• 한국건설관리학회논문집
• /
• 제7권4호
• /
• pp.100-108
• /
• 2006

대부분의 건설현장에서 기후에 대한 공기산정은 정확한 자료 없이 현장관리자의 경험과 직관에 의해 작업불능일수를 정함으로써 잦은 공기조정으로 인한 경제적 손실은 물론 공사주체들 간의 이해관계에서도 많은 문제점을 안고 있다. 일부 건설 현장과 선행연구에서는 작업불능일 산정기준으로 과거 일정기간의 기상평균값을 사용하고 있지만, 과거 산정기간에 대한 기준이 정립되지 않아 현장마다 각기 다른 산정기간을 적용하고 있으며, 적용기간에 따라 산정한 작업불능일수가 서로 다른 실정이다. 뿐만 아니라 최근 대두되고 있는 기후변화는 기후예측을 보다 어렵게 만들고 있다. 따라서 본 연구에서는 기후조건별 작업불능일 산정을 위한 산술평균값들 중 최근 몇 년 기간을 산술평균으로 한 예측값이 실제값과의 오차를 최소화시킬 수 있는지 검토하여, 보다 예측성이 높은 산정방법을 제안하고자 한다.

• 한국화재소방학회논문지
• /
• 제29권5호
• /
• pp.88-95
• /
• 2015

본 논문에서는 일상생활에서 화재에 대한 주민들의 경각심을 고취시킬 수 있도록 기상조건에 따른 화재위험을 평가할 수 있는 날씨 관련 서비스를 제안한다. 제안된 서비스는 기상예보에 따른 화재위험평가등급과 특정 기상조건에서 화재요인에 따른 화재위험도를 제공한다. 제안한 서비스에서는 데이터마이닝 기법인 의사결정트리를 이용하여 화재조사데이터와 관측된 기상데이터로부터 화재위험평가등급을 산출할 수 있는 화재 위험도 매트릭스를 생성한다. 주민들은 제안한 서비스를 통해 특정 기상조건에서 화재요인에 따라 화재위험도를 직접 평가할 수 있고, 화재위험도를 저감시킬 수 있는 예방책을 사용자가 선택할 수 있다. 제안한 서비스를 시스템화하여 서비스의 현실성을 확인하였다. 시스템은 온라인상에서 기상청의 기상예보가 갱신될 때마다 시도별로 기상예보에 따른 화재위험평가등급을 표시하고, 각 시도별로 해당 기상조건에서 화재요인에 따라 화재위험도를 평가할 수 있다.

• The Plant Pathology Journal
• /
• 제39권6호
• /
• pp.548-565
• /
• 2023

Armillaria root disease affects forests around the world. It occurs in many habitats and causes losses in the infested stands. Weather conditions are important factors for growth and development of Armillaria species. Yet, the relation between occurrence of damage caused by Armillaria disease and weather variables are still poorly understood. Thus, we used generalized linear mixed models to determine the relationship between weather conditions of current and previous year (temperature, precipitation and their deviation from long-term averages, air humidity and soil temperature) and the incidence of Armillaria-induced damage in young (up to 20 years old) and older (over 20 years old) coniferous stands in selected forest districts across Poland. We used unique data, gathered over the course of 23 years (1987-2009) on tree damage incidence from Armillaria root disease and meteorological parameters from the 24-year period (1986-2009) to reflect the dynamics of damage occurrence and weather conditions. Weather parameters were better predictors of damage caused by Armillaria disease in younger stands than in older ones. The strongest predictor was soil temperature, especially that of the previous year growing season and the current year spring. We found that temperature and precipitation of different seasons in previous year had more pronounced effect on the young stand area affected by Armillaria. Each stand's age class was characterized by a different set of meteorological parameters that explained the area of disease occurrence. Moreover, forest district was included in all models and thus, was an important variable in explaining the stand area affected by Armillaria.

