• Journal of the Korea Concrete Institute
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• v.17 no.4 s.88
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• pp.621-628
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• 2005

Recently, it is noticed that autogenous shrinkage of high-performance concrete causes early crack in high performance concrete structures. The purpose of the present study is to derive a realistic equation to estimate the autogenous shrinkage of high performance concrete and to apply to structural analysis. For this purpose, several series of concrete specimens have been tested. When water-binder ratio is fixed to $30\%$, major test variables were the type and contents of mineral admixture. The autogenous shrinkage of HPC with fly ash slightly decreased than that of OPC concrete, but the use of blast furnace slag increased with the autogenous shrinkage. A prediction equation to estimate the autogenous shrinkage of HPC with mineral admixture was derived and proposed in this study. The proposed equation show reasonably good correlation with test data on autogenous shrinkage of HPC with mineral admixture. The finite element program developed in this study provides the useful tool for the flexural analysis including the autogenous shrinkage model. By this program, we know that the tensile stress considering the autogenous shrinkage of reinforced concrete structures increase $20\~27\%$ than that not considering.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.5
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• pp.92-103
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• 2015

Box-Wilson experimental design method, known as central composite design, is the design of any information-gathering exercises where variation is present. This method was devised to gather as much data as possible in spite of the low design cost. This method was employed to model the effect of mixing factors on several performances of 60 MPa high strength self compacting concrete and to numerically calculate the optimal mix proportion. The nonlinear relations between factors and responses of HSSCC were approximated in the form of second order polynomial equation. In order to characterize five performances like compressive strength, passing ability, segregation resistance, manufacturing cost and density depending on five factors like water-binder ratio, cement content, fine aggregate percentage, fly ash content and superplasticizer content, the experiments were made at the total 52 experimental points composed of 32 factorial points, 10 axial points and 10 center points. The study results showed that Box-Wilson experimental design was really effective in designing the experiments and analyzing the relation between factor and response.

• Journal of the Korean Society of Hazard Mitigation
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• v.3 no.4 s.11
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• pp.119-129
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• 2003

Concrete and steel are essential structural materials in the construction. But, concrete, different from steel, consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructors. Concrete have two kinds of properties, immediately knowing properties such as slump, air contents and time dependent one like strength. Therefore, concrete mixes depend on experiences of experts. However, at point of time using High Performance Concrete, new method is wanted because of more ingredients like mineral and chemical admixtures and lack of data. 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 ate 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, slump, and air contents 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 for Nondestructive Testing
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• v.23 no.2
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• pp.98-106
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• 2003

Nondestructive test (NDT) provides much information on concrete without damage of structural functions. Of NDT methods, elastic wave propagation methods, such as ultrasonic pulse velocity (UPV) method and impact-echo (IE) method, have been successfully used to estimate the strength, elastic modulus, and Poisson's ratio of concrete as well as to detect the internal microstructural change and defects. In this study, the concretes with water-binder ratio ranging from 0.27 to 0.50 and fly ash content of 20% were made and then their longitudinal wave velocities were measured by UPV and IE method, respectively. Test results showed that the UPV is greater than the longitudinal wave velocity measured by the If method, i.e., rod-wave velocity obtained from the same concrete cylinder. It was found that the difference between the two types of velocities decreased with increasing the ages of concrete and strength level. Moreover, for the empirical formula, the dynamic Poisson's ratio, static and dynamic moduli of elasticity, and velocity-strength relationship were determined. It was observed that the Poisson's ratio and the modulus of elasticity determined by the dynamic method are greater than those determined by the static test. Consequently, for the more accurate estimation of concrete properties using the elastic wave velocities, the characteristics of these velocities should be understood.

• Journal of the Korean Recycled Construction Resources Institute
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• v.2 no.3
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• pp.247-254
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• 2014

The present study prepared lightweight foam-soil concrete mixtures classified into three groups. Considering the sustainablility, workability, and compressive strength development of such concrete, high-volume supplementary cementitious materials (SCMs) were used as follows: 20% cement, 15% fly ash, and 65% ground granulated blast-furnace slag. As main test parameters selected for achieving the compressive strength of 1MPa and dry density of $1,000kg/m^3$, the unit solid content (dredged soil and binder) ranged between 900 and $1,807kg/m^3$, and soil-to-binder ratio varied between 3.0 and 7.0. Test results revealed that the flow of the lightweight foam-soil concrete tended to decrease with the increase of unit soil content. The compressive strength of such concrete increased with the increase with the unit binder content, whereas it decreased as soil-to-binder ratio increased, indicating that the compressive strength can be formulated as a function of its dry density and soil-to-binder ratio.