PURPOSES : The purpose of this study is to develop a regression model to predict the International Roughness Index(IRI) and Surface Distress(SD) for the estimation of HPCI using Expressway Pavement Management System(PMS).METHODS : To develop an HPCI prediction model, prediction models of IRI and SD were developed in advance. The independent variables considered in the models were pavement age, Annual Average Daily Traffic Volume(AADT), the amount of deicing salt used, the severity of Alkali Silica Reaction(ASR), average temperature, annual temperature difference, number of days of precipitation, number of days of snowfall, number of days below zero temperature, and so on.RESULTS : The present IRI, age, AADT, annual temperature differential, number of days of precipitation and ASR severity were chosen as independent variables for the IRI prediction model. In addition, the present IRI, present SD, amount of deicing chemical used, and annual temperature differential were chosen as independent variables for the SD prediction model.CONCLUSIONS: The models for predicting IRI and SD were developed. The predicted HPCI can be calculated from the HPCI equation using the predicted IRI and SD.

Impact damage tolerance is an important design requirement for composite structures. In this study, the effect of post impact damage and hole size of the composite sandwich skin / sandwich with core specimen on compressive strength of the laminate was analyzed. Three specimen tests were performed in this research. Two tests were carried out on pure bending test specimens subjected to impact damage to the skin and specimen with a hole in one of its skin as a damage. Through this test, we compared the reduction of compressive strength due to the size of skin damage and the size of the hole. Also, core-free specimen with an open hole under uniaxial loading were tested to produce reference data for comparison with the series tested earlier. As results of the tests, the sandwich beams with damage size and open hole are almost identical, and we concluded that the prediction of compressive strength reduction after impact of the sandwich skin structure can be predicted using an analytical model assuming skin open hole as impact inputs.

In this study, a model was developed to predict for Disinfection By-Products (DBPs) generated in water supply networks and consumer premises, before and after the introduction of advanced water purification facilities. Based on two-way ANOVA, which was carried out to statistically verify the water quality difference in the water supply network according to introduce the advanced water treatment process. The water quality before and after advanced water purification was shown to have a statistically significant difference. A multiple regression model was developed to predict the concentration of DBPs in consumer premises before and after the introduction of advanced water purification facilities. The prediction model developed for the concentration of DBPs accurately simulated the actual measurements, as its coefficients of correlation with the actual measurements were all 0.88 or higher. In addition, the prediction for the period not used in the model development to verify the developed model also showed coefficients of correlation with the actual measurements of 0.96 or higher. As the prediction model developed in this study has an advantage in that the variables that compose the model are relatively simple when compared with those of models developed in previous studies, it is considered highly usable for further study and field application. The methodology proposed in this study and the study findings can be used to meet the level of consumer requirement related to DBPs and to analyze and set the service level when establishing a master plan for development of water supply, and a water supply facility asset management plan.

Pulp and paper industry produces large volumes of wastewater and residual sludge waste, resulting in many issues in relation to wastewater treatment and sludge disposal. Contaminants in pulp and paper wastewater include effluent solids, sediments, chemical oxygen demand (COD), and biological oxygen demand (BOD), which should be treated by wastewater treatment processes such as coagulation and biological treatment. However, few works have been attempted to predict the treatment efficiency of pulp and paper wastewater. Accordingly, this study presented empirical models based on experimental data in laboratory-scale coagulation tests and compared them with statistical models such as artificial neural network (ANN). Results showed that the water quality parameters such as turbidity, suspended solids, COD, and UVA can be predicted using either linear or expoential regression models. Nevertheless, the accuracies for turbidity and UVA predictions were relatively lower than those for SS and COD. On the other hand, ANN showed higher accuracies than the emprical models for all water parameters. However, it seems that two kinds of models should be used together to provide more accurate information on the treatment efficiency of pulp and paper wastewater.

본 연구에서는 축산식품인 편육을 대상으로 황색포도상 구균의 성장예측모델을 개발하였다. 편육에서 황색포도상 구균의 성장패턴은 4, 10, 20, 37oC의 보관온도에서 측정 되었으며, 황색포도상구균은 각각의 저장 온도에서 모두 증가하는 것으로 나타났다. 편육에 오염된 황색포도상구 균의 생육결과를 토대로 Baranyi model을 이용하여 유도 기(LPD)와 최대성장률(μmax)을 산출한 결과, 유도기는 4, 10, 20, 37oC에서 212.81, 79.67, 3.12, 2.21 h으로 온도에 반비례한 것으로 나타났고 최대성장률은 같은 보관온도에 서 0.004, 0.009, 0.130, 0.568 log CFU/g/h으로 온도에 비 례한 것으로 조사되었다. 2차 모델은 μmax의 경우, square root model, LPD는 polynomial equation을 사용하여 산출 하였고, 개발한 모델의 적합성을 평가하기 위해 통계적 지 표인 RMSE 값을 계산한 결과, 비교적 0에 가까운 0.42로 도출되어 모델이 적합한 것으로 확인되었다. 따라서 개발된 모델이 편육에 대한 황색포도상구균의 성장 예측모델로 사용 가능하다고 판단되어지며, 편육에서의 식중독을 예방하고 미생물학적 위생관리기준을 설정하는데 기초자 료로 활용될 수 있을 것으로 사료된다.

