This study aims to develop a regression model using data from the Ammunition Stockpile Reliability Program (ASRP) to predict the shelf life of 81mm mortar high-explosive shells. Ammunition is a single-use item that is discarded after use, and its quality is managed through sampling inspections. In particular, shelf life is closely related to the performance of the propellant. This research seeks to predict the shelf life of ammunition using a regression model. The experiment was conducted using 107 ASRP data points. The dependent variable was 'Storage Period', while the independent variables were 'Mean Ammunition Velocity,' 'Standard Deviation of Mean Ammunition Velocity,' and 'Stabilizer'. The explanatory power of the regression model was an R-squared value of 0.662. The results indicated that it takes approximately 55 years for the storage grade to change from A to C and about 62 years to change from C to D. The proposed model enhances the reliability of ammunition management, prevents unnecessary disposal, and contributes to the efficient use of defense resources. However, the model's explanatory power is somewhat limited due to the small dataset. Future research is expected to improve the model with additional data collection. Expanding the research to other types of ammunition may further aid in improving the military's ammunition management system.

In the military, ammunition and explosives stored and managed can cause serious damage if mishandled, thus securing safety through the utilization of ammunition reliability data is necessary. In this study, exploratory data analysis of ammunition inspection records data is conducted to extract reliability information of stored ammunition and to predict the ammunition condition code, which represents the lifespan information of the ammunition. This study consists of three stages: ammunition inspection record data collection and preprocessing, exploratory data analysis, and classification of ammunition condition codes. For the classification of ammunition condition codes, five models based on boosting algorithms are employed (AdaBoost, GBM, XGBoost, LightGBM, CatBoost). The most superior model is selected based on the performance metrics of the model, including Accuracy, Precision, Recall, and F1-score. The ammunition in this study was primarily produced from the 1980s to the 1990s, with a trend of increased inspection volume in the early stages of production and around 30 years after production. Pre-issue inspections (PII) were predominantly conducted, and there was a tendency for the grade of ammunition condition codes to decrease as the storage period increased. The classification of ammunition condition codes showed that the CatBoost model exhibited the most superior performance, with an Accuracy of 93% and an F1-score of 93%. This study emphasizes the safety and reliability of ammunition and proposes a model for classifying ammunition condition codes by analyzing ammunition inspection record data. This model can serve as a tool to assist ammunition inspectors and is expected to enhance not only the safety of ammunition but also the efficiency of ammunition storage management.

In order to prevent accidents via defective ammunition, this paper analyzes recent research on ammunition life prediction methodology. This workanalyzes current shelf-life prediction approaches by comparing the pros and cons of physical modeling, accelerated testing, and statistical analysis-based prediction techniques. Physical modeling-based prediction demonstrates its usefulness in understanding the physical properties and interactions of ammunition. Accelerated testing-based prediction is useful in quickly verifying the reliability and safety of ammunition. Additionally, statistical analysis-based prediction is emphasized for its ability to make decisions based on data. This paper aims to contribute to the early detection of defective ammunition by analyzing ammunition life prediction methodology hereby reducing defective ammunition accidents. In order to prepare not only Korean domestic war situation but also the international affairs from Eastern Europe and Mid East countries, it is very important to enhance the stability of organizations using ammunition and reduce costs of potential accidents.

When considering military operations that require rapid response time, forward supply operation of various type of ammunition is essential. Also, t is necessary to supply ammunition in a timely manner before an ammunition shortage situation occurs. In this study, we propose a mathematical model for allocation of ammunition to ammunition storehouse at the Ammunition Supply Post (ASP). The model has several objectives. First, it ensures that the frequent used ammunition is stored in a distributed manner at a high workability ammunition storehouses. Second, infrequent used ammunition is required to be stored intensively at a single storehouse as much as possible. Third, capacity of the storehouse and compatible storage restriction required to be obeyed. Lastly, criticality of ammunition should be considered to ensure safety distance. We propose an algorithm to find the pareto-based optimal solution using the mathematical model in a reasonable computation time. The computational results show that the suggested model and algorithm can solve the real operational scale of the allocation problem.

