• 환경영향평가
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• 제14권4호
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• pp.157-164
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• 2005

Existing models that predict of Daily water supply include statistical models and neural network model. The neural network model was more effective than the statistical models. Only neural network model, which predict of Daily water supply, is focused on estimation of the operational control. Neural network model takes long learning time and gets into local minimum. This study proposes Neuro Genetic hybrid model which a combination of genetic algorithm and neural network. Hybrid model makes up for neural network's shortcomings. In this study, the amount of supply, the mean temperature and the population of the area supplied with water are use for neural network's learning patterns for prediction. RMSE(Root Mean Square Error) is used for a MOE(Measure Of Effectiveness). The comparison of the two models showed that the predicting capability of Hybrid model is more effective than that of neural network model. The proposed hybrid model is able to predict of Daily water, thus it can apply real time estimation of operational control of water works and water drain pipes. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 11.81% and the average error was lower than 1.76%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Nuclear Engineering and Technology
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• 제55권3호
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• pp.1140-1151
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• 2023

Fully Ceramic Microencapsulated (FCM) fuel is emerging advanced fuel material for the future nuclear reactors. The fuel pellet in the FCM fuel is composed of matrix and a large number of TRistructural-ISOtopic (TRISO) fuel particles which are randomly dispersed in the SiC matrix. The minimum layer thickness in a TRISO fuel particle is on the order of 10^-5 m, and the length of the FCM pellet is on the order of 10^-2 m. Hence, the heat transfer in the FCM pellet is a multi-scale phenomenon. In this study, three multi-scale heat conduction models including the Multi-region Layered (ML) model, Multi-region Non-layered (MN) model and Homogeneous model for FCM pellet were constructed. In the ML model, the random distributed TRISO fuel particles and coating layers are completely built. While the TRISO fuel particles with coating layers are homogenized in the MN model and the whole fuel pellet is taken as the homogenous material in the Homogeneous model. Taking the results by the ML model as the benchmark, the abilities of the MN model and Homogenous model to predict the maximum and average temperature were discussed. It was found that the MN model and the Homogenous model greatly underestimate the temperature of TRISO fuel particles. The reason is mainly that the conventional equivalent thermal conductivity (ETC) models do not take the internal heat source into account and are not suitable for the TRISO fuel particle. Then the improved ETCs considering internal heat source were derived. With the improved ETCs, the MN model is able to capture the peak temperature as well as the average temperature at a wide range of the linear powers (165 W/cm~ 415 W/cm) and the packing fractions (20%-50%). With the improved ETCs, the Homogenous model is better to predict the average temperature at different linear powers and packing fractions, and able to predict the peak temperature at high packing fractions (45%-50%).

• 한국정밀공학회지
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• 제14권4호
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• pp.38-45
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• 1997

A new dynamic model for the cutting process inb the end milling process is developed. This model, which describes the dynamic response of the end mill, the chip load geometry including tool runout, the dependence of the cutting forces on the chip load, is used to predict the dynamic cutting force during the end milling process. In order to predict accurately cutting forces and tool vibration, the model which uses instantaneous specific cutting force, inclueds both regenerative effect and penetration effect, The model is verified through comparisons of model predicted cutting force with measured cutting force obtained from machining experiments.

• Nuclear Engineering and Technology
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• 제31권2호
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• pp.236-255
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• 1999

An improved mechanistic model was developed to predict a convective boiling critical heat flux (CHF) in the vertical round tubes with uniform heat fluxes. The CHF formula for subcooled and low quality boiling was derived from the local conservation equations of mass, energy and momentum, together with appropriate constitutive relations. The model is characterized by the momentum balance equation to determine the limiting transverse interchange of mass flux crossing the interface of wall bubbly layer and core by taking account of the convective shear effect due to the frictional drag on the wall-attached bubbles. Comparison between the present model predictions and experimental CHF data from several sources shows good agreement over a wide range of How conditions. The present model shows comparable prediction accuracy with the CHF look-up table of Groeneveld et al. Also the model correctly accounts for the effects of flow variables as well as geometry parameters.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2005년도 추계 학술발표회 제17권2호
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• pp.591-594
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• 2005

Concrete structure that has been constructed in real field is on multi-axial stress state condition. After placing of concrete, hydration heat and shrinkage of concrete can cause various stress conditions with respect to the restraint level and condition. So, to predict the early age behavior of concrete structure, multi-axial material model is required and microplane model is acceptable. Recently, many studies have been performed on the microplane model, but the model developed up to now has been related to hardened concrete that material property is constant with concrete age. So, it is inappropriate to apply this model immediately to analyze the early age behavior of concrete. In this study, microplane model that can predict early age behavior of concrete was developed and cracking analysis using that was performed to describe cracking behavior for massive concrete sturucture.

