• Steel and Composite Structures
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• v.43 no.3
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• pp.389-401
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• 2022

This study investigated the flowability and mechanical properties of cost-effective steel fiber reinforced ultra-high performance concrete (UHPC) by using locally available materials for field-cast application. To examine the effect of mixture constituents, five mixtures with different fractions of silica fume, silica powder, ground granulated blast furnace slag (GGBS), silica sand, and crushed natural sand were proportionally prepared. Comprehensive experiments for different mixture designs were conducted to evaluate the fresh- and hardened-state properties of self-consolidating UHPC. The results showed that the proposed UHPC had similar mechanical properties compared with conventional UHPC while the flow retention over time was enhanced so that the field-cast application seemed appropriately cost-effective. The self-consolidating UHPC with high flowability and low viscosity takes less total mixing time than conventional UHPC up to 6.7 times. The X-ray computed tomographic imaging was performed to investigate the steel fiber distribution inside the UHPC by visualizing the spatial distribution of steel fibers well. Finally, the tensile stress-strain curve for the proposed UHPC was proposed for the implementation to the structural analysis and design.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2007.04a
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• pp.25-28
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• 2007

In this study we measured the changes according to time respectively on the basis of 0, 30, 60 and 90 minutes, taking into consideration the decline in fluidity of concrete according to elapsed time to analyze manufacturing capability of batcher plant according to elapsed time of ready-mixed concrete manufactured in batcher plant, and offer basic data for mixture design of ultra-high strength concrete. The proportion of water-binder was 23.55, water content was 160kg/m3, proportion of replacement of crushed sand was 0, 20 and 40% at 3 level, and we applied to the same condition of triaxial component using blast furnace slag powder and silica fume as admixture. And to meet the demand of certain fluidity, we measured respectively on property before and after hardening of ultra-high strength concrete using superplasticizer. As a result of experiment, before hardening of ultra-high strength concrete showed the best fluidity in conditions of crushed sand replacement rates of 20% and superplasticizer composition of 1.95%, but it appeared that fluidity drops as time goes by in the same composition condition. And it appeared that when it comes to hardened, the changes of compression strength according to elapsed time by crushed sand replacement rates were within 1MPa. Therefore, it turned out that the difference of strength according to elapsed time was low and compression strength of 280dys in composition mentioned above appeared highly as 88MPa.

• 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.

• Journal of the Korea Concrete Institute
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• v.19 no.5
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• pp.549-555
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• 2007

Although blast furnace slag has been widely used in concrete as a cementitious admixture or aggregate for many years, the slowly cooled steel slag is not used in concrete but mainly in road. Its use in concrete operates problem such as the lack of volume stability due to high free CaO content, which can be potentially hazardous in concrete. However, the rapidly cooled steel slag by atomization has a low free CaO content, a high density, and a spherical shape, so it is expected to use in concrete so much. This paper is to understand the probability that the rapid cooled steel slag can replace the silica sand used as aggregate in the epoxy mortar. We did the experimental study on the properties of the epoxy mortar having various replacement proportion of rapidly cooled steel slag. This study shown that increasing content of the rapidly cooled steel slag in epoxy mortar lead to increase largely the passing time of nozzle by O-lot, compressive strength and flexural strength. However except the flow is almost same level. So we understand that the rapidly cooled steel slag has positive effect on increasing of properties in epoxy mortar.

• Journal of the Korea Institute of Building Construction
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• v.3 no.4
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• pp.79-86
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• 2003

