• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 봄 학술발표회 논문집
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• pp.682-687
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• 2000

In this research the remaining service life of the concrete due to the steel corrosion was predicted by three cases; causing carbonation, using sea sand, using deicing salts. In case of deterioration by carbonation, effective carbonation depth, effective coverage depth and relative humidity are considered for predicting method. In case of using sea sand, predicting method is made of rust growth equation from polarization resistance method. In case of using deicing salts, predicting method is made of transformation of Fick's law. Three methods are very useful in predicting service life of concrete.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2013년도 추계 학술논문 발표대회
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• pp.64-65
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• 2013

Recently, people are concerned about how to maintain structure well because of safety. For effective maintenance of the structure, it should be resolved about carbonation, Durability, and Service Life issues. Solving that problem will Increase Safety of Structure. The carbonation velocity is produced an effect on carbon dioxide density of surrounding near structures, the concrete quality Therefore, This study compares the Velocity of carbonation due to maintenance of the structure. Also, this study will find Service Life of Concrete Structure through Predicting Carbonation Depth.

• 한국안전학회지
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• 제30권6호
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• pp.102-109
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• 2015

In this study, on the basis of the results of the field survey and the theoretical consideration for Korean Standard Specification for concrete durability and maintenance, the following conclusions are derived. From the survey, the prediction equation of carbonation depth for the southwest region in Korea is experimentally proposed, $y_p=5.865{\sqrt{t}}$, which predicts about 60mm of the carbonation depth for the concrete structures of 100 years, a 1st class of target endurance period, under a combined deterioration environment like a marine environment. Considering that the marginal value for a carbonation depth limitation under very severely marine environment is 25mm, in accordance with the Specification, it is found that the predicting carbonation depth for the concrete cover depths, 100mm and 60mm are 63mm and 29.4mm, respectively. In conclusion, according to the equation and the Specification, it is strongly required that the reinforced concrete structures with the cover depth under 100mm have to make a protection from combined deterioration factors by any methods like a surface coating, an increment of cover depth or an application of a special concrete.

• KIEAE Journal
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• 제10권3호
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• pp.103-110
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• 2010

Carbonation is one of the major deterioration factors for concrete. So. lots of researchers have proposed the equations for determining carbonated depth and the initial time of steel corrosion due to carbonation to predict the service life of concrete structures. However, there are large gaps among the equations for predicting carbonation because each researcher has different considering factors to predict carbonation depth. So, in this study, we calculated the deviations of the proposed equations for carbonation, and we calculated each researcher different corrosion initiation time. However, it has a lot of deviation. Therefore, we evaluated the probability of steel corrosion considering each deviation using MCS, an analysis method based on probability theory. In the results, we have proposed much advanced information for determining service life of reinforced concrete structures due to carbonation.

• 한국공간구조학회논문집
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• 제23권4호
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• pp.81-88
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• 2023

Numerous factors contribute to the deterioration of reinforced concrete structures. Elevated temperatures significantly alter the composition of the concrete ingredients, consequently diminishing the concrete's strength properties. With the escalation of global CO2 levels, the carbonation of concrete structures has emerged as a critical challenge, substantially affecting concrete durability research. Assessing and predicting concrete degradation due to thermal effects and carbonation are crucial yet intricate tasks. To address this, multiple prediction models for concrete carbonation and compressive strength under thermal impact have been developed. This study employs seven machine learning algorithms-specifically, multiple linear regression, decision trees, random forest, support vector machines, k-nearest neighbors, artificial neural networks, and extreme gradient boosting algorithms-to formulate predictive models for concrete carbonation and thermal impact. Two distinct datasets, derived from reported experimental studies, were utilized for training these predictive models. Performance evaluation relied on metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analytical outcomes demonstrate that neural networks and extreme gradient boosting algorithms outshine the remaining five machine learning approaches, showcasing outstanding predictive performance for concrete carbonation and thermal effect modeling.

