• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.2
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• pp.80-83
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• 2002

The effect of chloride content on the corrosion of reinforced bar in concrete was studied. The mixing ratio of the concrete was 1 : 1.78 : 5.35 : 4.73 (water : content : ballast : sand). The studied chloride content was in the range of 0∼3.5 wt%. The corrosion potentials were measured in every week for two years. The copper-copper sulfate electrode (CSE) was employed as a reference electrode. After two years, the corroded structure was examined and compared to measured corrosion potential. Any visible difference was founded in the specimen located indoor and outdoor. The chloride concentration enhanced rusting and reinforced bar, shifting the potential to active range. The results showed good argument with Van daveer criteria. In 3.5 wt% chloride, the potential shifted belong -350 mV after 58week. Specimen in 1.75 wt% chloride, showed the potential between -200 mV∼-350 mV. However those in free chloride solution maintained above -200 mV for the studied period. It can the concluded that the chloride enhanced corrosion of rebar in concrete and the electrochemical potential can be a promising corrosion monitoring technique.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.2
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• pp.16-22
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• 2006

Stainless steel has widely been used in various industrial fields because it has high corrosion resistance. But, we have little design data about the creep life prediction of SUS316L stainless steel. Therefore, in this study, a series of creep tests and study on them under 16 constant stress and temperature combined conditions have been performed to get the creep design data and life prediction of SUS316L stainless steels and we have gotten the following results. First, the stress exponents decrease as the test temperatures increase. Secondly, the creep activation energy gradually decreases as the stresses become bigger. Thirdly, the constant of Larson-Miller parameters on this alloy is estimated about 10. And last, the creep rupture fractographs show the intergranular ductile fracture with many dimples.

• Computers and Concrete
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• v.13 no.1
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• pp.71-82
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• 2014

Chloride ion ingress is one of the major problems that affect the durability of concrete structures such as bridge decks, concrete pavements, and other structures exposed to harsh saline environments. Therefore, durability based design of concrete structures in severe condition has gained great significance in recent decades and various mathematical models for estimating the service life of rein-forced concrete have been proposed. In spite of comprehensive researches on the corrosion of rein-forced concrete, there are still various controversial concepts in quantitation of durability parameters such as chloride diffusion coefficient and surface chloride content. Effect of environment conditions on the durability of concrete structures is one of the most important issues. Hence, regional investigations are necessary for durability based design and evaluation of the models. Persian Gulf is one of the most aggressive regions of the world because of elevated temperature and humidity as well as high content of chloride ions in seawater. The aim of this study is evaluation of some parameters of durability of RC structures in marine environment from viewpoint of corrosion initiation. For this purpose, some experiments were carried out on the real RC structures and in laboratory. The result showed that various uncertainties in parameters of durability were existed.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.14 no.1
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• pp.11-19
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• 2016

This paper focuses on the estimation of durability and service-life of reinforced concrete structures in Wolsong Low- and intermediate-level wastes Disposal Center (WLDC) in Korea. There are six disposal silos located in the saturated environment. The silo concrete is degraded due to reactions with groundwater and chemical attacks, and finally it will lose its properties as a transport barrier. The infiltration of sulfate and magnesium, leaching of potassium hydroxide, and chlorine induced corrosion are the most significant factors for degradation of reinforced concrete structure in underground environment. From the result of evaluation of the degradation time for each factor, the degradation rate of the reinforced concrete due to sulfate and magnesium is $1.308{\times}10^{-3}cm/yr$, and it is estimated to take 48,000 years for full degradation while potassium hydroxide is leached in depth of less than 1.5 cm at 1,000 years after the initiation of degradation. In case of chlorine induced corrosion, it takes 1,648 years to initiate corrosion in the main reinforced bar and 2,288 years to reach the lifetime limit of the structural integrity, and thus it is evaluated as the most significant factor.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1280-1289
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• 2005

This paper presents the effects of corrosion environments of failure pressure model for buried pipelines on failure prediction by using a failure probability. The FORM (first order reliability method) is used in order to estimate the failure probability in the buried pipelines with corrosion defects. The effects of varying distribution types of random variables such as normal, lognormal and Weibull distributions on the failure probability of buried pipelines are systematically investigated. It is found that the failure probability for the MB31G model is larger than that for the B31G model. And the failure probability is estimated as the largest for the Weibull distribution and the smallest for the normal distribution. The effect of data scattering in corrosion environments on failure probability is also investigated and it is recognized that the scattering of wall thickness and yield strength of pipeline affects the failure probability significantly. The normalized margin is defined and estimated. Furthermore, the normalized margin is used to predict the failure probability using the fitting lines between failure probability and normalized margin.

