• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.536-544
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• 2016

Recently, with the increase in the number of high rise and huge scaled buildings, ultra-high strength concrete with 80~100 MPa has been used increasingly to withstand excessive loads. Among the components of concrete, the effects of the kinds and properties of fine aggregates on the performance and economic advantages of ultra-high strength concrete need to be evaluated carefully. Therefore, this study examined the effects of the type of fine aggregates and mixing methods on the engineering properties of ultra-high strength concrete by varying the fine aggregates including limestone fine aggregate (LFA), electrical arc slag fine aggregate (EFA), washed sea sand (SFA), and granite fine aggregate (GFA) and their mixtures. Ultra-high strength concrete was fabricated with a 20 % water to binder ratio (W/B) and incorporated with 70 % of Ordinary Portland cement: 20 % of fly ash:10 % silica fume. The test results indicate that for a given superplasticizer dose, the use of LFA resulted in increases in slump flow and L-flow compared to the mixtures using other aggregates due to the improved particle shape and grading of LFA. In addition, the use of LFA and EFA led to enhanced compressive strength and a decrease in autogenous shrinkage due to the improved elastic properties of LFA and the presence of free-CaO in EFA, which resulted in the formation of C-S-H.

• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.4
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• pp.287-294
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• 2019

GGBFS(Ground Granulated Blast Furnace Slag) has been widely used in concrete for its excellent resistance chloride and chemical attack, however cracks due to hydration heat and dry shrinkage are reported. In many International Standards, GGBFS with low fineness of 3,000 grade is classified for wide commercialization and crack control. In this paper, the mechanical and durability performance of concrete were investigated through two mix proportions; One (BS) has 50% of w/b(water to binder) ratio and 60% replacement ratio with low-fineness GGBFS, and the other (TS) has 50% of w/b and 60% replacement ratio with 4000 grade and FA (Fly Ash). The strength difference between TS and BS concrete was not great from 3 day to 91 day of age, and BS showed excellent performance for chloride diffusion and carbonation resistance. Two mixtures also indicate a high durability index (more than 90.0) for freezing-thawing since they contain sufficient air content. Through improvement of strength in low fineness GGBFS concrete at early age, mass concrete with low hydration heat and high durability can be manufactured.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.81-88
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• 2021

Structural health monitoring (SHM) systems have attracted considerable interest owing to the frequent earthquakes over the last decade. Smart concrete is a technology that can analyze the state of structures based on their electro-mechanical behavior. On the other hand, most research on the self-sensing response of smart concrete generally investigated the electro-mechanical behavior of smart concrete under a static loading rate, even though the loading rate under an earthquake would be much faster than the static rate. Thus, this study evaluated the electro-mechanical behavior of smart ultra-high-performance concrete (S-UHPC) at three different loading rates (1, 4, and 8 mm/min) using a Universal Testing Machine (UTM). The stress-sensitive coefficient (SC) at the maximum compressive strength of S-UHPC was -0.140 %/MPa based on a loading rate of 1 mm/min but decreased by 42.8% and 72.7% as the loading rate was increased to 4 and 8 mm/min, respectively. Although the sensing capability of S-UHPC decreased with increased load speed due to the reduced deformation of conductive materials and increased microcrack, it was available for SHM systems for earthquake detection in structures.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.243-252
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• 2019

Recently, as the utilization of underground space increases, the demand for underground excavation increases. In this study, the concrete mixture with a new material was used to develop and evaluate the stability of the CS-H wall that can greatly minimize the problems of existing wall and minimize the impact of ground depression and surrounding ground that may occur in the future for excavation of over 30 m deep in urban areas. The fiber reinforcement formulation of steel fibers, synthetic fibers, and glass fibers, along with fine aggregate parts of PS-ball and ferronickel, were mixed. The Mixture ratios were determined by conducting slump test compresive strength test, modulus of elastic test, flexural strength test, splitting tensile strength test and conductivity test. As a result of the test, the steel fiber mixture showed very good results compared to other reference values in all items, and it is considered to be the most suitable for the CS-H wall to be developed.

