• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1998.04a
• /
• pp.157-164
• /
• 1998

An elasto-plastic stochastic finite element method is developed to evaluate the probability of failure of the underground structure. The Mohr-Coulomb failure criteria is adopted for yield condition. The material properties such as the elastic modulus and the cohesion are assumed to be statistically independent random variables which are modeled as spatial stochastic fields. The displacements around the excavated area and the probability of the failure are examined by varying the coefficient of variance for each variables. It is found that the developed procedure can provide the proper probabilistic information about the failure of the underground structure

• ETRI Journal
• /
• v.25 no.2
• /
• pp.140-143
• /
• 2003

In this paper, we present a probabilistic approach to determining whether extracted facial features from a video sequence are appropriate for creating a 3D face model. In our approach, the distance between two feature points selected from the MPEG-4 facial object is defined as a random variable for each node of a probability network. To avoid generating an unnatural or non-realistic 3D face model, automatically extracted 2D facial features from a video sequence are fed into the proposed probabilistic network before a corresponding 3D face model is built. Simulation results show that the proposed probabilistic network can be used as a quality control agent to verify the correctness of extracted facial features.

• Journal of Environmental Impact Assessment
• /
• v.15 no.6
• /
• pp.373-383
• /
• 2006

The spatial mapping of risk is very useful data in planning for disaster preparedness. This research presents a methodology for making the landslide life risk map in the Boeun area which had considerable landslide damage following heavy rain in August, 1998. We have developed a three-stage procedure in spatial data analysis not only to estimate the probability of the occurrence of the natural hazardous events but also to evaluate the uncertainty of the estimators of that probability. The three-stage procedure consists of: (i)construction of a hazard prediction map of "future" hazardous events; (ii) validation of prediction results and estimation of the probability of occurrence for each predicted hazard level; and (iii) generation of risk maps with the introduction of human life factors representing assumed or established vulnerability levels by combining the prediction map in the first stage and the estimated probabilities in the second stage with human life data. The significance of the landslide susceptibility map was evaluated by computing a prediction rate curve. It is used that the Bayesian prediction model and the case study results (the landslide susceptibility map and prediction rate curve) can be prepared for prevention of future landslide life risk map. Data from the Bayesian model-based landslide susceptibility map and prediction ratio curves were used together with human rife data to draft future landslide life risk maps. Results reveal that individual pixels had low risks, but the total risk death toll was estimated at 3.14 people. In particular, the dangerous areas involving an estimated 1/100 people were shown to have the highest risk among all research-target areas. Three people were killed in this area when landslides occurred in 1998. Thus, this risk map can deliver factual damage situation prediction to policy decision-makers, and subsequently can be used as useful data in preventing disasters. In particular, drafting of maps on landslide risk in various steps will enable one to forecast the occurrence of disasters.

• The KIPS Transactions:PartD
• /
• v.9D no.6
• /
• pp.1119-1126
• /
• 2002

In this paper, we propose two predictive spatial data mining based on spatial statistics and apply for predicting the forest fire hazardous area. These are conditional probability and likelihood ratio methods. In these approaches, the prediction models and estimation procedures are depending un the basic quantitative relationships of spatial data sets relevant forest fire with respect to selected the past forest fire ignition areas. To make forest fire hazardous area prediction map using the two proposed methods and evaluate the performance of prediction power, we applied a FHR (Forest Fire Hazard Rate) and a PRC (Prediction Rate Curve) respectively. In comparison of the prediction power of the two proposed prediction model, the likelihood ratio method is mort powerful than conditional probability method. The proposed model for prediction of forest fire hazardous area would be helpful to increase the efficiency of forest fire management such as prevention of forest fire occurrence and effective placement of forest fire monitoring equipment and manpower.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.27 no.4
• /
• pp.258-265
• /
• 2015

Over the last 20 years, freak waves have attracted many researchers because of their unexpected behaviors and damages on offshore structures and vessels in the ocean and coastal waters. Despite many researches on the causes, mechanisms and occurrence of freak waves, we have not reached consensus on the results of the researches. This paper presents the occurrence probability of freak waves based on the analysis of wave records measured at coastal waters of Donghae harbor in the East Sea. Three freak waves were found which satisfied conditions of m and $H_S{\geq}2.5m$ and $H_m/H_S{\geq}2$. The occurrence probabilities of freak waves were estimated from extreme distributions by Mori, Rayleigh and Ahn, and found to be on the orders of O($10^{-1}$), O($10^{-2}$), and O($10^{-3}$), respectively. The occurrence probabilities of freak waves measured from waves records were estimated between O($10^{-2}$) and O($10^{-3}$), which were located between predictions by Rayleigh and Ahn's extreme probability distributions. However, we need more analysis of wave records obtained from diverse field conditions in order to verify the accuracy of the estimation of occurrence probability of freak waves.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.138-140
• /
• 2003

