• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.14 no.3
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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.

• New & Renewable Energy
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• v.5 no.3
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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.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.E
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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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• v.63 no.2
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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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.5
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• pp.999-1011
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• 1989

A consideration on the trubulence models for describing the redeveloping turbulent boundary layer beyond separation-reattachment in the flow over a backward-facing step is given through experimental and numerical studies. By considering the blance among the measured values of respective terms in the transport equations for the turbulent kinetic energy and the turbulent shear stress, the recovering process of the redeveloping boundary layer from non-equilibrium to equilibrium has been investigated, which takes place slowly over a substantial distance in the downstream direction. In the numerical study, the standard K-.epsilon. model and the Reynolds stress model have been applied to two kinds of flow regions, one for the entire downstream region after the backward-facing step and another for the downstream region after reattachment. Then the results are compared to a meaningful extent, with the experimental values of the turbulent kinetic energy k, the turbulent energy production term P, the dissipation term K-.epsilon. model, a necessity for a new modelling has been brought forward, which can be also applied to the case of the nonequlibrium turbulent flow.

• Proceedings of the Korea Concrete Institute Conference
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• 1995.04a
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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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• v.56 no.2
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.275-278
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• 2017

The automotive society is facing many challenges in minimizing the energy loss to improve performance and fuel economy of the vehicle. This work "Implement of Power Density for AC Generator Using a Fill Factor of Slot" is a research in Electrical Generator design, to improve power density of Alternator used in conventional IC engine powered vehicles. The power density of the alternator directly influences the fuel economy and performance in the motor vehicle. The size and weight of the alternator can be reduced by suitably designing power density of alternator. The simulation model of alternator is made and tested for different stator space factor using solid and round conductor to demonstrate the improvement in the output performance and efficiency. The result shows that there is an average 10% improvement in efficiency of alternator by using the solid conductor. The energy balance of the system also increased SOC in the base model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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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.