The purpose of study is to offer base data for high fluid concrete mix property, as grasp effect of aggregate to reach much more effect for producing high fluid concrete. For this study, there are three types of combined aggregates, river sand + river aggregate(type A), river sand + crusted aggregate(type B), washed sea sand + crushed aggregate(type C) and take a factor, water-contents, water-binder ratio and S/a. And so, we had following conclusion, resulting application-ability of high fluid mortar by K-slump tester to use a handy consistency measuring instrument. And so, we had following conclusion, resulting application-ability of high fluid concrete by K-slump tester to use a handy consistency measuring instrument. 1) In cafe of regular water binder ratio, high fluid concrete suffered much effect of combined aggregates and water binder ratio. Range of water binder ratio by combined aggregates is w/b 0.4 downward(type A and B), w/b 0.35 downward(type C). 2) Water contents to need for producing high fluid concrete is minimum 170kg/$\textrm{m}^3$ without regard to combined aggregates. 3) The effect of S/a on high fluid concrete by combined aggregates is approximately S/a 50% (type A and B), s/a 50-55% (type C). 4) Consistency measuring of high fluid concrete by K-slump tester is possible and first indication value, high fluid concrete can be produced, is 6~10.5cm.

• Journal of the Korea Institute of Building Construction
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• v.7 no.2 s.24
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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%.

• International Journal of Concrete Structures and Materials
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• v.7 no.3
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• pp.193-202
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• 2013

Geopolymer mortar compressed blocks were prepared using fly ash, ground granulated blast furnace slag, silica fume and metakaolin as binders and sand/quarry dust/pond ash as fine aggregate. Alkaline solution was used to activate the source materials for synthesizing the geopolymer mortar. Fresh mortar was used to obtain the compressed blocks. The strength development with reference to different parameters was studied. The different parameters considered were fineness of fly ash, binder components, type of fine aggregate, molarity of alkaline solution, age of specimen, fluid-to-binder ratio, binder-to-aggregate ratio, degree of saturation, etc. The compressed blocks were tested for compression at different ages. It was observed that some of the blocks attained considerable strength within 24 h under ambient conditions. The cardinal aim was to analyze the experimental data generated to formulate a phenomenological model to arrive at the combinations of the ingredients to produce geopolymer blocks to meet the strength development desired at the specified age. The strength data was analyzed within the framework of generalized Abrams' law. It was interesting to note that the law was applicable to the analysis of strength development of partially saturated compressed blocks when the degree of saturation was maintained constant. The validity of phenomenological model was examined with an independent set of experimental data. The blocks can replace the traditional masonry blocks with many advantages.

• Advances in concrete construction
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• v.8 no.2
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• pp.127-137
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• 2019

Roller Compacted Concrete (RCC) is a zero slump concrete consisting of a mixture of cementitious materials, sand, dense graded aggregates and water. In this study, an attempt has been made to investigate the effect of aggregate type on strength and abrasion resistance of RCC made by using granulated blast furnace slag (GGBS) as partial replacement of cement. Mix proportions of RCC were finalized based upon the optimum water content achieved in compaction test. Two different series of RCC mixes were prepared with two different aggregates: crushed gravel and limestone aggregates. In both series, cement was partially replaced with GGBS at a replacement level of 20%, 40% and 60%. Strength Properties and abrasion resistance of the resultant mixes was investigated. Abrasion resistance becomes an essential parameter for understanding the acceptability of RCC for rigid pavements. Experimental results show that limestone aggregates, with optimum percentage of GGBS, perform better in compressive strength and abrasion resistance as compared to the use of crushed gravel aggregates. Observed results are further supported by stoichiometric analysis of the mixes by using basic stoichiometric equations for hydration of major cement compounds.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.671-681
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• 2019

This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate ($Na_2SiO_3$) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature ($28^{\circ}C$) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.21-22
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• 2021

This study incorporates fine waste glass (GS) as a replacement for natural sand (NS) in ground granulated blast furnace slag (GGBS) based alkali activated mortar (AAm). Tests were conducted on the AAm to determine the mechanical properties, apparent porosity and the durability based on its resistance to Na2SO4 5% and H2SO4 2% concentrated solutions. The study revealed that increasing GS up to 100 wt%, increased strength and decreased porosity. The lower porosity attained with the incorporation of GS, improved the resistance of mortar to Na2SO4 and thus increasing durability. However, the durability of mortar to H2SO4 solution was negatively impacted with the further reduction of porosity observed with increasing GS above 50 wt.% believed to be caused by the stress induced as a result of expansive reaction products created when the mortar reacted with acid.