• Journal of Navigation and Port Research
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• v.31 no.3 s.119
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• pp.235-245
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• 2007

Stiffened steel plates are basic structural members on the deck and bottom structure in ship, offshore. It has a number of one sided stiffeners in either one or both directions, the latter structure was called grillage structure. At the ship structural desgn stage, one of the major consideration is evaluation for ultimate strength of the hull girder. In general, it is accepted that hull girder strength can be represented by the local strength of the longitudinal stiffened panel. In case of considering hogging condition in a stormy sea, stiffened panel was acting on the bottom structure under axial compressive load induced hull girder bending moment, also simultaneously arising local bending moment induced lateral pressure load. In this paper, results of the structural analysis have been compared with another detailed FEA program and prediction from design guideline and a series analysis was conducted consideration of changing parameters for instance, analysis range, cross-section of stiffener, web height and amplitude of lateral pressure load subjected to combined load (axial compression and lateral pressure load). It has been found that finite element modeling is capable of predicting the behaviour and ultimate load capacity of a simply supported stiffened plate subjected to combined load of axial compression and lateral pressure load It is expected that these results will be used to examine the effect of interaction between lateral pressure and axial loads for the ultimate load-carrying capacity based on the Ultimate Limit State design guideline.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.101-110
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• 2010

The increased occurrence of flooding due to typhoons and local rainfall has necessitated damage prevention through the systematic construction of damage history and quantitative analysis of flood prediction data. In this study, we constructed a disaster information map for practical use by combining digital images and continuous cadastral maps of damaged areas using a geographic information system to provide basic data and attribute information. In addition, we predicted the areas at risk of flash floods by calculating the flood capacity of the study area for different rainfall frequencies through flood inundation simulation, which was used to obtain comprehensive disaster information. Further, we calculated the extent of the flooded area and the damage rate for different rainfall frequencies using cadastral information. Flood inundation simulation in the case of heavy rainfall was found to help improve the ability to react to a flood and enhance the efficiency of rescue work by supporting decision-making for disaster management.

• The Journal of Engineering Geology
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• v.25 no.3
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• pp.331-337
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• 2015

A new technique is presented to detect unstable slope behavior, based on Hotelling's T² analysis of pore pressure and water content obtained during flume tests using granitic and gneissic weathered soils. Three sets of pore pressure-water content values were simultaneously obtained during each test, and T² statistics at the 90.0% and 95.0% confidence levels were calculated based on the correlations between values. The results show that unsuccessful detection of some local failures of the flume slope depended on the sensor position. In the case of global slope failures, anomalous behavior was detected between several hundred and several thousand seconds before the event as T² statistics exceeded the confidence interval 90%. Hotelling's T² analysis provides a single control criterion because it enables correlations between diverse measured values within the same slope; the criterion also includes stepwise criteria for a forecasting and warning system based on confidence levels.

• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.7_spc
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• pp.485-494
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• 2016

The risk-based assessment, also called time-based assessment of structure is usually performed to provide seismic risk evaluation of a target structure for its entire life-cycle, e.g. 50 years. The prediction of collapse probability is the estimator in the risk-based assessment. While the risk-based assessment is the key in the performance-based earthquake engineering, its application is very limited because this evaluation method is very expensive in terms of simulation and computational efforts. So the evaluation database for many archetype structures usually serve as representative of the specific system. However, there is no such an assessment performed for building stocks in Korea. Consequently, the performance objective of current building code, KBC is not clear at least in a quantitative way. This shortcoming gives an unresolved issue to insurance industry, socio-economic impact, seismic safety policy in national and local governments. In this study, we evaluate the comprehensive seismic performance of an low-rise residential buildings with discontinuous structural walls, so called piloti-type structure which is commonly found in low-rise domestic building stocks. The collapse probability is obtained using the risk integral of a conditioned collapse capacity function and regression of current hazard curve. Based on this approach it is expected to provide a robust tool to seismic safety policy as well as seismic risk analysis such as Probable Maximum Loss (PML) commonly used in the insurance industry.

• Journal of the Korean earth science society
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• v.41 no.5
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• pp.459-468
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• 2020

In this study, the selection criteria for the occurrence of sea breezes in the Boseong area during the spring season (March-May) of 2016-2017 were prepared for the analysis of vertical weather characteristics. For this purpose, wind speed values were determined using the measured precipitation, cloud volume, wind direction, the difference between the ground and sea temperature, a wind Profiler at an altitude of 1 km, and numerical model data. The dates of the sea breezes in Boseong were classified according to the selection criteria, and the spatial and temporal characteristics of the sea breezes were identified by analyzing the time and altitude of the sea breeze and the size of the wind speed. Sea breezes occurred 23 out of 183 days (12%), and in Boseong, at least 1.2 out of 10 spring days exhibited sea breezes. Sea winds ranged from 1200 to 1800 LST, mainly from ground to 700 m altitude during the day. In addition, the maximum wind speed averaged 4.9 m s^-1, at an altitude of 40 m at 1600 LST, showing relatively lower values than those in a preceding study. This seems to be owing to the reduction in wind speed due to the complexity of the coastal terrain.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.96-103
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• 2023

