• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.2
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• pp.88-94
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• 2010

A reliability analysis method is proposed in this paper to quantitatively evaluate the risk for internal stability of a quay wall constructed on the deep cement mixed ground, differentiating from the companion paper that mainly describes the external stability. Failure modes for toe pressure, shear strength of improved ground and extrusion of unimproved soft soil are investigated and compared in the risk estimation of internal stability using MVFOSM, FORM, and MCS. From the reliability analysis results for internal stability of a quay wall, the variance and distribution type of the compressive strength of Deep Mixed Soil-Cement appear to be very affective to the failure probability. On the other hand, other random variables seem to be relatively very insensitive to the probability of failure. It is therefore very important to rationally and accurately determine the probabilistic properties of the in-site compressive strength of Deep Mixed Soil-Cement.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.117-131
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• 2015

Conventional data envelopment analysis (DEA) models require that inputs and outputs are given as crisp values. Very often, however, some of inputs and outputs are given as imprecise data where they are only known to lie within bounded intervals. While a typical approach to addressing this situation for optimization models such as DEA is to conduct sensitivity analysis, it provides only a limited ex-post measure against the data imprecision. Robust optimization provides a more effective ex-ante measure where the data imprecision is directly incorporated into the model. This study aims to apply robust optimization approach to DEA models with imprecise data. Based upon a recently developed robust optimization framework which allows a flexible adjustment of the level of conservatism, we propose two robust optimization DEA model formulations with imprecise data; multiplier and envelopment models. We demonstrate that the two models consider different risks regarding imprecise efficiency scores, and that the existing DEA models with imprecise data are special cases of the proposed models. We show that the robust optimization for the multiplier DEA model considers the risk that estimated efficiency scores exceed true values, while the one for the envelopment DEA model deals with the risk that estimated efficiency scores fall short of true values. We also show that efficiency scores stratified in terms of probabilistic bounds of constraint violations can be obtained from the proposed models. We finally illustrate the proposed approach using a sample data set and show how the results can be used for ranking DMUs.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.51-61
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• 2006

An efficient and accurate hybrid reliability analysis method is proposed in this paper to quantify the risk of an axially loaded single pile considering pile-soil interaction behavior and uncertainties in various design variables. The proposed method intelligently integrates the concepts of the response surface method, the finite difference method, the first-order reliability method, and the iterative linear interpolation scheme. The load transfer method is incorporated into the finite difference method for the deterministic analysis of a single pile-soil system. The uncertainties associated with load conditions, material and section properties of a pile and soil properties are explicitly considered. The risk corresponding to both serviceability limit state and strength limit state of the pile and soil is estimated. Applicability, accuracy and efficiency of the proposed method in the safety assessment of a realistic pile-soil system subjected to axial loads are verified by comparing it with the results of the Monte Carlo simulation technique.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.67-75
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• 2022

The purpose of this study is to present an appropriate management plan as a supplement to the scientific evidence of the currently operated distancing system for preventing COVID-19. The currently being used mathematical models are expressed as simultaneous ordinary differential equations, there is a problem in that it is difficult to use them for the management of entry and exit of small business owners. In order to supplement this point, in this paper, a method for quantitatively expressing the risk of infection by people who gather is presented in consideration of the allowable risk given to the gathering space, the basic infection reproduction index, and the risk reduction rate due to vaccination. A simple quantitative model was developed that manages the probability of infection in a probabilistic level according to a set of visitors by considering both the degree of infection risk according to the vaccination status (non-vaccinated, primary inoculation, and complete vaccination) and the epidemic status of the virus. In a given example using the model, the risk was reduced to 55% when 20% of non-vaccinated people were converted to full vaccination. It was suggested that management in terms of quarantine can obtain a greater effect than medical treatment. Based on this, a generalized model that can be applied to various situations in consideration of the type of vaccination and the degree of occurrence of confirmed cases was also presented. This model can be used to manage the total risk of people gathered at a certain space in a real time, by calculating individual risk according to the type of vaccine, the degree of inoculation, and the lapse of time after inoculation.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.259-264
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• 2005

This paper presents a vital area identification (VAI) method based on the current fault tree analysis (FTA) and probabilistic safety assessment (PSA) techniques for the physical protection of nuclear power plants. A structured framework of a top event prevention set analysis (TEPA) application to the VAI of nuclear power plants is also delineated. One of the important processes for physical protection in a nuclear power plant is VAI that is a process for identifying areas containing nuclear materials, structures, systems or components (SSCs) to be protected from sabotage, which could directly or indirectly lead to core damage and unacceptable radiological consequences. A software VIP (Vital area Identification Package based on the PSA method) is being developed by KAERI for the VAI of nuclear power plants. Furthermore, the KAERI fault tree solver FTREX (Fault Tree Reliability Evaluation eXpert) is specialized for the VIP to generate the candidates of the vital areas. FTREX can generate numerous MCSs for a huge fault tree with the lowest truncation limit and all possible prevention sets.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.5
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• pp.371-380
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• 2017

