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.

Identifying the water circulation status is one of the indispensable processes for watershed management in an urban area. Recently, various water circulation models have been developed to simulate the water circulation, but it takes a lot of time and cost to make a water circulation model that could adapt the characteristics of the watershed. This paper aims to develop a water circulation state estimation model that could easily calculate the status of water circulation in an urban watershed by using multiple linear regression analysis. The study watershed is a watershed in Seoul that applied the impermeable area ratio in 1962 and 2000. And, It was divided into 73 watersheds in order to consider changes in water circulation status according to the urban characteristic factors. The input data of the SHER(Similar Hydrologic Element Response) model, a water circulation model, were used as data for the urban characteristic factors of each watershed. A total of seven factors were considered as urban characteristic factors. Those factors included annual precipitation, watershed area, average land-surface slope, impervious surface ratio, coefficient of saturated permeability, hydraulic gradient of groundwater surface, and length of contact line with downstream block. With significance probabilities (or p-values) of 0.05 and below, all five models showed significant results in estimating the water circulation status such as the surface runoff rate and the evapotranspiration rate. The model that was applied all seven urban characteristics factors, can calculate the most similar results such as the existing water circulation model. The water circulation estimation model developed in this study is not only useful to simply estimate the water circulation status of ungauged watersheds but can also provide data for parameter calibration and validation.

이 연구에서는 Earth Observing System Terra 위성에 탑재된 Moderate Resolution Imaging Spectroradiometer (MODIS) 협대역 방출율(채널 29, 30, 31) 자료와 다중선형회귀모형을 이용하여 지표면 광대역 방출율을 추정하였다. 다중선형회귀모형 도출 및 검증을 위한 분광 방출율 자료는 MODIS University of California, Santa Barbara와 Advanced Spaceborne Thermal Emission and Reflection Radiometer spectral library 의 307종(토양 123종, 식생 32종, 물 19종, 인위적 재료 43종, 바위 90종)을 사용하였다. 도출된 다중선형회귀모형의 결정계수(R 2 )는 0.95 (p< .001)로 높 게 나타났고 또한 이 모형 결과와 이론적 광대역 방출율 값의 평균제곱근오차(Root Mean Square Error)는 0.0070이었다. 그리고 이 연구 결과에 따라 계산된 지표면 광대역 방출율을 선행 연구 Wang et al. (2005)의 결과와 비교하였다. 그 결과 아시아, 아프리카, 오세아니아 지역에서 이 연구와 Wang et al. (2005)의 결과에 대한 1월 평균 지표면 광대역 방출율의 평균제곱근오차는 0.0054이었고 최소와 최대 편차는 각각 0.0027과 0.0067이었으며 이러한 통계 값은 8월에 도 유사하였다. 이 연구에서 다중선형회귀모형에 의하여 계산한 지표면 광대역 방출율은 Wang et al. (2005)의 값과 큰 차이가 없이 비교적 정확하게 산출되었으나 산출 정확성 향상을 위해서는 토지피복특성에 따른 차별화된 회귀모형 적 용 필요성이 제기된다.

이 연구는 북서태평양에서 여름철(7-9월) 동안 발생하는 태풍 빈도를 예측하기 위한 다중회귀모델을 4가지 원격패턴을 이용하여 개발하였다. 이 패턴은 4-5월 동안 동아시아 대륙에서의 시베리아 고기압 진동, 북태평양에서의 북태평양 진동, 호주근처의 남극진동, 적도 중앙태평양에서의 대기순환으로 대표된다. 이 통계모델은 이 모델로부터 예측된 높은 태풍발생빈도의 해와 낮은 태풍발생빈도의 해 사이에 차를 분석함으로써 검증되었다. 높은 태풍발생빈도의 해에는 다음과 같은 4가지의 아노말리 특성을 나타내었다: i) 동아시아 대륙에 고기압성 순환 아노말리(양의 시베리아 고기압진동), ii) 북태평양에 남저북고의 기압계 아노말리, iii) 호주 근처에 저기압성 순환 아노말리(양의 남극진동), iv) 봄부터 여름 동안 니뇨3.4 지역에 저기압성 순환 아노말리. 따라서 적도 서태평양에서 무역풍 아노말리는 양반구의 아열대 서태평양에 위치한 저기압성 순환 아노말리에 의해 약화되었다. 결국, 이러한 기압계 아노말리의 공간분포는 열대 서태평양에 대류를 억제하는 대신 아열대 서태평양에 대류를 강화시켰다.

