지구통계학적 진화전략 역산해석 기법의 소개 및 가상 대수층 수리전도도 분포 예측에의 적용

박은규,Park, Eungyu 대한자원환경지질학회 2020 자원환경지질 Vol.53 No.6

수리지질학을 포함한 많은 지질학 분야에 있어 지하 매질의 불균질성을 규명하는 것은 큰 중요성을 가진다. 본 연구에서는 최근 Park(2020)에 의해 소개된 바 있는 대수층을 구성하는 매질의 수리물성을 예측할 수 있는 기법의 개념 및 이론을 간단히 소개하고, 가상의 대수층에 해당 기법을 적용하여 기법에 의한 결과들의 다양한 시사점을 도출하였다. 소개하는 기법은 공분산행렬 적응 진화전략이라는 광역최적화 기법을 사용하며, 개념적으로 대수층에 가해지는 수리적 스트레스에 의한 지하수위 변화 자료를 동화하여 대수층 불균질성을 특성화하는 방법론이다. 가상의 대수층의 수리전도도 예측에 개발 기법을 적용한 결과, 총 40000개 미지의 값을 매우 빠른 시간 내에 예측함을 확인하였다. 또한, 예측의 결과는 레퍼런스 수리전도도와 수치적 및 구조적으로 큰 유사성을 보여 예측의 질적 수준이 높음을 확인하였다. 본 연구에서는 매우 제한적인 케이스에 대하여 적용을 실시하였으나, 기법의 추가개발을 통하여 보다 다양한 케이스에의 적용이 가능할 것으로 예상되며 현재 이를 위한 추가 개발이 이루어지고 있는 상황이다. 개발 기법은 수리지질학 분야 뿐만 아니라 다양한 지질학 및 지구물리 분야에 적용될 수 있는 잠재성을 갖추고 있다. In many geological fields, including hydrogeology, it is of great importance to determine the heterogeneity of the subsurface media. This study briefly introduces the concept and theory of the method that can estimate the hydraulic properties of the media constituting the aquifer, which was recently introduced by Park (2020). After the introduction, the method was applied to the synthetic aquifer to demonstrate the practicality, from which various implications were drawn. The introduced technique uses a global optimization technique called the covariance matrix adaptation evolution strategy (CMA-ES). Conceptually, it is a methodology to characterize the aquifer heterogeneity by assimilating the groundwater level time-series data due to the imposed hydraulic stress. As a result of applying the developed technique to estimate the hydraulic conductivity of a hypothetical aquifer, it was confirmed that a total of 40000 unknown values were estimated in an affordable computational time. In addition, the results of the estimates showed a close numerical and structural similarity to the reference hydraulic conductivity field, confirming that the quality of the estimation by the proposed method is high. In this study, the developed method was applied to a limited case, but it is expected that it can be applied to a wider variety of cases through additional development of the method. The development technique has the potential to be applied not only to the field of hydrogeology, but also to various fields of geology and geophysics. Further development of the method is currently underway.

자연 수리자극을 이용한 소유역 규모 대수층 수리전도도 특성화: 지구통계 진화전략 역산해석 기법의 적용 가능성 시험

박은규,Park, Eungyu 한국지하수토양환경학회 2020 지하수토양환경 Vol.25 No.4

In this study, the applicability of the geostatistical evolution strategy as an inverse analysis method of estimating hydraulic properties of small-scale basin was tested. The geostatistical evolution strategy is a type of data assimilation method that can effectively estimate aquifer hydraulic conductivity by combining a global optimization model of the evolution strategy and a local optimization model of the ensemble Kalman filtering. In the applicability test, the geometry, hydraulic boundary conditions, and the distribution of groundwater monitoring wells of Hanlim-Eup were employed. On the other hand, a synthetic hydraulic conductivity distribution was generated and used as the reference property for ease of estimation quality assessment. In the estimations, two different cases were tested where, in Case I, both groundwater levels and hydraulic conductivity measurements were assumed to be available, and only the groundwater levels were available, in Case II. In both cases, the reference and estimated hydraulic conductivity fields were found to show reasonable similarity, even though the prior information for estimation was not accurate. The ability to estimate hydraulic conductivity without accurate prior information suggests that this method can be used effectively to estimate mathematical properties in real-world cases, many of which little prior information is available for the aquifer conditions.

