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

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1682-1685
• /
• 2005

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolerance of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or estimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte-Carlo Method and got the probabilistic sensitivity. The sensitivity of structural response with respect to inconstant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Proceedings of the KIEE Conference
• /
• 2005.07a
• /
• pp.804-806
• /
• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are new iy defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.275-282
• /
• 2006

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolernce of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or etimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte Carlo simulation and got the probabilistic sensitivity. The sensitivity of structural response with respect to in constant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2007.04a
• /
• pp.639-644
• /
• 2007

The accurate peak response estimation of a seismically excited structure with frictional damping system(FDS) is very difficult since the structure with FDS shows nonlinear behavior dependent on the structural period, loading characteristics, and relative magnitude between the frictional force and the excitation load. Previous studies have estimated that by replacing a nonlinear system with an equivalent linear one or by employing the response spectrum obtained based on nonlinear time history and statistical analysis. In the case that on earthquake load is defined with probabilistic characteristics, the corresponding response of the structure with FDS has probabilistic distribution. In this study, nonlinear time history analyses were performed for the structure with FDS subjected to artificial earthquake loads generated using Kanai-Tajimi filter. An equation for the probability density function (PDF) of the displacement response is proposed by adapting the PDF of the normal distribution. Finally, coefficients of the proposed PDF is obtained by regression analysis of the statistical distribution of the time history responses. Finally, the correlation between PDFs and statistical response distribution is presented.

• Journal of the Korea Society for Simulation
• /
• v.26 no.1
• /
• pp.39-46
• /
• 2017

An arrangement of passive sonars is considered to be a fixed underwater surveillance system for detecting an anti-submarine consistently. An effectiveness score for optimizing the arrangement of passive sonars is defined in a function of the probability of detection and localization. These two features contain various probabilistic variations including seasons, sea states, depths of water, etc. Due to this reason, the effectiveness scores show probabilistic characteristics from the input of the arrangement of passive sonars. This paper defines the optimization problem having the results of probabilistic characteristics from various parameters of input conditions. Also, we suggest a simulation-based process of deciding the optimized arrangement of passive sonars using DPSO(Discrete binary version of PSO) method.

• Wind and Structures
• /
• v.30 no.4
• /
• pp.405-421
• /
• 2020

Quayside container cranes are important delivery machineries located in the most frontiers of container terminals, where strong wind attacks happen occasionally. Since the previous researches on quayside container cranes mainly focused on the mean wind load and static response characteristics, the fluctuating wind load and dynamic response characteristics require further investigations. In the present study, the aerodynamic wind loads on quayside container cranes were obtained from wind tunnel tests. The probabilistic and spectral models of the fluctuating aerodynamic loads were established. Then the joint probabilistic distributions of dynamic wind-induced responses were derived theoretically based on a series of Gaussian and independent assumption of resonant components. Finally, the results were validated by time domain analysis using wind tunnel data. It is concluded that the assumptions are acceptable. And the presented approach can estimate peak dynamic sliding force, overturning moments and leg uplifts of quayside container cranes effectively and efficiently.

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

• Proceedings of the KSR Conference
• /
• 2011.05a
• /
• pp.988-992
• /
• 2011

The buckling characteristics of the continuous welded rail track(CWR) is uncertainly varied by many influence factors, such as rail temperature, operating conditions of a train and maintenance of the track etc. Therefore, applying the probabilistic approach method is essential to rationally consider uncertainty and randomness of the various parameters that affect the track buckling. In this study, the probabilistic approach analysis was carried out and the results were compared with the deterministic approach using the buckling probability evaluation system of CWR tracks developed by our research team. From the comparison, it was identified that a probabilistic approach can quantitatively assess the reliability of the CWR tracks based on failure probability and can be used as a tool for decision making in track design, maintenance and operating etc.

• Advances in aircraft and spacecraft science
• /
• v.3 no.4
• /
• pp.503-521
• /
• 2016

Variances in turbomachinery blades caused by manufacturing, operation or regeneration can result in modified structural behavior. In this work, the scatter of geometrical and material properties of a turbine blade and its influence on structure performance is discussed. In particular, the vibration characteristics and the lifetime of a turbine blade are evaluated. Geometrical variances of the surface of the blades are described using the principal component analysis. The scatter in material properties is considered by 16 varying material parameters. Maximum vibration amplitudes and the number of load cycles the turbine blade can withstand are analyzed by finite element simulations incorporating probabilistic principles. The probabilistic simulations demonstrate that both geometrical and material variances have a significant influence on the scatter of vibration amplitude and lifetime. Dependencies are quantified and correlations between varied input parameters and the structural performance of the blade are detected.