• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.4
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• pp.145-155
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• 1992

The objective of the study is to evaluate the effect of variabilities (uncertainties) in materials and testing on contractor payment and to suggest a base for adjusting the unsuitable specification. Most commonly used acceptance plans were used to estimate payment using simulation. Simulation results that were graphically illustrated by means of operating characteristics (OC) curves in terms of expected payment showed that contractor received a reduced payment due to intrinsic sampling and test variabilies. The most significant reduction was caused due to relatively large magnitude of the testing variability. Therefore, the tolerance range in acceptance plan should be revised as compared with typical testing variability.

• Structural Engineering and Mechanics
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• v.46 no.1
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• pp.53-73
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• 2013

Prediction of prestressed concrete girder integral abutment bridge (IAB) load effect requires understanding of the inherent uncertainties as it relates to thermal loading, time-dependent effects, bridge material properties and soil properties. In addition, complex inelastic and hysteretic behavior must be considered over an extended, 75-year bridge life. The present study establishes IAB displacement and internal force statistics based on available material property and soil property statistical models and Monte Carlo simulations. Numerical models within the simulation were developed to evaluate the 75-year bridge displacements and internal forces based on 2D numerical models that were calibrated against four field monitored IABs. The considered input uncertainties include both resistance and load variables. Material variables are: (1) concrete elastic modulus; (2) backfill stiffness; and (3) lateral pile soil stiffness. Thermal, time dependent, and soil loading variables are: (1) superstructure temperature fluctuation; (2) superstructure concrete thermal expansion coefficient; (3) superstructure temperature gradient; (4) concrete creep and shrinkage; (5) bridge construction timeline; and (6) backfill pressure on backwall and abutment. IAB displacement and internal force statistics were established for: (1) bridge axial force; (2) bridge bending moment; (3) pile lateral force; (4) pile moment; (5) pile head/abutment displacement; (6) compressive stress at the top fiber at the mid-span of the exterior span; and (7) tensile stress at the bottom fiber at the mid-span of the exterior span. These established IAB displacement and internal force statistics provide a basis for future reliability-based design criteria development.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.121-133
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• 1993

Presented is a study on the establishment of a method of advanced reliability analysis for the realistic analysis and design of reinforced concrete(RC) structures. Considerable variabilities exist in concrete structures due to random nature of concrete materials and member dimensions. The present study analyzes first the uncertainties in concrete, reinforcements and member dimensions and then a method is proposed to determine the probability uncertainties of basic variables. The limit state equations are also proposed for the RC members with axial compression and bending and RC footings. The advanced invariant second-moment method is applied to analyze those structures. The present study provides an important base for realistic reliability analysis of RC structures.

• Earthquakes and Structures
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• v.18 no.3
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• pp.285-296
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• 2020

Dams are important structures for management of water supply for irrigation or drinking, flood control, and electricity generation. In seismic regions, the structural safety of concrete gravity dams is important due to the high potential of life and economic loss if they fail. Therefore, the seismic analysis of existing dams in seismically active regions is crucial for predicting responses of dams to ground motions. In this paper, earthquake response of concrete gravity dams is investigated using the finite element (FE) method. The FE model accounts for dam-water-foundation rock interaction by considering compressible water, flexible foundation effects, and absorptive reservoir bottom materials. Several uncertainties regarding structural attributes of the dam and external actions are considered to obtain the fragility curves of the dam-water-foundation rock system. The structural uncertainties are sampled using the Latin Hypercube Sampling method. The Pine Flat Dam in the Central Valley of Fresno County, California, is selected to demonstrate the methodology for several limit states. The fragility curves for base sliding, and excessive deformation limit states are obtained by performing non-linear time history analyses. Tensile cracking including the complex state of stress that occurs in dams was also considered. Normal, Log-Normal and Weibull distribution types are considered as possible fits for fragility curves. It was found that the effect of the minimum principal stress on tensile strength is insignificant. It is also found that the probability of failure of tensile cracking is higher than that for base sliding of the dam. Furthermore, the loss of reservoir control is unlikely for a moderate earthquake.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.3
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• pp.85-90
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• 1988

A probabilistic model for the failure in a homogeneous soil slope is presented. The Safety of the slope is measured through its probability of failure rather than the customary factor of safety. The safety margin of slope failure is assumed to follow a normal distribution. Sources of uncertainties affecting characterization of soil property in a homogeneous soil layer include inherent spatial variability., estimation error from insufficient samples, and measurement errors. Uncertainties of the shear strength-along potential failure surface are expressed by one-dimensional random field models. The rupture surface, created at toe of a soil slope, has been considered to propagate towards the boundary along a path following an exponential (log-spiral) law. Having derived the statistical characteristics of the rupture surface and of the forces which act along it, the probability of failure of the slope was found. Finally the developed procedure has been applied in a case study to yield the reliability of a soil slope.