대졸 청년 재직자의 직업가치 유형과 개인 및 직장 관련 요인과의 관계

박은규(Eungyu Park),조아름(A-Reum Jo) 한국기업교육학회 2022 기업교육과인재연구 Vol.24 No.2

본 연구는 한국고용정보원 직업가치관 검사의 직업가치 요인들을 활용하여, 대졸 청년 재직자 대상 직업가치 선호에 따른 직업가치 유형을 분류하고, 직업가치 유형과 개인 및 직장 관련 요인과의관계를 밝히고자 하였다. 이를 위해 한국고용정보원 워크넷 직업심리검사 DB 자료 중 2019년에 직업가치관 검사를 실시한 대졸 청년 재직자 13,596명을 대상으로 분석하였다. 직업가치 유형 구분을 위해 잠재프로파일 분석을실시한 결과, 대졸 청년 재직자의 직업가치 유형은 5가지 유형으로 도출되었고, 전반적 저인식형, 안정적 보상추구형, 가치고민형, 전반적 중시형, 안정지향형으로 명명하였다. 대졸 청년 재직자의 직업가치 유형별 개인특성과 관련한 영향요인을 분석한 결과, 개인특성인 성별, 연령, 학력, 결혼, 전공 모두 직업가치 유형에 유의한 영향을 미치는 것으로 나타났고, 직업가치 유형별 직장관련 요인의 차이 분석 결과, 이직 경험 여부를 제외하고, 사업체 규모, 이직경험 여부, 직업만족의 분포 차이는 유의미한 것으로 나타났다. 본 연구를 통해, 생애경력개발 관점에서의 대졸 청년 재직자의 유연한 직장적응 및 경력개발을 지원하고, 대졸 청년들의 직업가치를 고려한 합리적인 진로선택에 도움을 주기 위한 구체적이고 실질적인 개입 방안을 모색하였다는 데 의의가 있다. The purpose of this study is to identify the types of work value according to preference for youth employees with college graduates by using the work value factors of the Korea Employment Information Service(KEIS) Work Value Test, and to clarify the relationship between work value types and individual and workplace factors. For this purpose, we analyzed 13,596 youth employees with college graduates who took the work value test in 2019 among the data from the WORKNET vocational psychology test DB of the KEIS. As a result of conducting a latent profile analysis to classify work value types, there were five types of work value for youth employee with college graduates, and they were named as overall low perception type, stable reward seeking type, value concern type, overall emphasis type, and stability-oriented type. As a result of analyzing the influencing factors related to the individual characteristics of youth employee with college graduates by type of work value, it was found that the individual characteristics such as gender, age, educational background, marriage, and major all had a significant effect on the type of work value. As a result of analyzing the difference between workplace characteristics by work value type, it was found that the difference in the size of the business, turnover experience, and distribution of job satisfaction was significant, excluding turnover experience. Through this study, it is meaningful to seek specific and practical intervention to support flexible workplace adaptation and career development of college graduates from the perspective of life career development and to help them choose a reasonable career path considering the work value of youth employees with college graduates.

지열원 히트펌프 열풍건조기 개발

박성찬(Sungchan Park),박승태(Seungtae Park),김승용(Seungyong Kim),김동욱(Dongwook Kim),박은규(Eungyu Park),김영일(Young Il Kim),오상민(Sangmin Oh),금종수(Jongsoo Kum) 대한설비공학회 2016 대한설비공학회 학술발표대회논문집 Vol.2016 No.11

Geothermal heat pump type hot air dryer is being developed. For drying temperature 40~70℃, drying factor becomes 1.8 kg/kWh which is about 2.6 times greater than that of electric heater type dryer, for all year round. Further more, additional function of geothermal heat pump type hot air dryer like cooling and heating by ground loop water, can improve the economic efficiency of ground coupled system.