The risk-targeted seismic design concept was first included in ASCE/SEI 7-10 to address problems related to the uniform-hazard based seismic concept that has been constructed without explicitly considering probabilistic uncertainties in the collapse capacities of structures. However, this concept is not yet reflected to the current Korean building code(KBC) because of insufficient strong earthquake data occurred at the Korean peninsula and little information on the collapse capacities of structures. This study evaluates the risk-targeted seismic performance of steel ordinary concentrically braced frames(OCBFs). To do this, the collapse capacities of prototype steel OCBFs are assessed with various analysis parameters including building locations, building heights and soil conditions. The seismic hazard curves are developed using an empirical spectral shape prediction model that is capable of reflecting the characteristics of earthquake records. The collapse probabilities of the prototype steel OCBFs located at the Korean major cities are then evaluated using the risk integral concept. As a result, analysis parameters considerably influence the collapse probabilities of steel OCBFs. The collapse probabilities of taller steel OCBFs exceed the target seismic risk of 1 percent in 50 years, which the introduction of the height limitation of steel OCBFs into the future KBC should be considered.

• Journal of the Korean Geotechnical Society
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• v.31 no.8
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• pp.51-62
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• 2015

It is not possible to provide resonable evidence for embankment (or dam) overtopping in geotechnical engineering, and conventional analysis by hydrologic design has not provided the evidence for the overflow. However, hydrologic design analysis using Copula function demonstrates the possibility that dam overflow occurs when estimating rainfall probability with rainfall data for 40 years based on fluctuating water level of a dam. Hydrologic dam risk analysis depends on complex hydrologic analyses in that probabilistic relationship needs to be established to quantify various uncertainties associated with modeling process and inputs. The systematic approaches to uncertainty analysis for hydrologic risk analysis have not been addressed yet. In this paper, the initial level of a dam for stability of a dam is generally determined by normal pool level or limiting the level of the flood, but overflow of probability and instability of a dam depend on the sensitivity analysis of the initial level of a dam. In order to estimate the initial level, Copula function and HEC-5 rainfall-runoff model are used to estimate posterior distributions of the model parameters. For geotechnical engineering, slope stability analysis was performed to investigate the difference between rapid drawdown and overtopping of a dam. As a result, the slope instability in overtopping of a dam was more dangerous than that of rapid drawdown condition.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.35-44
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• 2019

The purpose of this study is to find out quantitative vulnerability assessment about COTS(Commercial Off The Shelf) O/S based I&C System. This paper analyzed vulnerability's lifecycle and it's impact. this paper is to develop a quantitative assessment of overall cyber security risks and vulnerabilities I&C System by studying the vulnerability analysis and prediction method. The probabilistic vulnerability assessment method proposed in this study suggests a modeling method that enables setting priority of patches, threshold setting of vulnerable size, and attack path in a commercial OS-based measurement control system that is difficult to patch an immediate vulnerability.

• Structural Engineering and Mechanics
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• v.78 no.3
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• pp.351-368
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• 2021

This paper, by applying a reliability-based framework, develops seismic vulnerability macrozonation maps for Tehran, the capital and one of the most earthquake-vulnerable city of Iran. Seismic performance assessment of 3-, 4- and 5-story steel moment resisting frames (SMRFs), designed according to ASCE/SEI 41-17 and Iranian Code of Practice for Seismic Resistant Design of Buildings (2800 Standard), is investigated in terms of overall maximum inter-story drift ratio (MIDR) and unit repair cost ratio which is hereafter known as "damage ratio". To this end, Tehran city is first meshed into a network of 66 points to numerically locate low- to mid-rise SMRFs. Active faults around Tehran are next modeled explicitly. Two different combination of faults, based on available seismological data, are then developed to explore the impact of choosing a proper seismic scenario. In addition, soil effect is exclusively addressed. After building analytical models, reliability methods in combination with structure-specific probabilistic models are applied to predict demand and damage ratio of structures in a cost-effective paradigm. Due to capability of proposed methodology incorporating both aleatory and epistemic uncertainties explicitly, this framework which is centered on the regional demand and damage ratio estimation via structure-specific characteristics can efficiently pave the way for decision makers to find the most vulnerable area in a regional scale. This technical basis can also be adapted to any other structures which the demand and/or damage ratio prediction models are developed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.1-8
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• 2024

This paper employs stochastic processing techniques to analyze explosion risks in plant facilities based on explosion return periods. Release probability is calculated using data from the Health and Safety Executive (HSE), along with annual leakage frequency per plant provided by DNV. Ignition probability, derived from various researchers' findings, is then considered to calculate the explosion return period based on the release quantity. The explosion risk is assessed by examining the volume, radius, and blast load of the vapor cloud, taking into account the calculated explosion return period. The reference distance for the design blast load model is determined by comparing and analyzing the vapor cloud radius according to the return period, historical vapor cloud explosion cases, and blast-resistant design guidelines. Utilizing the multi-energy method, the blast load range corresponding to the explosion return period is presented. The proposed return period serves as a standard for the design blast load model, established through a comparative analysis of vapor cloud explosion cases and blast-resistant design guidelines. The outcomes of this study contribute to the development of a performance-based blast-resistant design framework for plant facilities.