• The Journal of Engineering Geology
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• v.32 no.1
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• pp.157-171
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• 2022

Electrical resistivity tomography (ERT) is a traditional and representative geophysical method for determining the resistivity distributions of surrounding soil and rock volumes. Depth resolution profiles and sensitivity distribution sections of the resistivities with respect to various electrode configurations are calculated and investigated using numerical model data. Shallow vertical resolution decreases in the order of Wenner, Schlumberger, and dipole-dipole arrays. A high investigable depth in homogeneous medium is calculated to be 0.11-0.19 times the active electrode spacing, but is counterbalanced by a low vertical resolution. For the application of ERT depth resolution profiles and sensitivity distributions, we provide subsurface structure models for two types of land-creping failure (planar and curved), subvertical fracture, and weathered layer over felsic and mafic igneous rocks. The dipole-dipole configuration appears to be most effective for mapping land-creeping failure planes (especially for curved planes), whereas the Wenner array gives the best resolution of soil horizons and shallow structures in the weathered zone.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.155-163
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• 2023

Real-time monitoring technology is critical for ensuring the safety and reliability of nuclear power plant structures. However, the current seismic monitoring system has limited system identification capabilities such as modal parameter estimation. To obtain global behavior data and dynamic characteristics, multiple sensors must be optimally placed. Although several studies on optimal sensor placement have been conducted, they have primarily focused on civil and mechanical structures. Nuclear power plant structures require robust signals, even at low signal-to-noise ratios, and the robustness of each mode must be assessed separately. This is because the mode contributions of nuclear power plant containment buildings are concentrated in low-order modes. Therefore, this study proposes an optimal sensor placement methodology that can evaluate robustness against noise and the effects of each mode. Indicators, such as auto modal assurance criterion (MAC), cross MAC, and mode shape distribution by node were analyzed, and the suitability of the methodology was verified through numerical analysis.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.4
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• pp.222-230
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• 2023

In the present work, the scale effect on the Boil-Off Rate (BOR) was investigated based on an analytical method to systematically evaluate the thermal performance of a Liquefied Natural Gas (LNG) Cargo Containment System (CCS). A two-dimensional thermal resistance network model was developed to accurately estimate the heat ingress into the CCS from the outside. The analysis was performed for the KC-1 LNG membrane tank under the IGC and USCG design conditions. The ballast compartment of both the LNG tank and cofferdam was divided into six sections and a thermal resistance network model was made for each section. To check the validity of the developed model, the analysis results were compared with those from existing literature. It was shown that the BOR values under the IGC and USCG design conditions were agreed well with previous numerical results with a maximum error of 1.03% and 0.60%, respectively. A SDR, the scale factor of the LNG CCS was introduced and the BOR, air temperature of the ballast compartment, and the surface temperature of the inner hull were obtained to examine the influence of the SDR on the thermal performance. Finally, a correlation for the BOR was proposed, which could be expressed as a simple formula inversely proportional to the SDR. The proposed correlation could be utilized for predicting the BOR of a full-scale LNG tank based on the BOR measurement data of lab-scale model tanks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.311-319
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• 2006

A bed level change model(SED-FLUX) is introduced based on the realistic sediment transport process including bed load and suspended load behaviours at the bottom boundary layer. The model SED-FLUX includes wave module, hydrodynamic module and sediment transport and diffusion module that calculate suspended sediment concentration, net sediment erosion flux($Q_s$) and bed load flux. Bed load transport rate is evaluated by the van Rijn's TRANSPOR program which has been verified in wave-current fields. The net sediment erosion flux($Q_s$) at the bottom is evaluated as a source/sink term in the numerical sediment diffusion model where the suspended sediment concentration becomes a verification parameter of the $Q_s$. Bed level change module calculates a bed level change amount(${\Delta}h_{i,j}$) and updates a bed level. For the model verification the limit depth of the bed load transport is compared with the field experiment data and some formula on the threshold depth for the bed load movement by waves and currents. This model is applied to the beach profile changes by waves, then the model shows a clear erosion and accumulation profile according to the incident wave characteristics. Finally the beach evolution by waves and wave-induced currents behind the offshore breakwater is calculated, where the model shows a tombolo formation in the landward area of the breakwater.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3C
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• pp.143-155
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• 2006

SPT-Uphole tomography method was introduced for the evaluation of near subsurface shear wave velocity (Vs) distribution map. In SPT-Uphole method, SPT (Standard Penetration Test) which is common in geotechnical site investigation was used as a source and several surface geophones in line were used as receivers. Vs distribution map which is the triangular shape around the boring point can be developed by tomography inversion. To obtain the exact travel time information of shear wave component, a procedure using the magnitude summation of vertical and horizontal components was used based on the evaluation of particle motion at the surface. It was verified that proposed method could give reliable Vs distribution map through the numerical study using the FEM (Finite Element Method) model. Finally, SPT-Uphole tomography method was performed at the weathered soil site where several boring data with SPT-N values are available, and the feasibility of proposed method was verified in the field.

