• 제목/요약/키워드: Carbonation model

검색결과 74건 처리시간 0.025초

Prediction model for concrete carbonation depth using gene expression programming

  • Murad, Yasmin Z;Tarawneh, Bashar K;Ashteyat, Ahmed M
    • Computers and Concrete
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    • 제26권6호
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    • pp.497-504
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    • 2020
  • Concrete can lose its alkalinity by concrete carbonation causing steel corrosion. Thus, the determination of the carbonation depth is necessary. An empirical model is proposed in this research to predict the carbonation depth of concrete using Gene expression programming (GEP). The GEP model was trained and validated using a large and reliable database collected from the literature. The model was developed using the six parameters that predominantly control the carbonation depth of concrete including carbon dioxide CO2 concentration, relative humidity, water-to-cement ratio, maximum aggregate size, aggregate to binder ratio and carbonation period. The model was statistically evaluated and then compared to the Jiang et al. model. A parametric study was finally performed to check the proposed GEP model's sensitivity to the selected input parameters.

Microstructure modeling of carbonation of metakaolin blended concrete

  • Wang, Xiao-Yong;Lee, Han-Seung
    • Advances in concrete construction
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    • 제7권3호
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    • pp.167-174
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    • 2019
  • Metakaolin (MK), which is increasingly being used to produce high performance concrete, is produced by calcining purified kaolinite between 650 and $700^{\circ}C$ in a rotary kiln. The carbonation resistance of metakaolin blended concrete is lower than that of control concrete. Hence, it is critical to consider carbonation durability for rationally using metakaolin in the concrete industry. This study presents microstructure modeling during the carbonation of metakaolin blended concrete. First, based on a blended hydration mo del, the amount of carbonatable substances and porosity are determined. Second, based on the chemical reactions between carbon dioxide and carbonatable substances, the reduction of concrete porosity due to carbonation is calculated. Furthermore, $CO_2$ diffusivity is evaluated considering the concrete composition and exposed environment. The carbonation depth of concrete is analyzed using a diffusion-based model. The proposed microstructure model takes into account the influences of concrete composition, concrete curing, and exposure condition on carbonation. The proposed model is useful as a predetermination tool for the evaluation of the carbonation service life of metakaolin blended concrete.

Carbonation depth estimation in reinforced concrete structures using revised empirical model and oxygen permeability index

  • Chandra Harshitha;Bhaskar Sangoju;Ramesh Gopal
    • Computers and Concrete
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    • 제31권3호
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    • pp.241-252
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    • 2023
  • Corrosion of rebar is one of the major deteriorating mechanisms that affect the durability of reinforced concrete (RC) structures. The increase in CO2 concentration in the atmosphere leads to early carbonation and deterioration due to corrosion in RC structures. In the present study, an attempt has been made to modify the existing carbonation depth prediction empirical model. The modified empirical model is verified from the carbonation data collected from selected RC structures of CSIR-SERC campus, Chennai and carbonation data available from the reported literature on in-situ RC structures. Attempt also made to study the carbonation depth in the laboratory specimens using oxygen permeability index (OPI) test. The carbonation depth measured from RC structures and laboratory specimens are compared with estimated carbonation depth obtained from OPI test data. The modified empirical model shows good correlation with measured carbonation depth from the identified RC structures and the reported RC structures from the literature. The carbonation depth estimated from OPI values for both in-situ and laboratory specimens show lesser percentage of error compared to measured carbonation depth. From the present investigation it can be said that the OPI test is the suitable test method for both new and existing RC structures and laboratory RC specimens.

Self-terminated carbonation model as an useful support for durable concrete structure designing

  • Woyciechowski, Piotr P.;Sokolowska, Joanna J.
    • Structural Engineering and Mechanics
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    • 제63권1호
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    • pp.55-64
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    • 2017
  • The paper concerns concrete carbonation, the phenomena that occurs in every type of climate, especially in urban-industrial areas. In European Standards, including Eurocode (EC) for concrete structures the demanded durability of construction located in the conditions of the carbonation threat is mainly assured by the selection of suitable thickness of reinforcement cover. According to EC0 and EC2, the thickness of the cover in the particular class of exposure depends on the structural class/category and concrete compressive strength class which is determined by cement content and water-cement ratio (thus the quantitative composition) but it is not differentiated for various cements, nor additives (i.e., qualitative composition), nor technological types of concrete. As a consequence the selected thickness of concrete cover is in fact a far estimation - sometimes too exaggerated (too safe or too risky). The paper presents the elaborated "self-terminated carbonation model" that includes abovementioned factors and enables to indicate the maximal possible depth of carbonation. This is possible because presented model is a hyperbolic function of carbonation depth in time (the other models published in the literature use the parabolic function that theoretically assume the infinite increase of carbonation depth value). The paper discusses the presented model in comparison to other models published in the literature, moreover it contains the algorithm of concrete cover design with use of the model as well as an example of calculation of the cover thickness.

