• Journal of the Korean Solar Energy Society
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• v.29 no.5
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• pp.8-13
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• 2009

Feasibilities of the application of a micro gas turbine cogeneration system to a large size hospital building are studied by estimating energy demands and supplies. The energy demand for electricity is estimated by surveying and sorting the consumption records for various equipment and devices. The cooling heating, and hot water demands are further refined with TRNSYS and ESP-r to generate load profiles for the subsequent operation simulations. The operation of the suggested cogeneration system in conjunction with the load data is simulated for a time span of a year to predict energy consumption and gain profile. The simulation revealed that the thermal efficiency of the gas turbine is about 30% and it supplies 60% of the electricity required by the building. The recovered heat can meet 56% of total heating load and 67% of cooling, and the combined efficiency reaches up to 70%.

• Nuclear Engineering and Technology
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• v.45 no.6
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• pp.745-752
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• 2013

For thermo-fluid and safety analyses of a High Temperature Gas-cooled Reactor (HTGR), intensive efforts are in progress in the developments of the GAMMA+ code of Korea Atomic Energy Research Institute (KAERI) and the AGREE code of the University of Michigan (U of M). One of the important requirements for GAMMA+ and AGREE is an accurate modeling capability of a bypass flow in a prismatic core. Recently, a series of air experiments were performed at Seoul National University (SNU) in order to understand bypass flow behavior and generate an experimental database for the validation of computer codes. The main objective of the present work is to validate the GAMMA+ and AGREE codes using the experimental data published by SNU. The numerical results of the two codes were compared with the measured data. A good agreement was found between the calculations and the measurement. It was concluded that GAMMA+ and AGREE can reliably simulate the bypass flow behavior in a prismatic core.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.227-231
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• 2018

Indoor air pollution has become a serious issue, affecting the health and comfort of building occupants. Volatile organic compounds (VOCs) are among the most common indoor contaminants, and are released from numerous indoor emission sources. Among the VOCs, formaldehyde and toluene are toxic chemicals at low levels and are frequently detected indoors. Exposure to formaldehyde and toluene can irritate sensitive tissue and may increase the risk of cancer. Therefore, monitoring formaldehyde and toluene is critical for the health and comfort of residents. In addition, as human indoor activities can generate VOC gases, analysis of their influence on VOCs is needed. In this study, we compared electronic nose (E-Nose) data for formaldehyde and toluene with E-Nose data for indoor mixture gas with consideration for human indoor activities.

• The Journal of Korean Association of Computer Education
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• v.10 no.3
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• pp.1-8
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• 2007

In this paper, we introduce a new measure called surprisal that estimates the informativeness of transactional instances and attributes in the item response dataset and improve the quality of association rules. In order to this, we set artificial dataset and eliminate noisy and uninformative data using the surprisal first, and then generate association rules between items. And we compare the association rules from the dataset after surprisal-based pruning with support-based pruning and original dataset unpruned. Experimental result that the surprisal-based pruning improves quality of association rules in question item response datasets significantly.

• Journal of IKEEE
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• v.22 no.3
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• pp.672-679
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• 2018

Recently, microgrid (MG) has been proposed as one of the most critical solutions for various energy problems. For the optimal and economic operation of MGs, it is very important to forecast the load profile. However, it is not easy to predict the load accurately since the load in a MG is small and highly variable. In this paper, we propose an artificial neural network (ANN) based method to predict the energy use in campus buildings in short-term time series from one hour up to one week. The proposed method analyzes and extracts the features from the historical data of load and temperature to generate the prediction of future energy consumption in the building based on sparsified K-means. To evaluate the performance of the proposed approach, historical load data in hourly resolution collected from the campus buildings were used. The experimental results show that the proposed approach outperforms the conventional forecasting methods.