식품용수 수질자료를 이용한 지하수 오염 예측 모델 개발 및 소규모 유역에서의 검증

남성우,박은규,이명재,전선금,정혜민,김정우,Nam, Sungwoo,Park, Eungyu,Yi, Myeong-jae,Jeon, Seonkeum,Jung, Hyemin,Kim, Jeongwoo 한국지하수토양환경학회 2021 지하수토양환경 Vol.26 No.6

Groundwater is used in many areas in food industry such as food manufacturing, food processing, cooking, and liquor industry etc. in Korea. As groundwater occupies a large portion of food industry, it is necessary to predict deterioration of water quality to ensure the safety of food water since using undrinkable groundwater has a ripple effect that can cause great harm or anxiety to food users. In this study, spatiotemporal data aggregation method was used in order to obtain spatially representative data, which enable prediction of groundwater quality change in a small watershed. In addition, a highly reliable predictive model was developed to estimate long-term changes in groundwater quality by applying a non-parametric segmented regression technique. Two pilot watersheds were selected where a large number of companies use groundwater for food water, and the appropriateness of the model was assessed by comparing the model-produced values with those obtained by actual measurements. The result of this study can contribute to establishing a customized food water management system utilizing big data that respond quickly, accurately, and preemptively to changes in groundwater quality and pollution. It is also expected to contribute to the improvement of food safety management.

가우시안 프로세스 회귀분석을 이용한 지하수위 추세분석 및 장기예측 연구

김효건,박은규,정진아,한원식,김구영,Kim, Hyo Geon,Park, Eungyu,Jeong, Jina,Han, Weon Shik,Kim, Kue-Young 한국지하수토양환경학회 2016 지하수토양환경 Vol.21 No.4

The amount of groundwater related data is drastically increasing domestically from various sources since 2000. To justify the more expansive continuation of the data acquisition and to derive valuable implications from the data, continued employments of sophisticated and state-of-the-arts statistical tools in the analyses and predictions are important issue. In the present study, we employed a well established machine learning technique of Gaussian Process Regression (GPR) model in the trend analyses of groundwater level for the long-term change. The major benefit of GPR model is that the model provide not only the future predictions but also the associated uncertainty. In the study, the long-term predictions of groundwater level from the stations of National Groundwater Monitoring Network located within Han River Basin were exemplified as prediction cases based on the GPR model. In addition, a few types of groundwater change patterns were delineated (i.e., increasing, decreasing, and no trend) on the basis of the statistics acquired from GPR analyses. From the study, it was found that the majority of the monitoring stations has decreasing trend while small portion shows increasing or no trend. To further analyze the causes of the trend, the corresponding precipitation data were jointly analyzed by the same method (i.e., GPR). Based on the analyses, the major cause of decreasing trend of groundwater level is attributed to reduction of precipitation rate whereas a few of the stations show weak relationship between the pattern of groundwater level changes and precipitation.

이산화탄소 저장부지 위해성 관리를 위한 가상물리시스템 적용성 평가

정진아,박은규,전성천,김현준,윤성택,Jeong, Jina,Park, Eungyu,Jun, Seong-Chun,Kim, Hyun-Jun,Yun, Seong-Taek 대한자원환경지질학회 2017 자원환경지질 Vol.50 No.5

