• Title/Summary/Keyword: Real gas model

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Direct Observation of Premixed Flame Propagation Characteristics in an Annular Coaxial 5-Tubes Burner (환형 5중 동축관 연소기 내부에서의 예혼합 화염의 전파 특성 직접 관찰)

  • Cho, Moon Soo;Baek, Da Bin;Kim, Nam Il
    • Journal of the Korean Society of Combustion
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    • v.18 no.3
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    • pp.24-30
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    • 2013
  • Flame stabilization characteristics of premixed flames in an annular coaxial 5-tubes burner (AC5TB) were investigated experimentally. The AC5TB was made of five quartz tubes, and the flame stabilization conditions in that burner were investigated with the variation of equivalence ratio and the flow velocities. Flame behaviors inside of narrow annular tubes could be observed directly. Overall flame stabilization conditions were similar to that of the previous study, while the flame behaviors and structures were different mainly due to the controlled uniform distribution of the velocities in channels. Flame flashback conditions were thought to be governed by the competition between heat release rate, heat loss and heat recirculation in each channel. Stationary flames at a fixed location were compared in its velocity distribution and burned gas temperature across the channel. This AC5TB can be a basic configuration for the development of flame stabilization model of porous media combustors, and it will help understand about the real behavior of flames in meso-scale combustion spaces.

Estimation of Flight Fuel Consumption Based on Flight Track Data and Its Accuracy Analysis (항적자료를 활용한 항공기 연료 소모량 추정 및 정확도 분석)

  • Park, Jang-Hoon;Ku, Sung-Kwan;Baik, Ho-Jong
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.22 no.4
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    • pp.25-33
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    • 2014
  • As global warming becoming an environmentally serious issue, more attention is drawn to fuel consumption which is the direct source of green house gas emission. The fuel consumption by aircraft operation is not an exception. Motivated by the societal and environmental context, this paper explains a method for estimation of aircraft fuel consumed during their flights as well as the computational process using real flight track data. Applying so-called 'Total Energy Model' along with aircraft specific parameters provided in EUROCONTROL's Base of Aircraft Data (BADA) to aircraft radar track data, we estimate fuel consumption of individual aircraft flown between Gimpo and Jeju airports. We then assess the estimation accuracy by comparing the estimated fuel consumption with the actual one collected from an airline. The computational results are quite encouraging in that the method is able to estimate the actual fuel consumption within ${\pm}6{\sim}11%$ of error margin. The limitations and possible enhancements of the method are also discussed.

Real-time SCR-HP(Selective catalytic reduction - high pressure) valve temperature collection and failure prediction using ARIMA (ARIMA를 활용한 실시간 SCR-HP 밸브 온도 수집 및 고장 예측)

  • Lee, Suhwan;Hong, Hyeonji;Park, Jisoo;Yeom, Eunseop
    • Journal of the Korean Society of Visualization
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    • v.19 no.1
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    • pp.62-67
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    • 2021
  • Selective catalytic reduction(SCR) is an exhaust gas reduction device to remove nitro oxides (NOx). SCR operation of ship can be controlled through valves for minimizing economic loss from SCR. Valve in SCR-high pressure (HP) system is directly connected to engine exhaust and operates in high temperature and high pressure. Long-term thermal deformation induced by engine heat weakens the sealing of the valve, which can lead to unexpected failures during ship sailing. In order to prevent the unexpected failures due to long-term valve thermal deformation, a failure prediction system using autoregressive integrated moving average (ARIMA) was proposed. Based on the heating experiment, virtual data mimicking temperature range around the SCR-HP valve were produced. By detecting abnormal temperature rise and fall based on the short-term ARIMA prediction, an algorithm determines whether present temperature data is required for failure prediction. The signal processed by the data collection algorithm was interpolated for the failure prediction. By comparing mean average error (MAE) and root mean square error (RMSE), ARIMA model and suitable prediction instant were determined.

Development of Design Code for Oxidizer-Rich Preburner of Staged Combustion Cycle Engine Using Cantera (Cantera를 이용한 케로신 다단연소사이클 엔진용 산화제 과잉 예연소기 설계코드 개발)

  • Si-Yoon Kang;Seong-Ku Kim;Chulsung Ryu;Insang Moon
    • Journal of the Korean Society of Propulsion Engineers
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    • v.26 no.6
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    • pp.10-20
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    • 2022
  • The present study developed a design code for preburner of staged combustion cycle engines, which calculates preburnt gas at high-pressure oxidizer-rich conditions and predicts conjugate heat transfer and hydraulics of cryogenic fluid flow through cooling passages. It has been written based on the open-source library Cantera, into which this study has incorporated new source codes to predict correctly non-ideal thermodynamics and transport anomalies of the cryogenic fluid. For a preburner of 100 tonf-class booster engine currently under preliminary design, the present code demonstrated predictive capability and usability as a design code by comparing with CFD simulation.

