• Resources Recycling
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• v.21 no.1
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• pp.30-40
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• 2012

Electric arc furnace slag is made in ironworks during steel refining, it is been increasing chemical and physical resistibility using ageing method of unstable state of melting steel slag for using concrete's fine aggregates. Which is been changing stable molecular structure of aggregates, it restrains moving of ion and molecule. In Korea, KS F 4571 has been prepared for using the electric arc furnace oxidizing slag to concrete aggregates(EFS). In this study, Electric arc furnace oxidizing slag is used in the PRCC(Polymer Rapid setting Cement Concrete) which is applied a bridge pavement of rehabilitation, largely. The results showed that the increment of compressive strength development by 10- 20%. The flexural strength of EFS-Con increased greatly as the electric arc furnace oxidizing slag changed. The compressive strength and flexural strength developed enough for opening the overlayed EFS-Con to the traffic after 4 hours of EFS-Con placement. The permeability of EFS-Con was evaluated as negligible due to its very low charge passed. Thus, EFS-Con could be used at repairing or overlaying the concrete at fast-track job sites.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2002.11a
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• pp.29-36
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• 2002

High fluid concrete unlike OPC concrete is made with various material, and the phase of fresh concrete is considerably different. In order to understand fluidity phase and mix properties of high fluid concrete, concrete is required to access as suspension structure which consists of aggregate and paste. The focus of this paper is to analyze the test results and quantify the effect of mix proportions of molar and fineness modulus of ,and on the properties of fresh mortar. The effect of water-binder ratio, sand-binder ration, content; of ggbs (by mass of total cementitious materials), and various contents of water reducing agent on the yield stress and plastic viscosity of the mix is studied. Based on the experimental results, the following conclusion; can be drawn: (1) The mixing time needed (or high fluid mortar was approximately two times more than that of ordinary portland mortar. (2) The fluidity phase of mortar could be explained by yield stress of mix and the fluidity of mortar. (3) As the content of ggbs increased, yield stress of mortar was decreased and plastic viscosity of it was increased. (4) For the high fluid mortar, it was appeared that sand-binder ratio should be below 1.5.

• Journal of the Korean Recycled Construction Resources Institute
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• v.4 no.2
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• pp.97-106
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• 2009

self-loading, various problems related to construction can be solved as well as the save of construction cost. Thus, this study has an aim of applying foam concrete to structural purpose by adding bottom ash as a reinforcing material like fine aggregate, in contrast to conventional non-structural usage such as soundproofing or insulating materials. In addition, it was evaluated in terms of unit volume weight, flow value, air void, water absorption and dosage of foam agent wether replacement of cement by granulated blast furnace slag or fly-ash has an effect on the material characteristics of foam concrete. As results of experiments, it can be found that the increase of fine aggregate ratio, that is to say, the increase of bottom ash results in the increase of unit volume weight, while decreasing air void and flow value. But, appropriate addition of bottom ash to foam concrete makes it easy to control a homogeneous and uniform quality in foam concrete due to less sensitive to bubbles. As the replacement ratio of mineral admixtures such as granulated blast furnace slag and fly-ash increases, as unit volume weight tends to decrease. In the meanwhile, serious effects were shown on fluidity of foam concrete when more than limit of replacement ratio was applied.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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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.

• Smart Structures and Systems
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• v.26 no.2
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• pp.241-251
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• 2020

Due to the undeniable importance of approximating the concrete compressive strength (CSC) in civil engineering, this paper focuses on presenting four novel optimizations of multi-layer perceptron (MLP) neural network, namely artificial bee colony (ABC-MLP), grasshopper optimization algorithm (GOA-MLP), shuffled frog leaping algorithm (SFLA-MLP), and salp swarm algorithm (SSA-MLP) for predicting this crucial parameter. The used dataset consists of 103 rows of information concerning seven influential parameters (cement, slag, water, fly ash, superplasticizer, fine aggregate, and coarse aggregate). In this work, the best-fitted complexity of each ensemble is determined by a population-based sensitivity analysis. The GOA distinguished its self by the least complexity (population size = 50) and emerged as the second time-effective optimizer. Referring to the prediction results, all tested algorithms are able to construct reliable networks. However, the SSA (Correlation = 0.9652 and Error = 1.3939) and GOA (Correlation = 0.9629 and Error = 1.3922) performed more accurately than ABC (Correlation = 0.7060 and Error = 4.0161) and SFLA (Correlation = 0.8890 and Error = 2.5480). Therefore, the SSA-MLP and GOA-MLP can be promising alternatives to laboratorial and traditional CSC evaluative methods.

