• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2006.05a
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• pp.136-140
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• 2006

We are developing a vol-oxidizer which transforms the spent $UO_2$ pellets into the $U_3O_8$ power through oxidizing process. The vol-oxidizer consists of furnace, filter, heater and valve etc. When the filter is blocked by the powder, the internal pressure of the furnace is increased owing to the air flow restriction. Then, the furnace vessel is swelled and deformed by it. In this paper, we proposed a procedure of the thermal analysis for furnace vessel design of spent fuel vol-oxidizer. In this work, we determined the thickness of the furnace through analyzing the internal pressure and the thermal stress of the furnace with respect to various pressure and temperature. To analyze the thermal stress, we used ANSYS 8.0 for constructing a FEM model of the furnace, and then analyzed it based on the ASME code. We also surveyed the material property and yield stress of SUS304 with various temperature. Analysis results are compared with the yield stress of the material. We manufactured the furnace and conduct the verification experiments.

• 한국전산유체공학회:학술대회논문집
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• 2003.08a
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• pp.212-218
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• 2003

In order to analyze the heat transfer phenomena in the plasma flames, a mathematical model describing heat and fluid flow in an electric arc has been developed and used to predict heat transfer from the arc to the steel bath in a DC Electric Arc Furnace. The arc model takes the separate contributions to the heat transfer from each involved mechanism into account, i.e. radiation, convection and energy transported by electrons. The finite volume method and a SIMPLE algorithm are used for solving the governing MHD equations, i.e., conservation equations of mass, momentum, and energy together with the equations describing a $\kappa-\epsilon$ model for turbulence. The model predicts heat transfer for different currents and arc lengths. Finally these calculation results can be used as a useful insight into plasma phenomena of the industrial-scale electric arc furnace. From these results, it can be concluded that higher arc current and longer arc length give high heat transfer.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.182-187
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• 2007

A fuzzy modeling method is proposed to build the dynamic model of a walking-beam reheating furnace from the recorded data. In the proposed method, the number of membership function on each variable is increased individually and the modeling accuracy is evaluated iteratively. When the modeling accuracy is satisfied, the membership functions on each variable are fixed and the structure of fuzzy model is determined. Because the training data is limited, in this process, as the number of membership function increase, it is highly possible that some rules are missing, i.e., no data in the training set corresponds to the consequent part of a missing rule. To complete the rulebase, the output of the model constructed at the previous step is used to generate the consequent part of the missing rules. Finally, in the real time application, a rolling update scheme to rulebase is introduced to compensate the change of system dynamics and fine tune the rulebase. The proposed method is verified by the application to the modeling of a reheating furnace.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.448-453
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• 2008

This study describes design and development techniques of estimation models for process modeling. One case study is undertaken to design a model using standard gas furnace data. Neural networks (NN) and genetic programming (GP) are each employed to model the crucial relationships between input factors and output responses. In the case study, two models were generated by using 70% training data and evaluated by using 30% testing data for genetic programming and neural network modeling. The model performance was compared by using RMSE values, which were calculated based on the model outputs. The average RMSE for training and testing were 0.8925 (training) and 0.9951 (testing) for the NN model, and 0.707227 (training) and 0.673150 (testing) for the GP model, respectively. As concern the results, the NN model has a strong advantage in model training (using the all data for training), and the GP model appears to have an advantage in model testing (using the separated data for training and testing). The performance reproducibility of the GP model is good, so this approach appears suitable for modeling physical fabrication processes.

• Computers and Concrete
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• v.18 no.5
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• pp.937-950
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• 2016

This study applied autoclave expansion and heat curing to accelerate the hydration of concrete and investigated how these methods affect the expansion rate, crack pattern, aggregate size effect, and expansion of electric arc furnace oxidizing slag (EOS)-containing concrete. An expansion prediction model was simulated to estimate the expansion behavior over a long period and to establish usage guidelines for EOS aggregates. The results showed that the EOS content in concrete should range between 20% and 30% depending on the construction conditions, and that coarse aggregates with a diameter of ${\geq}4.75-mm$ are not applicable to construction engineering. By comparison, aggregates with a size of 1.18-0.03 mm resulted in higher expansion rates; these aggregates can be used depending on the construction conditions. On Day 21, the prediction model attained a coefficient of determination ($R^2$) of at least 0.9.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.8
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• pp.1251-1257
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• 2004

In order to analyze the heat transfer phenomena in the plasma flames, a mathematical model describing heat and fluid flow in an electric arc has been developed and used to predict heat transfer from the arc to the steel bath in a DC Electric Arc Furnace. The arc model takes the separate contributions to the heat transfer from each involved mechanism onto account, that is radiation, convection and energy transported by electrons. The finite volume method and a SIMPLE algorithm are used for solving the governing MHD equations, that are conservation equations of mass, momentum and energy together with the equations describing a standard k-${\varepsilon}$ model for turbulence. The model predicts heat transfer for different currents and arc lengths. Finally these calculation results can be used as a useful insight into plasma phenomena of the industrial-scale electric arc furnace. From these results, it can be concluded that higher arc current and longer arc length give high heat transfer

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.05a
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• pp.89-90
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• 2013

This study is to predict the compressive strength for the concrete of ground granulated blast-furnace slag, and use Plowman's, Gompertz's model. The results are as follows; The prediction compressive strength were simiar using Rastrup's equivalent age model. but The prediction compressive strength using Freiesleben's equivalent age model weren't simiar in bfs replacement Ratio of 50%, because it is analyzed as the activation energy.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.1
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• pp.113-120
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• 2016

Steel in a continuous reheat furnace is heated to higher temperature to be treated in the rolling steel process. Due to this reason the continuous reheat furnace system requires an optimal control system to adjust the temperature inside the furnace. Level 2 control systems for continuous reheat furnaces generate automatic heating set points for the level 1 system of the furnace based on the mathematical thermal model which can give a good estimation of steel heating inside the furnace and is used to adjust heating requirements to optimize furnace combustion. For the current study the analytic methodology based on the design procedure from the systems engineering to develop new level 2 control system of a continuous reheat furnace was proposed. The system analysis and the requirements of the level 2 control system were derived using the unified modeling language (UML) 2.0, and the design of database and the graphic user interface (GUI) for the level 2 control system were conducted.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1830-1835
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• 2003

A novel index representing burden distribution form in the blast furnace is developed and index estimation model is built with an empirical modeling method to monitor inner condition of the furnace without expensive sensors. To find the best combination of index and modeling method, two candidates for the index and four modeling methods have been examined. Results have shown that 3-D index have more resolution in describing the distribution form than 1-D index and ANN model produces smallest RMSE due to nonlinearity between the indices and charging mode. Although ANN has shown the best prediction accuracy in this study, PLS can be a good alternative due to its advantages in generalization capability, consistency, simplicity and training time. The second best result of PLS in the prediction results supports this fact.

• Journal of the Korean Society of Combustion
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• v.11 no.1
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• pp.34-42
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• 2006

Numerical analysis code has been developed to investigate the slab heating characteristics in a reheating furnace of a steel mill company. Unsteady 3-Dimensional behaviour can be predicted with the developed code. Premixed flame model is adopted for combustion phenomena and eddy dissipation model is used for turbulent combustion. Non -gray FVM radiation method is used to get a better accurate radiative solution. Slab movement can be fully traced from entrance into a reheating furnace until it#s exit and computation is performed during that period.