Airpower is a crucial force for suppressing military threats and achieving victory in wars. This study evaluates newly introduced fighter forces, considering factors such as fighter performance and power index, operational environment, capacity of each airbase, survivability, and force sustainment capability to determine the optimal deployment plan that maximizes operational effectiveness and efficiency. Research methods include optimization techniques such as MIP(mixed integer programming), allocation problems, and experimental design. This optimal allocation mathematical model is constructed based on various constraints such as survivability, mission criticality, and aircraft's performance data. The scope of the study focuses the fighter force and their operational radius is limited to major Air Force and joint operations, such as air interdiction, defensive counter-air operations, close air support, maritime operations and so on. This study aims to maximize the operational efficiency and effectiveness of fighter aircraft operations. The results of proposed model through experiments showed that it was for superior to the existing deployment plan in terms of operation and sustainment aspects when considering both wartime and peacetime.

This study aims to develop a deep learning model to monitor rice serving amounts in institutional foodservice, enhancing personalized nutrition management. The goal is to identify the best convolutional neural network (CNN) for detecting rice quantities on serving trays, addressing balanced dietary intake challenges. Both a vanilla CNN and 12 pre-trained CNNs were tested, using features extracted from images of varying rice quantities on white trays. Configurations included optimizers, image generation, dropout, feature extraction, and fine-tuning, with top-1 validation accuracy as the evaluation metric. The vanilla CNN achieved 60% top-1 validation accuracy, while pre-trained CNNs significantly improved performance, reaching up to 90% accuracy. MobileNetV2, suitable for mobile devices, achieved a minimum 76% accuracy. These results suggest the model can effectively monitor rice servings, with potential for improvement through ongoing data collection and training. This development represents a significant advancement in personalized nutrition management, with high validation accuracy indicating its potential utility in dietary management. Continuous improvement based on expanding datasets promises enhanced precision and reliability, contributing to better health outcomes.

본 논문에서는 다목적 구조물인 다중연결 해양부유체를 대상으로 변형 기반 모드 차수축소법을 적용하고 차수축소모델의 구조응 답 예측 성능을 향상시키기 위해 유전 알고리즘 기반의 센서 배치 최적화를 수행하였다. 다중연결 해양부유체의 차수축소모델 생성 에 필요한 변형 기반 모드 데이터를 얻기 위해 다양한 규칙파랑하중조건에 대한 유체-구조 연성 수치해석을 수행하고 변형 기반 모드 의 직교성, 자기상관계수를 이용하여 주요 변형 기반 모드를 선정하였다. 다중연결 해양부유체의 경우 차수축소모델의 구조응답 예 측 성능이 계측 및 예측 구조응답 위치에 따라 민감하기 때문에 유전 알고리즘 기반의 최적화를 수행하여 최적의 센서 배치를 도출하 였다. 최적화 결과, 모든 센서 배치 조합에 대한 차수축소모델 생성 및 예측 성능 평가 대비 약 8배의 계산 비용을 절감하였으며, 예측 성능 평가 지표인 평균 제곱근 오차가 초기 센서 배치보다 84% 감소하였다. 또한, 다중연결 해양부유체 모형시험 결과를 이용하여 불 규칙파랑하중에 대한 최적화된 센서 배치의 차수축소모델의 구조응답 예측 성능을 평가 및 검증하였다.

본 논문에서는 무도상 철도판형교에 열차하중이 재하되었을 때 변위를 최소화시키는 하부 수평브레이싱의 보강 형상 및 설치 위치를 검토하였다. 우선 거더와 수평 브레이싱으로 연결된 2거더 구조계의 전체 횡좌굴모멘트에 영향을 주는 요소를 검토하였다. 다음 으로는 무도상 철도판형교의 하부를 설치 위치를 달리하여 수평브레이싱으로 보강하였다. 보강된 무도상 철도판형교에 열차하중 및 거 더의 중심과 열차하중의 재하위치간의 편심거리(e)에 따라 발생하는 축방향의 비틀림모멘트를 고려하여 구조해석을 수행하였다. 보강모 델별로 지간 중앙에서의 단면의 중심에서 발생하는 변위를 검토하여 변위를 최소화시키는 모델을 선정하였다. 본 연구를 통하여 무도상 철도판형교에 열차하중 재하시 변위를 최소화시키는 하부 수평브레이싱의 보강 형상 및 설치 위치를 제안하였다.

In the automobile manufacturing industry, lightweight design is one of the essential challenges to be solved fundamentally. The vehicle wheels are classified as safety related components as the main substructure of the vehicle. In this study, we illustrate a technique for selecting the appropriate number of spokes. Based on the basic model of the selected number of spokes, we propose a method to maintain stiffness and design lightweight using topology optimization software. Based on the basic model of the selected number of spokes, it was redesigned to be lightweight while maintaining stiffness by utilizing topology optimization software. By comparing and reviewing the structural analysis results of the basic model and the redesigned model, a design technique that can maintain structural safety and reduce wheel mass was proposed.

