• Title/Summary/Keyword: Scenario prediction

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Prediction of Damage Area due to Explosion of LNG-Hydrogen Mixed Gas (도시가스-수소 혼합가스의 누출사고 영향범위 분석)

  • Chan-sik, Yoon;Jin-du, Yang;Gil-soo, Na;Sung-Hyun, Im;Ki-young, Kim;Eun-ki, Choi
    • Explosives and Blasting
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    • v.40 no.4
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    • pp.27-34
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    • 2022
  • The government is promoting various policies to reduce greenhouse gas emissions for carbon neutrality, one of the key tasks is to revitalize the hydrogen economy. As one of these policies the government has formulated a plan to incorporate hydrogen into existing city gas pipes, and aims to commercialize 20% hydrogen mixing by 2026. In preparation for the commercialization of city gas and hydrogen mixture, this study quantitatively predicts the scale of damage and the range of impact in the event of leakage of these two gas mixtures. The quantitative damage prediction method is to calculate the damage conversion distance through the calculation of the TNT equivalent by setting the leakage amount of the gas mixture in the event of an accident under a virtual scenario.

Validation of FDS for Fire in Underventilated Condition with Two rooms (환기가 제한된 두 개 격실 화재에서 FDS 검증분석)

  • Bae, Young-Bum;Keum, O-Hyun;Kim, Yun-Il;Ryu, Su-Hyun;Kim, Wee-Kyung;Park, Jong-Seuk
    • Proceedings of the Korea Institute of Fire Science and Engineering Conference
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    • 2008.11a
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    • pp.438-443
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    • 2008
  • Fire model shall be verified and validated to reliably show the predictive capabilities for a specific use. In the process of model verification and validation, both the acceptable uses and limitation of fire model are established. In this study, the results of FDS simulation are compared with the data of PRISME experiment such as temperature, heat release rate, heat flux, product concentrations in the under-ventilated two-room condition. Furthermore, the sensitivity of FDS under ventilation condition changes are evaluated. FDS provide the reliable prediction for under-ventilated two-room fire scenario with slightly deviation.

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A Study on Measuring Procedure and Analysis Technique of Ship Infrared Signature at Sea (해상에서 적외선신호의 계측절차 및 분석기법 연구)

  • Cho, Yong-Jin
    • Journal of Ocean Engineering and Technology
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    • v.23 no.3
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    • pp.53-58
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    • 2009
  • A scale model test for ship Infra-Red signature measurements at sea is impossible, because it is sensitive to the environment. Since we can't control the meteorological environment of the real sea, it can't be carried out with the desired maritime environments. Therefore, in the sea, we made measurements of the weather, operating conditions of the ship, and ship IR signatures under given conditions, and then analyzed them. Conversely, we compared the results of the test with a prediction for a given scenario condition. This paper describes the test items, procedures, and measuring instruments of the experiments at sea and the results from basic researches for methods of estimation and analysis of the measured data.

Development of Prediction Technique for Future Vegetation Information Using NOAA AVHRR Image and Weather Data Based on Climate Change Scenario (NOAA AVHRR 위성영상과 기후변화 시나리오에 의한 기상자료를 이용한 미래 식생정보 예측 기법 개발)

  • Ha, Rim;Shin, Hyung-Jin;Park, Geun-Ae;Kim, Seong-Joon
    • 한국공간정보시스템학회:학술대회논문집
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    • 2007.06a
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    • pp.162-168
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    • 2007
  • 기후변화는 강수유형, 기온상승과 일사량의 변화로 인한 증발산량의 변화, 유역 식생피복변화로 인한 지표-대기 관계의 변화와 같은 현상을 통해 지역 부존 수자원과 유출량에 큰 변화를 가져올 수 있다. 특히 지표면의 76%를 차지하고 있는 식생피복은 지표와 대기 사이의 물 순환과정에서 중요한 인자이다. 본 연구에서는 넓은 지역에 대한 식생피복의 파악이 용이한 NOAA 위성의 AVHRR (Advanced Very High Resolution Radiometer) 센서로부터 얻을 수 있는 정규화 식생지수 (Normalized Difference Vegetation Index, NDVI)를 통하여 현 식생정보를 정량화하였다. 이로부터 토지피복별 NDVI와 기상인자(기온, 강수량, 일조시간, 풍속, 습도) 사이의 상관관계를 분석하고, 이를 기후변화 시나리오에 의한 기상인자로 부터 토지피복에 따른 미래 NDVI를 추정하였다.

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Scenarios for Manufacturing Process Data Analysis using Data Mining (데이터 마이닝을 이용한 생산공정 데이터 분석 시나리오)

  • Lee, Hyoung-wook;Bae, Sung-min
    • Journal of Institute of Convergence Technology
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    • v.3 no.1
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    • pp.41-44
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    • 2013
  • Process and manufacturing data are numerously accumulated to the enterprise database in industries but little of those data are utilized. Data mining can support a decision to manager in process from the data. However, it is not easy to field managers because a proper adoption of various schemes is very difficult. In this paper, six scenarios are conducted using data mining schemes for the various situations of field claims such as yield problem, trend analysis and prediction of yield according to changes of operating conditions, etc. Scenarios, like templates, of various analysis situations are helpful to users.