• Journal of The Korea Institute of Healthcare Architecture
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• v.11 no.3
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• pp.51-60
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• 2005

Because of the rapid increase of the number of elderly people, there are many problem in modern society. Especially the support of elderly people is becoming the hot issue, which results from a nuclear family and social activity of woman. The Policy of community care of the elderly people in western is caused by a heavy cost and isolation from the society of a facility care policy. Since 1980, Concept of 'home care for elderly people' has been appeared in korea. The Facility causing by these movement is 'Multipurpose senior center'. The purpose of this study is to present the alternative data to improve the quality of medical and rehabilitation part in multipurpose senior center. Data collecting skills such as drawing documents analysis, interviews, observation were used to examine the condition of medical and rehabilitation. And, case study method was used to generate the alternative medel which can be used for the spatial composition and the area calculation.

• Preventive Nutrition and Food Science
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• v.13 no.4
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• pp.348-353
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• 2008

Aerobic bacterial growth on Korean pan.fried meat patties as a primary quality deterioration factor was modeled as a function of temperature to estimate microbial spoilage on a real.time basis under dynamic storage conditions. Bacteria counts in the stretch.wrapped foods held at constant temperatures of 0, 5, 10 and $15^{\circ}C$ were measured throughout storage. The bootstrapping method was applied to generate many resampled data sets of mean microbial counts, which were then used to estimate the parameters of the microbial growth model of Baranyi & Roberts in the form of differential equations. The temperature functions of the primary model parameters were set up with confidence limits. Incorporating the temperature dependent parameters into the differential equations of bacterial growth could produce predictions closely representing the experimental data under constant and fluctuating temperature conditions.

• Geomechanics and Engineering
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• v.14 no.3
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• pp.257-269
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• 2018

Analysis of slope stability failures, as one of the complex natural hazards, is one of the important research issues in the field of civil engineering. Present paper adopts and investigates four soft computing-based techniques for this problem: Patient Rule-Induction Method (PRIM), M5' algorithm, Group Method of data Handling (GMDH) and Multivariate Adaptive Regression Splines (MARS). A comprehensive database consisting of 168 case histories is used to calibrate and test the developed models. Six predictive variables including slope height, slope angle, bulk density, cohesion, angle of internal friction, and pore water pressure ratio were considered to generate new models. The results of test studies are used for feasibility, effectiveness and practicality comparison of techniques with each other, and with the other available well-known methods in the literature. Results show that all methods not only are feasible but also result in better performance than previously developed soft computing based predictive models and tools. It is shown that M5' and PRIM algorithms are the most effective and practical prediction models.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.43-46
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• 2008

Quad-Rotor, which consists of four blades, performs a flight task by controling each rotation speed of the four blades. Quad-Rotor blade making no use of cyclic pitch or collective one is a type of fixed-wing as different from helicopter blade. Although, Quad-Rotor is simple and easy to control for those reasons, blade configuration of the fixed wing is one of the critical factors in determining the performance of Quad-Rotor. In the present study, coefficients for thrust and power of Quad-Rotor blade were derived from the data acquired by using 6-component balances. Firstly, Measurements for aerodynamic force were conducted at various pitch angles (i.e., from 0$^{\circ}$ to 90$^{\circ}$ with the interval of 10$^{\circ}$). The blade used in this experiment has aspect ratio of 6 and chord length of 35.5 mm. Secondly, assembled-blade, which was an integral blade but divided into many pieces, was used in order to test aerodynamic forces along twist angles. The curve of thrust coefficient along pitch angle indicates a parabola form. Stall which occurs during wind tunnel test to calculate lift coefficient of airfoil does not generate. When deciding the blade twist angle, structural stability of blade should be considered together with coefficients of thrust and power. Those aerodynamic force data based on experimental study will be provided as a firm basis for the design of brand-new Quad-Rotor blade.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.599-607
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• 2002

The octree model, a hierarchical volume description of 3D objects, nay be utilized to generate projected images from arbitrary viewing directions, thereby providing an efficient means of the data base for 3D object recognition and other applications. We present 2D projected image and made pseudo gray image of object using octree model and multi level boundary search algorithm. We present algorithm for finding feature points of 2D and 3D image and finding matched points using geometric transformation. The algorithm is made of data base, it will be widely applied to 3D object modeling and efficient feature points application for basic 3D object research.