• 제목/요약/키워드: 가스예측

검색결과 1,314건 처리시간 0.038초

Prediction of Slagging Behavior of Coal Ash in Gasifier using DTF (DTF를 이용한 가스화기에서 석탄회의 Slagging 성향 예측에 관한 연구)

  • 정석우;김형택;이시훈
    • Proceedings of the Korea Society for Energy Engineering kosee Conference
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    • 한국에너지공학회 1994년도 춘계학술발표회 초록집
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    • pp.22-27
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    • 1994
  • 6종류의 유연탄을 대상으로 석탄회분의 용융온도와 화학적조성을 측정하고, 대상탄 회분에 대해 Rs 값과 Fs 값을 계산해 봄으로써 각 탄들의 Slagging 성향을 알아보았다. 그리고, 이 자료만으로는 정확한 Slagging 성향의 예측이 어려우므로 분류층 가스화기의 조건을 모사한 DTF(Drop Tube Furnace : 이하 DTF)장치를 이용하여 온도와 체류시간을 달리하면서 생성되는 Slag의 화학적조성, 강도, 점착속도 등을 측정하여 Slagging 형태의 가스화기 운전에 있어서 최적조건을 제시하고자 한다.

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천연가스 복합발전 플랜트의 성능예측

  • Lee, Jin-Wook;Lee, Chan;Cho, Byeong-Hwa
    • Proceedings of the Korea Society for Energy Engineering kosee Conference
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    • 한국에너지공학회 1994년도 춘계학술발표회 초록집
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    • pp.55-63
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    • 1994
  • 국내에서 실제 운전되고 있는 천연가스 복합발전플랜트의 성능 예측에 대한 공정전산 해석을 수행하였다. 가스터빈 사이클은 압축기, 연소기, 터빈 및 터빈 날개의 냉각을 위한 냉각계통으로 구성하였으며, 중기터빈 사이클은 폐열회수보일러, 고압/중압/저압터빈, 펌프 및 부속공정으로 구성하였다. 해석결과는 실제 플랜트의 운전자료와 정성적 및 정량적으로 잘 일치하였으며, 폐열회수보일러의 적절한 설계에 의하여 전체 플랜트의 출력향상을 도모할 수 있음을 제시하였다.

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A Statistical Model for Predicting Incipient Point and Quantity of Gas Condensate in Gas Pipelines (가스 배관내 가스 컨덴세이트의 발생 시작점 및 발생량 예측을 위한 통계 모델 연구)

  • Chang, Seung-Yong
    • Journal of the Korean Institute of Gas
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    • 제10권4호
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    • pp.1-5
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    • 2006
  • With the rapid increase in gas consumption, the role of pipelines as a transportation means of natural gas is increasing. In general, when natural gas is being transported in pipelines, some liquid mainly from formation of condensate is introduced and this phenomenon makes operational problems more complex in the gas industry. Thus, an appropriate method is necessary for predicting the effect of presence of gas condensate on operational efficiency. In this study, a statistical model was developed using an integrated single- and two-phase flows concept. Using this model, the effects of the incipient point of gas condensate and its quantity on outlet pressure were analyzed. Also, the effect of variations of flow regimes in two-phase region on outlet pressure after the incipient point was analyzed.

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Study on Prediction System Construction of Fire.Explosion Accident by NG & LPG among Domestic Gas Accidents (국내 가스 사고사례 중 NG 및 LPG의 가스 화재.폭발사고 예측시스템 구축에 관한 연구)

  • Ko Jae-Sun;Kim Hyo
    • Journal of the Korean Institute of Gas
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    • 제10권1호
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    • pp.48-55
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    • 2006
  • In order to establish the comprehensively, quantitatively predictable program to the fire and explosion accidents in the urban gas system, and to set up domestic criteria of societal risk, the collected urban gas accident data have been deeply analyzed. The Poisson probability distribution functions with t=5 for the database of the gas accidents in recent 11 year shows that 'careless work-explosion-pipeline' item has the lowest frequency, whereas 'joint loosening & erosion-release-pipeline' item has the highest frequency. And thus the proper counteractions must be carried out. The further works requires setting up successive database on the fire and explosion accidents systematically to obtain reliable analyses.

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Verification of Required Pressurant Mass Prediction Program for Propellant Tank through Flight Test Data (비행시험 데이터를 통한 추진제탱크 가압가스 요구량 예측 프로그램 검증)

  • Kwon, Oh-Sung;Han, Sang-Yeop;Cho, In-Hyun;Ko, Young-Sung
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 한국추진공학회 2010년도 제35회 추계학술대회논문집
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    • pp.723-725
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    • 2010
  • Calculation program to predict required pressurant mass for propellant tank was verified through flight test data. This program was already developed and verified through ground test data, but to increase reliability of program, it was compared with flight test data of KSR-III launched in 2002. Because pressurant temperature incoming to propellant tank was not measured in flight test, that was assumed in calculation program. Required pressurant mass and inside temperature of oxygen tank dome was compared. Validation of calculation program was verified by showing required pressurant mass accuracy of 6%.

