The battle vehicle has six types of indicators attached to the instrument panel in consideration of the special battlefield environment. However, many problems of moisture occurred during the operation of combat vehicles. These moisture phenomena can adversely affect aesthetics and functionality. Moisture is generated on the instrument panel due to the inflow of external moist air, the desorption of the moist air inside the parts, and the fluctuation of the dew point temperature. In this paper, we try to derive the root cause of various moisture generation and provide an improvement measures for moisture control. Therefore, the failure mechanism of the instrument panel may be analyzed and the design may be changed depending on the failure factor. Furthermore, the effect of the design change is verified, and the humidity performance is evaluated.

In this study, a smart skin system that combines SPD (suspended particle display) and LGG (Lighting Guide Glass) and its optimal control method was developed for the purpose of simultaneously reducing the lighting load and cooling load in office buildings. And a demonstration site was built to test the results. The demonstration site was constructed as an experimental group with a smart skin system installed and a control group with a general window system installed. When the cooling energy consumption of the experimental group to which the smart skin system was applied was reduced by about 36.9% compared to the control group, the lighting energy was also reduced by 54.4%.

This paper is about the selection of the optimum position of the driving system and the analysis of the load at that position in order to safely drive an object with heavy load on the turret with a linear actuator. Usually, linear actuator is required the greatest force when first lifting or pushing a structure, and it is determined by the initial angle and positions. After all, the optimal position of the linear actuator in a limited turret space is closely related the required load and driving performance of the linear actuator. Therefore, this paper contains the contents of securing the driving stability and performance at optimum position on the turret by considering the two cases of linear actuator position arrangement.

In this study, a model to optimize residual chlorine concentrations in a water supply system was developed using a multi-objective genetic algorithm. Moreover, to quantify the effects of optimized residual chlorine concentration management and to consider customer service requirements, this study developed indices to quantify the spatial and temporal distributions of residual chlorine concentration. Based on the results, the most economical operational method to manage booster chlorination was derived, which would supply water that satisfies the service level required by consumers, as well as the cost-effectiveness and operation requirements relevant to the service providers. A simulation model was then created based on an actual water supply system (i.e., the Multi-regional Water Supply W in Korea). Simulated optimizations were successful, evidencing that it is possible to meet the residual chlorine concentration demanded by consumers at a low cost.

최근, L형 도로측구 상 열화, 균열로 인한 유지보수 작업이 빈번해지고 있다. 본 논문에서는 쐐기 앵커를 이용한 L형 도로측구의 최적 설계에 대해 제시하고자 하였다. 해석 결과, 두 개의 쐐기앵커를 350mm로 관입시킨 경우에서 구조적 안정성을 충분히 확보하는 것을 확인하였다. 또한 3%의 개질유황 콘크리트 배합이 압축강도, 동결융해 등의 내구성 기준을 만족하였다. 반복하중에 대한 수치해석과 현장 평가가 수행 중에 있으며, 추후 해당 시스템의 적용성을 평가하기 위한 추적 조사가 이루어져야 할 것이다.

This study analyzed the appropriate placement method by floor for evacuating all occupants during the nighttime through evacuation simulation. The analysis results are as follows. First, when non-self evacuating patients were placed on the first floor, 266 patients and 6 workers were found to be evacuated after 460 seconds. This result shows that it is meaningful to place non-self evacuating patients on the lower floor with a time that is faster than 540 seconds, which is an evaluation criterion set using life Safety standards for human. This result is a time faster than the evaluation criteria of 540 seconds, which is set using the life safety standards, and it can be confirmed that it is meaningful to place non-self evacuating patients on the lower floor. Next, as a result of placing non-self evacuating patients from the first floor to the fourth floor, it was found that evacuation of all occupants required 460 seconds for the first floor, 834 seconds for the second floor, 1,508 seconds for the third floor, and 1,915 seconds for the fourth floor. These results indicate that the placement of non-self evacuating patients on the rest of the floors, except for the first floor, can lead to dangerous results in excess of 540 seconds, which is a flashover time. As a result, it is necessary to place non-self evacuating patients on a lower floor for safe evacuation. The study has limitations except for comparative analysis of changes in evacuation time due to changes in the number of workers at eldery care hospitals and situations in which fire-fighting facilities such as sprinkler facilities operated. It is necessary to study the evacuation time linked to the operation of the fire-fighting facilities and the evacuation time according to the change in the number of workers in the future.

