballistic equations to complete the ballistic model and it was confirmed that the calculated predicted trajectory from the ballistic model matched well with the measured trajectory from the aerodynamic performance firing tests.

Large planar military antenna boasts a range of electrical components, including TRA(Transmit-Receive Assembly), signal processors, etc. which engage in computations and calculations. These processes generate a significant amount of heat, leading to unforeseen consequences for the equipment. To mitigate these adverse effects, it's imperative to implement a cooling system that can effectively reduce heat-related issues. Given the antenna's intricate nature and the multitude of components it houses, a two-step estimation process is necessary. The first step involves a comprehensive model calculation to determine the total flow characteristics, while the second step entails a thermal analysis of individual TRA set. In this study, we depicted an antenna set using simplified 3D models of its components, considering their material and thermal properties. The sequential analysis process facilitated the calculation of branched flow rates, providing insights into the individual TRA. This approach also allowed us to design a cooling system for the TRA set, assessing its thermal stability in high-temperature environments. To ensure the optimal performance of TRA, breaking down the analysis into stages based on the cooling system's structure can assist operators in predicting numerical results more effectively.

Uumanned aerial vehicle(UAV) systems have been used in various fields including industry and military. According to increasing the number of UAVs, the attention on interoperable UAV systems is increasing. In this paper, we propose the practical design of datalink in interoperable UAV systems. For practical design, we firstly review the operational scenarios in the interoperable UAV system. We then propose the system model of the datalink in interoperable UAV system. Consequently, the technical components such as the design of the network, the link management, the support of the multicast transmission, the support for autonomous mission and flight safety, and the datalink security are derived and reviewed for the practical design.

The importance of geospatial information is increasingly highlighted in the defense domain. Accurate and up-to-date geospatial data is essential for situational awareness, target analysis, and mission planning in millitary operations. The use of high-resolution geospatial data in military operations requires large storage and fast image processing capabilities. Efficient image processing is required for tasks such as extracting useful information from satellite images and creating 3D terrain for mission planning, In this paper, we designed a cloud-based operational situation mixed reality visualization system that utilizes large-scale geospatial information distributed processed on a cloud server based on the container orchestration platform Kubernetes. We implemented a prototype and confirmed the suitability of the design.

This paper describes the results of the development of the the unmanned aerial vehicle system integration laboratory(UAV SIL) for the integrated verification. This UAV SIL is designed to test the robustness of the UAV system including the operational logics and the flight control system behaviors under many abnormal and emergency conditions such as data-link losses, airborne subsystem failures, engine shut down conditions, and ground control station faults. This paper presents how to build the UAV SIL and how to verify the in-development UAV system through the UAV SIL.

This study attempted to analyze the factors that influence the participation of beneficiary companies in the government's defense industry promotion support project. To this end, experimental data were analyzed by constructing a prediction model consisting of highly important variables in beneficiary company decisions among various company information using the decision tree model, one of the data mining techniques. In addition, various rules were derived to determine the beneficiary companies of the government's support project using the analysis results expressed as decision trees. Three policy measures were presented based on the important rules that repeatedly appear in different predictive models to increase the effect of the government's industrial development. Using the analysis methods presented in this study and the determinants of the beneficiary companies of the government support project will help create a sustainable future defense industry growth environment.

In this study, we conducted a survival analysis on battalion-level commanders(leaders), focusing on infantry battalion defensive operations using the big data of brigade-level KCTC(Korea Combat Training Center) training results. Unlike previous studies, we utilized the brigade-level KCTC training results data for the first time to conduct a survival analysis, and the research subjects were battalion-level commanders(leaders), which can affect the battle. At this time, the battle results were defined, and through cluster analysis, infantry battalions were divided into excellent, average, and insufficient units, and the difference in the survival rate of the commanders was analyzed through the Kaplan-Meier survival analysis. This provided an opportunity to objectively compare the differences between excellent and insufficient units. Subsequently, factors affecting the survival of commanders were derived using the Cox proportional hazard model, and it was possible to confirm the influencing factors from various angles by also using the survival tree model. Significance and limitations confirmed in the research process were presented as policy suggestions and future research directions.

Various vaccines were rapidly developed during the COVID-19 pandemic to prevent and treat infections but global infections continue, and concerns about new mutations and infectious diseases persist. Thus, active research focuses on developing, producing, and supplying vaccines and treatments for various infectious diseases and potential pandemics. Natural killer(NK) cells, as innate immune cells, can recognize and eliminate abnormal cells like virus-infected and cancer cells. Hence, their development as anticancer and antiviral treatments is rapidly advancing. In this study, optimal short-term culture conditions were identified for allogeneic NK cells by simplifying the culture process through the isolation of NK cells(referred to as NKi cells) and eliminating CD3+ cells(referred to as CD3- cells). NK cells demonstrated reduced viral titer in injection of NK cells into SARS-CoV-2 infected ACE-tg mice increased survival. The study's findings could form the basis for an antiviral treatment platform that swiftly responds to new viral disease pandemics.

The COVID-19 pandemic is not over despite the emergency use authorization as can see recent COVID-19 daily confirmed cases. The viruses are not only difficult to diagnose and treat due to random mutations, but also pose threat human being because they have the potential to be exploited as biochemical weapons by genetic manipulation. Therefore, it is inevitable to the rapid antibody-based therapeutic platform to quickly respond to future pandemics by new/re-emerging viruses. Although numerous researches have been conducted for the fast development of antibody-based therapeutics, it is sometimes hard to respond rapidly to new viruses because of complicated expression or purification processes for antibody production. In this study, a novel rapid antibody-based therapeutic platform using single B cell sorting method and mRNA-antibody. High immunogenicity was caused to produce antibodies in vivo through mRNA-antigen inoculation. Subsequently, antigen-specific antibody candidates were selected and obtained using isolation of B cells containing antibody at the single cell level. Using the antibody-based therapeutic platform system in this study, it was confirmed that novel antigen-specific antibodies could be obtained in about 40 days, and suggested that the possibility of rapid response to new variant viruses.