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Prediction Oil and Gas Throughput Using Deep Learning

  • Sangseop Lim
    • Journal of the Korea Society of Computer and Information
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    • 제28권5호
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    • pp.155-161
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    • 2023
  • 97.5% of our country's exports and 87.2% of imports are transported by sea, making ports an important component of the Korean economy. To efficiently operate these ports, it is necessary to improve the short-term prediction of port water volume through scientific research methods. Previous research has mainly focused on long-term prediction for large-scale infrastructure investment and has largely concentrated on container port water volume. In this study, short-term predictions for petroleum and liquefied gas cargo water volume were performed for Ulsan Port, one of the representative petroleum ports in Korea, and the prediction performance was confirmed using the deep learning model LSTM (Long Short Term Memory). The results of this study are expected to provide evidence for improving the efficiency of port operations by increasing the accuracy of demand predictions for petroleum and liquefied gas cargo water volume. Additionally, the possibility of using LSTM for predicting not only container port water volume but also petroleum and liquefied gas cargo water volume was confirmed, and it is expected to be applicable to future generalized studies through further research.

Study on Combustion Gas Properties of a Fuel-Rich Gas Generator (연료 과농 가스발생기의 연소 가스 물성치에 관한 연구)

  • 서성현;최환석;한영민;김성구
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • 제34권10호
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    • pp.56-60
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    • 2006
  • It is essential to predict thermodynamic properties of combustion gas with respect to a propellant mixture ratio for the development of a gas generator for a liquid rocket engine. The present study shows the temperature measurement of exit combustion gas as a function of a mixture ratio through the series of combustion tests of a fuel-rich gas generator with liquid oxygen and Jet A-1. The measurements of dynamic and static pressures, and combustion gas temperatures allowed the estimation of thermodynamic properties like a specific heat ratio, a gas constant, and a constant pressure specific heat of the combustion gas. The comparison of the experimental results with predictions made by interpolation parameters obtained from the modification of the chemical equilibrium code indicates that the interpolation method calibrated using the temperature measurements can be utilized as an effective tool for the initial design of a fuel-rich gas generator.

Prediction of Pressurant Mass Requirement for Propellant Tank with Operating Condition Variation (운용조건 변화에 따른 추진제탱크 가압가스 요구량 예측)

  • Kwon, Oh-Sung;Han, Sang-Yeop;Cho, In-Hyun
    • Aerospace Engineering and Technology
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    • 제10권1호
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    • pp.54-62
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    • 2011
  • The pressurant mass required for propellant tank pressurization with operating condition variation was estimated by using the numerical model already developed for this purpose. The model was applied to the concept design results of KSLV-II first stage oxygen tank. The supplied pressurant temperature, oxygen volumetric flow rate, and the ratio of length to diameter of the tank were selected as variables. The required pressurant mass and mass flow rate, collapse factor, ullage temperature distribution were predicted, and the results showed that the pressurant temperature had the largest effect on the amount of the required pressurant mass. The pressurizing efficiency of the propellant tank was calculated through analyzing energy distribution in the ullage. It was found that the gas-to-wall heat transfer in the ullage was dominant, and much of the pressurant energy was lost to tank wall heating.

City Gas Pipeline Pressure Prediction Model (도시가스 배관압력 예측모델)

  • Chung, Won Hee;Park, Giljoo;Gu, Yeong Hyeon;Kim, Sunghyun;Yoo, Seong Joon;Jo, Young-do
    • The Journal of Society for e-Business Studies
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    • 제23권2호
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    • pp.33-47
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    • 2018
  • City gas pipelines are buried underground. Because of this, pipeline is hard to manage, and can be easily damaged. This research proposes a real time prediction system that helps experts can make decision about pressure anomalies. The gas pipline pressure data of Jungbu City Gas Company, which is one of the domestic city gas suppliers, time variables and environment variables are analysed. In this research, regression models that predicts pipeline pressure in minutes are proposed. Random forest, support vector regression (SVR), long-short term memory (LSTM) algorithms are used to build pressure prediction models. A comparison of pressure prediction models' preformances shows that the LSTM model was the best. LSTM model for Asan-si have root mean square error (RMSE) 0.011, mean absolute percentage error (MAPE) 0.494. LSTM model for Cheonan-si have RMSE 0.015, MAPE 0.668.