• 한국항만경제학회지
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• 제28권1호
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• pp.105-122
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• 2012

항만에서 운용되는 선박, 트럭, 기차, 하역장비들이 배출하는 온실가스는 현장 근로자들뿐만 아니라 인근 지역민들의 건강 및 생활환경을 악화시키고 있다. 세계 주요항만 대기오염 문제 해결을 위해 다양한 노력을 하고 있다. 본 연구는 항만 중 온실가스 배출량 비중이 가장 높은 컨테이너터미널을 대상으로 온실가스 저감방안에 대한 연구를 하였다. 연구를 위해 먼저 저감대안들을 추출하였고 이에 대한 중요 우선순위를 결정하는 계층적 의사결정 모델 제시와 실증분석을 실시하였다. 컨테이너터미널 온실가스 저감대안을 선정 하는데 있어 5가지 요소 기준을 적용하였고, 실무자와 전문가의 의견을 수렴하여 대안들을 추출하였다. 또한 선정된 온실가스 저감방안에 대한 평가영역과 요소들을 평가하는데 있어 언어척도의 애매모호하고 불확실한 상황을 고려하여 퍼지모형과 계층적분석방법(Analytic Hierarchy Process)을 결합한 Fuzzy-AHP을 적용하였다. 연구결과 컨테이너터미널 온실가스 저감방안의 측정영역에 대한 중요도 평가는 장비영역이 가장 높았고, 다음으로 운영영역과 에너지영역 순으로 나타났다. 온실가스 저감대안들의 전체 우선순위를 보면 전기T/C 도입이 우선순위가 가장 높은 것으로 분석되었다. 다음으로 Y/T하이브리드 개조, AMP도입, MLS 도입 순으로 나타났다.

• 한국음향학회지
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• 제39권5호
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• pp.454-460
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• 2020

음성인식 기능을 제공하는 인공지능 비서들은 정확도가 뛰어난 클라우드 기반의 음성인식을 통해 동작한다. 클라우드 기반의 음성인식에서 시작 단어 인식은 대기 중인 기기를 활성화하는 데 중요한 역할을 한다. 본 논문에서는 공개 데이터셋인 구글의 Speech Commands 데이터셋을 사용하여 스펙트로그램 및 멜-주파수 캡스트럼 계수 특징을 입력으로 하여 모바일 기기에 대응한 저 연산 시작 단어 검출을 위한 합성곱 신경망의 성능을 비교한다. 본 논문에서 사용한 합성곱 신경망은 다층 퍼셉트론, 일반적인 합성곱 신경망, VGG16, VGG19, ResNet50, ResNet101, ResNet152, MobileNet이며, MobileNet의 성능을 유지하면서 모델 크기를 1/25로 줄인 네트워크도 제안한다.

• KEPCO Journal on Electric Power and Energy
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• 제2권2호
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• pp.211-221
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• 2016

전세계의 인구 증가와 경제 발전은 지속적인 에너지 수요의 증가를 가져오고 있다. 특히, 전력부분에서는 아시아 및 아프리카, 그리고 중남미 등의 개발도상국을 중심으로 그 수요가 지속적으로 증가하고 있어 주요 에너지원인 석탄의 이용도 지속적으로 증가할 것으로 예측되고 있다. 그러나, 이산화탄소 및 대기오염원, 그리고 미세먼지 등의 배출 등은 석탄을 이용한 전력생산에 있어 환경친화적인 기술로의 대응방안 마련과 더불어, 고효율의 다양한 저급연료를 활용할 수 있는 발전 기술의 개발이 요구되고 있다. 이에, 기술개발 및 그 상용화 시장이 점차 증대되고 있는 초초임계 순환유동층 보일러에 대한 관심이 증대하고 있다. 초초임계 순환 유동층 보일러는 중소형의 아임계의 드럼형 구조에서 벗어나 대용량화의 기본 구조인 Once Through 형태의 증기 순환 구조를 지니고 100-300 MWe의 상업용 모듈의 복제를 통해 600 MW급이 상용화 운전 중에 있으며, 향후 설계가 완성된 800 MWe의 상업화 진행이 기대되고 있다. 초초임계 순환유동층 보일러는 2017년 이후 아임계 순환유동층 보일러 설치 용량을 추월하여 표준형 모델이 될 것으로 전망되고 있어, 본 논문에서의 이의 기술적 배경과 개발 현황 그리고 시장전망 등을 통해 기술적 이해를 도모하고자 한다.

