• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.873-876
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• 2002

This paper presents the effect of internal corrosion, external corrosion, material properties, operation condition, earthquake, traffic load and design thickness in pipeline on the failure prediction using a failure probability model. A nonlinear corrosion is used to represent the loss of pipe wall thickness with time. The effects of environmental, operational, and design random variables such as a pipe diameter, earthquake, fluid pressure, a corrosion rate, a material yield stress and a pipe thickness on the failure probability are systematically investigated using a failure probability model for the corrosion pipeline.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.834-837
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• 2004

In this study, the electric accelerated reinforcing bar corrosion test was carried out to estimate the coefficient of electrolytic corrosion based on the concept of Faraday's law according to rebar corrosion rate and concrete compressive strength which had an effect on the actual corrosion mass loss. The results of this paper allow the prediction of corrosion amount in the electric accelerated reinforcing bar corrosion test method.

• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.403-410
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• 2002

This paper presents the effect of internal corrosion, external corrosion, material properties, operation condition, earthquake, traffic load and design thickness in pipeline on the failure prediction using a failure probability model. A nonlinear corrosion is used to represent the loss of pipe wall thickness with time. The effects of environmental, operational, and design random variables such as a pipe diameter, earthquake, fluid pressure, a corrosion rate, a material yield stress and a pipe thickness on the failure probability are systematically investigated using a failure probability model for the corrosion pipeline.

• Journal of the Korea institute for structural maintenance and inspection
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• v.4 no.1
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• pp.121-129
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• 2000

In general. service life of the sea-shore concrete structures is largely influenced by the corrosion of reinforcing steel due to the chloride contamination, and the penetration of chloride ions into concrete is governed by concrete condition state as a micro-structure. In this study, characteristics of chloride diffusion in concrete are analyzed in accordance with the mixing properties and durability of concrete, by considering the facts that micro-structure of concrete varies with the mixing properties and can indirectly be analyzed by using the durability test. In order to predict the service life of existing concrete structures, chloride diffusion equation for the concrete structures under various service conditions and the major parameters used in that equation are formulated as the mathematical models. Based on the results of chloride diffusion analysis in accordance with the mixing properties and durability of concrete and mathematical models formulated in this study, a prediction system is developed to predict the corrosion initiation of reinforcing steel in the sea-shore concrete structures.

• Corrosion Science and Technology
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• v.19 no.6
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• pp.302-309
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• 2020

This study aimed to predict the pitting corrosion characteristics of AL-6XN super-austenitic steel using multiple linear regression. The variables used in the model are degree of sensitization, temperature, and pH. Experiments were designed and cyclic polarization curve tests were conducted accordingly. The data obtained from the cyclic polarization curve tests were used as training data for the multiple linear regression model. The significance of each factor in the response (critical pitting potential, repassivation potential) was analyzed. The multiple linear regression model was validated using experimental conditions that were not included in the training data. As a result, the degree of sensitization showed a greater effect than the other variables. Multiple linear regression showed poor performance for prediction of repassivation potential. On the other hand, the model showed a considerable degree of predictive performance for critical pitting potential. The coefficient of determination (R2) was 0.7745. The possibility for pitting potential prediction was confirmed using multiple linear regression.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.2096-2101
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• 1999

This paper presents the effect of shape of external corrosion in pipeline on failure prediction by using numerical simulation. The numerical study for the pipeline failure analysis is based on the FEM(Finite Element Method) with an elastic-plastic and large-deformation analysis. The predicted failure stress assessed for the simulated corrosion defects having different corroded shapes along the pipeline axis are compared with those by methods specified in ANSl/ASME B31G code and a modified B31G code.