Ammunition Demilitarization facility (ADF) should be set up the feasible goals and continue to operate, taking into account non-profit characteristics. However, due to the lack of performance measurement methods in ADF, which are essential to national policy at a significant cost each year, the reliability of the evaluation results can be insufficient. In this paper, the Balanced Score Card (BSC) method was applied that could be evaluated to reflect the financial and non-financial features. The relevant literature research and army regulations reflected the results of various interviews of the expert group. The extraction of success performance area in ADF was confirmed using the BSC method and the Decision Variable (DV) candidate was created to use regression for selecting the DV. Additionally, the key performance indicator was presented by verification the feasibility of content by conducting the survey of experts. The implications of this paper are as follows. First, the proposed BSC model was found to be suitable for practical use in ADF reflecting the non-profit characteristics. Second, accurate evaluation of ADF can contribute to long-term development of ADF. Finally, it can be applied to the management process of the other military sector, so it can be expected to play a role in providing basic data and spreading it to other areas.

본 연구는 175 mm 포탄추진체로부터 nitrocellulose의 친 환경적 분리에 관한 연구이다. 현재 국내외적으로 폐 탄약의 보유량은 점점 증가되고 있는 추세이며 부분적으로 비군사화가 시행되고 있으나 여전히 누적되고 있는 실정이다. 기존의 소각, 기폭 등의 재래식 방법은 소음, 분진, 진동을 동반한 오염물질 누출로 대기 및 토양오염을 초래하므로 제한을 받고 있다. 따라서 비극성 용매를 이용하여 nitrocellulose를 녹여내고 과량의 물을 가하여, 용해도 차이를 이용하여 고 순도의 nitrocellulose를 고형성분으로 추출하고, 추출된 nitrocellulose와 실험실에서 합성된 nitrocellulose를 IR 및 TLC 법으로 비교분석하여 추출된 물질의 순도를 확인한 결과 거의 순수한 nitrocellulose를 추출해 낼 수 있었다.

Domestic 105㎜ HE (High Explosive) shell is composed of three parts that are Fuze, Projectile and Propellants. Among three parts, propelling charge of propellants part consists of single base propellants. It has been known that the lifespan of single base propellants is affected by a storage period. These are because Nitrocellulose (NC) which is the main component of propelling gunpowder can be naturally decomposed to unstable substances similar with other nitric acid ester. Even though it cannot be prevented fundamentally from being disassembled, a decomposition product (NO2, NO3, and HNO3) and tranquillizer DPA (Diphenylamine) having high reactivity are added into a propellant to restrain induction of automatic catalysis by a decomposition product. The decay rate of the tranquillizer is also affected by a production rate of the decomposition product of NC. Therefore, an accurate prediction of the Self-Life is required to ensure against risks such as explosion. Hereupon, this paper presents a new methodology to estimate the shelf-life of single base propellants using data of ASRP (Ammunition Stockpile Reliability Program) to domestic 105mm HE (propelling charge of propellants part). We selected four attributes that are inferred to have influence on distribution of the DPA amount in a propellant from the ASRP dataset through data mining processes. Then the selected attributes were used as independent variables in a regression analysis in order to estimate the shelf-life of single base propellants. 1)

본 연구에서는 전투시스템의 생존성을 향상하기 위한 기술개발의 일환으로서 전투시스템이 외부 위협탄에 의한 충격을 받았을 경우, 전투시스템의 순간화재 발생에 따른 취약성을 분석하는 기법을 개발하고자 전산모사 해석방법을 이용하여 전투시스템의 순간화재 발생 가능성에 대해서 고찰하였다. 전투시스템의 유형은 임의 모형의 전차를 대상으로 선정하였으며, 전차의 구성요소들 가운데 외부 위협탄에 의해 순간화재가 발생할 수 있는 critical component로서는 고폭탄(추진제 포함)과 연료탱크 가운데 연료탱크만을 대상으로 선정하였다. 연료탱크에 주입된 연료는 휘발유, 경유, 등유 세 가지를 선정하고 관련 물성값을 이용하였다. 외부 위협탄은 1,475 m/s의 탄속을 갖는 운동에너지탄 type A와 1,560 m/s의 탄속을 갖는 운동에너지탄 type B로 가정하여 전산모사 해석을 수행하였다. 해석 프로그램은 Autodyn 프로그램을 사용하였고, Shock model을 적용하여 Lagrange process를 사용해서 1㎜ 간격의 계산격자로 계산을 수행한 결과, 평균 2시간 정도(CPU：Intel Core2 Duo, Quad 2.93GHz, RAM：1.75GB)가 소요되었다. 장갑의 두께별 관통된 탄두로부터 연료로의 열전달에 따른 온도값들을 이용하여 연료의 발화온도와 비교하여 순간화재의 발생 가능성을 고찰한 결과, 모든 탄두의 온도가 각각의 연료들의 발화온도보다 낮기 때문에 순간화재가 발생하지 않는 것으로 생각된다.