• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.172-176
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• 2009

We developed a program, "CogenSim-$\mu$," to simulate the operation of micro-combined heat and power (${\mu}CHP$) system. The CogenSim-$\mu$ can reflect the variation of energy efficiency by handling the real-time loads (heat and power) fluctuation. The result obtained using this program was compared with the real operation of 30 kWe gas engine driven ${\mu}CHP$. It was found that the CogenSim-$\mu$ could predict the amount of generated-power, recovered-heat and consumed-fuel with the error less than 3%, and heat and power efficiency with the error less than 4%. The CogenSim-$\mu$ reconstructed the profile of on-off cycle, which represented the operation of a facility, with more than 93% accuracy. The CogenSim-$\mu$ can reflect the effects of various factors such as size of thermal storage tank, desired temperature of reservoir water, natural frequency of generator, etc. As a result, the CogenSim-$\mu$ can be used to optimize the ${\mu}CHP$ operation.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.08a
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• pp.126-133
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• 2004

Lots of researches and applications on the automated overhead cranes in shops have been done for some decades, but a few successful results are reported. Integrated crane control systems designed by famous engineering companies are still expensive and are not satisfactory in view of maintenance and reliability. A more reasonable control system fit to requirements of manufacturing industries is suggested in the study. The new deigned system has superior capabilities for anti-sway of rope and position control. The controller for automated operations is composed of a Linux-based PC for non real-time control and a high-speed PLC for hard real-time control. Some algorithms required for coil yard operations as well as main control algorithms such as reference position generation, position control and anti-sway control have been designed and fully tested on the new crane simulator. The designed crane control system showed satisfactory performance on position control accuracy and anti-sway of rope. The maximum positional error is 8mm and the maximum sway error is 0.1 degrees. The suggested control strategies have been successfully applied to the 10-1 crane in No. 4 CGL of in the Kwangyang Steel Works and in commercial operation.

• Laser Solutions
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• v.12 no.1
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• pp.19-24
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• 2009

Because of its fast and precise welding performance, laser welding is becoming a new excellent welding method. However, the precise focusing and robust seam tracking are required to apply laser welding to the practical fields. In order to laser weld a type of T joint like a circular pipe on a square pipe, which could be met in the three dimensional structure such as an aluminum space frame, a visual sensor system was developed for automation of focusing and seam tracking. The developed sensor system consists of a digital CCD camera, a structured laser, and a vision processor. It is moved and positioned by a 2-axis motorized stage, which is attached to a 6 axis robot manipulator with a laser welding head. After stripe-type structured laser illuminates a target surface, images are captured through the digital CCD camera. From the image, seam error and defocusing error are calculated using image processing algorithms which includes efficient techniques handling continuously changed image patterns. These errors are corrected by the stage off-line during welding or teaching. Laser welding of a circular pipe on a square pipe was successful with the vision tracking system by reducing the path positioning and de focusing errors due to the robot teaching or a geometrical variation of specimens and jig holding.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.10
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• pp.687-696
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• 2010

In this study, FDD algorithm was developed using the normalized distance method and general pattern classifier method that can be applied to constant air volume air handling unit(CAV AHU) system. The simulation model using TRNSYS and EES was developed in order to obtain characteristic data of CAV AHU system under the normal and the faulty operation. Sensitivity analysis of fault detection was carried out with respect to fault progress. When differential pressure of mixed air filter increased by more than about 105 pascal, FDD algorithm was able to detect the fault. The return air temperature is very important measurement parameter controlling cooling capacity. Therefore, it is important to detect measurement error of the return air temperature. Measurement error of the return air temperature sensor can be detected at below $1.2^{\circ}C$ by FDD algorithm. FDD algorithm developed in this study was found to indicate each failure modes accurately.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.513-520
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• 2002

