• Computers and Concrete
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• v.15 no.4
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• pp.589-606
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• 2015

It is well-documented that the major deterioration of coastal RC structures is chloride-induced corrosion. Therefore, regional investigations are necessary for durability based design and evaluation of the proposed service life prdiction models. In this paper, four reinforced concrete jetties exposed to severe marine environment were monitored to assess the long term chloride penetration at 6 months to 96 months. Also, some accelerated durability tests were performed on standard samples in laboratory. As a result, two time-dependent equations are proposed for basic parameters of chloride diffusion into concrete and then the corrosion initiation time is estimated by a developed probabilistic service life model Also, two famous service life prediction models are compared using chloride profiles obtained from structures after about 40 years in the tidal exposure conditions. The results confirm that the influence of concrete quality on diffusion coefficients is related to the concrete pore structure and the time dependence is due to chemical reactions of sea water ions with hydration products which lead a reduction in pore structure. Also, proper attention to the durability properties of concrete may extend the service life of marine structures greater than fifty years, even in harsh environments.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2547-2555
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• 2021

The frequency of reactor coolant leakage is expected to increase over the lifetime of a nuclear power plant owing to degradation mechanisms, such as flow-acceleration corrosion and stress corrosion cracking. When loss of coolant accidents (LOCAs) occur, several parameters change rapidly depending on the size and location of the cracks. In this study, leak flow during LOCAs is predicted using a deep fuzzy neural network (DFNN) model. The DFNN model is based on fuzzy neural network (FNN) modules and has a structure where the FNN modules are sequentially connected. Because the DFNN model is based on the FNN modules, the performance factors are the number of FNN modules and the parameters of the FNN module. These parameters are determined by a least-squares method combined with a genetic algorithm; the number of FNN modules is determined automatically by cross checking a fitness function using the verification dataset output to prevent an overfitting problem. To acquire the data of LOCAs, an optimized power reactor-1000 was simulated using a modular accident analysis program code. The predicted results of the DFNN model are found to be superior to those predicted in previous works. The leak flow prediction results obtained in this study will be useful to check the core integrity in nuclear power plant during LOCAs. This information is also expected to reduce the workload of the operators.

• Journal of Korean Association for Spatial Structures
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• v.23 no.3
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• pp.87-94
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• 2023

Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.

• Geomechanics and Engineering
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• v.18 no.4
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• pp.373-389
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• 2019

It is important to study the problem of durability for tunnel structures. As a main influence on the durability of tunnel structures, carbonation-induced corrosion is studied. For the complicated environment of tunnel structures, based on the data samples from real engineering examples, the intelligent method (genetic programming) is used to construct the service life prediction model of tunnel structures. Based on the model, the prediction of service life for tunnel structures in carbonation environments is studied. Using the data samples from some tunnel engineering examples in China under carbonation environment, the proposed method is verified. In addition, the performance of the proposed prediction model is compared with that of the artificial neural network method. Finally, the effect of two main controlling parameters, the population size and sample size, on the performance of the prediction model by genetic programming is analyzed in detail.

• Corrosion Science and Technology
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• v.12 no.3
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• pp.125-131
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• 2013

The most common pipe wall thinning degradation mechanisms that can occur in the steam and feedwater systems are FAC (Flow Acceleration Corrosion), cavitation, flashing, and LDIE (Liquid Droplet Impingement Erosion). Among those degradation mechanisms, FAC has been investigated by many laboratories and industries. Cavitation and flashing are also protected on the piping design phase. LDIE has mainly investigated in aviation industry and turbine blade manufactures. On the other hand, LDIE has been little studied in NPP (Nuclear Power Plant) industry. This paper presents the development of prediction system for pipe wall thinning caused by LDIE in terms of erosion rate based on air-water ratio and material. Experiment is conducted in 3 cases of air-water ratio 0.79, 1.00, and 1.72 using the three types of the materials of A106B, SS400, and A6061. The main control parameter is the air-water ratio which is defined as the volumetric ratio of water to air (0.79, 1.00, 1.72). The experiments were performed for 15 days, and the surface morphology and hardness of the materials were examined for every 5 days. Since the spraying velocity (v) of liquid droplets and their contact area ($A_c$) on specimens are changed according to the air-water ratio, we analyzed the behavior of LDIE for the materials. Finally, the prediction equations(i.e. erosion rate) for LDIE of the materials were determined in the range of the air-water ratio from 0 to 2%.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.1037-1040
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• 2008