Aerodynamic design and optimization of a multi-stage axial flow turbine using a one-dimensional method

  • Xinyang Yin;Hanqiong Wang;Jinguang Yang;Yan Liu;Yang Zhao;Jinhu Yang
    • Advances in aircraft and spacecraft science
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    • v.10 no.3
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    • pp.245-256
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    • 2023
  • In order to improve aerodynamic performance of multi-stage axial flow turbines used in aircraft engines, a one-dimensional aerodynamic design and optimization framework is constructed. In the method, flow path is generated by solving mass continuation and energy conservation with loss computed by the Craig & Cox model; Also real gas properties has been taken into consideration. To obtain an optimal result, a multi-objective genetic algorithm is used to optimize the efficiencies and determine values of various design variables; Final design can be selected from obtained Pareto optimal solution sets. A three-stage axial turbine is used to verify the effectiveness of the developed optimization framework, and designs are checked by three-dimensional CFD simulation. Results show that the aerodynamic performance of the optimized turbine has been significantly improved at design point, with the total-to-total efficiency increased by 1.17% and the total-to-static efficiency increased by 1.48%. As for the off-design performance, the optimized one is improved at all working points except those at small mass flow.

Using the Binomial Option Pricing Model for Strategic Sales of CER's to Improve the Economic Feasibility of CDM projects (이항옵션가격 모형을 활용한 CER 판매전략 구축과 이를 통한 CDM 사업 수익성 향상 방안에 관한 연구)

  • Koo, Bonsang;Park, Jong-Ho;Kim, Cheong-Woon
    • Korean Journal of Construction Engineering and Management
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    • v.15 no.1
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    • pp.111-121
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    • 2014
  • The Clean Development Mechanism (CDM) allows New & Renewable Energy projects to make additional income by selling CER's, which represent the amount of Green House Gases(GHG) that is reduced in the project. However, forward contracts used to hedge fluctuating market prices does not allow projects to sell CER's at a premium. As an alternate approach to maximize CER revenue, CER's are modeled as a 'real option', in which CER's are sold only above the desired sales price. Using the Binomial Option Pricing model, the resultant lattices are used to determine whether to sell, defer or abandon the option at individual nodes. Overlaying Pascal's Triangle on the lattices also enabled the calculation of the annual probabilities for deferring CER sales without incurring downside losses. Application to an actual Landfill Gas project showed increased overall NPV, and that CER sales could be deferred at a maximum of 2 years. The proposed framework allows transparency in the analysis and provides valuable and strategical information when making investment decisions related to CER sales of CDM projects.

A Study on the Method of Energy Evaluation in Water Supply Networks (상수관망의 에너지 평가기법에 관한 연구)

  • Kim, Seong-Won;Kim, Dohwan;Choi, Doo Yong;Kim, Juhwan
    • Journal of Korea Water Resources Association
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    • v.46 no.7
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    • pp.745-754
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    • 2013
  • The systematic analysis and evaluation of required energy in the processes of drinking water production and supply have attracted considerable interest considering the need to overcome electricity shortage and control greenhouse gas emissions. On the basis of a review of existing research results, a practical method is developed in this study for evaluating energy in water supply networks. The proposed method can be applied to real water supply systems. A model based on the proposed method is developed by combining the hydraulic analysis results that are obtained using the EPANET2 software with a mathematical energy model on the MATLAB platform. It is suggested that performance indicators can evaluate the inherent efficiency of water supply facilities as well as their operational efficiency depending on the pipeline layout, pipe condition, and leakage level. The developed model is validated by applying it to virtual and real water supply systems. It is expected that the management of electric power demand on the peak time of water supply and the planning of an energy-efficient water supply system can be effectively achieved by the optimal management of energy by the proposed method in this study.

An experimental study of smoke extraction efficiency along with ventilation building location in the mad tunnel (도로터널 내 환기소 위치별 방재 효율에 관한 실험적 연구)

  • Rie, Dong-Ho;Kim, Ha-Young;Yoon, Chan-Hoon;Kim, Jin
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.12 no.3
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    • pp.215-222
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    • 2010
  • An experimental study was carried out on a reduced scale model tunnel to investigate the efficiency of disaster prevention at underground and ground ventilation equipments for the fire in road tunnels. Based on Froude modeling, the 1/50 scaled model tunnel (20 m long) was manufactured. The vertical shafts that are used in the analysis of efficiency of disaster prevention are the two models that had considered when the real tunnels are designed and the amounts of smoke exhaust are applied the miniature of the real tunnels' smoke exhaust, 560 and $280\;m^3/s$. As the result of analysis, it is the possible the emissions of the entire quantity of CO gas through the vertical shafts. In the ground ventilation equipments, the concentration of CO is discharged 2.23~2,73 ppm smaller than the underground ventilation equipments. And the temperature rise in the ground ventilation equipments is $0.53{\sim}0.94^{\circ}C$ lower than in the underground ventilation equipments because of a cooling effect of the surface of the tunnel wall. As a result of analysis of CO concentration and the temperature rise in the modeling ventilation equipment, the position of ground ventilation equipment is more effective than the underground ventilation equipment in disaster prevention measures.

