• Nuclear Engineering and Technology
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• v.28 no.1
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• pp.17-26
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• 1996

The in-reactor fuel rod support conditions against the fretting wear-induced damage can be evaluated by residual spacer grid spring deflection or rod-to-grid gap. In order to evaluate the impact of fuel design parameters on the fretting wear-induced damage, a simulation methodology of the in-reactor fuel rod supporting conditions as a function of burnup has been developed and implemented in the GRIDFORCE program. The simulation methodology takes into account cladding creep rate, initial spring deflection, initial spring force, and spring force relaxation rate as the key fuel design parameters affecting the in-reactor fuel rod supporting conditions. Based on the parametric studies on these key parameters, it is found that the initial spring deflection, the spring force relaxation rate and cladding creepdown rate are in the order of the impact on the in-reactor fuel rod supporting conditions. Application of this simulation methodology to the fretting wear-induced failure experienced in a commercial plant indicates that this methodology can be utilized as an effective tool in evaluating the capability of newly developed cladding materials and/or new spacer grid designs against the fretting wear-induced damage.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1183-1192
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• 2020

Economic analysis is a basic step in establishing disaster mitigation measures, but it is difficult to verify the results due to uncertainty. Therefore, the scope of investigation and analysis is wide. However, it is difficult to predict the amount of damage caused by flooding because the collection of relevant data is limited in the ungauged basin. In this study, distributed runoff analysis and flooding analysis were performed, and a method of estimating the amount of flood damage in the ungauged basin was proposed using collectible social and economic indicators and flood analysis results. For distributed runoff analysis and flooding analysis, GRM (Grid based Rainfall-runoff Model) and G2D (Grid based 2-Dimensional land surface flood model) developed by Korea Institute of Civil engineering and Building Technology were used. The method of substituting collectible social and economic indicators into the simple method and improvement method was used to estimate the amount of flood damage. As a result of the study, it was possible to estimate the amount of flood damage using satellite data and social and economic indicators in the ungauged basin.

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.70-81
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• 2024

With heavy rainfall due to extreme weather causing increasing damage, the importance of urban flood forecasting continues to grow. To forecast urban flooding accurately and promptly, a sewer network and surface grid with appropriate detail are necessary. However, for urban areas with complex storm sewer networks and terrain structures, high-resolution grids and detailed networks can significantly prolong the analysis. Therefore, determining an appropriate level of network simplification and a suitable surface grid resolution is essential to secure the golden time for urban flood forecasting. In this study, InfoWorks ICM, a software program capable of 1D-2D coupled simulation, was used to examine urban flood forecasting performance for storm sewer networks with various levels of simplification and different surface grid resolutions. The inundation depth, inundation area, and simulation time were analyzed for each simplification level. Based on the analysis, the simulation time was reduced by up to 65% upon simplifying the storm sewer networks and by up to 96% depending on the surface grid resolution; further, the inundation area was overestimated as the grid resolution increased. This study provides insights into optimizing the simplification level and surface grid resolution for storm sewer networks to ensure efficient and accurate urban flood forecasting.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.3
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• pp.272-278
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• 2010

A method for damage detection in a plate structure is presented based on strain waves that are generated by impact or damage in the structure. Strain responses from continuous sensors, which are long ribbon-like sensors made from piezoceramic fibers or other materials, were used with a neural network technique to estimate the damage location. The continuous sensor uses only a small number of channels of data acquisition and can cover large areas of the structure. A grid type structural neural system composed of the continuous sensors was developed for effective damage localization in a plate structure. The ratios of maximum strains and arrival times of the maximum strains obtained from the continuous sensors were used as input data to a neural network. Simulated damage localizations on a plate were carried out and the identified damage locations agreed reasonably well with the exact damage locations.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.2 s.179
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• pp.81-87
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• 2006

