• 한국건축시공학회지
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• 제5권3호
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• pp.101-107
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• 2005

This paper reports the contribution of Shrinkage reducing admixture(SRA) to the physical properties and drying shrinkage of concrete. Dosage of SRA is varied with. For the properties of fresh concrete, an increase in SRA dosage results in a decrease in fluidity and air content, while setting time is accelerated. For the properties of hardened concrete, the incorporation of mineral admixture leads to a decrease in compressive strength at early age, whereas after 28 days, the incorporation of fly ash(FA) and blast furnace slag(BS) has greater compressive strength than conventional concrete without admixture. The use of SRA results in a decrease in compressive strength. The incorporation of SRA with every $1\%$ increase causes the decrease of compressive strength by as much as $3\~6\%$. For drying shrinkage properties, the incorporation of FA and BS reduces drying shrinkage slightly. The use of SRA also decreases drying shrinkage. Every $1\%$ of increase in SRA dosage can reduce drying shrinkage by as much as $10\~15\%$

• Computers and Concrete
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• 제19권6호
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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.

• Computers and Concrete
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• 제19권6호
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• pp.717-724
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• 2017

In this paper, four formulas are proposed via gene expression programming (GEP)-based models and regression analysis (RA) to predict the flexural strength ($f_s$) values of mortars containing different mineral admixtures that are ground granulated blast-furnace slag (GGBFS), silica fume (SF) and fly ash (FA) at different ages. Three formulas obtained from the GEP-I, GEP-II and GEP-III models are constituted to predict the $f_s$ values from the age of specimen, water-binder ratio and compressive strength. Besides, one formula obtained from the RA is constituted to predict the $f_s$ values from the compressive strength. To achieve these formulas in the GEP and RA models, 972 data of the experimental studies presented with mortar mixtures were gathered from the literatures. 734 data of the experimental studies are divided without pre-planned for these formulas achieved from the training and testing sets of GEP and RA models. Beside, these formulas are validated with 238 data of experimental studies un-employed in training and testing sets. The $f_s$ results obtained from the training, testing and validation sets of these formulas are compared with the results obtained from the experimental studies and the formulas given in the literature for concrete. These comparisons show that the results of the formulas obtained from the GEP and RA models appear to well compatible with the experimental results and find to be very credible according to the results of other formulas.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1998년도 가을 학술발표논문집(II)
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• pp.262-268
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• 1998

This research is to examine the selected method of optimal mixing proportion and cost analysis in the super flowing concrete. As confined water $ratio($\beta_p$)$ and K is introduced, itis to establish optimal mixing design of super flowing concrete according to the steps of paste, mortar and concrete. From paste and mortar test, it was led to $$\beta_p$$ and $K_p$satisfying the optimum condions depending on the kinds of binders. Then $$\beta_p$$ and $K_p$ is reflected to the mix condition of super flowing concrete. The result of test, the mix condition of super flowing concrete satisfied the quality performance of concrete with adjustment of additional rate of the superplasticizer. Besides, in case of design strength $350kg/\textrm{cm}^2$ of concrete, material cost in super flowing concrete is able to be reduced 5~16% in replacement of fly ash 30% in ordinary portland cement and slag cement.

• 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.

• 한국건축시공학회지
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• 제7권2호통권24호
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• pp.59-65
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• 2007

Recently, due to the increase of high-rise buildings construction, many researches for making harden of concrete earlier and remove of forms faster are being performed to reduce construction period. In this study, we compared and analysed the early strength properties of mortar according to the kinds and replacement ratio of mineral admixture to select the kinds and replacement ratio of mineral admixture of high early strength concrete. For this purpose, mortar mixtures according to the kinds(FA, MK, ZR, BFS, DM) and replacement ratio(0, 2, 4% by volume of sand) of mineral admixture were selected. From our test data, early-age compressive strength decreased in accordance with the increase of replacement ratio of fly-ash(FA) & blast furnace slag powder(BSF) and, in case of addition admixture, early-age compressive strength of with containing 4% appeared higher compared with containing 2%.