본 연구의 목적은 기상자료(강수량, 최고기온, 최저기온, 평균기온, 평균풍속) 기반의 다중선형 회귀모형을 개발하여 농업용저수지 저수율을 예측 하는 것이다. 나이브 베이즈 분류를 활용하여 전국 1,559개의 저수지를 지리형태학적 제원(유효저수량, 수혜면적, 유역면적, 위도, 경도 및 한발빈도)을 기준으로 30개 군집으로 분류하였다. 각 군집별로, 기상청 기상자료와 한국농어촌공사 저수지 저수율의 13년(2002~2014) 자료를 활용하여 월별 회귀모형을 유도하였다. 저수율의 회귀모형은 결정계수(R2)가 0.76, Nash-Sutcliffe efficiency (NSE)가 0.73, 평균제곱근오차가 8.33%로 나타났다. 회귀모형은 2년(2015~2016) 기간의 기상청 3개월 기상전망자료인 GloSea5 (GS5)를 사용하여 평가되었다. 현재저수율과 평년저수율에 의해 산정되는 저수지 가뭄지수(Reservoir Drought Index, RDI)에 의한 ROC (Receiver Operating Characteristics) 분석의 적중률은 관측값을 이용한 회귀식에서 0.80과 GS5를 이용한 회귀식에서 0.73으로 나타났다. 본 연구의 결과를 이용해 미래 저수율을 전망하여 안정적인 미래 농업용수 공급에 대한 의사결정 자료로 사용할 수 있을 것이다.

Wastewater treatment plant(WWTP) has been recognized as a high energy consuming plant. Usually many WWTPs has been operated in the excessive operation conditions in order to maintain stable wastewater treatment. The energy required at WWTPs consists of various subparts such as pumping, aeration, and office maintenance. For management of energy comes from process operation, it can be useful to operators to provide some information about energy variations according to the adjustment of operational variables. In this study, multiple regression analysis was used to establish an energy estimation model. The independent variables for estimation energy were selected among operational variables. The R2 value in the regression analysis appeared 0.68, and performance of the electric power prediction model had less than ±5% error.

In this study, pressure drop was measured in the pulse jet bag filter without venturi on which 16 numbers of filter bags (Ø140 × 850 ℓ) are installed according to operation condition(filtration velocity, inlet dust concentration, pulse pressure, and pulse interval) using coke dust from steel mill. The obtained 180 pressure drop test data were used to predict pressure drop with multiple regression model so that pressure drop data can be used for effective operation condition and as basic data for economical design. The prediction results showed that when filtration velocity was increased by 1%, pressure drop was increased by 2.2% which indicated that filtration velocity among operation condition was attributed on the pressure drop the most. Pressure was dropped by 1.53% when pulse pressure was increased by 1% which also confirmed that pulse pressure was the major factor affecting on the pressure drop next to filtration velocity. Meanwhile, pressure drops were found increased by 0.3% and 0.37%, respectively when inlet dust concentration and pulse interval were increased by 1% implying that the effects of inlet dust concentration and pulse interval were less as compared with those changes of filtration velocity and pulse pressure. Therefore, the larger effect on the pressure drop the pulse jet bag filter was found in the order of filtration velocity(Vf), pulse pressure(Pp), inlet dust concentration(Ci), pulse interval(Pi). Also, the prediction result of filtration velocity, inlet dust concentration, pulse pressure, and pulse interval which showed the largest effect on the pressure drop indicated that stable operation can be executed with filtration velocity less than 1.5 m/min and inlet dust concentration less than 4 g/m3. However, it was regarded that pulse pressure and pulse interval need to be adjusted when inlet dust concentration is higher than 4 g/m3. When filtration velocity and pulse pressure were examined, operation was possible regardless of changes in pulse pressure if filtration velocity was at 1.5 m/min. If filtration velocity was increased to 2 m/min. operation would be possible only when pulse pressure was set at higher than 5.8 kgf/cm2. Also, the prediction result of pressure drop with filtration velocity and pulse interval showed that operation with pulse interval less than 50 sec. should be carried out under filtration velocity at 1.5 m/min. While, pulse interval should be set at lower than 11 sec. if filtration velocity was set at 2 m/min. Under the conditions of filtration velocity lower than 1 m/min and high pulse pressure higher than 7 kgf/cm2, though pressure drop would be less, in this case, economic feasibility would be low due to increased in installation and operation cost since scale of dust collection equipment becomes larger and life of filtration bag becomes shortened due to high pulse pressure.