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Prediction of Future Sea Surface Temperature around the Korean Peninsular based on Statistical Downscaling (통계적 축소법을 이용한 한반도 인근해역의 미래 표층수온 추정)

  • Ham, Hee-Jung;Kim, Sang-Su;Yoon, Woo-Seok
    • Journal of Industrial Technology
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    • v.31 no.B
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    • pp.107-112
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    • 2011
  • Recently, climate change around the world due to global warming has became an important issue and damages by climate change have a bad effect on human life. Changes of Sea Surface Temperature(SST) is associated with natural disaster such as Typhoon and El Nino. So we predicted daily future SST using Statistical Downscaling Method and CGCM 3.1 A1B scenario. 9 points of around Korea peninsular were selected to predict future SST and built up a regression model using Multiple Linear Regression. CGCM 3.1 was simulated with regression model, and that comparing Probability Density Function, Box-Plot, and statistical data to evaluate suitability of regression models, it was validated that regression models were built up properly.

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Recommendation Technique using Social Network in Internet of Things Environment (사물인터넷 환경에서 소셜 네트워크를 기반으로 한 정보 추천 기법)

  • Kim, Sungrim;Kwon, Joonhee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.11 no.1
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    • pp.47-57
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    • 2015
  • Recently, Internet of Things (IoT) have become popular for research and development in many areas. IoT makes a new intelligent network between things, between things and persons, and between persons themselves. Social network service technology is in its infancy, but, it has many benefits. Adjacent users in a social network tend to trust each other more than random pairs of users in the network. In this paper, we propose recommendation technique using social network in Internet of Things environment. We study previous researches about information recommendation, IoT, and social IoT. We proposed SIoT_P(Social IoT Prediction) using social relationships and item-based collaborative filtering. Also, we proposed SR(Social Relationship) using four social relationships (Ownership Object Relationship, Co-Location Object Relationship, Social Object Relationship, Parental Object Relationship). We describe a recommendation scenario using our proposed method.

A Prediction Model on DC Distribution using Scenario Analysis (시나리오 분석을 통한 DC 배전시장 예측 모델의 적용)

  • Yeo, Seo-Hyun;Sun, Hwi-il;Park, Jin-Wook;Yoo, Dong-Wook;Song, Sung-Geun;Park, Sung-Jun
    • Proceedings of the KIPE Conference
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    • 2017.07a
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    • pp.475-476
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    • 2017
  • 본 논문은 다수의 국외 시장 전망 보고서를 기반으로 최근 해외 도입 및 국내 구축 예정인 DC 배전 시장 동향과 경제적 효율성을 분석하였다. 분석 방법은 3가지 시나리오에 따라 2030년까지의 시장 규모 추이를 예측하고, DC 배전을 구성하는 배전용 전력기기의 시장 규모를 도출하였다. 또한 시장점유율, 부가가치율, 온실가스 감축 등의 요소를 적용하여, 세계 시장에 대한 국내 기업 점유율에 따른 DC 배전의 편익을 계산하였다. 그 결과 2030년 기준 DC 배전 시장 규모의 긍정적 확장성을 예측할 수 있었으며, DC 배전용 전력기기 시장 규모와 이에 따른 경제적 편익을 확인하였다. 추후 연구에서는 DC 배전 시장을 구성하는 각 부문들의 규모 추이를 파악하고, 국내 DC 배전용 전력기기 개발 실데이터를 적용하여 비용편익비(BCR)를 도출하고자 한다.

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A Economic Prediction Model on VSC-HVDC Using Scenario Analysis (시나리오 분석을 통한 VSC-HVDC 경제성 예측 모델의 적용)

  • Sun, Hwi-il;Yeo, Seo-Hyun;Song, Sung-Geun;Park, Sung-Jun
    • Proceedings of the KIPE Conference
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    • 2017.07a
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    • pp.473-474
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    • 2017
  • 수도권 부하의 집중과 원거리 발전단지 위치는 우리나라 전력전송의 문제점이며, 전압형 HVDC 적용이 전력전송 문제의 대안이 되고 있다. 초기투자비가 높은 전압형 HVDC 사업의 경제적 타당성 확보의 방법은 기존 시장접근법의 부가가치 편익반영 외에 다른 각도의 다양한 편익산정법의 제안이 필요하다. 본 논문에서는 전압형 HVDC 사업 타당성 확보를 위한 피해비용저감방식의 다양한 편익을 도출하고 경제적 타당성을 제시하였다.

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L-PRS: A Location-based Personalized Recommender System

  • Kim, Taek-hun;Song, Jin-woo;Yang, Sung-bong
    • Proceedings of the KAIS Fall Conference
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    • 2003.11a
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    • pp.113-117
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    • 2003
  • As the wireless communication technology advances rapidly, a personalization technology can be incorporated with the mobile Internet environment, which is based on location-based services to support more accurate personalized services. A location-based personalized recommender system is one of the essential technologies of the location-based application services, and is also a crucial technology for the ubiquitous environment. In this paper we propose a framework of a location-based personalized recommender system for the mobile Internet environment. The proposed system consists of three modules the interface module, the neighbor selection module and the prediction and recommendation module. The proposed system incorporates the concept of the recommendation system in the Electronic Commerce along with that of the mobile devices for possible expansion of services on the mobile devices. Finally a service scenario for entertainment recommendation based on the proposed recommender system is described.

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