• 한국전산구조공학회논문집
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• 제25권4호
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• pp.339-346
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• 2012

본 논문에서는 구조물과 능동형 제진장치를 상용 구조해석 프로그램상에서 해석하는데 필요한 등가모델을 제시하였으며, 이를 통해 부재수준의 구조검토가 가능하도록 하기 위한 연구를 진행하였다. 능동형 제진장치를 일반적인 구조해석모델에 반영하기 위하여 가상의 스프링과 대쉬폿을 이용한 등가링크 모델과, 별도의 축소모델 해석결과를 바탕으로 산정된 제어력을 제진장치 설치위치에 하중으로 작용시키는 등가하중 모델을 제시하였다. 수직캔틸레버 모델과 주상복합 건물 모델을 대상으로 능동형 제어기 설계를 위해 모드에 기초한 축소모델을 구축하고, 이를 토대로 산정된 제어이득으로부터 등가모델을 도출하였다. 이들 모델에 대해 얻어진 가속도 및 변위의 RMS 응답과 최대 부재력을 토대로 등가해석모델의 유효성을 검증하였다. 결과적으로 능동형 제진장치의 상용 구조해석 프로그램을 통해 제어대상 구조물의 부재력 수준까지 상세한 구조검토가 가능함을 확인하였으며, 상대적으로 등가링크 모델이 더 우수한 정확도를 나타내었다.

• 콘크리트학회논문집
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• 제13권4호
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• pp.397-405
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• 2001

해안에 근접한 콘크리트 구조물이 동결음해 작용을 받을 경우, 내륙 콘크리트에 비해 내구성능 저하가 촉진된다. 그리고 최근 동절기에 차량의 안전 주행을 위해 도로 및 교량에 염화칼슘 등의 제설제의 산포량이 현격히 증가하고 있으며 이로 인해 내륙 콘크리트 구조물도 해안 콘크리트 구조물과 마찬가지로 동결융해와 염해의 복합작용에 의한 내구성능 저하가 염려된다. 미국, 일본 및 유럽 등에서는 제설제가 콘크리트에 미치는 영향에 대해 연구가 활발히 진행되고 있다. 그리고 제설제가 콘크리트에 미치는 영향을 검토하는 시험방법이 제정되었다. 그러나 우리 나라에서는 동결융해와 염해에 대한 복합 내구성능 저하시험방법은 제정되어 있지 않으며 또한 이에 대한 연구가 이루지지 않고 있다. 따라서 본 연구에서는 동결융해와 염해의 복합작용을 받는 콘크리트의 내구성능 저하를 평가하는 방법을 검토하기 위해 복합 내구성능 저하 실험을 실시하였다. 복합시험에서 시멘트 종류, 강도, 공기량 등이 스케링에 미치는 영향을 검토하였다. 그 결과, 염화물 존재 하에서 동결융해 작용을 받는 경우, 콘크리트의 스케링 손실이 촉진된다. 또한 스케링에 대한 저항성은 사용 시멘트 종류, 콘크리트의 강도, 공기량의 영향을 크게 받는다.

• Journal of Animal Science and Technology
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• 제60권1호
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• pp.30.1-30.10
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• 2018

Background: The poultry industry suffers losses from problems as pale, soft and exudative (PSE), and dark, firm and dry (DFD) meat can develop in meat as a result of short- and long-term stress, respectively. These abnormalities are impacted by pre-slaughter animal welfare. Methods: This work evaluated the effects of open vehicle container microclimate, throughout the $38{\pm}10km$ journey from the farm to the slaughterhouse, on commercially turkey transported during the Brazilian winter season. The journey was initiated immediately after water bath in truck fitted with portable Kestrel anemometers to measure air ventilation, relative humidity, temperature and ventilation. Results: The inferior compartments of the middle and rear truck regions showed highest temperature and relative humidity, and lower air ventilation. In addition, the superior compartments of the front truck regions presented lower temperature and wind chill, and highest air ventilation. The breast meat samples from animals located at the inferior compartments of the middle and rear truck regions and subjected to with water bath (WiB) treatment presented highest DFD-like and had lowest PSE-like meat incidence than those from animals located at other compartments within the container. Lower incidence of PSE-like meat was observed in birds without water bath (WoB). Conclusions: Assessment on turkeys transported under Brazilian southern winter conditions revealed that breast meat quality can be affected by relative humidity, air ventilation, temperature, and transport under subtropical conditions promoting color abnormalities and the formation of simultaneously PSE-like and DFD-like meat.