• 한국건설관리학회논문집
• /
• 제11권3호
• /
• pp.89-96
• /
• 2010

건설업은 옥외작업이 많기 때문에 날씨에 의한 영향이 매우 크므로, 날씨정보를 활용하고자 하는 노력을 기울여왔다. 하지만 실제로 건축현장에서 날씨정보를 어떻게 활용하고 있는지 현황파악에 대한 연구는 미흡하였다. 따라서 본 연구에서는 건축현장의 날씨정보 활용 현황을 분석하여 날씨정보의 활용성 향상방안을 제시하는 것을 목적으로 한다. 연구결과 현장 실무자들은 날씨정보가 성과향상에 도움이 될 것이라 인식하고 있지만, 날씨정보 활용에 관한 교육은 제대로 받지 못하였다는 것이 파악되었다. 또한 기상정보시스템의 날씨정보가 건축공사에서 활용하기에 적합하지 않아서 실제 업무에서 활용성이 떨어진다는 것이 파악되었다. 따라서 날씨정보 활용성을 향상시키기 위해서는 현장 실무자들에게 날씨정보 활용에 관하여 체계적인 교육을 실시해야 하며, 건축현장에 특화된 날씨정보를 제공하도록 기상정보시스템을 보완하는 것이 필요하다. 또한 장기적으로 건설날씨정보 전문가를 양성하여 건설업에 특화된 날씨정보를 지속적으로 유지, 관리할 수 있도록 해야 한다. 이를 통해서 날씨에 적극적으로 대응이 가능하며, 최종적으로는 현장의 성과가 향상될 것으로 기대된다.

• 한국항해학회지
• /
• 제11권1호
• /
• pp.107-144
• /
• 1987

In cold season, ice accretion on ship, drift ice, NW winter monsoon, developed extratropical cyclones and associated cold fronts, in warm season, tropical cyclones and dense sea fogs, are encountered very frequently in the North Pacific, especially in the northwest part of it. The two areas, namely, the northwest part of the North Pacific and Burmuda Triangle in the North Atlantic are generally known as most dangerous areas in the world because its high incidence of sea cascualities. In recent years, the small fisherboats operating in the northern seas were frequently sunk in a group as they encountered ice accretion or drift ice. And ocean going vessels were also sunk frequently due to strong winds and very high seas in winter monsoon or developed cyclones and cold fronts. The purpose of this paper is to analyze the real state of heavy weather conditions such as ice accretion on ship drift, ice, typhoons and sea fogs, and also to analyse the effect of these heavy weather phenomena on the vessels at sea, thus helping mariners operate in such heavy weather conditions.

• 한국잠사곤충학회지
• /
• 제36권2호
• /
• pp.110-114
• /
• 1994

93년 뽕나무 생육기에 내습한 이상저온 현상에 대한 감수정도와 요인을 분석하는 한편, 경감대책을 마련하기 위해 수원 잠업시험장과 충남 공주군에 소재한 충남도 잠업사업소 등 2개 장소에서 방임구를 대조로 요소엽면시비구 (요소 0.7%), 잠시비료 8호구 (요수 0.7%와 미량요소 함유), 그리고 질소질 6kg/10a를 황산암모늄으로 덧거름한 4개처리구를 설치하여 시험결과 다음과 같았다. 1. 여름베기후 뽕나무 생육기간 중인 6월 하순-9월 상순사이에 전국적으로 평년대비 평균기온은 1.4$^{\circ}C$ 낮았으며, 강우량은 83mm나 많았으며, 그 결과 가을뽕 수량은 평년대비 16.4% 감수되었는데, 뽕잎의 감수에 더 크게 영향하는 요인은 기온의 저하보다는 강우량의 과다에서 오는 질소질의 용탈에 원인하는 것으로 판단되었다. 2. 이상저온 내습시 생육부진을 막기 위해 요소 및 잠시비료 8호를 각각 엽면시비한 구보다는, 질소질 6kg/10a를 덧거름으로 시비한 구에서 5% 수준에서 통계적인 유의차가 인정될 정도로 증수되었다. 3. 뽕잎분석 결과 전질소 함량은 요소살포구와 질소질 덧거름구에서 방임구 3.53% 대비 0.53% 높았다.

