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.

PURPOSES : This paper presents the experimental results of tests conducted on concrete produced with air-cooled (AS) and water-cooled (WS) ground blast-furnace slag exposed to multi-deterioration environments of carbonation and scaling. METHODS : Carbonated and uncarbonated concrete specimens were regularly monitored according to the ASTM C 672 standard to evaluate the durability of concrete exposed to both scaling and combined carbonation and scaling conditions. Additionally, mechanical properties, such as compressive strength, flexural strength, and surface electric resistivity, were analyzed. RESULTS : It was found that concrete specimens produced with AS and WS had a beneficial effect on the mechanical properties because of the latent hydraulic properties of the AS and WS mineral admixtures. Moreover, carbonated concrete showed good scaling resistance in comparison to uncarbonated concrete, particularly for concrete produced with AS and WS. CONCLUSIONS : The improved scaling resistance of carbonated concrete showed that AS is a suitable option for binders used in cement concrete pavements subjected to combined carbonation and scaling.

온실가스의 대기 방출에 기인된 지구온난화는 범세계적인 주요 문제로 다루어지고 있으며, 이에 대한 많은 대책 중의 하나로 광물탄산화가 관심을 받고 있다. 본 연구에서는 다양한 조건에서 경량 기포콘크리트를 이용한 광물탄산화 실험을 수행하여 이들의 탄산화 재료로써의 가능성을 파악코자 하였다. 경량 기포콘 크리트는 광물탄산화의 주요성분인 CaO의 함량이 약 27wt.%에 달하여 탄산화를 위한 유망한 재료로 간주 할 수 있다. 이 함량 모두가 광물탄산화에 참여한다는 가정 하에 계산된 CaCO3 함량은 약 40wt.%이다. 경량 기포콘크리트로부터 광물탄산화 반응의 최적 조건은 단일상의 방해석이 형성된 고액비 0.01, 반응시간 180 분이며, 그리고 단일상 여부와 무관하게 즉 방해석과 바테라이트가 공존하는 경우, 고액비 0.06, 반응시간 180 분인 것으로 확인된다. 고액비 0.06이상인 경우, 방해석과 더불어 바테라이트가 공존하였으며, 이는 광물탄산화에 따라 초기에 형성된 바테라이트가 점차 방해석으로 상전이 된 데 반하여 후기에 형성된 바테라이트는 반응 종료 시까지 방해석으로 상전이 되지 못한데 원인이 있는 것으로 해석된다.

이산화탄소 농도가 높은 도심지의 경우 탄산화로 인한 철근부식이 발생하기 쉬우며 이는 콘크리트 구조물의 내구수명을 감소시킨다. 콘크리트 구조물의 경우 다양한 구속조건을 가지며 항상 외부의 재하하중을 받고 있다. 도입된 응력수준은 이산화탄소와 같은 유해인자의 확산을 변화시키며 탄산화 깊이의 변동성을 야기한다. 본 연구에서는 응력재하수준에 따른 탄산화 변동성을 정량화하였으며, 이를 이용하여 탄산화 예측식을 도출하였다. 내구성 설계인자인 피복두께, 이산화탄소 확산계수, 탄산화 반응 수화물, 그리고 외부 이산화탄소 농도를 확률 변수로 정의하였으며, MCS을 통하여 영향인자의 변동성에 따른 내구수명을 도출하였다. 또한 응력수준에 따라 변화하는 내구수명을 도출하였으며, 이를 결정론적인 방법의 결과와 비교하였다. 피복두께 및 내부 수화물 생성이 내구수명 변동성에 가장 큰 영향을 미쳤으며, 응력수준 을 고려한 내구수명평가는 유지관리 우선순위 설정에 합리적으로 적용할 수 있다.

콘크리트에서 염소 이온과 같은 열화물질의 이동은 응력상태 및 재령의 증가에 기인한 공극구조에 따라 변화한다. 본 연구에서는 재령 28일, 91일, 그리고 365일 양생된 OPC 콘크리트의 압축 및 인장 하중조건을 고려하여 촉진탄산화 실험을 실시하였으며, 탄산화 거동을 평가하였다. KS F 2584에 의거하여 탄산화 속도계수를 도출하였는데, 하중을 고려하지 않을 경우 탄산화 속도계수는 재령 28일 대비 재령 91일은 50.0 % 수준으로, 재령 365일에서는 44.8 % 수준으로 감소하였다. 28일 재령 시, 하중의 영향으로 인해 인장재하영역에서는 103.9 ~ 108.8 % 수준으로 압축재하영역에서는 91.9 ~ 104.6 % 수준으로 변화하였다. 재령이 증가함에 따라 탄산화 속도는 크게 감소하였는데, 30 % 인장재하영역에서는 탄산화 속도계수가 1년 경과시 47.3 % 수준으로, 60 % 인장재하영역에서는 52.5 % 수준으로 감소하였으며 30 % 압축재하영역에서는 45.8 %로, 60 % 압축재하영역에서는 44.9 % 수준으로 감소하였다. 압축재하영역 30 %에서는 공극압밀로 인해 탄산화 속도계수가 감소하였으나 하중의 증가에 따라 압축재하영역 60 %에서는 미세균열의 영향으로 탄산화 속도계수가 증가하였다. 또한 인장재하영역은 압축부와는 다르게 탄산화 속도계수가 선형적으로 증가하는 경향을 나타내었다.