목적 : 인공지능의 기계학습 또는 심층학습을 이용한 연구가 다양한 분야에서 시도되고 있다. 본 연구는 공공 시력데이터를 자동화 수집하고, 수집한 데이터를 기계학습에 적용 및 예측하였다. 다양한 학습모델간 성능을 비교 함으로써, 시과학분야에서 적용 가능한 기계학습 최적화모델을 제시함에 있다. 방법 : 국민건강보험(NHISS) 및 통계포털(KOSIS)에 발표된 국민 시력분포 현황관련 자료를 특정 색인을 포함하 는 자료검색기법인 크롤링(crawling)을 사용하여 검색 및 수집을 자동화하였다. 2011년부터 2018년까지 보고된 모든 자료를 수집하였으며, 데이터 학습을 위해 Linear Regression, LASSO, Ridge, Elastic Net, Huber Regression, LASSO/LARS, Passive Aggressive Regressor 그리고 Pansacregressor 총 8개 모델을 사용하여 각각 데이터 학습 하였다. 결과 : 수집한 데이터를 기반으로 기계학습 모델을 통해 2018년을 예측하였다. 각 모델간 2018년도 실제-예측데 이터 차이를 MAE(Mean Absolute Error)와 RMSE(Root Mean Square Error) 점수로 각각 나타냈다. 학습모델 별 차이 중 MAE 평가결과 모델간 우/좌 Linear Regression(0.22/0.22), LASSO(0.83/0.81), RIDGE(0.31/0.31), Elastic Net(0.86/0.84), Huber Regression(0.14/0.07), LASSO/LARS(0.15/0.14), Passive Aggressive Regressor (0.29/0.18) 그리고 RANSA Regressor(0.22/0.22)를 보였다. RMSE에서 Linear Regression(0.40/0.40), LASSO (1.08/1.06), Ridge(0.54/0.54), Elastic Net(1.19/1.17), Huber Regression(0.20/0.20), LASSO/LARS(0.24/0.23), Passive Aggressive Regressor(0.21/0.58) 그리고 RANSA Regressor(0.40/0.40) 각각 나타냈다. 결론 : 본 연구는 자동화 자료검색 및 수집을 위한 크롤링 기법을 이용하여 데이터를 수집하였다. 이를 기반으 로 고전 선형모델을 기계학습에 적용할 수 있도록 하고, 데이터 학습을 위한 8개 학습모델들 간 성능을 비교하였다.

Hydro-electric power is a method of generating electricity from the rotational force of turbine blades by using the potential energy of a river or reservoir water. Recently, the necessity of small hydropower development is expanding due to the development and support of renewable energy, and because of the difficulty and environmental problems of huge dams. The purpose of this paper is to deal with a method of increasing the efficiency of small water turbine that can be adopt in low head condition. In order to improve the turbine efficiency, channel shape is optimized in order to minimize head loss using computational fluid dynamics. The angle values for the contraction and enlargement part of the channel where the turbine is located are found from the analyses. Additionally, three-dimensional analysis is applied to the optimized channel shape in order to confirm the optimized pipe.

The estimation of heat source model is very important for heat transfer analysis with finite element method. Part I of this study used adaptive simulated annealing which is one of the global optimization algorithm for anticipating the parameters of the Goldak model. Although the analysis with 3D model which depicted the real situation produced the correct answer, that took too much time with moving heat source model based on Fortran and Abaqus. This research suggests the procedure which can reduce time with maintaining quality of analysis. The lead time with 2D model is reduced by 90% comparing that of 3D model, the temperature distribution is similar to each other. That is based on the saturation of heat transfer among the direction of heat source movement. Adaptive simulated annealing with 2D model can be used to estimate more proper heat source model and which could enhance to reduce the resources and time for experiments.

The purpose of this study was to derive the conditions for manufacturing rice porridge with optimum properties after reheating. The characteristics of rice porridge according to the soaking time, water addition rate, heating temperature, heating time, and cooling conditions were compared using the ‘Samkwang’ cultivar. In Step Ⅰ, as the heating temperature increased, the weight change decreased and the viscosity increased, and the temperature known as the main factor of the gelatinization also appeared to affect the viscosity increase. In Step Ⅱ, the viscosity and the texture properties was not significantly different as the soaking time was reduced, and 10 minutes was suitable because of due to the shortening effect of the total process time. In Step Ⅲ, the residual heat was lowered by cooling after the rice porridge production, so the viscosity could be greatly reduced. Also, it was confirmed that the water addition rate of 900% and the heating temperature of 15 minutes were optimal manufacturing conditions. The next study will investigate the porridge processability of rice cultivars using these results.

본 논문에서는 초고층 건물의 철근콘크리트 아웃리거 벽체 개구부의 최적설계를 위한 수학적 최적화 프레임워크를 제시하였다. 전용 유한요소해석 프로그램을 이용하여 아웃리거 벽체를 해석하였으며 깊은 보의 스트럿-타이 거동을 고려하여 개구부를 배치하였다. 최적화를 위해 파이썬 SciPy 라이브러리 중 순차이차계획법(Sequential Quadratic Programming)을 이용하여 제약 경계 최적화를 수행 하였다. 최적화에 필요한 미분가능한 연속 함수를 얻어내기 위해 선형 보간법을 사용하였으며, 최적화 프로그램의 효율성을 위해 데이터베이스를 이용하였다. 2변수 최적화의 결과를 탐색 알고리즘의 이동 경로를 통해 살펴본 결과 알고리즘이 최적화된 결과를 효율적으로 찾아냄을 확인하였다. 그리고 개구부의 폭을 모두 같게 설정한 것이 아닌 각각의 개구부의 크기를 개별 변수로 설정하였을 경우 목적함수의 값이 최소화되어 더 우수한 최적화 결과를 도출함을 확인하였다. 또한, 최적화의 과정에 있어 데이터베이스를 이용할 경우 최적화 시간을 효과적으로 단축시킬 수 있음을 확인하였다.