• Transactions of the Korean Society of Mechanical Engineers
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• v.8 no.1
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• pp.1-9
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• 1984

In the utilization of solar energy most often a flat solar collector is used for solar heating, system. Since solar energy is absorbed through this solar collector, it is considered to be a most important part in the whole solar heating system. The purpose of the present investigation is to evaluate the influence of varying design parameters for thermal performances of flat-plate solar collector. By analysing these parameters, optimum design of solar collector would become possible. Specification of the existing solar collector are utilized in calculation as a starting point. Analysis is carried out numerically for "Unit Solar Collector" which is composed of fin and tube. Among design parameters. such parameters as mass flow rate per unit area, tube spacing and fin thickness are selected as variables in the computer simulation model. Results are presented for thermal performances of flat-plate solar collector for each important design parameters, so that predictions become possible through numerical analysis without performing experiments whenever it is required. required.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05a
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• pp.57-61
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• 1997

A Canadian Deuterium Uranium (CANDU) reactor core calculation was performed using lattice parameters generated by HELIOS. The HELIOS-based lattice parameters were processed by TABGEN in a form suitable for the core analysis code RFSP. The core calculation was performed and the results were compared to those of the reference calculation which uses POWDERPUFS-V (PPV) for the lattice parameter generation. The characteristics of the core calculated based on the PPV and HELIOS lattice parameters match within 0.4%$\Delta$k and 7% for the excess reactivity and the channel power distribution, respectively.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2463-2466
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• 2003

This paper studied the pattern recognition algorithm and feature parameters for emotion recognition. In this paper, KNN algorithm was used as the pattern matching technique for comparison, and also VQ and GMM were used lot speaker and context independent recognition. The speech parameters used as the feature are pitch, energy, MFCC and their first and second derivatives. Experimental results showed that emotion recognizer using MFCC and their derivatives as a feature showed better performance than that using the Pitch and energy Parameters. For pattern recognition algorithm, GMM based emotion recognizer was superior to KNN and VQ based recognizer

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.955-964
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• 2011

In renewable energy system such as flywheel energy storage system, wind power and solar power, the motor/generator is the important key for offering the electric energy to the electric loads. For example, the heavy and large flywheel is rotated by electromagnetic torque of pemanent magnet synchronous motor (PMSM) and, in case of a breakdown of electric current, the PMSM used as generator supplies electric energy for the various electric utilities using mechanical rotation energy of the flywheel. Thus, design of a motor/generator should be performed in effort to reduce cogging torque and electromagnetic loss for high efficiency. In our paper, a slotless permanent magnet synchronous motor/generator (SPMSM/G) with output power 15kW at the rotor speed 18000rpm is designed from electromagnetic analysis and dynamic performance analysis. In analytical approach, design parameters such as back electro-motive force (back EMF), inductance and electromagnetic torque are derived from analytical method which is one of the electromagnetic analysis method. And using the design parameters, this paper deal with system design considering the driving characteristics and electric load in required power. Finally, the analytical results are verified by the experiment and finite element method (FEM).

• Geomechanics and Engineering
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• v.22 no.6
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• pp.489-496
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• 2020

This study proposes a new empirical model to effectively predict the excavation performance of a shield tunnel boring machine (TBM). The TBM performance is affected by the geological and geotechnical characteristics as well as the machine parameters of TBM. Field penetration index (FPI) is correlated with rock mass parameters to analyze the effective geotechnical parameters influencing the TBM performance. The result shows that RMR has a more dominant impact on the TBM performance than UCS and RQD. RMR also shows a significant relationship with the specific energy, which is defined as the energy required for excavating the unit volume of rock. Therefore, the specific energy can be used as an indicator of the mechanical efficiency of TBM. Based on these relationships with RMR, this study suggests an empirical performance prediction model to predict FPI, which can be derived from the correlation between the specific energy and RMR.

• Journal of Computational Design and Engineering
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• v.1 no.4
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• pp.256-265
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• 2014

Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using non-dominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2017.05a
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• pp.37-38
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• 2017

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.254-259
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• 1995

Large scale display panel(LSDP) is a main component in the next generation main control rooms. LSDP is located at the front of VDU-based operator's workstation and plays an important role in providing operators with overall information of plant status through mimic diagram, text/digit, graph, and so on. A critical matter determined at the first stage of LSDP design is how much information is displayed, because the information density of LSDP affects operator's performance. Many human factors guidelines recommend low information density of displays to avoid degrade of operator's performance, but doesn't provide a useful limit of information density. In this paper, we considered information density as the number of plant parameters and investigated the proper number of plant parameters through a human factors experiment. The experiment with 4 subjects was carried out and response time, error, and heart rate variation as criterion measures were recorded and analyzed. As the results, it is identified that the proper number of parameters in a LSDP is about thirty.

• Carbon letters
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• v.28
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• pp.72-80
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• 2018

In this study, an empirical relationship between the energy band gap of multi-walled carbon nanotubes (MWCNTs) and synthesis parameters in a chemical vapor deposition (CVD) reactor using factorial design of experiment was established. A bimetallic (Fe-Ni) catalyst supported on $CaCO_3$ was synthesized via wet impregnation technique and used for MWCNT growth. The effects of synthesis parameters such as temperature, time, acetylene flow rate, and argon carrier gas flow rate on the MWCNTs energy gap, yield, and aspect ratio were investigated. The as-prepared supported bimetallic catalyst and the MWCNTs were characterized for their morphologies, microstructures, elemental composition, thermal profiles and surface areas by high-resolution scanning electron microscope, high resolution transmission electron microscope, energy dispersive X-ray spectroscopy, thermal gravimetry analysis and Brunauer-Emmett-Teller. A regression model was developed to establish the relationship between band gap energy, MWCNTs yield and aspect ratio. The results revealed that the optimum conditions to obtain high yield and quality MWCNTs of 159.9% were: temperature ($700^{\circ}C$), time (55 min), argon flow rate ($230.37mL\;min^{-1}$) and acetylene flow rate ($150mL\;min^{-1}$) respectively. The developed regression models demonstrated that the estimated values for the three response variables; energy gap, yield and aspect ratio, were 0.246 eV, 557.64 and 0.82. The regression models showed that the energy band gap, yield, and aspect ratio of the MWCNTs were largely influenced by the synthesis parameters and can be controlled in a CVD reactor.

• Transactions of the Korean hydrogen and new energy society
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• v.27 no.1
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• pp.1-12
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• 2016

In this study, CFD model for a Heat Exchange Steam Reformer (HESR) used for a 10kW SOFC system is developed for the design optimization of the HESR. The model is used to explore the effect of design parameters on the performance of the HESR. In the HESR, heat is delivered from the hot gas channel to the fuel channel to supply the heat required for the fuel reforming. In the fuel channel where the fuel is reformed, thermo-fluid dynamics, heat transfer, and chemical reaction are considered to predict the performance of the reformer. The model is validated with experimental data within 2~3% error. The validated model is used for the parametric study of the HESR design. Channel length, channel diameter, and flow direction are selected as the design parameters. The effects of the HESR design parameters on the outlet temperature, outlet H2 mole fraction, and pressure drop across the reformer are presented using the model.