• Earthquakes and Structures
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• v.13 no.3
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• pp.221-230
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• 2017

One of the important phases of probabilistic performance-based methodology is establishing appropriate probabilistic seismic demand models (PSDMs). These demand models relate ground motion intensity measures (IMs) to demand measures (DMs). The objective of this paper is selection of the optimal IMs in probabilistic seismic demand analysis (PSDA) of the RC high-rise buildings. In selection process features such as: efficiency, practically, proficiency and sufficiency are considered. RC high-rise buildings with core wall structural system are selected as a case study building class with the three characteristic heights: 20-storey, 30-storey and 40-storey. In order to determine the most optimal IMs, 720 nonlinear time-history analyses are conducted for 60 ground motion records with a wide range of magnitudes and distances to source, and for various soil types, thus taking into account uncertainties during ground motion selection. The non-linear 3D models of the case study buildings are constructed. A detailed regression analysis and statistical processing of results are performed and appropriate PSDMs for the RC high-rise building are derived. Analyzing a large number of results it are adopted conclusions on the optimality of individual ground motion IMs for the RC high-rise building.

• Computational Structural Engineering
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• v.2 no.2
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• pp.93-99
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• 1989

Since 1960's, structural engineers have recognized that the inherent random nature of loadings and materials as well as the imperfect structural analysis may be important factors in the structural safety evaluation. Based on the successful developments of the reliability-based structural analysis and design, the design criteria of the standards are recently developed(or modified) in the light of the probabilistic concepts. To develop the probability - based criteria for the domestic buildings, the probabilistic characteristic of loadings acting on structures should be defined first. In this study, therefore, live load data on apartment buildings have been collected and analyzed in systematic manner, and their probabilistic characteristics have been studied. Based on the results, the lifetime extreme values are computed and compared with current design loads. More rational design loads are suggested, which are more consistent in the probabilistic concepts.

• Journal of the Korean GEO-environmental Society
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• v.10 no.7
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• pp.111-115
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• 2009

In Korea, the probabilistically developed seismic hazard maps are used with deterministically derived seismic site coefficients in developing the design response spectrum of a specific site. Even though the seismic hazard maps and seismic site coefficients are incompatible, the current design code ignores such incompatibility. If the seismic hazard map and seismic coefficients are both developed in identical probabilistic framework, such problems can be solved. Unfortunately, the available method cannot be use to derive "true" probabilistic site coefficients. This study uses the ground motion time histories, which were developed as the result of a new probabilistic seismic hazard analysis in the companion paper, as input motions in performing one-dimensional equivalent linear site response analyses, from which the uniform hazard response spectra are generated. Another important characteristic of the hazard response spectra are that the uncertainties and randomness of the ground properties are accounted for. The uniform hazard spectra are then used to derive probabilistic site coefficients. Comparison of probabilistic and deterministically site coefficients demonstrate that there is a distinct discrepancy between two coefficients.

• 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.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.21-28
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• 2006

Vibration of a non-linear system with multiple degrees of freedom under random parametric excitations was evaluated by probabilistic method. The non-linear characteristic terms of system structure were quasi-linearized and excitation terms were remained as they were. An analytical method where the expectation values of square mean of error was minimized was used. The numerical results were compared with those obtained by Monte Carlo simulation. A linear congruential generator and Box-Muller method were used in Monte Carlo simulation. The comparison showed the results by probabilistic method agreed well with those by Monte Carlo simulation.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.12 s.189
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• pp.72-79
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• 2006

Vibration of a non-linear system under random parametric excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were An analytical method where the square mean of error was minimized was used An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.113-114
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• 2006

Vibration of a non-linear system under random excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were. An analytical method where the square mean of error was minimized was used. An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Structural Engineering and Mechanics
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• v.84 no.6
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• pp.831-849
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• 2022

One of the most prevalent causes of reinforced concrete (RC) structural deterioration is chloride-induced corrosion. This paper aims to provide a comprehensive insight into the environmental effect of RC's chloride ingress process. The first step is to investigate how relative humidity, temperature, and wind influence chloride ingress into concrete. The probability of initiation time of chloride-induced corrosion is predicted using a probabilistic model that considers these aspects. Parametric analysis is conducted on several factors impacting the corrosion process, including the depth of concrete cover, surface chloride concentration, relative humidity, and temperature to expose environmental features. According to the findings, environmental factors such as surface chloride concentration, relative humidity and temperature substantially impact on the time to corrosion initiation. The long- and short-distance impacts are also examined. The meteorological data from the National Meteorological Center of China are collected and used to analyze the environmental characteristics of the chloride ingress issue for structures along China's coastline. Finally, various recommendations are made for improving durability design against chloride attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2259-2277
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• 2023

We propose a probabilistic fish growth model for smart aquaculture systems equipped with IoT sensors that monitor the ecological environment. As IoT sensors permeate into smart aquaculture systems, environmental data such as oxygen level and temperature are collected frequently and automatically. However, there still exists data on fish weight, tank allocation, and other factors that are collected less frequently and manually by human workers due to technological limitations. Unlike sensor data, human-collected data are hard to obtain and are prone to poor quality due to missing data and reading errors. In a situation where different types of data are mixed, it becomes challenging to develop an effective fish growth model. This study explores the unique characteristics of such a combined environmental and weight dataset. To address these characteristics, we develop a preprocessing method and a probabilistic fish growth model using mixed data sampling (MIDAS) and overlapping mixtures of Gaussian processes (OMGP). We modify the OMGP to be applicable to prediction by setting a proper prior distribution that utilizes the characteristic that the ratio of fish groups does not significantly change as they grow. We conduct a numerical study using the eel dataset collected from a real smart aquaculture system, which reveals the promising performance of our model.

• Journal of the Korean Geotechnical Society
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• v.25 no.11
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• pp.87-103
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• 2009

To determine the reliable probabilistic distribution model of geotechnical properties, outlier and randomness test for analysis data, parameter estimation of probabilistic distribution model, and goodness-of-fit test for model parameter and probabilistic distribution model have to be performed in sequence. In this paper, the probabilistic distribution model's geotechnical properties of Songdo area in Incheon are estimated by the above proposed procedure. Also, the coefficient of variation (COV) representing the variability of geotechnical properties is determined for several geotechnical properties. Reliable probabilistic distribution model and COV of geotechnical properties can be used for probability-based design procedure and reasonable choice of design value in deterministic design method.