• Computers and Concrete
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• 제13권2호
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• pp.149-171
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• 2014

This study presents the mathematical model for predicting chloride penetration into saturated concrete under non-isothermal condition. The model considers not only diffusion mechanism but also migration process of chloride ions and other chemical species in concrete pore solution such as sodium, potassium, and hydroxyl ions. The coupled multi-ionic transport in concrete is described by the Nernst-Planck equation associated with electro-neutrality condition. The coupling parameter taken into account the effect of temperature on ion diffusion obtained from available test data is proposed and explicitly incorporated in the governing equations. The coupled transport equations are solved using the finite element method. The numerical results are validated with available experimental data and the comparison shows a good agreement.

• Computers and Concrete
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• 제11권3호
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• pp.253-270
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• 2013

The aim of the present paper is to show the application of optimization strategies for the cost of beams in reinforced concrete buildings and to propose pre-sizing parameters. In order for these goals to be met, an optimization software program was developed. The program combines the analysis of structures by the grid model, reinforced concrete sizing, and the simulated annealing optimization heuristic. Sizing is compliant with the NBR 6118 (2007) Brazilian standard, according to which flexural, shearing, torsion, and web reinforcements and serviceability limit states (deflection and crack width limitation) are checked. Besides the dimensions of the situations mentioned above, the influence the cost of each material (steel, concrete and formwork) has on the overall cost of structures was also determined.

• Computers and Concrete
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• 제24권5호
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• pp.469-488
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• 2019

In this research study, the artificial neural networks approach is used to estimate the ultimate shear capacity of reinforced concrete beams with transverse reinforcement. More specifically, surrogate approaches, such as artificial neural network models, have been examined for predicting the shear capacity of concrete beams, based on experimental test results available in the pertinent literature. The comparison of the predicted values with the corresponding experimental ones, as well as with available formulas from previous research studies or code provisions highlight the ability of artificial neural networks to evaluate the shear capacity of reinforced concrete beams in a trustworthy and effective manner. Furthermore, for the first time, the (quantitative) values of weights for the proposed neural network model, are provided, so that the proposed model can be readily implemented in a spreadsheet and accessible to everyone interested in the procedure of simulation.

• Computers and Concrete
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• 제29권3호
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• pp.145-159
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• 2022

In this study, the extreme learning machine and deep learning models were devised to estimate the bond strength of corroded reinforcement in concrete. The six inputs and one output were used in this study. The compressive strength, concrete cover, bond length, steel type, diameter of steel bar, and corrosion level were selected as the input variables. The results of bond strength were used as the output variable. Moreover, the Analysis of variance (Anova) was used to find the effect of input variables on the bond strength of corroded reinforcement in concrete. The prediction results were compared to the experimental results and each other. The extreme learning machine and the deep learning models estimated the bond strength by 99.81% and 99.99% accuracy, respectively. This study found that the deep learning model can be estimated the bond strength of corroded reinforcement with higher accuracy than the extreme learning machine model. The Anova results found that the corrosion level was found to be the input variable that most affects the bond strength of corroded reinforcement in concrete.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 가을 학술논문 발표대회
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• pp.158-159
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• 2021

When the porous concrete is exposed to the external environment, the internal relative humidity changes from time to time due to the inflow and outflow of moisture. This change in moisture is affected by temperature. The temperature and humidity of concrete is dominant in the carbonation rate, the largest cause of deterioration of concrete. In this study, actual weather data were used as boundary conditions. A carbonization model of concrete temperature and humidity and calcium hydroxide was constructed to perform long-term analysis. There is a slight error in the carbonation formula of the Japanese Academy of Architecture applying the Kishtani coefficient, a representative experimental formula related to carbonization, and the analysis result values. However, considering that it behaves very similarly, it is thought that a fairly reliable numerical analysis model has been established. A slight error is believed to be due to the fact that the amount of residual calcium hydroxide in the carbonated site has not yet been clearly identified.

• Computers and Concrete
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• 제16권6호
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• pp.825-846
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• 2015

In this study, shear tests on steel fiber reinforced-prestressed concrete (SFR-PSC) members were conducted with test parameters of the concrete compressive strength, the volume fraction of steel fibers, and the level of effective prestress. The SFR-PSC members showed higher shear strengths and stiffness after diagonal cracking compared to the conventional prestressed concrete (PSC) members without steel fibers. In addition, their shear deformational behavior was measured using the image-based non-contact displacement measurement system, which was then compared to the results of nonlinear finite element analyses (NLFEA). In the NLFEA proposed in this study, a bi-axial tensile behavior model, which can reflect the tensile behavior of the steel fiber-reinforced concrete (SFRC) in a simple manner, was introduced into the smeared crack truss model. The NLFEA model proposed in this study provided a good estimation of shear behavior of the SFRPSC members, such as the stiffness, strengths, and failure modes, reflecting the effect of the key influential factors.