Generally, human stampedes and crowd collapses occur when people press against each other, causing falls that may result in death or injury. Particularly, crowd accidents have become increasingly common since the 1990s, with an average of 380 deaths annually. For instance, in Korea, a stampede occurred during the Itaewon Halloween festival on October 29, 2022, when several people crowded onto a narrow, downhill road, which was 45 meters long and between 3.2 and 4 meters wide. Precisely, this stampede was primarily due to the excessive number of people relative to the road size. Essentially, stampedes can occur anywhere and at any time, not just at events, but also in other places where large crowds gather. More specifically, the likelihood of accidents increases when the crowd density exceeds a turbulence threshold of 5-6 /m². Meanwhile, festivals and events, which have become more frequent and are promoted through social media, garner people from near and far to a specific location. Besides, as cities grow, the number of people gathering in one place increases. While stampedes are rare, their impact is significant, and the uncertainty associated with them is high. Currently, there is no scientific system to analyze the risk of stampedes due to crowd concentration. Consequently, to prevent such accidents, it is essential to prepare for crowd disasters that reflect social changes and regional characteristics. Hence, this study proposes using digital topographic maps and crowd-density risk simulations to develop a 3D model of the region. Specifically, the crowd density simulation allows for an analysis of the density of people walking along specific paths, which enables the prediction of danger areas and the risk of crowding. By using the simulation method in this study, it is anticipated that safety measures can be rationally established for specific situations, such as local festivals, and preparations may be made for crowd accidents in downtown areas.

• Korean Journal of Construction Engineering and Management
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• v.12 no.6
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• pp.110-119
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• 2011

Global warming caused by excessive greenhouse gas emission is causing climate change all over the world. In Korea, greenhouse gas emission from residential buildings accounts for about 10% of gross domestic emission. Also, the number of deteriorated multi-family housing complexes is increasing. Therefore, the goal of this research is to establish the bases to manage energy consumption continuously and methodically during MR&R period of multi-family housings. The research process and methodologies are as follows. First, research team collected the data on project characteristics and energy consumption of multi-family housing complexes in Seoul. Second, an ontology-based breakdown structure was established with some primary characteristics affecting the energy consumption, which were selected by statistical analysis. Finally, a predictive model of energy consumption was developed based on the ontology-based breakdown structure, with application of CBR, ANN, MRA and GA. In this research, PASW (Predictive Analytics SoftWare) Statistics 18, Microsoft EXCEL, Protege 4.1 were utilized for data analysis and prediction. In future research, the model will be more continuous and methodical by developing the web-base system. And it has facility manager of government or local government, or multi-family housing complex make a decision with definite references regarding moderate energy consumption.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.5
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• pp.45-54
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• 2007

Time/frequency analysis has been extensively used in biomedical signal processing. By extracting some essential features from the electro-physiological signals, these methods are able to determine the clinical pathology mechanisms of some diseases. However, this method assumes that the signal should be stationary, which limits its application in non-stationary system. In this paper, we develop a new signal processing method using Hilbert-Huang Transform to perform analysis of the nonlinear and non-stationary ventricular fibrillation(VF). Hilbert-Huang Transform combines two major analytical theories: Empirical Mode Decomposition(EMD) and the Hilbert Transform. Hilbert-Huang Transform can be used to decompose natural data into independent Intrinsic Mode Functions using the theories of EMD. Furthermore, Hilbert-Huang Transform employs Hilbert Transform to determine instantaneous frequency and amplitude, and therefore can be used to accurately describe the local behavior of signals. This paper studied for Return Of Spontaneous Circulation(ROSC) and non-ROSC prediction performance by Support Vector Machine and three parameters(EMD-IF, EMD-FFT) extracted from ventricular fibrillation ECG waveform using Hilbert-Huang transform. On the average results of sensitivity and specificity were 87.35% and 76.88% respectively. Hilbert-Huang Transform shows that it enables us to predict the ROSC of VF more precisely.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.91-99
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• 2014

The common-rail injectors are the most critical component of the CRDI diesel engines that dominantly affect engine performances through high pressure injection with exact control. Thus, from now on the advanced combustion technologies for common-rail diesel injection engine require high performance fuel injectors. Accordingly, the previous studies on the numerical and experimental analysis of the diesel injector have focused on a optimum geometry to induce proper injection rate. In this study, computational predictions of performance of the diesel injector have been performed to evaluate internal flow characteristics for various needle lift and the spray pattern at the nozzle exit. To our knowledge, three-dimensional computational fluid dynamics (CFD) model of the internal flow passage of an entire injector duct including injection and return routes has never been studied. In this study, major design parameters concerning internal routes in the injector are optimized by using a CFD analysis and Response Surface Method (RSM). The computational prediction of the internal flow characteristics of the common-rail diesel injector was carried out by using STAR-CCM+7.06 code. In this work, computations were carried out under the assumption that the internal flow passage is a steady-state condition at the maximum needle lift. The design parameters are optimized by using the L16 orthogonal array and polynomial regression, local-approximation characteristics of RSM. Meanwhile, the optimum values are confirmed to be valid in 95% confidence and 5% significance level through analysis of variance (ANOVA). In addition, optimal design and prototype design were confirmed by calculating the injection quantities, resulting in the improvement of the injection performance by more than 54%.