• Computers and Concrete
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• v.21 no.4
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• pp.463-470
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• 2018

In the present study, soft computing i.e., machine learning techniques and regression models algorithms have earned much importance for the prediction of the various parameters in different fields of science and engineering. This paper depicts that how regression models can be implemented for the prediction of compressive strength of concrete. Three models are taken into consideration for this; they are Gaussian Process for Regression (GPR), Multi Adaptive Regression Spline (MARS) and Minimax Probability Machine Regression (MPMR). Contents of cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, fine aggregate and age in days have been taken as inputs and compressive strength as output for GPR, MARS and MPMR models. A comparatively large set of data including 1030 normalized previously published results which were obtained from experiments were utilized. Here, a comparison is made between the results obtained from all the above mentioned models and the model which provides the best fit is established. The experimental results manifest that proposed models are robust for determination of compressive strength of concrete.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.11a
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• pp.68-71
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• 2013

Reactive Powder Concrete (RPC) is an ultra high strength and high ductility cement-based composite material and has shown some promise as a new generation concrete in construction field. It is characterized by a silica fume-cement mixture with very low water-binder (w/b) ratio and very dense microstructure, which is formed using various powders such as cement, silica fume and very fine quartz sand (0.15~0.4mm) instead of ordinary coarse aggregate. However, the unit weight of cement in RPC is as high as 900~1,000 kg/㎥ due to the use of very fine sand instead of coarse aggregate, and a large volume of relatively expensive silica fume as a high reactivity pozzolan is also used, which is not produced in Korea and thus must be imported. Since the density of RPC has a heavy weight at 2.5~3.0 g/㎤. In this study, the modified RPC was made by the combination of ternary pozzolanic materials such as blast furnace slag and fly ash, silica fume in order to economically and practically feasible for Korea's situation. The fire resistance and structural behavior of the modified RPC exposed to high temperature were investigated.

• Smart Structures and Systems
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• v.30 no.2
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• pp.195-207
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• 2022

Computational drawbacks associated with regular predictive models have motivated engineers to use hybrid techniques in dealing with complex engineering tasks like simulating the compressive strength of concrete (CSC). This study evaluates the efficiency of tree potential metaheuristic schemes, namely shuffled complex evolution (SCE), multi-verse optimizer (MVO), and beetle antennae search (BAS) for optimizing the performance of a multi-layer perceptron (MLP) system. The models are fed by the information of 1030 concrete specimens (where the amount of cement, blast furnace slag (BFS), fly ash (FA1), water, superplasticizer (SP), coarse aggregate (CA), and fine aggregate (FA2) are taken as independent factors). The results of the ensembles are compared to unreinforced MLP to examine improvements resulted from the incorporation of the SCE, MVO, and BAS. It was shown that these algorithms can considerably enhance the training and prediction accuracy of the MLP. Overall, the proposed models are capable of presenting an early, inexpensive, and reliable prediction of the CSC. Due to the higher accuracy of the BAS-based model, a predictive formula is extracted from this algorithm.

• 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.

• Journal of the Korea Concrete Institute
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• v.21 no.1
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• pp.55-64
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• 2009

This study is aimed to derive the optimum mix proportion of the combined self compacting concrete according to cement types (blast-furnace slag cement and belite cement) and to propose the basic data to field construction work after evaluating the quality properties. Specially, lime stone powder (LSP) as binder and viscosity agent are used in the combined self compacting concrete because slurry wall of an underground LNG storage tank should be kept stability of quality during concrete working. Replacement ratio of LSP is determined by confined water ratio test and main design factors including fine aggregate ratio ($S_r$), coarse aggregate ratio ($G_v$) and water-cement ratio (W/C) are selected. Also, quality properties including setting time, bleeding content, shortening depth and hydration heat on the optimum mix proportion of the combined self compacting concrete according to cement type are compared and analyzed. As test results, the optimum mix proportion of the combined self compacting concrete according to cement type is as followings. 1) Slag cement type-replacement ratio of LSP 13.5%, $S_r$ 47% and W/C 41%. 2) Belite cement type-replacement ratio of LSP 42.7%, Sr 43% and W/C 51%. But optimum coarse aggregate ratio is 53% regardless of cement types. Also, as test results regarding setting time, bleeding content, shortening depth and hydration heat of the combined self compacting concrete by cement type, belite cement type is most stable in the quality properties and is to apply the actual construction work.