This study is to investigate and analyze the correlation of carbonation according to strength of concrete members for bridge in marine enviroment. Also depth of carbonation according to age for 100 years is estimated by carbonation rate coefficient. As a result of the measurement, it was found that the depth of carbonation decreases with increasing strength. This is because it is considered that water-cement ratio and amount of unit cement are influenced by the concrete mixing. Also, It is anticipated that rebar corrosion due to carbonation will not occur in concrete members.

The main cause of corrosion in reinforced concrete is diffusion of degradation factors such as chloride ions, carbon dioxide, and sulfate ions. To monitor the extent of the corrosion in reinforced concrete, it is necessary to recognize and track the diffusion of degradation factors. In this paper, we suggest thin-film iron sensorto measure the penetration of chloride ions. The sensor indicates results as electrical resistance and change in electrical resistance. The sensor and contact pad are connected by an anisotropic conducting film (ACF) bonding in order to reduce the influence of the contact electrical resistance. The sensor’s electrical resistance increases with corrosive behavior and external chloride ion concentration. Use of these thin-film iron sensors enables measurement and monitoring of the depth of chloride ion diffusion in concrete.

In this paper, Results of mock-up test for mitigating carbonation of high volume mineral admixture concrete by spreading waste cooking oil. Concrete incorporating 60% of BS and 30% of FA with the size of 900×600×200 are discussed. Denatured Silicate paint is also applied to compare the performance. Test results indicate that the application of ERCO and DSP enhance carbonation resistance.

In this study, the compressive strength and flexural strength of concrete were evaluated by making 50% and 100% admixture ratio of recycled aggregate and recycled aggregate through nano bubble carbonation modification

In previous research team had reported that the durability of carbonation is improved by filling voids due to the saponification reaction of oil and concrete. The purpose of this study was to have experimental investigation the effect of mock-up experiment on the carbonation resistance of the waste concrete admixture.

In reinforced concrete structures, carbonation phenomena associated with deterioration is important. So, this study conducted a visual inspection and a concrete durability test in Precise Safety Diagnosis, analyzed the result, and tried to suggest a reasonable repair method and range of concrete carbonation.

As the importance of maintenance of reinforced concrete structures spreads, interest in the durability of structures is increasing. Among them, carbonation of concrete is one of the main deterioration factors of reinforced concrete structures. For quantitative evaluation of carbonation, many researchers are predicting carbonation considering water-cement ratio and environmental requirements. In this study, we studied the parameters based on the concrete made of ordinary Portland cement in the existing experimental data. The depth of carbonation deduced from the learning is applied to the carbonation by applying the deep learning.

In this study, the compressive strength and flexural strength of concrete were evaluated by making 50% and 100% admixture ratio of recycled aggregate and recycled aggregate through nano bubble carbonation modification.

In previous research team had reported that the durability of carbonation is improved by filling voids due to the saponification reaction of oil and concrete. The purpose of this study was to have experimental investigation the effect of mock-up experiment on the carbonation resistance of the waste concrete admixture.

reinforced concrete structures, carbonation phenomena associated with deterioration is important. So, this study conducted a visual inspection and a concrete durability test in Precise Safety Diagnosis, analyzed the result, and tried to suggest a reasonable repair method and range of concrete carbonation.

Concrete with a pore solution of pH 10-12 is less alkaline than sound concrete but would still produce a strong color hange with phenolphthalein indicator. It therefore follows that the indicator test is likely to underestimate the depth to which carbonation has occurred. The indicator has not changed color near the top and bottom surfaces, suggesting that these near-surface regions are carbonated to a depth of at least 3 mm from the top surface and 5 mm from the lower surface. Where the indicator has turned purple - the center of the slab - the pH of the concrete pore fluid remains high (above 8.6, probably nearer 10).. Based on the above technical background, this study was devoted to examine the depth analysis of carbonated concrete quantitatively.

The purpose of the present study is to investigate some effects of concrete according to addition of blast furnace slag and sulfuric alkali-activator. Blast furnace slag was used at 30~80% replacement by weight of cement, and liquid sulfur having NaOH additives was chosen as the alkaline activator. In order to evaluate characteristics of blast furnace slag concrete with sulfuric alkali activators, compressive strength test, carbonation test were performed.

In this study is investigated nano-modified sulfur concrete carbonation resistance. Weight fraction of nano-modified sulfur are 0%, 3%, and 5% by cement's weight. The experiment result showed that there seem to be similarity in compressive strength according to weight fraction. and, the increase in nano-modified sulfur content enhanced concrete's carbonation resistance.

In reinforced concrete (RC) structures, concrete carbonation depth is an important criterion for the deterioration of durability of RC structures. Concrete carbonation is influenced by multiple factors such as chloride attack, crack, concrete compressive strength, etc. However, due to its complex mechanism, most previous studies considered only one or two deterioration factors to estimate the concrete carbonation depth. In this study, therefore, inspection data were collected from 8 buildings, and the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm that estimates the concrete carbonation depth of RC structures has been proposed. The proposed ANFIS model provided good estimations on the carbonation depths.