The stability analysis of rock slope can be predicted using a suitable field data but it cannot be predicted unless suitable field data was taken. In this study, artificial neural networks theory is applied to predict plane failure that has a few data. It is well known that human brain has the advantage of handling disperse and parallel distributed data efficiently. On the basis of this fact, artificial neural networks theory was developed and has been applied to various fields of science successfully In this study, error back-propagation algorithm that is one of the teaching techniques of artificial neural networks is applied to predict plane failure. In order to verify the applicability of this model, a total of 30 field data results are used. These data are used for training the artificial neural network model and compared between the predicted and the measured. The simulation results show the potentiality of utilizing the neural networks for effective safety factor prediction of plane failure. In conclusion, the well-trained artificial neural network model could be applied to predict the plane failure stability of rock slope.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.715-718
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• 2016

SpaceWire invented for on-board data handling in a spacecraft has Time-Code defined for time synchronization over SpaceWire network. Delay and jitter of the transmission of Time-Code caused when a Time-Code travels through a network are the main reasons of time synchronization error. This work proposes a scheme that can reduce the time synchronization error by using extended Time-Codes. The proposed scheme can remove both transmission jitter and transmission delay. The scheme will be validated in a simulation environment built with OMNeT++.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.13-30
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• 2019

This paper presents the recent improvements in the DeCART code for HTGR analysis. A new 190-group DeCART cross-section library based on ENDF/B-VII.0 was generated using the KAERI library processing system for HTGR. Two methods for the eigen-mode adjoint flux calculation were implemented. An azimuthal angle discretization method based on the Gaussian quadrature was implemented to reduce the error from the azimuthal angle discretization. A two-level parallelization using MPI and OpenMP was adopted for massive parallel computations. A quadratic depletion solver was implemented to reduce the error involved in the Gd depletion. A module to generate equivalent group constants was implemented for the nodal codes. The capabilities of the DeCART code were improved for geometry handling including an approximate treatment of a cylindrical outer boundary, an explicit border model, the R-G-B checker-board model, and a super-cell model for a hexagonal geometry. The newly improved and implemented functionalities were verified against various numerical benchmarks such as OECD/MHTGR-350 benchmark phase III problems, two-dimensional high temperature gas cooled reactor benchmark problems derived from the MHTGR-350 reference design, and numerical benchmark problems based on the compact nuclear power source experiment by comparing the DeCART solutions with the Monte-Carlo reference solutions obtained using the McCARD code.

• Advances in materials Research
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• v.11 no.1
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• pp.75-90
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• 2022

In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.1
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• pp.37-41
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• 2022

Because sulfur hexafluoride(SF₆) is classified as one of the six major greenhouse gases, SF₆ handling in power plant such as recovery, purification, and reuse is considered to be important. KEPCO has focused to develop the advanced recovery and purification technology of SF₆ reuse. SF₆ analysis includes the on-site analyses and on-line analyzer; i.e., (1) on-site analysis has an error rate of ±0.5% and (2) on-line analysis has an error rate of ±0.1%, which is possible to adjust operating conditions and to make the work more conveniently by analyzing SF₆ concentration before and after purification step. This paper presents an online analysis method in the SF₆ purification and reuse system. In addition, the analysis results and quality guarantees for each section of the analysis system were presented.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.72-81
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• 2023

We introduce tightly-coupled GNSS-LiDAR-Inertial state estimator, which is capable of SLAM (Simultaneously Localization and Mapping) and autonomous driving. Long term drift is one of the main sources of estimation error, and some LiDAR SLAM framework utilize loop closure to overcome this error. However, when loop closing event happens, one's current state could change abruptly and pose some safety issues on drivers. Directly utilizing GNSS (Global Navigation Satellite System) positioning information could help alleviating this problem, but accurate information is not always available and inaccurate vertical positioning issues still exist. We thus propose our method which tightly couples raw GNSS measurements into LiDAR-Inertial SLAM framework which can handle satellite positioning information regardless of its uncertainty. Also, with NLOS (Non-light-of-sight) satellite signal handling, we can estimate our states more smoothly and accurately. With several autonomous driving tests on AGV (Autonomous Ground Vehicle), we verified that our method can be applied to real-world problem.