• 한국항해항만학회지
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• 제45권3호
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• pp.87-94
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• 2021

국제해사기구의 연료유 황 함유량 제한 등, 세계적으로 강화되고 있는 환경규제로 LNG를 선박 연료로 사용하는 연구 및 사업이 활발히 진행되고 있다. 본 연구에서는 기본설계 되어 있는 부유식 벙커링 터미널(FLBT, Floating LNG bunkering terminal)을 대상으로, STS LNG 하역 작업을 위해 접안 하는 과정을 수치 시뮬레이션으로 평가하였다. 수치해석에서는 예인선이 대상선박을 밀 경우 이를 가상의 펜더로 가정하였으며, 당길 때는 HMPE 로프 특성을 적용하였다. 해석에는 파랑, 조류, 바람 1년 재현 확률의 해상조건을 적용하였다. 수치모델은 선행 모형시험 결과로부터 조정되어 정확한 결과를 얻을 수 있도록 하였다. 해석 결과 LNG선은 대부분의 1년 환경조건에서 안전한 접안이 가능하였다. 파랑 방향에 따라 안정성의 차이가 큼으로 FLBT의 Heading control 기능을 적용하여 횡파를 피한다면 더욱 안정적인 운용이 가능할 것이다.

• 한국산학기술학회논문지
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• 제22권4호
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• pp.212-219
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• 2021

운송차량에 의한 화학사고는 매년 전체 화학사고의 20 %를 차지하지만 영향평가 정보를 알 수 없는 상황이 반복되어 사고대응 과정에서 어려움을 겪게 되는 문제점이 존재한다. 본 연구에서는 국내 사용량이 많고 사고 위험성이 높으며, 최근 7년간 사고 빈도가 높은 염소와 불화수소를 대상으로 탱크로리로 운반하는 과정에서 누출사고가 발생하였을 경우 현장에서 이격거리 산정을 위하여 활용될 수 있는 피해예측범위 산정표 및 산정식을 개발하였다. 화학물질의 누출속도와 기상조건 중 풍속, 온도에 따른 산정표를 조사하였으며, 산정표를 적용하기 힘든 특수한 상황에서는 산정식을 적용할 수 있도록 통계 프로그램 R을 사용하여 산정식을 도출하였다. 유관기관에서는 현장에서 연구에서 도출된 산정표 및 산정식을 활용하면 화학사고 피해 최소화 및 이격거리 설정, 주민대피 결정 등의 의사결정 측면에서 중요한 정보로써 사용할 수 있을 것으로 사료된다.

• 한국항공운항학회지
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• 제26권4호
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• pp.36-42
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• 2018

Although continuous passenger injuries and physical damages are repeated due to the unexpected aviation turbulence encountered during operations, there is still exist the limitation for preventing recurrence of similar events because the lack of real-time information and delay in technological developments regarding various operating conditions and variable weather phenomena. The purpose of this study is to compare and analyze the meteorological data of the aviation turbulence occurred and actual flight data extracted from the Quick Access Recorder(QAR) to provide some precursors that the pilot can identify aviation turbulence early by referring thru the flight instrumentation indications. The case applied for this study was recent event, a scheduled flight from Incheon Airport, Korea to Narita Airport, Japan that suddenly encountered turbulence at an altitude of approximately 14,000 feet during approach. According to the Korea Meteorological Administration(KMA)'s Regional Data Assessment and Prediction System(RDAPS) data, it was observed that the strong amount of vorticity in the rear area of jet stream, which existed near Mount Fuji at that time. The QAR data analysis shows significant changes in the aircraft's parameters such as Pitch and Roll angle, Static Air Temperature(SAT), and wind speed and direction in tens of seconds to minutes before encounter the turbulence. If the accumulate reliability of the data in addition and verification of various parameters with continuous analysis of additional cases, it can be the precursors for the pilot's effective and pre-emptive action and conservative prevention measures against aviation turbulence to reduce subsequent passenger injuries in the aviation operations.

• Smart Structures and Systems
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• 제24권2호
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• pp.243-256
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• 2019

