• Journal of the Korean Geotechnical Society
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• v.25 no.5
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• pp.53-64
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• 2009

Many slope failures are induced by rainfall infiltration. A lot of recent researches are therefore focused on rainfall-induced slope instability and the rainfall infiltration is recognized as the important triggering factor. The rainfall infiltrates into the soil slope and makes the matric suction lost in the slope and even the positive pore water pressure develops near the surface of the slope. They decrease the resisting shear strength. In Korea, a few public institutions suggested conservative slope design guidelines that assume a fully saturated soil condition. However, this assumption is irrelevant and sometimes soil properties are misused in the slope design method to fulfill the requirement. In this study, a more relevant slope stability evaluation method is suggested to take into account the real rainfall infiltration phenomenon. Unsaturated soil properties such as shear strength, soil-water characteristic curve and permeability for Korean weathered soils were obtained by laboratory tests and also estimated by artificial neural network models. For real-time assessment of slope instability, failure warning criteria of slope based on deterministic and probabilistic analyses were introduced to complement uncertainties of field measurement data. The slope stability evaluation technique can be combined with field measurement data of important factors, such as matric suction and water content, to develop an early warning system for probably unstable slopes due to the rainfall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.1 no.1
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• pp.21-32
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• 1981

Recent trends in design standards development in some European countries and U.S.A. have encouraged the use of probabilistic limit sate design concepts. Reliability based design criteria such as LSD, LRFD, PBLSD, adopted in those advanced countries have the potentials that they afford for symplifying the design process and placing it on a consistent reliability bases for various construction materials. A reliability based design criteria for RC flexural members are proposed in this study. Lind-Hasofer's invariant second-moment reliability theory is used in the derivation of an algorithmic reliability analysis method as well as an iterative determination of load and resistance factors. In addition, Cornell's Mean First-Order Second Moment Method is employed as a practical tool for the approximate reliability analysis and the derivation of design criteria. Uncertainty measures for flexural resistance and load effects are based on the Ellingwood's approach for the evaluation of uncertainties of loads and resistances. The implied relative safety levels of RC flexural members designed by the strength design provisions of the current standard code were evaluated using the second moment reliability analysis method proposed in this study. And then, resistance and load factors corresponding to the target reliability index(${\beta}=4$) which is considered to be appropriate level of reliability considering our practices are calculated by using the proposed methods. These reliability based factors were compared to those specified by our current ultimate strength design provisions. It was found that the reliability levels of flexural members designed by current code are not appropriate, and the code specified resistance and load factors were considerably different from the reliability based resistance and load factors proposed in this study.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.1
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• pp.35-45
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• 2007

The log data collected from mobile devices contains diverse meaningful and practical personal information. However, this information is usually ignored because of its limitation of memory capacity, computation power and analysis. We propose a novel method that detects landmarks of meaningful information for users by analyzing the log data in distributed modules to overcome the problems of mobile environment. The proposed method adopts Bayesian probabilistic approach to enhance the inference accuracy under the uncertain environments. The new cooperative modularization technique divides Bayesian network into modules to compute efficiently with limited resources. Experiments with artificial data and real data indicate that the result with artificial data is amount to about 84% precision rate and about 76% recall rate, and that including partial matching with real data is about 89% hitting rate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.785-791
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• 2023

Risk management is essential for preventing accidents arising from uncertainties in TBM tunnel projects, especially concerning managing the risk of TBM tunnel collapse, which can cause extensive damage from the tunnel face to the ground surface. In addition, prioritizing risks is necessary to allocate resources efficiently within time and cost constraints. Therefore, this study aimed to establish a TBM risk database through case studies of TBM accidents and determine a risk priority for TBM tunnel collapse using the Bayes theorem. The database consisted of 87 cases, dealing with three accidents and five geological sources. Applying the Bayes theorem to the database, it was found that fault zones and weak ground significantly increased the probability of tunnel collapse, while the other sources showed low correlations with collapse. Therefore, the risk priority for TBM tunnel collapse, considering geological sources, is as follows: 1) Fault zone, 2) Weak ground, 3) Mixed ground, 4) High in-situ stress, and 5) Expansive ground. In practice, the derived risk priority can serve as a valuable reference for risk management, enhancing the safety and efficiency of TBM construction. It provides guidance for developing appropriate countermeasure plans and allocating resources effectively to mitigate the risk of TBM tunnel collapse.

• Journal of the Korean Geotechnical Society
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• v.25 no.10
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• pp.87-97
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• 2009

The seismic site coefficients are often used with the seismic hazard maps to develop the design response spectrum at the surface. The site coefficients are most commonly developed deterministically, while the seismic hazarde maps are derived probabilistically. There is, hence, an inherent incompatibility between the two approaches. However, they are used together in the seismic design codes without a clear rational basis. To resolve the fundamental imcompatibility between the site coefficients and hazard maps, this study uses a novel probabilistic seismic hazard analysis (PSHA) technique that simulates the results of a standard PSHA at a rock outcrop, but integrates the site response analysis function to capture the site amplification effects within the PSHA platform. Another important advantage of the method is its ability to model the uncertainty, variability, and randomness of the soil properties. The new PSHA was used to develop fully probabilistic site coefficients for site classes of the seismic design code and another sets of site classes proposed in Korea. Comparisons highlight the pronounced discrepancy between the site coefficients of the seismic design code and the proposed coefficients, while another set of site coefficients show differences only at selected site classes.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.1
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• pp.37-43
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• 2010