The aim of this study is to evaluate the effect of spatial resolutions on the accuracy to landslide susceptibility mapping. For this, landslide locations were identified in the Boun, Korea from interpretation of aerial photographs and field surveys. The topographic, soil, forest, geologic, linearment and land use data were collected, processed and constructed into a spatial database using GIS and remote sensing data. The 15 factors that influence landslide occurrence were extracted and calculated from the spatial database with 5m, 10m, 30m, 100m and 200m spatial resolutions. Landslide hazardous area were analysed and mapped using the landslide-occurrence factors by probability model, likelihood ratio, for the five cases spatial resolutions. The results of the analysis were verified using the landslide location data. In the cases of spatial resolution 5m, 10m and 30m, the verification results was similar, but in the cases of 100m and 200m the results worse than the others. Because the scale of input data was 1:5,000 ? 1:50,000, so the cases of 5m, 10m and 30m have similar accuracy but the cases of 100m and 200m have the lower accuracy. From this, there is an effect of spatial resolutions on accuracy and landslide susceptibility mapping the result is dependent on input map.

• Journal of the Korean Statistical Society
• /
• v.28 no.4
• /
• pp.457-468
• /
• 1999

Autologistic lattice process is used to model binary spatial data. A conditional probability is derived for the incomplete data where the lattice consists of partially yet systematically observed sites. This result, which is interesting in its own right, is in turn applied to area prediction in the plane.

• Journal of the Korean GEO-environmental Society
• /
• v.22 no.11
• /
• pp.5-13
• /
• 2021

The interest of expecting the liquefaction damage is increasing due to the liquefaction in Pohang in 2017. Liquefaction is defined as a phenomenon that the ground can not support the superstructure due to loss of the strength of the ground. As an alternative against this, many studies are being conducted to increase the precision and to compose a liquefaction hazard map for the purpose of identifying the scale of liquefaction damage using the liquefaction potential index (LPI). In this research, in order to analyze the degree of precision with regard to spatial interpolation objects such as LPI value and geotechnical information for LPI determination, liquefaction hazard map were made for the target area. Furthermore, based on the trend of precision, probability value was analyzed using probability maps prepared through qualitative characteristics. Based on the analysis results, the precision of the liquefaction hazard map setting the spatial interpolation object as geotechnical information is higher than that as LPI value. Furthermore, the precision of the liquefaction hazard map does not affect the distribution of the probability value.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.10 no.4
• /
• pp.349-360
• /
• 2008

In this paper, the modeling procedure of random field with an elasto-plastic finite element algorithm and probability of failure on closely-spaced tunnel were investigated. Local average subdivision (LAS) method which can generate discrete random variables fast and accurately as well as change the resolution in certain region was used. And correlated value allocating and weighted average method were suggested to implement geometrical characteristics of tunnel. After the probability of failure on the test problem was thoroughly investigated using random finite element method, the results were compared with the deterministic strength reduction factor method and single random variable method. Of particular importance in this work, is the conclusion that the probability of failure determined by simplified probabilistic analysis, in which spatial variability is ignored by assuming perfect correlation, can be estimated from the safety factor determined by strength reduction factor method. Also, single random variable method can lead to unconservative estimates of the probability of failure.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.38 no.11
• /
• pp.1144-1151
• /
• 2010

The increasing number of orbital debris objects is a risk for satellites because of past 50 years space activities. The LEO (low earth orbit) where KOMPSAT-2 and KOMPSAT-5 are operated is including about 84% of the total space debris. Thus, the space missions need to consider the space debris. In this paper, we analysis the orbit characteristics and spatial density of space debris about KOMPSAT-2 that is in activity and KOMPSAT-5 that will be launched in 2010. Analyzed probability damage and collision with space debris are also performed. ESA MASTER2005 and of NASA DAS2.0 are used to analysis KOMPSAT mission environment. As a result, it is noted that KOMPSAT-2's collision probability was far more than KOMPSAT-5 because KOMPSAT-2's orbit has high density composed space debris.