• 한국건설관리학회논문집
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• 제14권5호
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• pp.153-163
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• 2013

건축물이 고층화, 대형화 될수록 수직 양중 계획 및 운영에 관한 중요성이 부각되고 있다. 이에 프로젝트 초기 단계에 실제 모델과 유사한 건설용 리프트 양중계획을 수립하려는 노력이 계속되고 있지만 프로젝트 착수 후 리프트 운행을 컨트롤 할 수 있는 시스템은 부재한 실정이다. 따라서 본 논문에서는 건설용 리프트 운영 효율증대를 위하여 센서를 사용한 리프트 운행 정보를 수집하고 실시간 분석이 가능한 건설용 리프트 최적화 운행 시스템 개발을 실시 및 검증 단계를 수행하여, 양중 효율의 지표가 되는 사용자 대기 시간의 단축을 도모하고 향후 무인 스마트 리프트의 초석이 되는 시스템을 제시하고자 한다.

• 대기
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• 제20권2호
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• pp.131-151
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• 2010

This study establishes a conceptual model to analyze heavy rainfall events in Korea using multi-functional transport satellite-1R satellite images. Three heavy rainfall episodes in two major synoptic types, such as synoptic low (SL) type and synoptic flow convergence (SC) type, are analyzed through a conceptual model procedure which proceeds on two steps: 1) conveyer belt model analysis to detect convective area, and 2) cloud top temperature analysis from black body temperature (TBB) data to distinguish convective cloud from stratiform cloud, and eventually estimate heavy rainfall area and intensity. Major synoptic patterns causing heavy rainfall are Changma, synoptic low approach, upper level low in the SL type, and upper level low, indirect effect of typhoon, convergence of tropical air in the SC type. The relationship between rainfall and TBBs in overall well resolved areas of heavy rainfall. The SC type tended to underestimate the intensity of heavy rainfall, but the analysis with the use of water vapor channel has improved the performance. The conceptual model improved a concrete utilization of images and data of satellite, as summarizing characteristics of major synoptic type causing heavy rainfall and composing an algorism to assess the area and intensity of heavy rainfall. The further assessment with various cases is required for the operational use.

• 대기
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• 제26권1호
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• pp.85-95
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• 2016

In this study, we investigated the variabilities of wind speed of 850 hPa and precipitable water over the East Asia region using the NCEP Final Analysis data from December 2001 to November 2011. A large variance of wind speed was observed in northern and eastern China during the winter period. During summer, the regions of the East China Sea, the South Sea of Japan and the East Sea show large variances in the wind speed caused by an extended North Pacific High and typhoon activities. The large variances in the wind speed in the regions are shown to be correlated with the inter-annual variability of precipitable water over the inland region of windward side of the Korean Peninsula. Based on the investigation, sensitivity tests to the domain size were performed using the WRF model version 3.6 for heavy precipitation events over the Korean Peninsula for 26 and 27 July 2011. Numerical experiments of different domain sizes were set up with 5 km horizontal and 50 levels vertical resolutions for the control and the first experimental run, and 9 km horizontal for the second experimental run. We found that the major rainfalls correspond to shortwave troughs with baroclinic structure over Northeast China and extended North Pacific High. The correlation analysis between the observation and experiments for 1-h precipitation indicated that the second experiment with the largest domain had the best performance with the correlation coefficient of 0.79 due to the synoptic-scale systems such as short-wave troughs and North Pacific High.

• 대기
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• 제26권1호
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• pp.59-72
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• 2016

The comparison of prediction errors in geopotential height, temperature, and precipitation forecasts is made quantitatively to evaluate medium-range forecast skills between Global Seasonal Forecasting System version 5 (GloSea5) and Unified Model (UM) in operation by Korea Meteorological Administration during 2014. In addition, the performances in prediction of sea surface temperature anomaly in NINO3.4 region, Madden and Julian Oscillation (MJO) index, and tropical storms in western north Pacific are evaluated. The result of evaluations appears that the forecast skill of UM with lower values of root-mean square error is generally superior to GloSea5 during forecast periods (0 to 12 days). The forecast error tends to increase rapidly in GloSea5 during the first half of the forecast period, and then it shows down so that the skill difference between UM and GloSea5 becomes negligible as the forecast time increases. Precipitation forecast of GloSea5 is not as bad as expected and the skill is comparable to that of UM during 10-day forecasts. Especially, in predictions of sea surface temperature in NINO3.4 region, MJO index, and tropical storms in western Pacific, GloSea5 shows similar or better performance than UM. Throughout comparison of forecast skills for main meteorological elements and weather extremes during medium-range, the effects of initial and model errors in atmosphere-ocean coupled model are verified and it is suggested that GloSea5 is useful system for not only seasonal forecasts but also short- and medium-range forecasts.

