• 한국지열·수열에너지학회논문집
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• 제14권3호
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• pp.15-20
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• 2018

To study the effects of solar energy in a greenhouse, outdoor air temperature and wind speed on inside air temperature, a simulation model for forecasting the greenhouse air temperature was conducted on the basis of the energy and mass balance theory. Application of solar energy to the greenhouse is major area in the renewable energy research and development in order to save energy. Recently, considering the safety and efficiency of the heating of greenhouse, clean energy such as geothermal and solar energy has received much attention. The analysed greenhouse has $50m^2$ of ground area which located in jocheon-ri of Jeju Province. Experiments were carried out to collect data to validate the model. The results showed that the simulated air temperature inside a plastic greenhouse agreed well with the measured data.

• 신재생에너지
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• 제5권3호
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• pp.40-48
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• 2009

Recovered heat has been considered as a renewable energy in Europe since 2008 because its great effect on energy saving and carbon decreasing in plant process. Energy saving and decreasing green gas are critical issue today, so various technologies to save energy and decrease carbon dioxide in plant process have been applied to many industrial area. In this paper, the feasibility of condenser heat recovery by heat pump in power plant for district heating and fuel line preheating were reviewed by verifying energy (heat) balance and mass balance of power plant model. Some ways to compose proper system to recover heat of condenser are suggested and their possibilities are also reviewed. Limitations on heat recovery in power plant are also reviewed. The results are verified by calculating input/output energy based on actual performance test data of Taean Thermal Power Plant in Korea. There is noticeable improvement of plant performance in some cases which demand low temperature (<100 C) heat like distrcit heating, fuel line heating, and so forth.

• 한국인공지능학회지
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• 제12권1호
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• 한국농공학회지
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• 제32권E호
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• pp.88-94
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• 1990

Several models physically based to predict the evolution of the snowpack have been proposed. Validity of these models for hourly estimation is, however, questionable, since they have been tested only on a daily basis. A computational model to predict the amount of snowpack on an hourly basis in terms of snowload from a set of meterological measurements was developed and investigated the rapid snowmelt conditions during Fohn events in the Takada plain.

• Structural Engineering and Mechanics
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• 제63권2호
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• pp.207-215
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• 2017

The paper presents the studies carried out on low velocity impact of Ultra high performance concrete (UHPC) panels of size $350{\times}350{\times}10mm^3$ and $350{\times}350{\times}15mm^3$. The panels are cast with 2 and 2.5% micro steel fibre and compared with UHPC without fiber. The panels are subjected to low velocity impact, by a drop-weight hemispherical impactor, at three different energy levels of 10, 15 and 20 J. The impact force obtained from the experiments are compared with numerically obtained results using finite element method, theoretically by energy balance approach and empirically by nonlinear multi-genetic programming. The predictions by these models are found to be in good coherence with the experimental results.

• 대한기계학회논문집
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• 제13권5호
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• pp.999-1011
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• 1989

본 연구의 목적은 첫째, 재발달 경계층에서의 난류에서지 및 난류전단응력에 대한 전달방정식들의 각 항의 측정자료들을 보다 정확히 제시하고 항들간의 균형을 비교 평가함으로써 비평형 유동으로부터 평형유동으로 회복되는 과정을 검토하고, 둘째, 대표적인 난류 모델들로써 표존 k-.epsilon.모델 및 레이놀즈 응력 모델을 사용한 수치계산을 수행함으로써 이와같은 모델들이 비평형 유동을 서술함에 있어 발생될 수 있는 문제점들을 고찰하는데 있다.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1995년도 봄 학술발표회 논문집
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• pp.237-244
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• 1995

Fracture properties for LEFM, S-FPZ and NS-FPZ models were determined using by finite element method and energy balance from the experimental results of three-point bend tests. For the LEFM model the stress intensity factor needed to increase continuously with crack extension, and for the S-FPZ model the fracture process zone characteristics need to change continuously if the critical stress intensity factor was to remain constant. The LEFM model showed the largest resistance and the slowest crack extension, while the NS-FPZ model showed the smallest resistance and the fastest crack extension. The responses for the S-FPZ model were intermediate between those for the LEFM and NS-FPZ models and the total fracture energy densities for the S-FPZ and NS-FPZ models and the total fracture energy densities for the S-FPZ and NS-FPZ models were equal.

• Nuclear Engineering and Technology
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• 제56권2호
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• pp.624-635
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• 2024

In two-fluid simulations of flow boiling, the modeling of the mean bubble diameter is a key parameter in the closure relations governing the intefacial transfer of mass, momentum, and energy. Monodispersed approach proved to be insufficient to describe the significant variation in bubble size during flow boiling in a heated pipe. A population balance model (PBM) has been employed to address these shortcomings. During nucleate boiling, vapor bubbles of a certain size are formed on the heated wall, detach and migrate into the bulk flow. These bubbles then grow, shrink or disintegrate by evaporation, condensation, breakage and aggregation. In this study, a parametric analysis of the PBM aggregation and breakage models has been performed to investigate their effect on the radial distribution of the mean bubble diameter and vapor volume fraction. The simulation results are compared with the DEBORA experiments (Garnier et al., 2001). In addition, the influence of PBM parameters on the local distribution of individual bubble size groups was also studied. The results have shown that the modeling of aggregation process has the largest influence on the results and is mainly dictated by the collisions due to flow turbulence.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.275-278
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• 2017

차량의 교류발전기는 성능 및 효율에 따라 자동차의 연비와 배기가스에 많은 영향을 준다. 효율을 개선시키고 연비를 향상시키려는 노력은 자동차업체및 업체를 중심으로 계속되고 있다. 본논문은 A교류 발전기의 설계절차를 정리하고 같은 크기의 교류발전기에서 출력을 최적화하는 인자를 발굴하여 실차의 조건에서 충방전 Simulation을 통해 Energy Balance를 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3621-3640
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• 2016

In the process of k-coverage of the target node, there will be a lot of data redundancy forcing the phenomenon of congestion which reduces network communication capability and coverage, and accelerates network energy consumption. Therefore, this paper proposes a novel energy balanced k-coverage control algorithm based on probability model (EBKCCA). The algorithm constructs the coverage network model by using the positional relationship between the nodes. By analyzing the network model, the coverage expected value of nodes and the minimum number of nodes in the monitoring area are given. In terms of energy consumption, this paper gives the proportion of energy conversion functions between working nodes and neighboring nodes. By using the function proportional to schedule low energy nodes, we achieve the energy balance of the whole network and optimizing network resources. The last simulation experiments indicate that this algorithm can not only improve the quality of network coverage, but also completely inhibit the rapid energy consumption of node, and extend the network lifetime.