• 콘크리트학회논문집
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• 제12권5호
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• pp.69-80
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• 2000

This paper presents the prediction of remaining service life of the concrete due to steel corrosion caused by the following three cases; carbonation, using sea sand and using deicing salts. The assessment of initiation period was generalized considering the existing perdiction models in the literature, corrosion experiment and field assessment. To evaluate the prediction equation of rust growth, the corrosion accelerating experiments was performed. The polarization resistance was measured by potentiostat and the conversion coefficient of polarzation resistance to corrosion rate was determined by the measurement of real mass loss. Chloride content, carbonation, cover depth, relative humidity, water-cement ratio(W/C), and the use of deicing salts were taken into account and the resulting prediction equation of rust growth was proposed on the basis of these properties. The proposed equation is to predict the rust growth during any specified period of time and be effective in particular for predicting service life of concrete in the case of using sea sand.

• 한국건축시공학회지
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• 제17권3호
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• pp.235-243
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• 2017

본 연구에서는 탄산화가 이미 진행된 콘크리트 구조물을 대상으로 촉진 탄산화 실험을 실시하였다. 각 보수재별 탄산화 속도계수를 도출 후 보수후의 탄산화 진행 예측식을 이용하여 탄산화 진행 예측한다. 또한 신뢰성 확보를 위하여 FDM과 FEM 해석을 통한 탄산화 깊이 예측을 비교했다. 그 결과 보수후 탄산화 예측식을 이용하면 탄산화 깊이를 예측할 수 있으며, 초기 $Ca(OH)_2$ 농도 40%로 가정할 때 해석 값과 실험값이 거의 유사함을 알 수 있었다.

• 콘크리트학회논문집
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• 제15권4호
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• pp.529-540
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• 2003

최근 콘크리트 내구성설계에 관한 연구가 활발히 진행되고 있으며, 사용수명 예측이 핵심인 내구성 평가모델 개발이 그 좋은 예이다. 본 연구에서는 콘크리트 구조물의 잔존수명예측 모델을 개발하여 적정시기의 유지보수를 통한 경제적 구조물 사용을 목적으로 하였다. 육지 콘크리트 구조물인 저수지의 콘크리트 구조물 부분을 대상으로 전국 70개 지구를 선정하고, TG/DTA 법과 페놀프탈레인 지시약법으로 중성화를, pH메타법으로 pH 값을 측정하여 탄산칼슘함량 대비 사용연수, pH값, 콘크리트 피복 두께의 관계함수를 각각 유도한 후 가능한 최소의 자료측정으로 잔존수명을 예측할 수 있는 모델을 개발하였다. 개발된 잔존수명예측 모델은 탄산가스등의 고정변수에 의한 실내촉진실험 자료기반 모델과 달리 동결융해작용, 중성화, 철근 부식 등 복합적인 열화작용이 동시에 일어나는 현장의 환경적 영향을 받은 구조물에서 측정한 자료를 기반으로 개발되었다. 이러한 점에서 그 신뢰성을 높게 평가 받을 수 있을 것이며, 시설물 유지관리자에게 적정 보수보강 시점을 제공하여 경제적인 구조물 사용에 도움을 줄 수 있을 것으로 판단된다.

• 콘크리트학회논문집
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• 제19권3호
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• pp.385-389
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• 2007

In this study, it was investigated the resistance of OPC, 60% GGBS, 20% PFA and 10% SF mortar specimens against sulfuric acid corrosion. As an index for degree of acid corrosion, the corrosion depth was evaluated. Then, it was found that an increase in the duration of immersion and a decrease in the pH, as expected, resulted in a more severe corrosion irrespective of binders; 60% GGBS mortar specimen was the most resistant to sulfuric acid corrosion. From the laboratory testing of sulfuric acid corrosion, an empirical prediction model was suggested as a power function of time and the pH of sulfuric acid, and was applied to an assessment of concrete structures exposed to an acidic environment. It was found that the empirical model gave a more precise prediction of sulfuric acid deterioration of concrete rather than a conventional model, mostly used for predicting carbonation of concrete.