• Computers and Concrete
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• v.2 no.4
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• pp.325-343
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• 2005

Chloride ingress is a common cause of deterioration of reinforced concrete located in coastal zone. Modeling the chloride ingress is an important basis for designing reinforced concrete structures and for assessing the reliability of an existing structure. The modeling is also needed for predicting the deterioration of a reinforced structure. The existing deterministic solution for prediction model of corrosion initiation cannot reflect uncertainties which input variables have. This paper presents an approach to the fuzzy arithmetic based modeling of the chloride-induced corrosion of reinforcement in concrete structures that takes into account the uncertainties in the physical models of chloride penetration into concrete and corrosion of steel reinforcement, as well as the uncertainties in the governing parameters, including concrete diffusivity, concrete cover depth, surface chloride concentration and critical chloride level for corrosion initiation. There are a lot of prediction model for predicting the time of reinforcement corrosion of structures exposed to chloride-induced corrosion environment. In this work, RILEM model formula and Crank's solution of Fick's second law of diffusion is used. The parameters of the models are regarded as fuzzy numbers with proper membership function adapted to statistical data of the governing parameters instead of random variables of probabilistic modeling of Monte Carlo Simulation and the fuzziness of the time to corrosion initiation is determined by the fuzzy arithmetic of interval arithmetic and extension principle. An analysis is implemented by comparing deterministic calculation with fuzzy arithmetic for above two prediction models.

• Corrosion Science and Technology
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• v.8 no.2
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• pp.81-88
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• 2009

Chloride induced corrosion of steel reinforcement inside concrete is a major concern for concrete structures exposed to a marine environment. It is well known that transport of chloride ions in concrete occurs mainly through ionic/molecular diffusion, as a gradient of chloride concentration in the concrete pore solution is set. In the process of chloride transport, a portion of chlorides are bound in cement matrix then to be removed in the pore solution, and thus only the rest of chlorides which are not bound (i.e. free chlorides) leads the ingress of chlorides. However, since the measurement of free/bound chloride content is much susceptible to environmental conditions, chloride profiles expressed in total chlorides are evaluated to use in many studies In this study, the capacity of chloride binding in cement matrix was monitored for 150 days and then quantified using the Langmuir isotherm to determine the portions of free chlorides and bound chlorides at given total chlorides and the redistribution of free chlorides. Then, the diffusion of chloride ion in concrete was modeled by considering the binding capacity for the prediction of chloride profiles with the redistribution. The predicted chloride profiles were compared to those obtained from conventional model. It was found that the prediction of chloride profiles obtained by the model has shown slower diffusion than those by the conventional ones. This reflects that the prediction by total chloride may overestimate the ingress of chlorides by neglecting the redistribution of free chlorides caused by the binding capacity of cement matrix. From the evaluation, it is also shown that the service life prediction using the free chloride redistribution model needs different expression for the chloride threshold level which is expressed by the total chlorides in the conventional diffusion model.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4060-4066
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• 2021

Flow-accelerated corrosion (FAC) of carbon steel piping is a significant problem in nuclear power plants. The basic process of FAC is currently understood relatively well; however, the accuracy of prediction models of the wall-thinning rate under an FAC environment is not reliable. Herein, we propose a methodology to construct pipe wall-thinning rate prediction models using artificial neural networks and a convolutional neural network, which is confined to a straight pipe without geometric changes. Furthermore, a methodology to generate training data is proposed to efficiently train the neural network for the development of a machine learning-based FAC prediction model. Consequently, it is concluded that machine learning can be used to construct pipe wall thinning rate prediction models and optimize the number of training datasets for training the machine learning algorithm. The proposed methodology can be applied to efficiently generate a large dataset from an FAC test to develop a wall thinning rate prediction model for a real situation.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.04a
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• pp.71-76
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• 1996

Recently, large scale concrete structures exposed to severe environment are increasingly built in various locations. The corrosion may affect severely the durability and service life of such a concrete structure. It is, therefore, necessary to develop durable concrete to enhance the corrosion resistance. The corrosion resistance of concrete can be identified through accelerated corrosion test. The purpose of the present paper is, therefore, to devise a reasonable and accurate method to predict the amount of corrosion of reinforcing steels. The proposed method which is basically based on the concept of Faraday's Law, determines the corroded amount of a re-bar according to accelerated corrosion time. The corrosion is accelerated by employing the potentiometric corrosion test arrangement. The effects of admixtures in concrete including fly ash and silica fume have been also studied to explore the relative corrosion resistance of concrete.