• 콘크리트학회논문집
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• 제13권6호
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• pp.637-644
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• 2001

본 논문에서는 콘크리트 댐체의 균열 발생 및 진전해석을 포함하는 비선형 지진해석에서 유한요소망 의존성을 제거시키고 안정적인 해를 얻기 위하여 균열모형으로 사용되는 소성손상모형 및 손상역학모형을 duvaut-lions모형에 기초한 점소성모형으로 정규화하는 방법을 기술하였다. 제안된 방법으로 정규화된 소성손상모형과 그렇지 않은 소성손상모형를 이용하여 지진하중을 받는 콘크리트 댐체의 동적 손상해석을 수행하여 여러 형태의 유한요소망이 해석결과에 미치는 영향을 분석하였다. 해석결과로부터 정규화한 소성손상모형은 유한요소망의 크기 및 배열에 영향을 크게 받지 않고 객관적이며 안정적인 해를 계산하는 반면, 정규화되지 않은 균열모형은 요소망에 의존적인 불안정한 결과를 산출함을 관찰할 수 있었다.

• 한국건축시공학회지
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• 제7권4호
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• pp.145-151
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• 2007

In this paper, tests are carried out in order to investigate the strength development of concrete under various binder types, W/B and curing temperature ranged from $5{\sim}20^{\circ}C$. Fly ash and blast furnace slag were incorporated by as much as 30%, respectively. Strength development of concrete are estimated using Logistic model and strength ratio of concrete at 28days to that at early age are also investigated. According to experimental results, it is found that good agreements are obtained between measured values and calculated ones using logistic model below $20^{\circ}C$. Strength ratio of concrete at 28days to that at early age increases in case W/B decreases and curing temperature increases. Tables and graphs for strength ratio of concrete are provided in this paper. It is capable of obtaining and predicting the periods to attain design strength by considering increment factor of strength easily with the table and graphs presented in this paper. This paper presents the reference data to decide removal time of form, time to reach target strength and strength inspection of remicon whether the test specimens meet the specified criteria of compressive strength. Multi regression models with respect to the relationship between 7days compressive strength and 28 days compressive strength depending on W/B and admixture types are presented.

• Structural Engineering and Mechanics
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• 제49권3호
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• pp.373-393
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• 2014

A finite element model for predicting the entire nonlinear behavior of reinforced high-strength concrete continuous beams is described. The model is based on the moment-curvature relations pre-generated through section analysis, and is formulated utilizing the Timoshenko beam theory. The validity of the model is verified with experimental results of a series of continuous high-strength concrete beam specimens. Some important aspects of behavior of the beams having different tensile reinforcement ratios are evaluated. In addition, a parametric study is carried out on continuous high-strength concrete beams with practical dimensions to examine the effect of tensile reinforcement on the degree of moment redistribution. The analysis shows that the tensile reinforcement in continuous high-strength concrete beams affects significantly the member behavior, namely, the flexural cracking stiffness, flexural ductility, neutral axis depth and redistribution of moments. It is also found that the relation between the tensile reinforcement ratios at critical negative and positive moment regions has great influence on the moment redistribution, while the importance of this factor is neglected in various codes.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2009년도 춘계 학술대회 제21권1호
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• pp.275-276
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• 2009

본 논문에서는 중성화에 노출된 콘크리트 구조불의 내구성을 예측하기 위한 새로운 접근 방법을 제시한다. 이 예측 방법은, 새로운 계측 데이터 있을 때 베이스 이론에 근거하여 지속적으로 업데이팅 을 할 수 있다. 모델 매개변수의 확률론적인 특성이 고려된다. 염해 해석 모델의 절차는 라틴 하이퍼 큐브 샘플 추출법으로 간단하게 정리되고 이를 통해 얻는 표본으로 결정된다. 이러한 새로운 방법은 중요한 콘크리트 구조물을 설계하기에 아주 유용하고 모니터링을 통한 실 콘크리트 구조물의 잔존수명을 예측 할 수 있다.