Determination of the most meaningful structural modes and gaining insight into how these modes evolve are important issues for long-term structural health monitoring of the long-span bridges. To address this issue, modal parameters identified throughout the life of the bridge need to be compared and linked with each other, which is the process of mode tracking. The modal frequencies for a long-span bridge are typically closely-spaced, sensitive to the environment (e.g., temperature, wind, traffic, etc.), which makes the automated tracking of modal parameters a difficult process, often requiring human intervention. Machine learning methods are well-suited for uncovering complex underlying relationships between processes and thus have the potential to realize accurate and automated modal tracking. In this study, Gaussian mixture model (GMM), a popular unsupervised machine learning method, is employed to automatically determine and update baseline modal properties from the identified unlabeled modal parameters. On this foundation, a new mode tracking method is proposed for automated mode tracking for long-span bridges. Firstly, a numerical example for a three-degree-of-freedom system is employed to validate the feasibility of using GMM to automatically determine the baseline modal properties. Subsequently, the field monitoring data of a long-span bridge are utilized to illustrate the practical usage of GMM for automated determination of the baseline list. Finally, the continuously monitoring bridge acceleration data during strong typhoon events are employed to validate the reliability of proposed method in tracking the changing modal parameters. Results show that the proposed method can automatically track the modal parameters in disastrous scenarios and provide valuable references for condition assessment of the bridge structure.

• Membrane and Water Treatment
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• 제10권1호
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• pp.1-11
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• 2019

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) predicted that recent extreme hydrological events would affect water quality and aggravate various forms of water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed and sunlight) were established using the Representative Concentration Pathways (RCP) 8.5 climate change scenario suggested by the AR5 and calculated the future runoff for each target period (Reference:1989-2015; I: 2016-2040; II: 2041-2070; and III: 2071-2099) using the semi-distributed land use-based runoff processes (SLURP) model. Meteorological factors that affect water quality (precipitation, temperature and runoff) were inputted into the multiple linear regression analysis (MLRA) and artificial neural network (ANN) models to analyze water quality data, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (T-N) and total phosphorus (T-P). Future water quality prediction of the Anseongcheon River basin shows that DO at Gongdo station in the river will drop by 35% in autumn by the end of the $21^{st}$ century and that BOD, COD and SS will increase by 36%, 20% and 42%, respectively. Analysis revealed that the oxygen demand at Dongyeongyo station will decrease by 17% in summer and BOD, COD and SS will increase by 30%, 12% and 17%, respectively. This study suggests that there is a need to continuously monitor the water quality of the Anseongcheon River basin for long-term management. A more reliable prediction of future water quality will be achieved if various social scenarios and climate data are taken into consideration.

• 대한한방부인과학회지
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• 제34권4호
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• pp.131-150
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• 2021

Objectives: The purpose of this study is to analyze the domestic study trends on Korean medicine treatment of Sanhupung. Methods: Case studies applying Korean medicine treatment on Sanhupung were searched through 5 domestic journal databases. General characteristics, interventions, outcomes, and results of the selected studies were analyzed. Also, the quality of the case studies was reviewed based on the CAse REport (CARE) guideline and Joanna Briggs Institute (JBI) critical appraisal checklist. Results: 11 studies (16 cases) were found to be analyzed according to their general characteristics, symptoms, interventions, treatment period, outcome, and results. The most common complaint of Sanhupung patients was pain, and the most applied intervention for Sanhupung was herbal medicine and acupuncture. The duration of treatment ranged from 9 days to 4 months. All case studies reported that the Korean medicine treatment was effective in treating Sanhupung. According to the quality assessment, 'Timeline of case', 'Diagnostic challenges', 'Intervention adherence and tolerability', 'Adverse and unanticipated events', and 'Informed consent' were showed low reporting rates. Conclusions: Further clinical studies are needed to establish the evidence for Korean medicine treatment for Sanhupung.

• 대기
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• 제32권4호
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• pp.367-379
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• 2022

In this paper, the evaluation of the performance of Korea Meteorological Administratio (KMA) Global Seasonal forecasting system version 6 (GloSea6) is presented by assessing the effects of larger ensemble size and carrying out the test using different initial conditions for hindcast in sub-seasonal to seasonal scales. The number of ensemble members increases from 3 to 7. The Ratio of Predictable Components (RPC) approaches the appropriate signal magnitude with increase of ensemble size. The improvement of annual variability is shown for all basic variables mainly in mid-high latitude. Over the East Asia region, there are enhancements especially in 500 hPa geopotential height and 850 hPa wind fields. It reveals possibility to improve the performance of East Asian monsoon. Also, the reliability tends to become better as the ensemble size increases in summer than winter. To assess the effects of using different initial conditions, the area-mean values of normalized bias and correlation coefficients are compared for each basic variable for hindcast according to the four initial dates. The results have better performance when the initial date closest to the forecasting time is used in summer. On the seasonal scale, it is better to use four initial dates, where the maximum size of the ensemble increases to 672, mainly in winter. As the use of larger ensemble size, therefore, it is most efficient to use two initial dates for 60-days prediction and four initial dates for 6-months prediction, similar to the current Time-Lagged ensemble method.