In order to predict the remaining life of marine concrete structures under climatic loads, it is necessary to develop an analytical approach to predict the time and space dependent deterioration of concrete structures due to mainly chloride attack up to corrosion initiation and additional deterioration like cracking of cover concrete. This study aims to introduce FEM model for life-time simulation of concrete structures subjected to chloride attack. In order to consider uncertainties in materials as well as environmental parameters for the prediction, Monte Carlo Simulation is integrated in that FEM modeling for reliability-based remaining service life prediction. The paper is organized as follows: firstly general scheme for reliability-based remaining service life of concrete structures is introduced, then the FEM models for chloride penetration, corrosion product expansion and cover cracking are briefly explained, finally an example is demonstrated and the effects of localization of chloride concentration and corrosion product expansion on service life using above model are discussed.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.513-516
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• 2008

In this study the prediction model of Chloride Ion progress rate of concrete using steel powder as an addition is developed, in which the reduction of not only the diffusion rate of $Cl^-$ but also the corrosion rate by replenishment of pore by corrosion products. The model is based on the diffusions of $Cl^-$ and its reaction with $Fe^{2+}$, in chloride attack progression region. The model can also explain the characteristics of chloride ion permeation resistance of concrete that the matrix is densified due to corrosion products. The prediction by the model agreed well the experimental data in which the concrete using steel powder, and it showed the lower rate in long-term age to Chloride Ion progress rate than the concrete without steel powder. Consequently the model can predict Chloride Ion progress rate of concrete exposed in the atmosphere regardless of the water-to-cement raito, the amount of the content of steel powder, etc.

• Corrosion Science and Technology
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• v.12 no.6
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• pp.265-273
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• 2013

Ti-stabilized 11 wt% Cr ferritic stainless steels (FSSs) for automotive exhaust systems have been experienced intergranular corrosion (IC) in some heat-affected zone (HAZ). The effects of sensitizing heat-treatment and silicon on IC were studied. Time-Temperature-Sensitization (TTS) curves showed that sensitization to IC was observed at the steels heat-treated at the temperature lower than $650^{\circ}C$ and that silicon improved IC resistance. The sensitization was explained by chromium depletion theory, where chromium is depleted by precipitation of chromium carbide during sensitizing heat-treatment. It was confirmed with the results from the analysis of precipitates as well as the thermodynamical prediction of stable phases. In addition, the role of silicon on IC was explained with the stabilization of grain boundary. In other words, silicon promoted the formation of the grain boundaries with low energy where precipitation was suppressed and consequently, the formation of Cr-depleted zone was retarded. The effect of silicon on the formation of grain boundaries with low energy was proved by the analysis of coincidence site lattice (CSL) grain boundary, which is a typical grain boundary with low energy.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.5
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• pp.737-745
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• 2006

The goal of this study is to present an external pit corrosion rate($p_{ecr}$) model with considering both the age of pipe and the soil characteristics. The correlation of nonlinear exponential model among conventional empirical models was a little higher than other empirical models in the prediction of $p_{ecr}$ according to the age of pipe. However, there has been a limit to predict Peer with the model by using only a pipe age since installation as a variable. The soil analysis results from sixty nine samples showed that all of the samples were non corrosive in the assessment of ANSI/AWWA scoring system. The correlation of soil corrosion factors and $p_{ecr}$ was also low. The application result of linear and nonlinear regression models that soil characteristics only showed a low correlation with $p_{ecr}$ Proposed nonlinear regression model in this study, with considering both the age of pipe and the soil characteristics, showed a little higher correlation ($R^2=0.46$) than conventional model.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.3
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• pp.435-451
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• 2015

Evaluation of the performance of aging structures is essential in the oil and gas industry, where the inaccurate prediction of structural performance can have significantly hazardous consequences. The effects of structure failure due to the significant reduction in wall thickness, which determines the burst strength, make it very complicated for pipeline operators to maintain pipeline serviceability. In other words, the serviceability of gas pipelines and elbows needs to be predicted and assessed to ensure that the burst or collapse strength capacities of the structures remain less than the maximum allowable operation pressure. In this study, several positions of the corrosion in a subsea elbow made of API X42 steel were evaluated using both design formulas and numerical analysis. The most hazardous corrosion position of the aging elbow was then determined to assess its serviceability. The results of this study are applicable to the operational and elbow serviceability needs of subsea pipelines and can help predict more accurate replacement or repair times.