• 한국콘크리트학회:학술대회논문집
• /
• 한국콘크리트학회 1999년도 학회창립 10주년 기념 1999년도 가을 학술발표회 논문집
• /
• pp.767-770
• /
• 1999

The carbonation process is affected both by the concrete material properties such as W/C ratio, types of cement and aggregated, admixture characteristics and the environmental factors such as CO2 concentration, temperature, humidity. Based on results of preliminary research on carbonation, this study is to propose a carbonation prediction model by taking into account of prediction model by taking into account of CO2 concentration and W/C ratio among major factors affecting the carbonation process.

• Geomechanics and Engineering
• /
• 제18권4호
• /
• pp.373-389
• /
• 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.

• 한국구조물진단유지관리공학회 논문집
• /
• 제11권5호
• /
• pp.81-88
• /
• 2007

환경노출로부터 야기되는 콘크리트 열화 중에서, 도심지 및 지하구조물의 탄산화에 대한 문제가 증가되고 있다. 그러나 현재 국내 콘크리트 구조물의 탄산화 예측에 사용되는 예측식은 국내 콘크리트 구조물의 노출환경을 고려하지 않고 기존 외국의 문헌에 수록되어 있는 예측식을 직접적으로 사용하여 오차를 수반하게 된다. 본 연구의 목적은 국내에서 시공되는 콘크리트 구조물의 노출환경에 따라 탄산화 깊이를 예측할 수 탄산화 예측식을 제안하는데 있다. 이를 위해, 기존 탄산화 예측식을 분석하였으며, 국내에서 광범위하게 시공된 콘크리트 구조물에 대한 실태조사자료를 이용하여 콘크리트 구조물의 노출환경을 고려한 보정계수를 도출하였다. 최종적으로 보정계수를 강도의 함수로 구현하여 국내의 대표적인 콘크리트 구조물의 노출환경에 따른 탄산화 예측식을 제안하였다.

• 한국건축시공학회:학술대회논문집
• /
• 한국건축시공학회 2010년도 춘계 학술논문 발표대회 1부
• /
• pp.229-230
• /
• 2010

The Carbonation, one of the main deterioration factors of concrete, reduces capacity of members with providing rebar corrosion environment. Consequently it suggested standards of all countries of world, carbonation depth prediction equation of respective researchers and time to rebar corrosion initiation. As a result of carbonation depth prediction equation calculation, difference of time to rebar corrosion initiation is 149 years and difference of carbonation depth prediction equation is 162 years when water cement ratio is 50%. So a study on rebar corrosion with carbonation depth will need existing reliable data and verifications by experiment.

• 한국건축시공학회:학술대회논문집
• /
• 한국건축시공학회 2019년도 춘계 학술논문 발표대회
• /
• pp.30-31
• /
• 2019

Carbonation of the root concrete reduces the durability of the reinforced concrete, and it is important to check the carbonation resistance of the concrete to ensure the durability of the reinforced concrete structure. In this study, a basic study on the prediction of carbonation progress was conducted by considering the mixing conditions of concrete using deep learning algorithm during the theory of artificial neural network theory. The data used in the experiment used values that converted the carbonation velocity coefficient obtained from the mixing conditions of concrete and the accelerated carbonation experiment into the actual environment. The analysis shows that the error rate of the deep learning model according to the Hidden Layer is the best for the model using five layers, and based on the five Hidden layers, we want to verify the predicted performance of the carbonation speed coefficient of the carbonation test specimen in which the exposure experiment took place in the real environment.

• 한국건설순환자원학회논문집
• /
• 제10권3호
• /
• pp.261-268
• /
• 2022

본 연구에서는 국내 환경에서 장기간 옥외 노출 시험을 수행하였으며 이 중 콘크리트의 탄산화 특성에 대해 분석하였다. 시험체는 물/시멘트비에 따라 40 %, 50 % 및 60 %로 총 3종류를 대상으로 수행하였으며, 재령 3년차 및 재령 15년차의 탄산화 측정 및 분석하였으며 이를 대상으로 장기 탄산화 예측 모델을 도출하여 국내외 탄산화 예측 모델과 비교·분석하였다. 분석결과, 물/시멘트비에 따라 탄산화가 증가하는 경향을 보였으며 물/시멘트비 40 %를 기준으로 물/시멘트비 50 %의 경우 약 1.8배, 물/시멘트비 60 %의 경우 약 3.7배 증가하였다. 재령에 따른 탄산화를 비교한 결과 기존 문헌처럼 재령에 따라 증가하는 경향을 보였으며 본 시험체의 경우 재령 15년차 탄산화 값이 재령 3년차 기준 약 3배 정도 높게 나타났다. 본 연구에서 실측한 탄산화를 바탕으로 국내외 탄산화 예측 모델과 비교한 결과 기존 예측 모델과 많은 차이를 보이고 있으며, 추후 지속적으로 데이터를 확보하여 검증 및 개선할 예정이다.

• 콘크리트학회논문집
• /
• 제22권2호
• /
• pp.209-217
• /
• 2010

최근 콘크리트의 탄산화 진행 예측을 위한 수식적 모델들이 보고되고 있으며, 이러한 모델들은 $Ca(OH)_2$과 $CO_2$의 화학적 반응과 $CO_2$의 확산에 대한 관계를 연구하고 있다. 이 모델들은 콘크리트의 탄산화 영역에서 $CO_2$가 확산하고 콘크리트 중의 탄산화 영역과 미탄산화 영역과의 경계면에서 $Ca(OH)_2$와 반응한다는 가정에 기초하고 있다. 이 연구에서는 콘크리트중의 $CO_2$ 확산 및 탄산화진행영역에서의 $CaCO_3$와 $Ca(OH)_2$의 공존을 고려한 $CO_2$와 $Ca(OH)_2$와의 반응을 모델화한 것이다. 콘크리트 탄산화진행을 보다 정확하게 표현하기 위해 콘크리트 투기계수로서 탄산화진행모델에 적용하여 $CO_2$확산 계수를 유추하였다. 모델에 의한 예측은 W/C에 따라 페인트처리를 실시한 콘크리트의 촉진탄산화의 실험 결과와 아주 유사하게 나타나, 콘크리트 투기계수를 이용한 탄산화 진행속도 기본방정식을 활용하여 촉진환경 및 일반 대기환경에서 탄산화 진행예측이 가능함으로서 철근콘크리트구조물의 내구성설계를 위한 보다 정량적인 수명예측이 가능할 것으로 사료된다.

• 한국공간구조학회논문집
• /
• 제23권4호
• /
• pp.81-88
• /
• 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
• /
• 제12권5호
• /
• pp.69-80
• /
• 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.

• 한국구조물진단유지관리공학회 논문집
• /
• 제6권1호
• /
• pp.149-158
• /
• 2002

The carbonation process is affected by both the concrete material properties such as W/C ratio, types of cement and aggregates, admixture characteristics and the environmental factors such as $CO_2$ concentration, temperature, humidity. Based on results of preliminary study on carbonation, this study is to develop a carbonation prediction model by taking account of $CO_2$ concentration, temperature, humidity ad W/C ratio among major factor affecting the carbonation process. And to constitute a model formula which correspond to the mix design of the nuclear power plant, test coefficient that correspond to the design of the nuclear power plant is obtained based on the results of accelerated carbonation test. Also a field coefficient which is obtained based on results of the field examination is included to improve the conformity of the actual structures of nuclear power plant.