최근 국내외에서는 수질안정성 향상 및 부지면적 저감을 위해 막여과 공정도입이 활발한 추세이며 특히, 정수처리 분야에서는 정밀여과(Microfiltration) 및 한외여과(Ultrafiltration) 공정이 많이 적용되고 있다. 막여과 공정의 경제성 향상을 위해서는 세정 시점의 예측 및 세정 주기 연장이 매우 중요한 요소이다. 따라서, 본 연구에서는 인공신경망(Artificial neural network)을 활용하여 UF 공정차압(Transmembrane pressure) 예측 모델을 개발하고자 한다. 입력변수로는 유입수 온도, pH, 탁도 등의 일평균값을 이용하였다.

The objective of this study is to propose a simple and accurate analytical model for HSS braces. For this purpose, a physical theory model is adopted. Rectangular hollow section steel (HSS) braces are considered in this study. To accurately simulate the cyclic behavior of braces using the physical theory model, empirical equations calculating constituent parameters are implemented on the analytical model, which were proposed in the companion paper. The constituent parameters are cyclic brace growth, cyclic buckling load, and the incidence of local buckling and fracture. The analytical model proposed in this study was verified by comparing actual and simulated cyclic curves of brace specimens. It is observed that the proposed model accurately simulates the cyclic behavior of the braces throughout whole response range.

보리, 밀 등에서 발생되는 붉은곰팡이병균(Fusarium)은 전세계적으로 분포하고 있으며 작물의 수확량을 감소시키고 품질을 저하시키는 원인이 된다. 특히, 곰팡이병균은 deoxynivalenol(DON), nivalenol(NIV), zearalenone(ZEA) 등과 같은 제2차 대사산물인 곰팡이 독소를 생성하여 사람과 가축에 치명적인 피해를 주기도 한다. 발암물질로 알려진 곰팡이독 소는 조리 및 가공 후에도 분해되지 않는 특성으로 인해 오염된 곡물을 미리 검출하여 폐기해야 그 피해를 막을 수 있다. 기존 곰팡이독소 검출을 위해서는 정확성이 높은 TLC, HPLC, ELISA 등을 사용하고 있지만 고가 장비 및 전문 인력이 요구되고 있으며 분석을 위해 장시간이 소요되는 단점이 있다. 따라서 본 연구에서는 1175∼2170 nm의 근적 외선(NIR) 파장대역을 가진 분광센서를 이용하여 곰팡이독소(DON)에 오염된 겉보리 시료의 농도를 예측하고자 하였 다. 겉보리 시료에 적용된 곰팡이독소(DON)의 농도별로 0, 10, 100, 10000 ppm으로 각각 20립씩 총 80립을 조제하였 다. 용매는 아세트나이트릴에 침지하였으며 질소를 이용하여 건조시켜 곰팡이 독소를 조제하였으며 NIR 분광센서를 이용하여 총 3회 반복 측정하였다. 겉보리의 농도별 곰팡이독소를 예측하기 위해서 교정 및 검정 PLSR(Partial least square regression) 모델을 개발하였으며 각각의 반사 스펙트럼 전처리별 R2, SEC, SEP 등의 값을 산출하여 예측성능을 비교하였다.