• Computers and Concrete
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• 제10권6호
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• pp.557-573
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• 2012

This paper discusses the combined application of two different techniques, Neural Networks (NN) and Principal Component Analysis (PCA), for improved prediction of concrete properties. The combination of these approaches allowed the development of six neural networks models for predicting slump and compressive strength of concrete with mineral additives such as blast furnace slag, fly ash and silica fume. The Back-Propagation Multi-Layer Perceptron (BPMLP) with Bayesian regularization was used in all these models. They are produced to implement the complex nonlinear relationship between the inputs and the output of the network. They are also established through the incorporation of a huge experimental database on concrete organized in the form Mix-Property. Thus, the data comprising the concrete mixtures are much correlated to each others. The PCA is proposed for the compression and the elimination of the correlation between these data. After applying the PCA, the uncorrelated data were used to train the six models. The predictive results of these models were compared with the actual experimental trials. The results showed that the elimination of the correlation between the input parameters using PCA improved the predictive generalisation performance models with smaller architectures and dimensionality reduction. This study showed also that using the developed models for numerical investigations on the parameters affecting the properties of concrete is promising.

• Advances in materials Research
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• 제3권2호
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• pp.61-75
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• 2014

This study aimed to investigate the suitability of some concrete components for producing "high-performance heavy density concrete" using different types of aggregates that could enhances the shielding efficiency against ${\gamma}$-rays. 15 mixes were prepared using barite, magnetite, goethite and serpentine aggregates along with 10% silica fume, 20% fly ash and 30% blast furnace slag to total OPC content for each mix. The mixes were subjected to compressive strength at 7, 28 and 90 days. In some mixes, compressive strengths were also tested up to 90 days upon replacing sand with the fine portions of magnetite, barite and goethite. The mixes containing magnetite along with 10% SF reaches the highest compressive strength exceeding over M60 requirement by 14% after 28 days. Whereas, the compressive strength of concrete containing barite was very close to M60 and exceeds upon continuing for 90 days. Also, the compressive strength of high-performance concrete incorporating magnetite fine aggregate was significantly higher than that containing sand by 23%. On the other hand, concrete made with magnetite fine aggregate had higher physico-mechanical properties than that containing barite and goethite. High-performance concrete incorporating magnetite fine aggregate enhances the shielding efficiency against ${\gamma}$-rays.

• 한국농공학회논문집
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• 제54권2호
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• pp.157-166
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• 2012

Most of the roads are paved with impermeable materials such as asphalt concrete and cement concrete, and in the event of heavy rainfall, rainwater directly flows into river through a drainage hole on the pavement surface. This large quantity of rainwater directly spilled into the river frequently leads to the flooding of urban streams, damaging lowlands and the lower reaches of a river. In recent years there has been a great deal of ongoing research concerning water permeability and drainage in pavements. Accordingly, in this research, a porous polymer concrete was developed for permeable pavement by using unsaturated polyester resin as a binder, recycled aggregate as coarse aggregate, fly ash and blast furnace slag as filler, and its physical and mechanical properties were investigated. Also, 3 types of permeable polymer block by optimum mix design were developed and rainfall runoff reduction effects by permeability pavement using permeable polymer block were analyzed based on hydraulic experimental model. The infiltration volume, infiltration ratio, runoff initial time and runoff volume in permeability pavement with permeable polymer block of $300{\times}300{\times}80$ mm were evaluated for 50, 100 and 200mm/hr rainfall intensity.

• Computers and Concrete
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• 제10권2호
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• pp.95-104
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• 2012

This study uses recycled green building materials based on a Taiwan-made recycled mineral admixture (including fly ash, slag, glass sand and rubber powder) as replacements for fine aggregates in concrete and tests the properties of the resulting mixtures. Fine aggregate contents of 5% and 10% were replaced by waste LCD glass sand and waste tire rubber powder, respectively. According to ACI concrete-mixture design, the above materials were mixed into lightweight aggregate concrete at a constant water-to-binder ratio (W/B = 0.4). Hardening (mechanical), non-destructive and durability tests were then performed at curing ages of 7, 28, 56 and 91 days and the engineering properties were studied. The results of these experiments showed that, although they vary with the type of recycling green building material added, the slumps of these admixtures meet design requirements. Lightweight aggregate yields better hardened properties than normal-weight concrete, indicating that green building materials can be successfully applied in lightweight aggregate concrete, enabling an increase in the use of green building materials, the improved utilization of waste resources, and environmental protection. In addition to representing an important part of a "sustainable cycle of development", green building materials represent a beneficial reutilization of waste resources.