• Asian Journal of Innovation and Policy
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• v.9 no.2
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• pp.133-144
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• 2020

Korean economy has experienced a very rapid growth largely due to the change of the innovation system since the last half century. The recent outbreak of COVID-19 impacts the global economy as well as Korea's innovation system. In order to understand the influence of the shock to the Korean technological system, we have forecast the future of the system combining qualitative and quantitative techniques such as expert panel, cross impact analysis, and scenario planning. According to the results, we have identified 39 driving forces influencing the change of Korea's technological innovation system. Four scenarios have been suggested based on the predetermined factors and core uncertainties. In other words, uncertainties of emergence of the regions and global value chains generate four scenarios: regional growth, unstable hope, returning to the past, and regional conflicts. The 'regional growth' scenario is regarded as the most preferable, whereas the 'regional conflicts' scenario is unavoidable. In conclusion, we put forward some policy implications to boost the regional innovation system by exploiting the weakened global value chains in order to move on to the most preferable scenario away from the return to the past regime.

• Journal of the Korean Society of Safety
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• v.27 no.6
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• pp.115-121
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• 2012

This paper, being the second in a two-part series, presents the robust performance of the proposed design method which can enhance a reliability-based design optimization(RBDO) under the uncertainties of probabilistic models. The robust performances of the solutions obtained by the proposed method, described in the Part 1, are investigated through the parametric studies. A 10-bar truss example is considered, and the uncertain parameters include the number of data observed, and the variations of applied loadings and allowable stresses. The numerical results show that the proposed method can produce a consistent result despite of the large variations in the parameters. Especially, even with the relatively small data set, the analysis results show that the exact probabilistic model can be successfully predicted with optimized design sections. This consistency of estimating appropriate probability model is also observed in the case of the variations of other parameters, which verifies the robustness of the proposed method.

• Smart Structures and Systems
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• v.31 no.1
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• pp.29-43
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• 2023

This study investigates the possibility of damage detection of a real bridge by means of a modal parameter-based finite element (FE) model update. Field moving vehicle experiments were conducted on an actual steel plate girder bridge. In the damage experiment, cracks were applied to the bridge to simulate damage states. A fast Bayesian FFT method was employed to identify and quantify uncertainties of the modal parameters then these modal parameters were used in the Bayesian model update. Material properties and boundary conditions are taken as uncertainties and updated in the model update process. Observations showed that although some differences existed in the results obtained from different model classes, the discrepancy between modal parameters of the FE model and those experimentally obtained was reduced after the model update process, and the updated parameters in the numerical model were indeed affected by the damage. The importance of boundary conditions in the model updating process is also observed. The capability of the MCMC model update method for application to the actual bridge structure is assessed, and the limitation of FE model update in damage detection of bridges using only modal parameters is observed.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.135-143
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• 2014

In this study, Chungju inflow was simulated for climate change considering the uncertainties of GCMs and a stochastic model. TFN (Transfer Function Noise) model and 4 different GCMs (CNRM, CSIRO, CONS, UKMO) based on IPCC AR4 A2 scenario were used. In order to evaluate uncertainty of TFN model, 100 cases of noises are applied to the TFN model. Thus, 400 cases of inflow results are simulated. Future inflows according to the GCMs show different rates of changes for the future 3 periods relative to the past 30-years reference period. As the results, the summer inflow shows increasing trend and the spring inflow shows decreasing trend based on AR4 A2 scenario.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.197-197
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• 2016

Forecasting future drought events in a region plays a major role in water management and risk assessment of drought occurrences. The creeping characteristics of drought make it possible to mitigate drought's effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, a new probabilistic scheme is proposed to forecast droughts, in which a discrete-time finite state-space hidden Markov model (HMM) is used aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The 3-month standardized precipitation index (SPI) is employed to assess the drought severity over the selected five stations in South Kore. A reversible jump Markov chain Monte Carlo algorithm is used for inference on the model parameters which includes several hidden states and the state specific parameters. We perform an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to derive a probabilistic forecast that considers uncertainties. Results showed that the HMM-RCP forecast mean values, as measured by forecasting skill scores, are much more accurate than those from conventional models and a climatology reference model at various lead times over the study sites. In addition, the probabilistic forecast verification technique, which includes the ranked probability skill score and the relative operating characteristic, is performed on the proposed model to check the performance. It is found that the HMM-RCP provides a probabilistic forecast with satisfactory evaluation for different drought severity categories, even with a long lead time. The overall results indicate that the proposed HMM-RCP shows a powerful skill for probabilistic drought forecasting.