This study aims at providing basic data to objectively evaluate the areas suitable for reintroduction of the species of Asiatic black bear (Ursus thibetanus) in order to effectively preserve the Asiatic black bears in the Korean protection areas including national parks, and for the species restoration success. To this end, this study predicted the potential habitats in East Asia, Southeast Asia and India, where there are the records of Asiatic black bears’ appearances using the Maxent model and environmental variables related with climate, topography, road and land use. In addition, this study evaluated the effects of the relevant climate and environmental variables. This study also analyzed inhabitation range area suitable for Asiatic black and geographic change according to future climate change. As for the judgment accuracy of the Maxent model widely utilized for habitat distribution research of wildlife for preservation, AUC value was calculated as 0.893 (sd=0.121). This was useful in predicting Asiatic black bears’ potential habitat and evaluate the habitat change characteristics according to future climate change. Compare to the distribution map of Asiatic black bears evaluated by IUCN, Habitat suitability by the Maxent model were regionally diverse in extant areas and low in the extinct areas from IUCN map. This can be the result reflecting the regional difference in the environmental conditions where Asiatic black bears inhabit. As for the environment affecting the potential habitat distribution of Asiatic black bears, inhabitation rate was the highest, according to land coverage type, compared to climate, topography and artificial factors like distance from road. Especially, the area of deciduous broadleaf forest was predicted to be preferred, in comparison with other land coverage types. Annual mean precipitation and the precipitation during the driest period were projected to affect more than temperature’s annual range, and the inhabitation possibility was higher, as distance was farther from road. The reason is that Asiatic black bears are conjectured to prefer more stable area without human’s intervention, as well as prey resource. The inhabitation range was predicted to be expanded gradually to the southern part of India, China’s southeast coast and adjacent inland area, and Vietnam, Laos and Malaysia in the eastern coastal areas of Southeast Asia. The following areas are forecast to be the core areas, where Asiatic black bears can inhabit in the Asian region: Jeonnam, Jeonbuk and Gangwon areas in South Korea, Kyushu, Chugoku, Shikoku, Chubu, Kanto and Tohoku’s border area in Japan, and Jiangxi, Zhejiang and Fujian border area in China. This study is expected to be used as basic data for the preservation and efficient management of Asiatic black bear’s habitat, artificially introduced individual bear’s release area selection, and the management of collision zones with humans.

The axial thrust acting on the turbocharger rotor is basically generated by the unbalance between turbine wheel gas forces and compressor wheel air forces. It has a significant influence on the friction losses, which reduces the overall efficiency and performance of high-speed turbocharger. Therefore, it’s important to calculate the thrust forces under operating conditions (surge, choke and etc.) in a turbocharger. The purpose of this paper is the development of numerical simulation methods which were verified by experimental results of axial thrust and thermally induced constraint tests of the turbocharger. The first FE model showed the relationship between thrust forces and strains by calculating the strains on specially designed thrust bearing and were compared with test results. And the second one is to identify the thermally induced strains in order to remove the thermal effects from measured strains. With these models, it’s possible to inversely predict the magnitudes of the axial thrust by directly measured strains and temperatures under operating turbocharger.

기상 조건을 고려하여 교통사고 발생 원인과의 관계를 분석한 연구에서는 갑작스러운 온도 또는 기상 상 태의 변화는 교통사고에 영향을 준다는 결론을 제시하고 있다. 특히, 동절기에 기온이 떨어지는 경우, 도로 결빙에 의한 교통사고가 발생할 가능성이 높으며, 도로 표면에서 발생하는 결빙 현상은 운전자가 육안으로 쉽게 관측 할 수 없는 한계를 가진다. 따라서, 노면에 발생하는 결빙은 교통사고의 원인으로 작용 할 수 있 기 때문에, 결빙이 발생한 구간에서 운전자의 주의를 높여 줄 수 있는 대안 등이 요구된다. 결빙 현상은 야 간과 같이 온도가 낮아지는 시간에 발생하므로, 결빙을 예측하기 위해서는 노면 온도에 대한 정보가 필요하 다. 그러나, 노면온도 변화에 직･간접적으로 영향을 주는 대기 기상정보는 거시적(5km*5km 단위) 범위에 서 정보가 제공되므로, 운전자가 주행하는 도로망에 대한 정확한 정보를 제공하는데 어려움이 따른다. 따라 서, 본 연구에서는 운전자가 주행하는 도로망에 대기 온도를 제공 및 예측하기 위해 대기온도, 대기습도, 풍 향 등을 고려한 기상정보와 노면 온도 자료를 활용하여 노면 온도를 예측하는 모형을 개발하고자 한다. 노면 온도 예측 모형을 개발하기 위하여 Thermal Mapping 장비가 장착된 차량을 이용하였으며, Thermal Mapping 장비를 통해 노면온도, 대기온도, 대기습도를 측정한다. 또한, 시스템적으로 GPS가 연계되어 있어서, 정확한 위치 정보의 취득이 가능하며, 노면온도에 영향을 미치는 기상정보는 기상청에 서 수집하여 제공하는 온도, 습도, 풍속 등을 이용하였다. 또한, 지형의 요소를 교량부, 산지부, 평지부, 해안, 내륙을 구분하여 지형적인 요소도 반영 될 수 있도록 하였다. 예측 모형은 비선형 분석 모형을 사용 하여 노면 예측 정확도에 적합한 알고리즘을 사용할 계획이며, 본 연구의 결과는 기상과 관련된 교통안전 관련 연구에 활용될 것으로 기대한다.