This study has been focused on the analysis of high speed shear forming process for lead-acid battery grids. The grid plays an important role of electrical charge. It is necessary to ensure the best battery's performance that the grid should have a best quality. The clearance between punch and die, the velocity of punch and the critical damage value are very important parameters for making a good grid form. The finite element analysis of the shear forming process is carried out by measuring and optimizing these three important parameters. The result of this study concludes that these parameters has a great influence on grid quality.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.6
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• pp.294-302
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• 2005

PV system's islanding occurs when the uitilty grid is removed but local sources continue to operate and provide power to local loads. Islanding is one of the serious problems in an electric power system connected with dispersed power sources. Also, this can present safety hazards and the possibility of damage to other electric equipments. If the real and reactive power of RLC load and PV system are closely matched, islanding detection by passive methods becomes difficult. This paper shows the simulation and comparision for the previous active methods and novel islanding detection method using frequency drift is proposed for grid-connected PV system.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.1
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• pp.14-21
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• 1994

The studios on the stability of damaged ships have been carried out continuously to prevent frequent damages or sinkings which cause large loss of life and fortunes. For dry cargo ships, continuing losses have resulted in new legislation of the probabilistic damage stability. IMO has developed requirements for the subdivison and damage stability of dry cargo ships based on probabilistic concepts. The calculation of the probabilistc damage stability is a complicated and iterative job hence development of computer programs is indispensable. In this research, programming of the probabilistic damage stability according to new requirements has been done and the results were compared with those carried out by the other foreign packages. New algorithm using a grid model in a transversal section was introduced to reduce efforts in preparing input data for damage scenarios and as a result, has brought significant improvement in efficiency and performance.

• Earthquakes and Structures
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• v.11 no.5
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• pp.841-859
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• 2016

Bridge bearings are important connection elements between bridge superstructures and substructures, whose health states directly affect the performance of the bridges. This paper systematacially presents a new method to identify the bridge bearing damage based on the neural network theory. Firstly, based on the analysis of different damage types, a description of the bearing damage is introduced, and a uniform description for all the damage types is given. Then, the feasibility and sensitivity of identifying the bearing damage with bridge vibration modes are investigated. After that, a Radial Basis Function Neural Network (RBFNN) is built, whose input and output are the beam modal information and the damage information, respectively. Finally, trained by plenty of data samples formed by the numerical method, the network is employed to identify the bearing damage. Results show that the bridge bearing damage can be clearly reflected by the modal information of the bridge beam, which validates the effectiveness of the proposed method.

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• Journal of the Korean Society of Safety
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• v.11 no.4
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• pp.135-142
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• 1996

Prolonged in-plant personnel exposure to high noise levels results in permant hearing damage. There are no way to correct this hearing damage by treatment or use of hearing aids. Therefore, every employer is responsible for providing a workplace free of such hazards as excessive noise. This study was carried out to evalute and predict a given noise environment based on specific limit as the noise guarantee for a newly-founded petrochemical plant. The maximum total sound level should not exceed 85dBA in the work area, except where the area is defined as a restricted area and 70dBA at the plant boundary. Prediction of the noise levels within the plant area for a newly-founded petrochemical plant was achieved by dividing all plant area into 20m$\times$20m regular grid spaces and noise level inside the area or unit that in-plant personel exposure to high noise levels was estimated computed into 5m$\times$5m regular grid spaces. The noise level at the grid point that was propagated from each of the noise sources(equipments) computed using the methematical formula was defined as follows : $SPL_2$=$SPL_1-20log{\frac{r_2}{r_1}}$(dB) where $SPL_1$ =sound pressure level at distance $r_1$ from the source $SPL_2$=sound pressure level at distance $r_2$ from the source As a result, the equipments exceeded noise limit or irritaring noise levels were identified on the specific grid coordinates. As for equipments in the area that show high noise levels, appropriate counter-measures for noise control (by barriers, enclosure, silencers, or the change of equipments, for example) should be reviewed. Methods for identifying sources of noise applied in this study should be the model for prediction of the noise levels for any newly-founded plant.