Enhanced mass balance Tafel slope model for computer based FEM computation of corrosion rate of steel reinforced concrete coupled with CO2 transport

  • Hussain, Raja Rizwan
    • Computers and Concrete
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    • 제8권2호
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    • pp.177-192
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    • 2011
  • This research paper aims at computer based modeling of carbonation induced corrosion under extreme conditions and its experimental verification by incorporating enhanced electrochemical and mass balance equations based on thermo-hygro physics with strong coupling of mass transport and equilibrium in micro-pore structure of carbonated concrete for which the previous research data is limited. In this paper the carbonation induced electrochemical corrosion model is developed and coupled with carbon dioxide transport computational model by the use of a concrete durability computer based model DuCOM developed by our research group at concrete laboratory in the University of Tokyo and its reliability is checked in the light of experiment results of carbonation induced corrosion mass loss obtained in this research. The comparison of model analysis and experiment results shows a fair agreement. The carbonation induced corrosion model computation reasonably predicts the quantitative behavior of corrosion rate for normal air dry relative humidity conditions. The computational model developed also shows fair qualitative corrosion rate simulation and analysis for various pH levels and coupled environmental actions of chloride and carbonation. Detailed verification of the model for the quantitative carbonation induced corrosion rate computation under varying relative conditions, different pH levels and combined effects of carbonation and chloride attack remain as scope for future research.

배합인자를 고려한 딥러닝 알고리즘 기반 탄산화 진행 예측에 관한 기초적 연구 (A Fundamental Study on the Prediction of Carbonation Progress Using Deep Learning Algorithm Considering Mixing Factors)

  • 정도현;이한승
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2019년도 춘계 학술논문 발표대회
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    • pp.30-31
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    • 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.

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Evaluation of carbonation service life of slag blended concrete considering climate changes

  • Wang, Xiao-Yong;Luan, Yao
    • Computers and Concrete
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    • 제21권4호
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    • pp.419-429
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    • 2018
  • Climate changes, such as increasing of $CO_2$ concentration and global warming, will impact on the carbonation service life of concrete structures. Moreover, slag blended concrete has a lower carbonation resistance than control concrete. This study presents a probabilistic numerical procedure for evaluating the impact of climate change on carbonation service life of slag blended concrete. This numerical procedure considers both corrosion initiation period and corrosion propagation period. First, in corrosion initiation period, by using an integrated hydration-carbonation model, the amount of carbonatable substances, porosity, and carbonation depth are calculated. The probability of corrosion initiation is determined through Monte Carlo method. Second, in corrosion propagation period, a probabilistic model is proposed to calculate the critical corrosion degree at surface cracking, the probability of surface cracking, and service life. Third, based on the service life in corrosion initiation period and corrosion propagation period, the whole service life is calculated. The analysis shows that for concrete structures with 50 years service life, after considering climate changes, the service life reduces about 7%.

수산화칼슘 용해도와 공극률 감소를 고려한 간략화 된 탄산화 모델 (Simplified Carbonation Model Considering Ca(OH)2 Solubility and Porosity Reduction)

  • 이윤;권성준;박기태
    • 한국구조물진단유지관리공학회 논문집
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    • 제19권1호
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    • pp.128-138
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    • 2015
  • 탄산화는 지하구조물과 같이 이산화탄소의 농도가 높고 강우로부터 보호되는 콘크리트 구조물에 매우 심각한 열화현상이다. 탄산화 깊이 및 수화물의 변화를 평가하기 위해 많은 연구가 진행되고 있으나 해석모델의 복잡성, 이산화탄소 확산계수 모델링 등의 어려움으로 인해 실제 탄산화 거동을 제한적으로 모사하고 있다. 본 연구에서는 기존의 탄산화 모델링 (Ducom)에 대하여 확산계수 모델링, 공극률 감소 모델, 이산화탄소의 장기반응률 등을 개선하여 개선된 탄산화 모델을 제시하였다. 검증을 위하여 온도변화를 고려한 촉진탄산화 시험. 공극률 평가 시험 (수은압입법)을 수행하였으며, 탄산화 깊이를 개선되기 전/후의 모델과 비교하였다. 또한 수산화칼슘의 중량변화와 실태조사결과를 이용하여 낮은 이산화탄소에 노출된 콘크리트 구조물의 탄산화 깊이를 제안된 모델과 비교하였다. 제안된 모델은 확산계수 감소성, 공극률 감소성을 적절하게 반영하여 기존의 모델에 비해 합리적인 결과 (수산화칼슘 소모량, 탄산화 깊이)를 나타내었다.

콘크리트 내부 상대습도를 고려한 탄산화 깊이 산정 수치해석 모델 구축 (Development of Analytic Model for Estimation of the Carbonation Depth Considering the R.H. in the Concrete)

  • 박동천;조규환;안재철;강병희
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2012년도 추계 학술논문 발표대회
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    • pp.71-72
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    • 2012
  • The purpose of this study is to evaluate the depth of carbonation considering the relative humidity in concrete using the FEM model. The difference of relative humidity in concrete has not been considered in calculating the carbonation depth in analytic model. That reason can make the over estimation in expectation of RC structure durability. The temperature and R.H. expectation model and the carbonation depth expectation model are development in past author's studies. The two models are coupled in this study. The fact that there is the difference between actual environment and acceleration test is revealed from FEM numerical analysis.

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Prediction model of service life for tunnel structures in carbonation environments by genetic programming

  • Gao, Wei;Chen, Dongliang
    • Geomechanics and Engineering
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    • 제18권4호
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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.