In this paper, a reliability-based design optimization is developed for the topology design of linear structures using a performance measure approach. Spatial domain is discretized using three dimensional Reissner-Mindlin plate elements and design variable is taken as the material property of each element. A continuum based adjoint variable method is employed for the efficient computation of sensitivity with respect to the design and random variables. The performance measure approach of RBDO is employed to evaluate the probabilistic constraints. The topology optimizationproblem is formulated to have probabilistic displacement constraints. The uncertainties such as material property and external loads are considered. Numerical examples show that the developed topology optimization method could effectively yield a reliable design, comparing with the other methods such as deterministic, safety factor, and worst case approaches.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.3
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• pp.71-86
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• 1983

Current R.C. retaining wall design is bared on WSD, but the reliability based design method is more rational than the WSD. For this reason, this study proposes a reliability based design criteria for the cantilever retaining wall, which is most common type of retaining wall, and also proposes the theoretical bases of nominal safety factors of stability analysis by introducing the reliability theory. The limit state equations of stability analysis and design of each part of cantilever retaining wall are derived and the uncertainty measuring algorithms of each equation are also derived by MFOSM using Coulomb's coefficient of the active earth pressure and Hansen's bearing capacity formula. The levels of uncertainties corresponding to these algorithms are proposed appropriate values considering our actuality. The target reliability indices (overturning: ${\beta}_0$=4.0, sliding: ${\beta}_0$=3.5, bearing capacity: [${\beta}_0$=3.0, design for flexure: [${\beta}_0$=3.0, design for shear: ${\beta}_0$=3.2) are selected as optimal values considering our practice based on the calibration with the current R.C. retaining wall design safety provisions. Load and resistance factors are measured by using the proposed uncertainties and the selected target reliability indices. Furthermore, a set of nominal safety factors, allowable stresses, and allowable shear stresses are proposed for the current WSD design provisions. It may be asserted that the proposed LRFD reliability based design criteria for the R.C. retaining wall may have to be incorporated into the current R.C. design codes as a design provision corresponding to the USD provisions of the current R.C. design code.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.360-373
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• 2017

The BTO-a projects is the types, which has a demand risk among the type of PPP projects in Korea. When demand risk is realized, private investor encounters financial difficulties due to lower revenue than its expectation and the government may also have a problem in stable infrastructure operation. In this regards, the government has applied various risk sharing policies in response to demand risk. However, the amount of government's risk sharing is the government's contingent liabilities as a result of demand uncertainty, and it fails to be quantified by the conventional NPV method of expressing in the text of the concession agreement. The purpose of this study is to estimate the value of investment risk sharing by the government considering the demand risk in the profit sharing system (BTO-a) introduced in 2015 as one of the demand risk sharing policy. The investment risk sharing will take the form of options in finance. Private investors have the right to claim subsidies from the government when their revenue declines, while the government has the obligation to pay subsidies under certain conditions. In this study, we have established a methodology for estimating the value of investment risk sharing by using the Black - Scholes option pricing model and examined the appropriateness of the results through case studies. As a result of the analysis, the value of investment risk sharing is estimated to be 12 billion won, which is about 4% of the investment cost of the private investment. In other words, it can be seen that the government will invest 12 billion won in financial support by sharing the investment risk. The option value when assuming the traffic volume risk as a random variable from the case studies is derived as an average of 12.2 billion won and a standard deviation of 3.67 billion won. As a result of the cumulative distribution, the option value of the 90% probability interval will be determined within the range of 6.9 to 18.8 billion won. The method proposed in this study is expected to help government and private investors understand the better risk analysis and economic value of better for investment risk sharing under the uncertainty of future demand.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.587-598
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• 2012

Successful implementation of infrastructure asset management system can be started with rich and reliable data. However, measurement errors in the data have always existed in the real world caused for many unknown reasons. It disturbs maintenance activities of agencies, and makes negative effects to reliability of research results on forecasting deterioration process and life cycle cost. Above all, it makes a contradiction that road agencies cannot believe their inspection data surveyed by their hands. It is particularly serious in the road pavement management field. Although road agencies are well recognized the fact, inspecting without measurement error would be a great challenge. Considering the facts, this paper aimed to suggest statistical error processing methods to correct latent error included in pavement surface inspection data. As alternatives, this paper suggested two methods based on probability distribution to consider structure of error and reliability of the data. The suggested methods were empirically tested by using pavement inspection data from Korean National Highway. As the result, this paper confirmed that conventional error processing that just removes only visible errors is not enough to cover uncertainty in pavement deterioration process. The suggested methods would be useful for improving reliability of analysis results required for road infrastructure asset management.

• The Journal of Bigdata
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• v.7 no.1
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• pp.99-111
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• 2022

A simulation technique can be used to analyze performance measures and support decision makings in manufacturing systems considering operational uncertainty and complexity. The simulation requires an input modeling procedure to reflect the target system's characteristics. However, data collection to build a simulation is quite limited when a target system includes manual productions with a lot of operational time such as construction equipment assembly lines. This study proposes a procedure for simulation input modeling using video data when it is difficult to collect enough input data to fit a probability distribution. We conducted a video-data analysis and specify input distributions for the simulation. Based on the proposed procedure, simulation experiments were conducted to evaluate key performance measures of the target system. We also expect that the proposed procedure may help simulation-based decision makings when obtaining input data for a simulation modeling is quite challenging.