• Computers and Concrete
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• v.22 no.2
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• pp.167-182
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• 2018

The modeling of loss of bond between reinforcing bars (rebars) and concrete due to corrosion is useful in studying the behavior and prediction of residual load bearing capacity of corroded reinforced concrete (RC) members. In the present work, first the possibility of using different methods to simulate the rebars-concrete bonding, which is used in three-dimensional (3D) finite element (FE) modeling of corroded RC beams, was explored. The cohesive surface interaction method was found to be most suitable for simulating the bond between rebars and concrete. Secondly, using the cohesive surface interaction approach, the 3D FE modeling of the behavior of non-corroded and corroded RC beams was carried out in an ABAQUS environment. Experimental data, reported in literature, were used to validate the models. Then using the developed models, a parametric study was conducted to examine the effects of some parameters, such as degree and location of the corrosion, on the behavior and residual capacity of the corroded beams. The results obtained from the parametric analysis using the developed model showed that corrosion in top compression rebars has very small effect on the flexural behaviors of beams with small flexural reinforcement ratio that is less than the maximum ratio specified in ACI-318-14 (singly RC beam). In addition, the reduction of steel yield strength in tension reinforcement due to corrosion is the main source of reducing the load bearing capacity of corroded RC beams. The most critical corrosion-induced damage is the complete loss of bond between rebars and the concrete as it causes sudden failure and the beam acts as un-reinforced beam.

• 한국신재생에너지학회:학술대회논문집
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• 2011.11a
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• pp.63.1-63.1
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• 2011

To analyze the phenomenon of corrosion in the PV module, we experimented damp heat test at $85^{\circ}C$/85% relative humidity(RH) and $65^{\circ}C$/85% RH for 2,000 hours, respectively. We used 30 mini-modules designed of 6inch one cell. Despite of 2,000 hours test, measured $P_{max}$ is not reached failure which is defined less than 80% compared to initial $P_{max}$. Therefore, we calculate proper curve fitting over 2,000 hours. Data less than 80% $P_{max}$ is found and B10 lifetime is calculated by the number of failure specimens and weibull distribution. Using B10 lifetime that the point of failure rate 10% and Peck's model, the predictable equation of lifetime was derived under temperature and humidity condition.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.15 no.2
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• pp.64-70
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• 2019

In recent years, attention has been paid to the integrity of steam generator (SG) tubes due to severe accident and beyond design basis accident conditions. In these transient conditions, steam generator tubes may be damaged by high temperature and pressure, which might result in a risk of fission products being released to the environment due to the failure. Alloy 690 which has increased the Cr content has been replaced for the SG tube due to its high corrosion resistance against stress corrosion cracking (SCC). However, there is lack of research on the high temperature creep rupture and life prediction model of Alloy 690. In this study, creep test was performed to estimate the high temperature creep rupture life of Alloy 690 using tube specimens. Based on manufacturer's creep data and creep test results performed in this study, creep life prediction was carried out using the Larson-Miller (LM) Parameter, Orr-Sherby-Dorn (OSD) parameter, Manson-Haford (MH) parameter, and Wilshire's approach. And a hyperbolic sine (sinh) function to determine master curves in LM, OSD and MH parameter methods was used for improving the creep life estimation of Alloy 690 material.

• Corrosion Science and Technology
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• v.20 no.2
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• pp.62-68
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• 2021

Artificial neural network techniques show an excellent ability to predict the data (output) for various complex characteristics (input). It is primarily specialized to solve nonlinear relationship problems. This study is an experimental investigation that applies artificial neural network techniques and an experimental design to predict the cyclic polarization curves of the super-austenitic stainless steel AL-6XN alloy with sensitization. A cyclic polarization test was conducted in a 3.5% NaCl solution based on an experimental design matrix with various factors (degree of sensitization, temperature, pH) and their levels, and a total of 36 cyclic polarization data were acquired. The 36 cyclic polarization patterns were used as training data for the artificial neural network model. As a result, the supervised learning algorithms with back-propagation showed high learning and prediction performances. The model showed an excellent training performance (R²=0.998) and a considerable prediction performance (R²=0.812) for the conditions that were not included in the training data.

• Corrosion Science and Technology
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• v.20 no.2
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• pp.52-61
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• 2021

This study using experimental design and linear regression technique was implemented in order to predict the pitting potential of stainless steel in marine environments, with the target materials being AL-6XN and STS 316L. The various variables (inputs) which affect stainless steel's pitting potential included the pitting resistance equivalent number (PRNE), temperature, pH, Cl^- concentration, sulfate levels, and nitrate levels. Among them, significant factors affecting pitting potential were chosen through an experimental design method (screening design, full factor design, analysis of variance). The potentiodynamic polarization test was performed based on the experimental design, including significant factor levels. From these testing methods, a total 32 polarization curves were obtained, which were used as training data for the linear regression model. As a result of the model's validation, it showed an acceptable prediction performance, which was statistically significant within the 95% confidence level. The linear regression model based on the full factorial design and ANOVA also showed a high confidence level in the prediction of pitting potential. This study confirmed the possibility to predict the pitting potential of stainless steel according to various variables used with experimental linear regression design.