전 세계적으로 해상을 마주하고 있는 여러 국가들은 기존의 전력 생산방식의 단점을 극복하고 해상풍력 개발을 통한 친환경에 너지자원을 활용하고 있다. 해상은 넓은 해역에 대규모 풍력단지를 개발할 수 있는 장점이 있으나 해양구조물의 설치로 인해 선박의 안 전운항이 위협받고 있다. 이에 따라, 선박 통항로와 해상풍력단지 간 상호 미치는 영향에 대해 분석하여 선박이 안전하게 운항할 수 있도 록 PIANC에서는 표준 Guideline을 제시하였다. 그럼에도 불구하고, 표준 Guideline은 모든상황에서 동일한 이격거리를 산정하였다. 따라서 본 연구에서는 선회성능, 조우상태, 환경외력, 해상밀집도, 해상풍력발전기, 항로형태 등을 요소로 반영한 선박 통항로와 해상풍력단지 간 최적의 이격거리 산정 모델을 개발하였다. 개발된 모델 검증을 위한 시뮬레이션 결과, 운항 준비상태에 따른 입지 특성별 선회성능 크기 는 산정 모델에서 제시한 크기와 유사하였다.

Due to environmental pollution, regulations on fossil fuels are required. There is a movement for the regulations by using LNG fueled propulsion ships. LNG is an eco-friendly fuel that does not emit NOx or SOx during combustion, but its boiling point is -163°C. Under that condition, the use of metal is restricted, and IMO defined applicable materials through IGC code. Among the metals, 9% nickel steel is one of excellent mechanical properties such as yield strength and tensile strength in cryogenic condition. Thus 9% nickel steel is widely used in cryogenic storage containers for ships. In addition, laser welding, which minimizes thermoelastic distortion by applying a concentrated heat source to a narrow area for a short period of time, is in the spotlight. So, this study is a basic research to predict and respond to thermal distortion during laser welding. Secondary version of the representative heat source model was derived through the author's previous research with STS304L, and the heat source model was derived by applying the heat source model to 9% nickel steel in this study. 9% nickel steel is a material that is in high demand and is widely used in the manufacture of cryogenic containers, so this study is expected to be able to respond immediately to the field.

This study examines the optimum shape of a trolley, the driving device of the retractable membrane roof. The closed-type trolley was determined as the model of the study, and a trolley composed of cylindrical-shaped inner and outer holders was selected as the basic model. Based on this model, a cylindrical-based optimal trolley model was proposed. In the basic trolley model, steel was used for the outer holder, and steel, titanium, and aluminum were used for the inner holder. In each case, the most economical shape for the external load of the basic model was newly proposed through the topology optimization process, and the finite element analysis results of the proposed model were compared to define the durability and economics. Here, topology optimization analysis and finite element analysis used the commercial software ANSYS. As a result of optimization, the volume of the outer holder of the trolley was reduced by 58.2% and the volume of the inner holder was reduced by 25.0% compared to the basic model. In the case of stress, a stress increase of 43.2 to 79.2% occurred depending on the material of the inner holder, but it was found to be significantly lower than the yield strength, thereby ensuring safety.

Although retailers deals with a large number of single-term inventory items, but few cases have been considered in the areas of practical decision making. However, recent moves to strengthen fair trade have created a real need for single-period inventory decision-making problems. This study addresses the problem of ordering quantity decisions that are expected to maximize profits using classical newsvendor models. The research target is data on seasonal and perishable products from retail. We also use data from retailers to actually apply the newsvendor model and calculate the results to compare performance. It also suggests solutions for estimating demand for products sold in order to apply newsvendor models that utilize actual demand ratio versus forecast demand. This study would like to examine the effectiveness of this research through data analysis and make some suggestions for applying it to reality.

Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.

It is very crucial activities that Korean army have to detect and recognize enemy’s locations and types of weapon of their artillery firstly for effective operation of friendly force’s artillery weapons during wartime. For these activities, one of the most critical artillery weapon systems is the anti-artillery radar (hereafter; radars) for immediate counter-fire operations against the target. So, in early wartime these radar’s roles are very important for minimizing friendly force’s damage because arbiters have to recognize a several enemy’s artillery positions quickly and then to take an action right away. Up to date, Republic of Korea Army for tactical artillery operations only depends on individual commander’s intuition and capability. Therefore, we propose these radars allocation model based on integer programming that combines ArcGIS (Geographic Information System) analysis data and each radar’s performances which include allowable specific ranges of altitude, azimuth (FOV; field of view) and distances for target detection, and weapons types i.e., rocket, mortars and cannon ammo etc. And we demonstrate the effectiveness of their allocation’s solution of available various types of radar asset through several experimental scenarios. The proposed model can be ensured the optimal detection coverage, the enhancement of artillery radar’s operations and assisting a quick decision for commander finally.