• Communications of Mathematical Education
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• v.37 no.3
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• pp.349-368
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• 2023

The revised 2022 educational curriculum highlighted the significance of mathematical literacy as a foundational competency that can be cultivated through the learning of various subjects, along with language proficiency and digital literacy. However, due to the lack of a precise definition for mathematical literacy, there exists a challenge in systematically implementing it across all subjects in the educational curriculum. The aim of this study is to clarify the definition of mathematical literacy in the curriculum through a literature review and to analyze the application patterns of mathematical literacy in other subjects so that mathematical literacy can be systematically applied as a basic literacy in Korea's curriculum. To achieve this, the study first clarifies and categorizes the meaning of mathematical literacy through a comparative analysis of terms such as numeracy and mathematical competence via a literature review. Subsequently, the study compares the categories of mathematical literacy identified in both domestic and international educational curricula and analyzes the application of mathematical literacy in the education curriculum of New South Wales (NSW), Australia, where mathematical literacy is reflected in the achievement standards across various subjects. It is expected that understanding each property by subdividing the meaning of mathematical literacy and examining the application modality to the curriculum will help construct a curriculum that reflects mathematical literacy in subjects other than mathematics.

• Tunnel and Underground Space
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• v.33 no.5
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• pp.414-424
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• 2023

In this study, a total of 326 data on a variety of geometric parameters of pick cutters and the corresponding cuttable rock conditions were collected and built as a database. Statistical analysis of the database showed that there is a significant positive correlation between the parameters that define the geometry of a pick cutter, especially between the parameters related to the length of a pick cutter and the geometry of a tungsten carbide insert. The diameter of a pick cutter shaft was also strongly correlated with the geometry of the inserts. On the other hand, it was difficult to find a clear correlation between the parameters for the rock conditions defined by the four conditions and the geometric parameters of pick cutters, which may be due to the uncertainty of the rock mass and the fact that the application of a pick cutter is presented as a range rather than a numerical single value. However, the mean values of geometric parameters of pick cutters tend to increase as a rock mass becomes harder. However, the pick length parameters are found to decrease as a rock mass becomes harder, which may be a way to reduce the moments that can occur when using long pick cutters in a hard rock condition.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.483-490
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• 2022

Floating LiDAR is a system that provides a new paradigm for wind condition observation, which is essential when creating an offshore wind farm. As it can save time and money, minimize environmental impact, and even reduce backlash from local communities, it is emerging as the industry standard. However, the design and verification of a stable platform is very important, as disturbance factors caused by fluctuations of the buoy affect the reliability of observation data. In Korea, due to the nation's late entry into the technology, a number of foreign equipment manufacturers are dominating the domestic market. The west coast of Korea is a shallow sea environment with a very large tidal difference, so strong currents repeatedly appear depending on the region, and waves of strong energy that differ by season are formed. This paper conducted a study examining buoys suitable for LiDAR operation in the waters of Korea, which have such complex environmental characteristics. In this paper, we will introduce examples of optimized design and verification of ship-type buoys, which were applied first, and derive important concepts that will serve as the basis for the development of various platforms in the future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.489-498
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• 2023

Advancements in hardware performance and computing technology have facilitated the progress of climate prediction models to address climate change. The Korea Meteorological Administration employs the GloSea6 model with supercomputer technology for operational use. Various universities and research institutions utilize the Low-GloSea6 model, a low-resolution coupled model, on small to medium-scale servers for weather research. This paper presents an analysis using Intel VTune Profiler on Low-GloSea6 to facilitate smooth weather research on small to medium-scale servers. The tri_sor_dp_dp function of the atmospheric model, taking 1125.987 seconds of CPU time, is identified as a hotspot. Nonlinear regression models, a machine learning technique, are applied and compared to existing functions conducting numerical operations. The K-Nearest Neighbors regression model exhibits superior performance with MAE of 1.3637e-08 and SMAPE of 123.2707%. Additionally, the Light Gradient Boosting Machine regression model demonstrates the best performance with an RMSE of 2.8453e-08. Therefore, it is confirmed that applying a nonlinear regression model to the tri_sor_dp_dp function during the execution of Low-GloSea6 could be a viable alternative.