• International Journal of Highway Engineering
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• v.15 no.3
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• pp.1-8
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• 2013

PURPOSES : This study is to evaluate the feasibility of using the alkali activated cement concrete for application of partial-depth repair in pavement. METHODS : This study analyzes the compressive strength of alkali activated cement mortar based on the changes in the amount/type/composition of binder(portland cement, fly ash, slag) and activator(NaOH, $Na_2SiO_3$, $Na_2CO_3$, $Na_2SO_4$). The mixture design is divided in case I of adding one kind-activator and case II of adding two kind-activators. RESULTS : The results of case I show that $Na_2SO_4$ based mixture has superior the long-term strength when compared to other mixtures, and that $Na_2CO_3$ based mixture has superior the early strength when compared to other mixtures. But the mixtures of case I is difficult to apply in the material for early-opening-to-traffic, because the strength of all mixtures isn't meet the criterion of traffic-opening. The results of case II show that NaOH-$Na_2SiO_3$ based mixtures has superior the early/long-term strength when compared to NaOH-$Na_2SiO_3$ based mixtures. In particular, the NaOH-$Na_2SiO_3$ based some mixtures turned out to pass the reference strength(1-day) of 21MPa as required for traffic-opening. CONCLUSIONS : With these results, it could be concluded that NaOH-$Na_2SiO_3$ based mixtures can be used as the material of pavement repair.

• Computers and Concrete
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• v.12 no.6
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• pp.785-802
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• 2013

Ready-mixed soil material, known as a kind of controlled low-strength material, is a new way of soil cement combination. It can be used as backfill materials. In this paper, artificial neural network and nonlinear regression approach were applied to predict the compressive strength of ready-mixed soil material containing Portland cement, slag, sand, and soil in mixture. The data used for analyzing were obtained from our testing program. In the experiment, we carried out a mix design with three proportions of sand to soil (e.g., 6:4, 5:5, and 4:6). In addition, blast furnace slag partially replaced cement to improve workability, whereas the water-to-binder ratio was fixed. Testing was conducted on samples to estimate its engineering properties as per ASTM such as flowability, strength, and pulse velocity. Based on testing data, the empirical pulse velocity-strength correlation was established by regression method. Next, three topologies of neural network were developed to predict the strength, namely ANN-I, ANN-II, and ANN-III. The first two models are back-propagation feed-forward networks, and the other one is radial basis neural network. The results show that the compressive strength of ready-mixed soil material can be well-predicted from neural networks. Among all currently proposed neural network models, the ANN-I gives the best prediction because it is closest to the actual strength. Moreover, considering combination of pulse velocity and other factors, viz. curing time, and material contents in mixture, the proposed neural networks offer better evaluation than interpolated from pulse velocity only.

• Computers and Concrete
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• v.19 no.3
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• pp.275-282
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• 2017

The aim of this study is to build Machine Learning models to evaluate the effect of blast furnace slag (BFS) and waste tire rubber powder (WTRP) on the compressive strength of cement mortars. In order to develop these models, 12 different mixes with 288 specimens of the 2, 7, 28, and 90 days compressive strength experimental results of cement mortars containing BFS, WTRP and BFS+WTRP were used in training and testing by Random Forest, Ada Boost, SVM and Bayes classifier machine learning models, which implement standard cement tests. The machine learning models were trained with 288 data that acquired from experimental results. The models had four input parameters that cover the amount of Portland cement, BFS, WTRP and sample ages. Furthermore, it had one output parameter which is compressive strength of cement mortars. Experimental observations from compressive strength tests were compared with predictions of machine learning methods. In order to do predictive experimentation, we exploit R programming language and corresponding packages. During experimentation on the dataset, Random Forest, Ada Boost and SVM models have produced notable good outputs with higher coefficients of determination of R2, RMS and MAPE. Among the machine learning algorithms, Ada Boost presented the best R2, RMS and MAPE values, which are 0.9831, 5.2425 and 0.1105, respectively. As a result, in the model, the testing results indicated that experimental data can be estimated to a notable close extent by the model.