In the satellite operation phase, a ground station should continuously monitor the status of the satellite and sends out a tasking order, and a satellite should transmit data acquired in the space to the Earth. Therefore, the communication between the satellites and the ground stations is essential. However, a satellite and a ground station located in a specific region on Earth can be connected for a limited time because the satellite is continuously orbiting the Earth, and the communication between satellites and ground stations is only possible on a one-to-one basis. That is, one satellite can not communicate with plural ground stations, and one ground station can communicate with plural satellites concurrently. For such reasons, the efficiency of the communication schedule directly affects the utilization of the satellites. Thus, in this research, considering aforementioned unique situations of spacial communication, the mixed integer programming (MIP) model for the optimal communication planning between multiple satellites and multiple ground stations (MS-MG) is proposed. Furthermore, some numerical experiments are performed to verify and validate the mathematical model. The practical example for them is constructed based on the information of existing satellites and ground stations. The communicable time slots between them were obtained by STK (System Tool Kit), which is a well known professional software for space flight simulation. In the MIP model for the MS-MG problems, the objective function is also considered the minimization of communication cost, and ILOG CPLEX software searches the optimal schedule. Furthermore, it is confirmed that this study can be applied to the location selection of the ground stations.

This study aimed to develop a method to optimize residual chlorine concentrations in the process of providing water supply. To this end, this study developed a model capable of optimizing the chlorine input into the clearwell in the purification plant and the optimal installation location of rechlorination facilities, and chlorine input. This study applied genetic algorithms finding the optimal point with appropriate residual chlorine concentrations and deriving a cost-optimal solution. The developed model was applied to SN purification plant supply area. As a result, it was possible to meet the target residual chlorine concentration with the minimum cost. Also, the optimal operation method in target area according to the water temperature and volume of supply was suggested. On the basis of the results, this study derived the most economical operational method of coping with water pollution in the process of providing water supply and satisfying the service level required by consumers in the aspects of cost effectiveness. It is considered possible to appropriately respond to increasing service level required by consumers in the future and to use the study results to establish an operational management plan in a short-term perspective.

In this study, we propose a method of optimal placement technique of artificial reef considering characteristics of sea areas and provide basic data for efficient budget execution. In addition, we will contribute to increasing the economic efficiency by improving the fisheries productivity by suggesting the scientific basis for the policy data and the increase of the catch through the resource creation based on the ecological information about the biology. Especially, in order to establish the effective disposition (optimum separation distance) of artificial reef considering characteristics of biological and engineering factors, it is necessary to review the artificial reef installation management regulations and investigate the biological effects of artificial reef facilities, is needed. Through this, it is expected that the ground data of the direction of the policy promotion will be derived by suggesting the placement condition of the artificial reef complex which can maximize the resource composition effect according to the target fish species.

For the development of processed food for hypoglcemia, it is important to construct model system to confirm factors that reduce the glycemic index in real food. This study was to investigate the relationship between the gel model system and real food the high amylose type of segoami using response surface methodology. The independent variables were concentration (X1; 10, 15, 20, 25, and 30%) and steaming time (X2; 30, 35, 40, 45, and 50 min). The predicted glycemic index (Y1) was analyzed as a dependent variable. The regression of pGI was 0.7343, indicating that the model fits the data well in the prediction test. The predict glycemic index of the gel was in the range of 71.38 ~ 83.78, depending on the gel preparation conditions and predicted optimum condition was 23.7% gel concentration and 43.8 minutes of gelatinization. The predict glycemic index of rice gel were decreased with an increase of gel concentration, rather than the steaming time. In order to confirm the effect on in vitro digestibility in real food, the real food (Garraedduk) was prepared by applying the optimal conditions. As a result, there was no significant difference between the predicted value (77.1) and the experiment value (76.6). This result showed that the in vitro digestibility in real food can be predicted by applying the gel model system.

It is considered necessary to renewal a considerable number of water supply facilities in Korea because they began to be intensively buried in the period of rapid economic growth. Accordingly, local water providers are required to take measures against this situation, but they have currently been caught in a vicious circle of the lack of budget spent in renewing water supply facilities because county-based small-scale local water supply cannot afford to cover annual expenditures with their revenues from water rates. Therefore, this study developed an optimal renewal planning model capable of achieving a balance of financial revenue and expenditure in local water supply using nonlinear programming and furthermore of minimizing the total cost incurred during the analysis. To this end, this study selected the water supply area located in County Y as a research area to build the financial revenue and expenditure and used Solver function provided by Microsoft Excel to use nonlinear programming. As a result, this study developed an optimal renewal planning model minimizing incurred costs in consideration of 6 items in the financial revenue and expenditure. The optimal renewal plan was modeled according to the available annual budget. As a result, this study proposed SICD, a scenario to minimize total costs from the perspective of water suppliers, and SITS, a scenario to minimize the increase in water rates from the perspective of consumers. It can be said that the method proposed in this study is the core of the optimal financial and renewal plans as a final stage of asset management for water supply facilities. Therefore, it is considered possible for local water providers to use the method proposed in this study according to circumstances for the asset management of water supply facilities.