• 대한조선학회논문집
• /
• 제52권2호
• /
• pp.110-118
• /
• 2015

Weather routing method is one of the best practices of SEEMP (Ship Energy Efficiency Management Plan) for fuel-efficient operation of ship. KR is carrying out a basic research for development of the weather routing algorithm and making a monitoring system by FOC (Fuel Oil Consumption) analysis compared to the reference, which is the great circle route. The added resistances applied global sea/weather data can be calculated using ship data, and the results can be corrected to ship motions. The global sea/weather data such as significant wave height, ocean current and wind data can be used to calculate the added resistances. The reference route in a usual navigation is the great circle route, which is the shortest distance route. The global sea/weather data can be divided into grids, and the nearest grid data from a ship's position can be used to apply a ocean going vessel's sea conditions. Powell method is used as an optimized routing technique to minimize FOC considered sea/weather conditions, and FOC result can be compared with the great circle route result.

• 한국산업융합학회 논문집
• /
• 제23권6_2호
• /
• pp.1025-1032
• /
• 2020

In this paper, we propose a method to classify road weather conditions into rain, fog, and sun using a SVM (Support Vector Machine) classifier after extracting weather features from images acquired in real time using an optical sensor installed on a roadside post. A multi-dimensional weather feature vector consisting of factors such as image sharpeness, image entropy, Michelson contrast, MSCN (Mean Subtraction and Contrast Normalization), dark channel prior, image colorfulness, and local binary pattern as global features of weather-related images was extracted from road images, and then a road weather classifier was created by performing machine learning on 700 sun images, 2,000 rain images, and 1,000 fog images. Finally, the classification performance was tested for 140 sun images, 510 rain images, and 240 fog images. Overall classification performance is assessed to be applicable in real road services and can be enhanced further with optimization along with year-round data collection and training.

• 대한설비공학회지:설비저널
• /
• 제14권4호
• /
• pp.322-356
• /
• 1985

The outdoor design conditions for summer and winter are basic data required for determining the heating and cooling loads and HVAC equipment capacity. The latest study reported was based on the 1960's weather data, which is widely used by HVAC design engineers in Korea. The purpose of this paper is to update the outdoor design conditions for HVAC loads and equipments based on the weather data for the 1970's. The weather conditions of 24 sites, namely Sokcho, Chuncheon, Gangreung, Seoul, Inchon, Ulreungdo, Suweon, Seosan, Cheongju, Daejeon, Chupungryeong, Pohang, Gunsan, Daegu, Jeonju, Ulsan, Kwangju, Busan, Chungmu, Mokpo, Yeosu, Jeju, Seogwipo, and Jinju have been analyzed to calculate the outdoor design conditions. This analys is performed on the basis of TAC $1\%,\;TAC\;2.5\%,\;and\;TAC\;5\%$.

• 설비공학논문집
• /
• 제28권12호
• /
• pp.467-476
• /
• 2016

As the energy saving issues become one of the important global agenda, the building simulation method is generally used to predict the inside energy usage to establish the power-saving strategies. To foretell an accurate energy usage of a building, proper and typical weather data are needed. For this reason, typical weather data are fundamental in building energy simulations and among the meteorological factors, the solar irradiation is the most important element. Therefore, preparing solar irradiation is a basic factor. However, there are few places where the horizontal solar radiation in domestic weather stations can be measured, so the prediction of the solar radiation is needed to arrive at typical weather data. In this paper, four solar radiation prediction models were analyzed in terms of their applicability for domestic weather conditions. A total of 12 regions were analyzed to compare the differences of solar irradiation between measurements and the prediction results. The applicability of the solar irradiation prediction model for a certain region was determined by the comparisons. The results were that the Zhang and Huang model showed the highest accuracy (Rad 0.87~0.80) in most of the analyzed regions. The Kasten model which utilizes a simple regression equation exhibited the second-highest accuracy. The Angstrom-Prescott model is easily used, also by employing a plain regression equation Lastly, the Winslow model which is known for predicting global horizontal solar irradiation at any climate regions uses a daily integration equation and showed a low accuracy regarding the domestic climate conditions in Korea.