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김양균,이제겸,이승원,Kim, Yangkyun,Lee, Je-Kyum,Lee, Sean Seungwon 한국터널지하공간학회 2022 한국터널지하공간학회논문집 Vol.24 No.5
As many tunnels generally have been constructed, various experiences and techniques have been accumulated for tunnel design as well as tunnel construction. Hence, there are not a few cases that, for some usual tunnel design works, it is sufficient to perform the design by only modifying or supplementing previous similar design cases unless a tunnel has a unique structure or in geological conditions. In particular, for a tunnel blast design, it is reasonable to refer to previous similar design cases because the blast design in the stage of design is a preliminary design, considering that it is general to perform additional blast design through test blasts prior to the start of tunnel excavation. Meanwhile, entering the industry 4.0 era, artificial intelligence (AI) of which availability is surging across whole industry sector is broadly utilized to tunnel and blasting. For a drill and blast tunnel, AI is mainly applied for the estimation of blast vibration and rock mass classification, etc. however, there are few cases where it is applied to blast pattern design. Thus, this study attempts to automate tunnel blast design by means of machine learning, a branch of artificial intelligence. For this, the data related to a blast design was collected from 25 tunnel design reports for learning as well as 2 additional reports for the test, and from which 4 design parameters, i.e., rock mass class, road type and cross sectional area of upper section as well as bench section as input data as well as16 design elements, i.e., blast cut type, specific charge, the number of drill holes, and spacing and burden for each blast hole group, etc. as output. Based on this design data, three machine learning models, i.e., XGBoost, ANN, SVM, were tested and XGBoost was chosen as the best model and the results show a generally similar trend to an actual design when assumed design parameters were input. It is not enough yet to perform the whole blast design using the results from this study, however, it is planned that additional studies will be carried out to make it possible to put it to practical use after collecting more sufficient blast design data and supplementing detailed machine learning processes.
개방 공간에서 발생하는 수소-공기 혼합 가스 폭연에 대한 실험적/해석적 연구
김양균,박병직,Kim, Yangkyun,Park, Byoung Jik 한국안전학회 2021 한국안전학회지 Vol.36 No.1
Experimental and analytical investigations are performed to explore the explosion characteristics of a hydrogen-air mixture in open atmosphere. A hydrogen-air mixture tent of total volume of 27 m<sup>3</sup>, with 40% hydrogen volume, is used to observe overpressure at a distance from the ignition source. Vapor cloud explosion analyses are performed using the TNO multi-energy model and Baker-Strehlow-Tang model. The results of these analyses are compared with experiment done from this study and references. The experimental results with and without obstacles indicate that the overpressure values measured at a distance of 4.5-21.5 m from the ignition source are about 9.4-3.6 kPa and 6.5-2 kPa, respectively. This implies that the overpressure with obstacles is approximately 1.7 times greater than that without obstacles. Analytical observation indicates that the results obtained with the Baker-Strehlow-Tang model with M<sub>f</sub> = 0.2-0.35 are in good agreement with those of most of the previous studies, including that obtained from this study. Moreover, the TNO multi-energy model with a volume of 27 m<sup>3</sup> well predicts the overpressure obtained from this study. Further studies should considered explosions in semi-confined spaces, which is more suitable for hydrogen refueling stations.
Exploring the Appropriate Operation Ratio on Hospital Revenue Cost and Profit
김양균,성주호,강중철 한국데이터정보과학회 2007 한국데이터정보과학회지 Vol.18 No.1
Many previous researchers tried to analysis relationship between financial index of hospitals such as revenue, expenses, and profit and hospital outcome such as number of inpatient and outpatient or, between that financial index and hospital size including number of hospital beds. However, these studies did not find exact relationship between financial index and hospital efficiency and productivity. Therefore, purpose of the study explores exact relationship between hospital financial outcome and hospital efficiency and productivity using adjusted inpatient days concept from American Hospital Association. Through the empirical analysis, the researchers find that hospital profit has the U-shape quadratic function to operation ratio. 66.9% of operation ratio is changing point and hospitals with 55.8% through 75.0% of operation ration have experience deficit situation. Considering the hospital circumstance, Korean hospitals would be to maintain general hospital type with various specialty departments.