역삼투 해수담수화 공정에서 막 오염은 생산수량 감소 및 공정의 에너지 소비량 증가를 야기한다. 막간 차압 증가, 생산수량 감소 외에 막 저항 값의 증가는 막 오염 정도를 판단하는 수치로 사용이 가능하다. 특히 막 저항 값 기반의 세정은 막 오염 제어를 통해 역삼투 해수담수화 공정에서 막의 성능 유지 시 사용 가능하다. 이에 본 연구에서는 해수 수질 인자 및 공정 운전 인자에 기반하여 막 저항 값을 예측하는 알고리즘을 제안한다. 알고리즘은 해수담수화 플랜트의 운전 데이터에 기반하여 인자들과 막 저항 값 사이의 관계를 학습하고 검증과정을 거쳐 막 오염 발생 시점을 사전에 예측하는 방식으로 개발되었다. 예측 정확도를 분석하고 개발된 알고리즘의 수정을 통해 예측 정확도 향상을 위한 연구를 진행하였다.

Pipe Deterioration Prediction (PDP) and Pipe Failure Risk Prediction (PFRP) models were developed in an attempt to predict the deterioration and failure risk in water mains using fuzzy technique and the markov process. These two models were used to determine the priority in repair and replacement, by predicting the deterioration degree, deterioration rate, failure possibility and remaining life in a study sample comprising 32 water mains. From an analysis approach based on conservative risk with a medium policy risk, the remaining life for 30 of the 32 water mains was less than 5 years for 2 mains (7%), 5-10 years for 8 (27%), 10-15 years for 7 (23%), 15-20 years for 5 (17%), 20-25 years for 5 (17%), and 25 years or more for 2 (7%).

The polyurethane spring, which provides the restoring force for a sliding bridge bearing, governs the overall behavior of the bearing. An analytical model, therefore, which reflects actual geometrical shape and can be utilized easily in engineering practice, is needed to be developed. In this paper, a simplified model for analyzing the polyurethane spring utilized in the sliding bridge bearing is presented. The model is developed for a cylindrical tube based on Gent’s model, and can be utilized for various height-diameter ratios. The accuracy of the proposed model are compared to existing models via experimental data as well as numerical analysis results. The comparison result shows that the proposed model can be used in estimating mechanical behavior of the cylindrical tube shaped polyurethane spring.

질산성질소는 자연계의 질소 순환과정에서 발생되며, 수중에서는 질산성질소가 무기이온인 질산염(NO3 - )의 형태로 존재한다. 질산성질소는 과도한 질소비료시비나 동물의 분뇨에 의해 오염된 지하수에 존재하며, 인체에 노출 시 암과 같은 질병 유발 가능성을 높인다. 본 연구에서는 흡착등온식 및 흡착속도식 모델을 이용하여 질산염 농도 및 시간에 따른 키토산 비드의 수중 질산염 흡착특성을 평가하였다. 질산염의 농도에 따른 흡착실험에서 Langmuir와 Freundlich 식을 이용하여 최대흡착량 및 흡착형태를 산출한 결과, 키토산 비드의 질산염 흡착형태는 Langmuir식에 가장 일치되 는 경향을 보였으며, 이때 키토산 비드의 질산염 최대흡착량은 14.83 mg 질산염/g 키토산비드이었다. 질산염의 시간에 따른 흡착실험에서 1차속도식 및 2차속도식을 이용하여 질산염의 흡착속도 및 확산형태를 평가한 결과, 키토산 비드 의 초기 흡착속도는 외부확산에 의한1차속도식 경향을 보였으며, 일정시간이 지난 후에는 내부확산에 의한 2차속도식 형태의 경향을 보였다. 본 연구에서 수행한 흡착 모델에 따른 수중질산염의 제거 연구는 키토산 비드의 흡착 형태 및 질산염 제거량을 수학적으로 예측하는데 도움이 된다.

Disinfectant/oxidation process is a crucial process in water treatment for supplying safe drinking water. Chlorination is still widely used for water treatment area due to its effectiveness on microbial inactivation and economic feasibility. Recently, disinfection concern in marine environment is increasing, for example, movement of hazardous marine organism due to ballast water, marine environmental degradation due to power plant cooling water discharge, and increase of the amount of disinfectant in the offshore plant. It is needed to conduct the assessment of disinfectant behavior and the development of disinfectant prediction model in seawater. The appropriate prediction model for disinfectant behavior is not yet provided. The objective of the study is to develop chlorine decay model in seawater. Various model types were applied to develop the seawater chlorine decay model, such as first order decay model, EPA model, and two-phase model. The model simulation indicated that chlorine decay in seawater is influenced by both organic and inorganic matter in seawater. While inorganic matter has a negative correlation with the chlorine decay, organic matter has a positive correlation with the chlorine decay.