• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.846-851
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• 2005

In this paper, we propose Genetic Algorithms(GAs)-based Optimized Polynomial Neural Networks(PNN). The proposed algorithm is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional neural networks and can be generated in a dynamic manner. As each node of PNN structure, we use several types of high-order polynomial such as linear, quadratic and modified quadratic, and it is connected as various kinds of multi-variable inputs. The conventional PNN depends on the experience of a designer that select the number of input variables, input variable and polynomial type. Therefore it is very difficult to organize optimized network. The proposed algorithm leads to identify and select the number of input variables, input variable and polynomial type by using Genetic Algorithms(GAs). The aggregate performance index with weighting factor is proposed as well. The study is illustrated with tile NOx omission process data of gas turbine power plant for application to nonlinear process. In the sequel the proposed model shows not only superb predictability but also high accuracy in comparison to the existing intelligent models.

• Journal of Navigation and Port Research
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• v.30 no.8 s.114
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• pp.649-655
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• 2006

Waves progressing into the coastal area can be amplified, swashed and overtopped by a wave overtopping control structure, and it converts the kinetic energy of the waves to the potential energy with a hydraulic head above the mean sea level by conserving the overflow in a reservoir. Then the potential energy in the form of hydraulic head can be converted to electric power utilizing extremely low-head hydraulic turbine. This study aims to find the most optimal shape of wave overtopping structure which maximizes overtopping volume rate of sea water. Laboratory experiments for the performance evaluation of wave overtopping control structures were carried out in three dimensional wave tank, and the three dimensional structure models with planar wave concentration shapes(B/b) were manufactured into five classes, which were optimized by cross sectional parameters of the structure, ie, length of ramp(l), gradient of inclined ramp($cot{\phi}$) and freeboard height of the wave overtopping structure($h_e$) proposed by Shin and Hong(2005). The wave overtopping discharges were investigated with 20 incident wave conditions and wave directions of $0^{\circ},\;15^{\circ},\;30^{\circ}$.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of the Korean Institute of Gas
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• v.25 no.6
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• pp.22-28
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• 2021

Combustion characteristics were examined experimentally for a swirl-stabilized double cone premixed burner nozzle used for industrial gas turbines for power generation. An original model and a variant with a different fuel injection pattern are tested to compare their combustion characteristics such as NOx, CO and stability in pressurized conditions with single burner-flame and in an ambient multi-flame conditions with multi-burners. Test results show that NOx emissions are smaller for the variant, whose number of fuel holes is reduced with the same total area of fuel holes, in ambient and pressurized single-flame conditions with single burner, which results from enhanced fuel/air mixing due to a higher penetration of fuel into the air stream. The multi-burnerflame test results show that NOx emissions are smaller for the variant due to reduced flame interactions, which, on the contrary, slightly reduces the stability margin. On-site test results fromin an actual power plants also show that NOx emissions are reduced for the variant, compared with the original one, which is in agreement with the lab test results stated above.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.963-969
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• 2021

The wind data measured from local meteorological masts is used to evaluate wind speed distribution and energy production in the specified site for wind farm However, wind data measured from meteorological masts often contain missing information or insufficient desired height or data length, making it difficult to perform wind turbine control and performance simulation. Therefore, long-term continuous wind data is very important to assess the annual energy production and the capacity factor for wind turbines or wind farms. In addition, if seasonal influences are distinct, such as on the Korean Peninsula, wind data with seasonal characteristics should be considered. This study presents methodologies for generating synthetic wind that take into account fluctuations in both wind speed and direction using the hidden Markov model, which is a statistical method. The wind data for statistical processing are measured at Maldo island in the Kokunnsan-gundo, Jeonbuk Province using the Automatic Weather System (AWS) of the Korea Meteorological Administration. The synthetic wind generated using the hidden Markov model will be validated by comparing statistical variables, wind energy density, seasonal mean speed, and prevailing wind direction with measurement data.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.12
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• pp.715-732
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• 2009

This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2008. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) Research trends in thermal and fluid engineering have been surveyed in the categories of general fluid flow, fluid machinery and piping, new and renewable energy, and fire. Well-developed CFD technologies were widely applied in developing facilities and their systems. New research topics include fire, fuel cell, and solar energy. Research was mainly focused on flow distribution and optimization in the fields of fluid machinery and piping. Topics related to the development of fans and compressors had been popular, but were no longer investigated widely. Research papers on micro heat exchangers using nanofluids and micro pumps were also not presented during this period. There were some studies on thermal reliability and performance in the fields of new and renewable energy. Numerical simulations of smoke ventilation and the spread of fire were the main topics in the field of fire. (2) Research works on heat transfer presented in 2008 have been reviewed in the categories of heat transfer characteristics, industrial heat exchangers, and ground heat exchangers. Research on heat transfer characteristics included thermal transport in cryogenic vessels, dish solar collectors, radiative thermal reflectors, variable conductance heat pipes, and flow condensation and evaporation of refrigerants. In the area of industrial heat exchangers, examined are research on micro-channel plate heat exchangers, liquid cooled cold plates, fin-tube heat exchangers, and frost behavior of heat exchanger fins. Measurements on ground thermal conductivity and on the thermal diffusion characteristics of ground heat exchangers were reported. (3) In the field of refrigeration, many studies were presented on simultaneous heating and cooling heat pump systems. Switching between various operation modes and optimizing the refrigerant charge were considered in this research. Studies of heat pump systems using unutilized energy sources such as sewage water and river water were reported. Evaporative cooling was studied both theoretically and experimentally as a potential alternative to the conventional methods. (4) Research papers on building facilities have been reviewed and divided into studies on heat and cold sources, air conditioning and air cleaning, ventilation, automatic control of heat sources with piping systems, and sound reduction in hydraulic turbine dynamo rooms. In particular, considered were efficient and effective uses of energy resulting in reduced environmental pollution and operating costs. (5) In the field of building environments, many studies focused on health and comfort. Ventilation. system performance was considered to be important in improving indoor air conditions. Due to high oil prices, various tests were planned to examine building energy consumption and to cut life cycle costs.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.143-150
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• 2012

A simulation methodology and corresponding program based on it is to be discussed for analyzing the effects of the networking operation of existing DHC system in connection with CHP system on-site. The practical simulation for arbitrary areas with various building compositions is carried out for the analysis of operational features in both systems, and the various aspects of thermal energy grids with connecting operation are highlighted through the detailed assessment of predicted results. The intrinsic operational features of CHP prime movers, gas engine, gas turbine etc., are effectively implemented by realizing the performance data, i.e. actual operation efficiency in the full and part loads range. For the sake of simplicity, a simple mathematical correlation model is proposed for simulating various aspects of change effectively on the existing DHC system side due to the connecting operation, instead of performing cycle simulations separately. The empirical correlations are developed using the hourly based annual operation data for a branch of the Korean District Heating Corporation (KDHC) and are implicit in relation between main operation parameters such as fuel consumption by use, heat and power production. In the simulation, a variety of system configurations are able to be considered according to any combination of the probable CHP prime-movers, absorption or turbo type cooling chillers of every kind and capacity. From the analysis of the thermal network operation simulations, it is found that the newly proposed methodology of mathematical correlation for modelling of the existing DHC system functions effectively in reflecting the operational variations due to thermal energy grids with connecting operation. The effects of intrinsic features of CHP prime-movers, e.g. the different ratio of heat and power production, various combinations of different types of chillers (i.e. absorption and turbo types) on the overall system operation are discussed in detail with the consideration of operation schemes and corresponding simulation algorithms.