• Computers and Concrete
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• v.19 no.4
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• pp.419-427
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• 2017

With the rising global environmental awareness on energy saving and carbon reduction, as well as the environmental transition and natural disasters resulted from the greenhouse effect, waste resources should be efficiently used to save environmental space and achieve environmental protection principle of "sustainable development and recycling". This study used recycled cement mortar and adopted the volumetric method for experimental design, which replaced cement (0%, 10%, 20%, 30%) with recycled materials (fly ash, slag, glass powder) to test compressive strength and ultrasonic pulse velocity (UPV). The hyperbolic function for nonlinear multivariate regression analysis was used to build prediction models, in order to study the effect of different recycled material addition levels (the function of $R_m$(F, S, G) was used and be a representative of the content of recycled materials, such as fly ash, slag and glass) on the compressive strength and UPV of cement mortar. The calculated results are in accordance with laboratory-measured data, which are the mortar compressive strength and UPV of various mix proportions. From the comparison between the prediction analysis values and test results, the coefficient of determination $R^2$ and MAPE (mean absolute percentage error) value of compressive strength are 0.970-0.988 and 5.57-8.84%, respectively. Furthermore, the $R^2$ and MAPE values for UPV are 0.960-0.987 and 1.52-1.74%, respectively. All of the $R^2$ and MAPE values are closely to 1.0 and less than 10%, respectively. Thus, the prediction models established in this study have excellent predictive ability of compressive strength and UPV for recycled materials applied in cement mortar.

• Advances in concrete construction
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• v.9 no.6
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• pp.547-556
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• 2020

This study aimed to develop reference materials (RMs) that are chemically stable and can simulate the flow characteristics of cement paste. To this end, the candidate components of RMs were selected considering the currently required properties of RMs. Limestone, slag, silica, and kaolin were selected as substitutes for cement, while glycerol and corn syrup were selected as matrix fluids. Moreover, distilled water was used for mixing. To select the combinations of materials that meet all the required properties of RMs, flow characteristics were first analyzed. The results revealed that silica and kaolin exhibited bilateral nonlinearity. When an analysis was conducted over time, slag exhibited chemical reactions, including strength development. Moreover, fungi were observed in all mixtures with corn syrup. On the other hand, the combination of limestone, glycerol, and water exhibited a performance that met all the required properties of RMs. Thus, limestone, glycerol, and water were selected as the components of the RMs. When the influence of each component of the RMs on flow characteristics was analyzed, it was found that limestone affects the yield value, while the ratio of water and glycerol affects the plastic viscosity. Based on this, it was possible to select the mixing ratios for the RMs that can simulate the flow characteristics of cement paste under each mixing ratio. This relationship was established as an equation, which was verified under various mixing ratios. Finally, when the flow characteristics were analyzed under various temperature conditions, cement paste and the RMs exhibited similar tendencies in terms of flow characteristics. This indicated that the combinations of the selected materials could be used as RMs that can simulate the flow characteristics of cement paste with constant quality under various mixing ratio conditions and construction environment conditions.

• Journal of the Korea Institute of Building Construction
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• v.11 no.6
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• pp.547-556
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• 2011

The primary factors affecting concrete sulfate resistance are the chemical composition of the Portland cement, and the chemistry and quantity of mineral admixtures. To investigate the effect of those on the sulfate attack, the testing program involved several different mortar mixes using the standardized test, ASTM C1012. Four different cements were evaluated, including one Type I cement, two Type I-II cements, and one Type V cement. Mortar mixes were also made with mineral admixtures, as each cement was combined with three different types of mineral admixtures. One Class F fly ash, one Class C fly ash, and one ground granulated blast furnace slag (GGBFS) were added in various percent volumetric replacement levels. Expansion measurements were taken and investigated with the expansion criteria recommended by ASTM.