• Computers and Concrete
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• v.19 no.6
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• pp.651-658
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• 2017

High-performance concrete, besides aggregate, cement, and water, incorporates supplementary cementitious materials, such as fly ash and blast furnace slag, and chemical admixture, such as superplasticizer. Hence, it is a highly complex material and modeling its behavior represents a difficult task. This paper presents an evolutionary system for the prediction of high performance concrete strength. The proposed framework blends a recently developed version of genetic programming with a local search method. The resulting system enables us to build a model that produces an accurate estimation of the considered parameter. Experimental results show the suitability of the proposed system for the prediction of concrete strength. The proposed method produces a lower error with respect to the state-of-the art technique. The paper provides two contributions: from the point of view of the high performance concrete strength prediction, a system able to outperform existing state-of-the-art techniques is defined; from the machine learning perspective, this case study shows that including a local searcher in the geometric semantic genetic programming system can speed up the convergence of the search process.

• Journal of the Korea Institute of Building Construction
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• v.7 no.3
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• pp.123-130
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• 2007

This study investigated the fundamental properties and shrinkage properties of high performance concrete with water/binder ratio of 0, 30 and with combination of expansive additive and shrinkage reducing agent. According to the results, the fluidity of high performance concrete showed lower the using method in combination with expansive additive and shrinkage reducing agent than the separately using method of that, so the amount of superplasticizer increased when the adding ratio of expansive additive and shrinkage reducing agent increased. However the air content of concrete increased when used in combination with expansive additive and shrinkage reducing agent, so the amount of AE agent decreased. The compressive strength showed the highest at 5% of expansive additive, and decreased with an increase of the amount of shrinkage reducing agent. Furthermore, in order to reduce the shrinkage of high performance concrete, it was found that the using method in combination with expansive additive and shrinkage reducing agent was more effective than separately using method of that. Autogenous shrinkage was predicted using JCI model. Because JCI model is unable to consider the effect of EA and SRA, correction factor should be added to enhance the accuracy.

• Proceedings of the Korea Concrete Institute Conference
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• 1997.10a
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• pp.408-415
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• 1997

Bond strength of reinforcing bar to high-performance concrete using Belite cement is explored using beam end test specimen. The key parameters for the bond test are slump of concrete, top bar effect, and strength of concrete in addition to concrete covers. Specimen failed in the typical brittle bond failure splitting the concrete cover as the wedging action. The test results show that for the group with portland cement I using superplasticizer additional slump does not decrease the bond strength of the top bar is less than bond strength of bottom bar, but the top bar factor satisfy the modification factor for top reinforcement. The result also show that bond strength is function of square root of concrete compressive strength and cover thickness. More detailed evaluation will be conducted from the test specimen with high strength concrete using the belite cement.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.05a
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• pp.93-95
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• 2013

Recently, with the increase in the construction of ultra-high buildings and long-span structures, there is great demand for high-strength concrete which can reduce the structural weight and thickness of member sections. While developing high-strength concrete to meet performance requirements, certain issues at the design stage must also be considered. The issues include diseconomy from a great amount of per-unit cement, spalling failure by fire at ultra-high building, autogenous shrinkage caused by increased hydration activity of binder from use of a superplasticizer. Therefore, the purpose of this study is examined the strain characteristics of Fiber-reinforced-high-strength concrete(FRHSC), which differ from those of general concrete owing to autogenous shrinkage. Based on the experimental data, we proposed an autogenous shrinkage prediction model.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.05a
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• pp.545-550
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• 2002

Concrete is one of the essential structural materials in the construction. But, concrete consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructor. Therefore, concrete mixes depend on experiences of experts. However, it is more and more difficult to determine concrete mixes design by empirical means because more ingredients like mineral and chemical admixtures are included. Artificial Neural Networks(ANN) are a mimic models of human brain to solve a complex nonlinear problem. They are powerful pattern recognizers and classifiers, also their computing abilities have been proven in the fields of prediction, estimation and pattern recognition. Here, among them, the back propagation network and radial basis function network are used. Compositions of high-performance concrete mixes are eight components(water, cement, fine aggregate, coarse aggregate, fly ash, silica fume, superplasticizer and air-entrainer). Compressive strength and slump are measured. The results show that neural networks are proper tools to minimize the uncertainties of the design of concrete mixtures.

• Journal of the Korean Society of Safety
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• v.18 no.3
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• pp.109-113
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• 2003

Concrete and shotcrete should withstand the conditions for which they have been designed, without deterioration, over a period of years. But connote and shotcrete are being deteriorated according to aging by internal and external causes. Recently, many studies on the durability of concrete have been conducted But the durability of shotcrete is rarely studied. So, in this study, chloride ion penetration test freeze and thaw test neutralization test were conducted to examine the durability characteristics of shotcrete with several accelerator and chemical admixture types. These results indicate that shotcrete with allah free accelerator and with superplasticizer are durable. Therefore, the present study provides a fm base to make high performance shotcrete.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.04a
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• pp.66-71
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• 2000

Recently, great efforts and investment have been made in order to achieve economical production by applying new methods like minimization of man-power into construction field. Therefore in this study, we have been focused on the development and practical using of high of high flowing concrete with fly ash, superplasticizer and viscocity agent, also we find out the optimum mix proportions to accomplish good wuality high flowing concrete. The results of this study show that high flowing concrete with the ratio of fly ash replacement of 20%, viscosity agent of 300g/㎥ and superplsticizer 2.0%(C$\times$%) in W/B of 35, 45% has better performance than the high flowing concrete without fly ash replacement

• Proceedings of the Korean Institute of Building Construction Conference
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• 2006.11a
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• pp.107-110
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• 2006

The purpose of this study is to suggest a reference data for the development of high workable and normal strength concrete using Polycarboxylate superplasticizer and granulated blast furnace slag as concrete admixtures. So in this study, it is quantitatively evaluated the workability, compressive strength, the heat of hydration and dry shrinkage of high workable concrete on normal compressive strength($21{\sim}27MPa$) for the practical use in construction field. As a result of this study, it is appeared that the performance of high workable and normal strength concrete is superior than that of ready-mixed concrete of the same strength through the B/P tests in the plants.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.293-296
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• 2001

This paper presents the results of field application test on the manufacturing of high fluidity concrete by applying flowing methods with segregation reducing type superplasticizer. Base concrete is made with 20% of fly ash, which is flowed during the transportation. According to test results, fluidity, placeability and segregation reducing performance meet the range of high fluidity concrete after flowing, while air loss occurs due to fly ash. There are no noticeable differences in compressive strengths between non-compacting and compacting methods. According to non-destructive tests with rebound and core strength test, we cannot detect any differences in strength according to the height in the structures.

• Computers and Concrete
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• v.13 no.5
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• pp.621-632
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• 2014

This paper is aimed at adapting Artificial Neural Networks (ANN) to predict the compressive strength of High Performance Concrete (HPC) containing binary and quaternary blends. The investigations were done on 23 HPC mixes, and specimens were cast and tested after 7, 28 and 56 days curing. The obtained experimental datas of 7, 28 and 56 days are trained using ANN which consists of eight input parameters like cement, metakaolin, blast furnace slag and fly ash, fine aggregate, coarse aggregate, superplasticizer and water binder ratio. The corresponding output parameters are 7, 28 and 56 days compressive strengths. The predicted values obtained using ANN show a good correlation between the Experimental data. The performance of the 8-9-3-3 architecture was better than other architectures. It concluded that ANN tool is convenient and time saving for predicting compressive strength at different ages.