• 대기
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• 제26권1호
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• pp.1-18
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• 2016

Eleven Tropical Cyclone (TC) intensity guidance models in the western North Pacific have been validated over 2008~2014 based on various analysis methods according to the lead time of forecast, year, month, intensity, rapid intensity change, track, and geographical area with an additional focus on TCs that influenced the Korean peninsula. From the evaluation using mean absolute error and correlation coefficients for maximum wind speed forecasts up to 72 h, we found that the Hurricane Weather Research and Forecasting model (HWRF) outperforms all others overall although the Global Forecast System (GFS), the Typhoon Ensemble Prediction System of Japan Meteorological Agency (TEPS), and the Korean version of Weather and Weather Research and Forecasting model (KWRF) also shows a good performance in some lead times of forecast. In particular, HWRF shows the highest performance in predicting the intensity of strong TCs above Category 3, which may be attributed to its highest spatial resolution (~3 km). The Navy Operational Global Prediction Model (NOGAPS) and GFS were the most improved model during 2008~2014. For initial intensity error, two Japanese models, Japan Meteorological Agency Global Spectral Model (JGSM) and TEPS, had the smallest error. In track forecast, the European Centre for Medium-Range Weather Forecasts (ECMWF) and recent GFS model outperformed others. The present results has significant implications for providing basic information for operational forecasters as well as developing ensemble or consensus prediction systems.

• 대기
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• 제24권2호
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• pp.245-251
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• 2014

Statistical trajectory analysis has been widely used to identify potential source regions for chemically and radiatively important chemical species in the atmosphere. The most widely used method is a statistical source-receptor model developed by Stohl (1996), of which the underlying principle is that elevated concentrations at an observation site are proportionally related to both the average concentrations on a specific grid cell where the observed air mass has been passing over and the residence time staying over that grid cell. Thus, the method can compute a residence-time-weighted mean concentration for each grid cell by superimposing the back trajectory domain on the grid matrix. The concentration on a grid cell could be used as a proxy for potential source strength of corresponding species. This technical note describes the statistical trajectory approach and introduces its application to estimate potential source regions of $CO_2$ enhancements observed at Korean Global Atmosphere Watch Observatory in Anmyeon-do. Back trajectories are calculated using HYSPLIT 4 model based on wind fields provided by NCEP GDAS. The identified $CO_2$ potential source regions responsible for the pollution events observed at Anmyeon-do in 2010 were mainly Beijing area and the Northern China where Haerbin, Shenyang and Changchun mega cities are located. This is consistent with bottom-up emission information. In spite of inherent uncertainties of this method in estimating sharp spatial gradients within the vicinity of the emission hot spots, this study suggests that the statistical trajectory analysis can be a useful tool for identifying anthropogenic potential source regions for major GHGs.

• 대기
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• 제27권2호
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• pp.235-249
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• 2017

This paper describes methodology verifying near-surface predictability of numerical weather prediction models against the surface synoptic weather station network (SYNOP) observation. As verification variables, temperature, wind, humidity-related variables, total cloud cover, and surface pressure are included in this tool. Quality controlled SYNOP observation through the pre-processing for data assimilation is used. To consider the difference of topographic height between observation and model grid points, vertical inter/extrapolation is applied for temperature, humidity, and surface pressure verification. This verification algorithm is applied for verifying medium-range forecasts by a global forecasting model developed by Korea Institute of Atmospheric Prediction Systems to measure the near-surface predictability of the model and to evaluate the capability of the developed verification tool. It is found that the verification of near-surface prediction against SYNOP observation shows consistency with verification of upper atmosphere against global radiosonde observation, suggesting reliability of those data and demonstrating importance of verification against in-situ measurement as well. Although verifying modeled total cloud cover with observation might have limitation due to the different definition between the model and observation, it is also capable to diagnose the relative bias of model predictability such as a regional reliability and diurnal evolution of the bias.