• 설비공학논문집
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• 제12권7호
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• pp.632-641
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• 2000

The present study concerns the simulation of supply-air control in a variable air volume (VAV) system. A stratified lumped thermal model (multi-zone model) is suggested to predict local thermal response of an air-conditioned space. The effects of various thermal parameters such as the cooling system capacity, the thermal mass of air-conditioned space, the time delay of thermal effect, and the building envelope heat transmission are investigated in detail. Further, the influence of control parameters, PI control factor and the sensor location on a VAV system is quantitatively delineated. The results obtained show that the previous homogeneous lumped thermal model (1-zone model) may predict a significantly different thermal response in the air-conditioned space according to the sensor location.

• Structural Engineering and Mechanics
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• 제77권5호
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• pp.651-659
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• 2021

In this study, a new constitutive model has been developed to predict the elastic behavior of plain weave textile composites, using the finite element (FE) method. The geometric conditions and basic assumptions of this model are based on the basics of a continuum theory developed for the plane curved composites. In this model, the mechanical properties of the weave region and pure matrix region is calculated separately and then imported for the FE analysis. This new constitutive model is used to implement the mechanical properties of weave region in the representative volume element (RVE). The constitutive relations are implemented as user-material subroutine code (UMAT) in ABAQUS® FE software. The results of FE analysis have been compared with experimental results and other data available in the literature. These comparisons confirmed the capability of the presented model for the prediction of effective elastic properties of plain weave fabric composites.

• 스마트미디어저널
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• 제12권5호
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• pp.9-16
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• 2023

In the recommendation system of the credit card company, it is necessary to understand the customer patterns to predict a customer's next merchant based on their histories. The data we want to model is much more complex and there are various patterns that customers choose. In such a situation, it is necessary to use an effective model that not only shows the relevance of the merchants, but also the relevance of the customers relative to these merchants. The proposed model aims to predict the next merchant for the customer. To improve prediction performance, we propose a novel model, called Customer-based Recommendation Model (CRM), to produce a more efficient representation of customers. For the next merchant recommendation system, we use a synthetic credit card usage dataset, BC'17. To demonstrate the applicability of the proposed model, we also apply it to the next item recommendation with another real-world transaction dataset, IJCAI'16.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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• pp.448-455
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• 2005

In this paper, an analytical model for estimation of the time at which the concrete surface begins to dry is introduced to predict whether or not plastic shrinkage cracks occur. First of all, the validity of a consolidation model for bleeding of cement paste proposed by Tan et al. is verified by comparing the analytical results with the experimental results, and used to evaluate the rate and amount of bleed water of concrete. Also an analytical model for evaporation of bleed water which considers the effect of the temperature variation of concrete surface due to hydration heat on the evaporation rate is proposed, and the experimental and analytical results are then compared to verify the validity of the introduced model. In advance, the time at which the concrete surface begins to dry is estimated using above two analytical models, and compared with the experimental results about the time at which plastic shrinkage cracks occur. From the comparison, it is verified that the proposed model can predict the occurrence of plastic shrinkage cracking with comparative precision.

• Journal of Radiation Protection and Research
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• 제28권3호
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• pp.239-245
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• 2003

Every nuclear power plant measured concentrations of tritium in groundwater and surface water around the plants periodically. It was not easy to predict the tritium concentration only with these measurement data in case of various release scenarios. KAERI developed a new approach to find the relationship between the tritium release rate and tritium concentration in the environment. The approach was based upon a dynamic compartment model. In this paper the dynamic compartment model was modified to predict the tritium behavior more accurately. The mechanisms considered for the transfer of tritium between the compartments were evaporation, groundwater flow, infiltration, runoff, and hydrodynamic dispersion. Time dependent source terms of the compartment model were introduced to refine the release scenarios. Also, transfer coefficients between the compartments were obtained using realistic geographical data. In order to illustrate the model various release scenarios were developed, and the change of tritium concentration in groundwater and surface water around the nuclear power plants was estimated.