본 연구에서는 이산화탄소 지중저장 부지관리를 위한 가상물리시스템(Cyber Physical System, CPS)의 적용성을 검토하였다. 특히, 이산화탄소 누출 예측을 위한 가상트윈으로써 서배깅 회귀분석 기법을 활용하였고, 실제 모니터링 자료를 이용하여 해당기법의 성능을 검증하였다. 검증 결과, 서배깅 회귀분석 기법이 자료 내 이상치에 대하여 견고한 추세 예측성능을 보여주었으며 장기 농도변화 예측성능 또한 우수함을 확인하였다. 또한 적은 연산자원을 활용하여 즉시적인 예측결과를 도출함에 따라 이산화탄소 누출 실시간 예측 및 위험 경보에도 적합함을 알 수 있었다. 이러한 결과들은 서배깅 회귀분석 기법을 가상트윈으로 활용하는 CPS가 이산화탄소 누출 위험을 효율적으로 관리하는데 활용 될 수 있음을 보여준다. In the present study, adaptability of cyber-physical system (CPS) for risk management of $CO_2$ storage site is examined and the subagging regression (SBR) method is proposed as a key component of the cyber-twin to estimate the risk due to potential $CO_2$ leakage. For these purposes, $CO_2$ concentration data monitored from a controlled $CO_2$ release field experiment is employed to validate the potentialities of the SBR method. From the validation study, it is found that the SBR method has robust estimation capability by showing minimal influence from anomalous measurements, and makes stable and sound predictions for the forthcoming $CO_2$ concentration trend. In addition, the method is found to be well suited as a tool of operational risk assessment based on real-time monitoring data due to the computational efficiency. The overall results suggest that the SBR method has potential to be an important component comprising the cyber twin of CPS for risk management of $CO_2$ storage site.

가우시안 프로세스 회귀분석을 이용한 지하수 수질자료의 해석

구민호,박은규,정진아,이헌민,김효건,권미진,김용성,남성우,고준영,최정훈,김덕근,조시범,Koo, Min-Ho,Park, Eungyu,Jeong, Jina,Lee, Heonmin,Kim, Hyo Geon,Kwon, Mijin,Kim, Yongsung,Nam, Sungwoo,Ko, Jun Young,Choi, Jung Hoon,Kim, Deog-Geun,Jo, 한국지하수토양환경학회 2016 지하수토양환경 Vol.21 No.6

Gaussian process regression (GPR) is proposed as a tool of long-term groundwater quality predictions. The major advantage of GPR is that both prediction and the prediction related uncertainty are provided simultaneously. To demonstrate the applicability of the proposed tool, GPR and a conventional non-parametric trend analysis tool are comparatively applied to synthetic examples. From the application, it has been found that GPR shows better performance compared to the conventional method, especially when the groundwater quality data shows typical non-linear trend. The GPR model is further employed to the long-term groundwater quality predictions based on the data from two domestically operated groundwater monitoring stations. From the applications, it has been shown that the model can make reasonable predictions for the majority of the linear trend cases with a few exceptions of severely non-Gaussian data. Furthermore, for the data shows non-linear trend, GPR with mean of second order equation is successfully applied.