Development of System Dynamics model for Electric Power Plant Construction in a Competitive Market (경쟁체제 하에서의 발전소 건설 시스템 다이내믹스 모델 개발)

  • 안남성
    • Korean System Dynamics Review
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    • v.2 no.2
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    • pp.25-40
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    • 2001
  • This paper describes the forecast of power plant construction in a competitive korean electricity market. In Korea, KEPCO (Korea Electric Power Corporation, fully controlled by government) was responsible for from the production of the electricity to the sale of electricity to customer. However, the generation part is separated from KEPCO and six generation companies were established for whole sale competition from April 1st, 2001. The generation companies consist of five fossil power companies and one nuclear power company in Korea at present time. Fossil power companies are scheduled to be sold to private companies including foreign investors. Nuclear power company is owned and controlled by government. The competition in generation market will start from 2003. ISO (Independence System Operator will purchase the electricity from the power exchange market. The market price is determined by the SMP(System Marginal Price) which is decided by the balance between demand and supply of electricity in power exchange market. Under this uncertain circumstance, the energy policy planners such as government are interested to the construction of the power plant in the future. These interests are accelerated due to the recent shortage of electricity supply in California. In the competitive market, investors are no longer interested in the investment for the capital intensive, long lead time generating technologies such as nuclear and coal plants. Large unclear and coal plants were no longer the top choices. Instead, investors in the competitive market are interested in smaller, more efficient, cheaper, cleaner technologies such as CCGT(Combined Cycle Gas Turbine). Electricity is treated as commodity in the competitive market. The investors behavior in the commodity market shows that the new investment decision is made when the market price exceeds the sum of capital cost and variable cost of the new facility and the existing facility utilization depends on the marginal cost of the facility. This investors behavior can be applied to the new investments for the power plant. Under these postulations, there is the potential for power plant construction to appear in waves causing alternating periods of over and under supply of electricity like commodity production or real estate production. A computer model was developed to sturdy the possibility that construction will appear in waves of boom and bust in Korean electricity market. This model was constructed using System Dynamics method pioneered by Forrester(MIT, 1961) and explained in recent text by Sternman (Business Dynamics, MIT, 2000) and the recent work by Andrew Ford(Energy Policy, 1999). This model was designed based on the Energy Policy results(Ford, 1999) with parameters for loads and resources in Korea. This Korea Market Model was developed and tested in a small scale project to demonstrate the usefulness of the System Dynamics approach. Korea electricity market is isolated and not allowed to import electricity from outsides. In this model, the base load such as unclear and large coal power plant are assumed to be user specified investment and only CCGT is selected for new investment by investors in the market. This model may be used to learn if government investment in new unclear plants could compensate for the unstable actions of private developers. This model can be used to test the policy focused on the role of unclear investments over time. This model also can be used to test whether the future power plant construction can meet the government targets for the mix of generating resources and to test whether to maintain stable price in the spot market.

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Deep Learning Based Prediction Method of Long-term Photovoltaic Power Generation Using Meteorological and Seasonal Information (기후 및 계절정보를 이용한 딥러닝 기반의 장기간 태양광 발전량 예측 기법)

  • Lee, Donghun;Kim, Kwanho
    • The Journal of Society for e-Business Studies
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    • v.24 no.1
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    • pp.1-16
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    • 2019
  • Recently, since responding to meteorological changes depending on increasing greenhouse gas and electricity demand, the importance prediction of photovoltaic power (PV) is rapidly increasing. In particular, the prediction of PV power generation may help to determine a reasonable price of electricity, and solve the problem addressed such as a system stability and electricity production balance. However, since the dynamic changes of meteorological values such as solar radiation, cloudiness, and temperature, and seasonal changes, the accurate long-term PV power prediction is significantly challenging. Therefore, in this paper, we propose PV power prediction model based on deep learning that can be improved the PV power prediction performance by learning to use meteorological and seasonal information. We evaluate the performances using the proposed model compared to seasonal ARIMA (S-ARIMA) model, which is one of the typical time series methods, and ANN model, which is one hidden layer. As the experiment results using real-world dataset, the proposed model shows the best performance. It means that the proposed model shows positive impact on improving the PV power forecast performance.