지구통계 기법을 이용한 오일샌드 저류층 해석 및 스팀주입중력법을 이용한 비투멘 회수 적지 선정 사전 연구

정진아,박은규,Jeong, Jina,Park, Eungyu 대한자원환경지질학회 2013 자원환경지질 Vol.46 No.4

본 연구에서는 캐나다 아사바스카 지역의 맥머레이층에 대한 3차원 지구통계 모사를 실시하였으며 모사 결과를 바탕으로 심부지열회수방법을 통한 경제적 산출 가능 지역을 가늠하고자 하였다. 비투멘의 효율적인 생산을 위하여 SAGD 공법의 최적 입지를 선정하는데 있어 스팀챔버의 충분한 수직적 연장성을 확보하는 것은 중요한 사항이다. 연구지역에서 획득한 110개의 시추공 자료에 대하여 마르코프 전이 확률 기반의 분석을 실시하였으며 이를 바탕으로 맥머레이층 구성 암상에 대한 추계론적 예측을 실시하였다. 추계론적 모사를 통하여 획득한 다중재현을 기반으로 앙상블 확률 분포도를 제작하였으며 이는 각 암상이 분포 할 수 있는 포텐셜을 보여준다. 앙상블 확률 분포도를 이용하여 투수성 퇴적층(역질 퇴적층 및 사질 퇴적층)에 대한 누적 층후도를 구성하였으며 이를 바탕으로 SAGD 공법이 적용될 수 있는 최적 입지를 선정하였다. SAGD 최적 입지 선정을 위한 추가적인 분석을 실시하기 위하여 전이율을 바탕으로 한 단일 퇴적층의 평균적인 수직 및 수평적 연장성을 산정하였다. 투수성 퇴적층의 평균적인 수직적 연장성은 대체로 투수성 퇴적층에 대한 누적층후도 분포도와 유사한 분포 양상을 보이나 일부 누적 층후가 큰 위치에서 유사하지 않은 양상을 보인다. 이는 누적 층후도와 평균적인 수직적 연장성 분포 양상이 유사하지 않은 지역은 투수성 퇴적층과 다른 암상과의 교호성은 매우 크나 투수성 퇴적층의 수직적인 연장성은 좋지 않음을 의미한다. 따라서 누적층후도 뿐 만 아니라 투수성 퇴적층의 수직적 연장성 또한 충분히 고려하였을 때 건전한 SAGD 최적 입지를 선정하는데 충분히 신뢰성 있는 결론을 도출 할 것으로 판단된다. In the study, three-dimensional geostatistical simulations on McMurray Formation which is the largest oil sand reservoir in Athabasca area, Canada were performed, and the optimal site for steam assisted gravity drainage (SAGD) was selected based on the predictions. In the selection, the factors related to the vertical extendibility of steam chamber were considered as the criteria for an optimal site. For the predictions, 110 borehole data acquired from the study area were analyzed in the Markovian transition probability (TP) framework and three-dimensional distributions of the composing media were predicted stochastically through an existing TP based geostatistical model. The potential of a specific medium at a position within the prediction domain was estimated from the ensemble probability based on the multiple realizations. From the ensemble map, the cumulative thickness of the permeable media (i.e. Breccia and Sand) was analyzed and the locations with the highest potential for SAGD applications were delineated. As a supportive criterion for an optimal SAGD site, mean vertical extension of a unit permeable media was also delineated through transition rate based computations. The mean vertical extension of a permeable media show rough agreement with the cumulative thickness in their general distribution. However, the distributions show distinctive disagreement at a few locations where the cumulative thickness was higher due to highly alternating juxtaposition of the permeable and the less permeable media. This observation implies that the cumulative thickness alone may not be a sufficient criterion for an optimal SAGD site and the mean vertical extension of the permeable media needs to be jointly considered for the sound selections.

다양한 기계학습 기법의 암상예측 적용성 비교 분석

정진아,박은규,Jeong, Jina,Park, Eungyu 한국지하수토양환경학회 2016 지하수토양환경 Vol.21 No.3

In the present study, we applied various machine learning techniques comparatively for prediction of subsurface structures based on multiple secondary information (i.e., well-logging data). The machine learning techniques employed in this study are Naive Bayes classification (NB), artificial neural network (ANN), support vector machine (SVM) and logistic regression classification (LR). As an alternative model, conventional hidden Markov model (HMM) and modified hidden Markov model (mHMM) are used where additional information of transition probability between primary properties is incorporated in the predictions. In the comparisons, 16 boreholes consisted with four different materials are synthesized, which show directional non-stationarity in upward and downward directions. Futhermore, two types of the secondary information that is statistically related to each material are generated. From the comparative analysis with various case studies, the accuracies of the techniques become degenerated with inclusion of additive errors and small amount of the training data. For HMM predictions, the conventional HMM shows the similar accuracies with the models that does not relies on transition probability. However, the mHMM consistently shows the highest prediction accuracy among the test cases, which can be attributed to the consideration of geological nature in the training of the model.