• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.731-738
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• 2002

Recently, as large constructions on the coast are performed frequently, surface layer stabilization method which Is one of the improvement methods for dredged soft clay has been applied. However, there have been few studies about the surface layer stabilization method. The purpose of this study is to clarify characteristics of ultra-soft marine clay and hardening agent. Also, optimal mixture ratio of hardening agent was verified through the laboratory tests such as statistical analysis and pilot tests. Laboratory tests were performed with proper hardening agent and test soil and standard mixing tables of hardening agent were determined according to ground conditions through statistical analysis. Also, applicability of surface layer stabilization method to field was verified by pilot tests. From the results of the tests, it was found that hardening agent materials such as cement, slag, fly-ash, inorganic salts, arwin, gypsum etc. affect on the appearing compressive strength. It was defined optimal mixture ratio which satisfies the required compressive strength from the statistical analysis. Also, It was compared the effect of ground improvement by cements and hardening agents through the pilot tests. This study will serve as data for design or construction criteria of stabilization of surface layer on ultra-soft marine clay.

• Computers and Concrete
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• v.27 no.1
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• pp.21-28
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• 2021

The Artificial Neural Network (ANN) is a system, which is utilized for solving complicated problems by using nonlinear equations. This study aims to investigate compressive strength, rebound hammer number (RN), and ultrasonic pulse velocity (UPV) of sustainable concrete containing various amounts of fly ash, silica fume, and blast furnace slag (BFS). In this study, the artificial neural network technique connects a nonlinear phenomenon and the intrinsic properties of sustainable concrete, which establishes relationships between them in a model. To this end, a total of 645 data sets were collected for the concrete mixtures from previously published papers at different curing times and test ages at 3, 7, 28, 90, 180 days to propose a model of nine inputs and three outputs. The ANN model's statistical parameter R2 is 0.99 of the training, validation, and test steps, which showed that the proposed model provided good prediction of compressive strength, RN, and UPV of sustainable concrete with the addition of cement.

• Structural Engineering and Mechanics
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• v.77 no.1
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• pp.103-114
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• 2021

Ultra high strength concrete (UHSC) originally proposed by Richards and Cheyrezy (1995) composed of cement, silica fume, quartz sand, quartz powder, steel fibers, superplasticizer etc. Later, other ingredients such as fly ash, GGBS, metakaoline, copper slag, fine aggregate of different sizes have been added to original UHSC. In the present investigation, the combined effect of coarse aggregate (6mm - 10mm) and steel fibers (0.50%, 1.0% and 1.5%) has been studied on UHSC mixes to evaluate mechanical and fracture properties. Compressive strength, split tensile strength and modulus of elasticity were determined for the three UHSC mixes. Size dependent fracture energy was evaluated by using RILEM work of fracture and size independent fracture energy was evaluated by using (i) RILEM work of fracture with tail correction to load - deflection plot (ii) boundary effect method. The constitutive relationship between the residual stress carrying capacity (σ) and the corresponding crack opening (w) has been constructed in an inverse manner based on the concept of a non-linear hinge from the load-crack mouth opening plots of notched three-point bend beams. It was found that (i) the size independent fracture energy obtained by using above two approaches yielded similar value and (ii) tensile stress increases with the increase of % of fibers. These two fracture properties will be very much useful for the analysis of cracked concrete structural components.

• 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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• 2021.05a
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• pp.23-24
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• 2021

The use of recycled concrete aggregates (RCA) as a substitute for natural aggregates in new concrete produces both economic and environmental advantages. Most of the RCA applications for pavements have been primarily applied to support layers for roads and airfields. This paper summarizes a work completed at the University of Illinois in partnership with the O'Hare Modernization Program to examine the effect of coarse and fine RCA on the concrete's fresh and hardened properties for airfield rigid pavement applications. Ten different RCA concrete mixtures were prepared with the incorporation of different percentages of RCA fines as well as replacement of cement with high volume percentages of supplementary cementitious materials such as Class C fly ash and ground granulated blast furnace slag to improve the workability and long-term properties of RCA concrete. All the mixes on this stage included 100% recycled coarse aggregates and the Two-Stage Mixing Approach was used as a mixing procedure. Based on the results obtained in the research, mixes with high percentages of recycled fine and coarse aggregates could be used for construction of airfield concrete pavements in conjunction with supplementary cementitious materials

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.126-127
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• 2020

Recently, as interest in environmental issues increases, minimizing carbon dioxide generated during cement manufacturing is a problem to be solved. In order to solve such a problem, it is required to use an industrial by-product of recycled aggregate, blast furnace slag, and circulating fluidized bed boiler fly ash to replace it on the basis of geopolymer(=cementless). This study examines the characteristics of eco-friendly artificial stone according to the mixing ratio of geopolymer-based recycled aggregate. As a result of the experiment, when the addition rate of the alkali stimulant was 15% and the mixing ratio of the circulating aggregate was 70%, the flexural strength and compressive strength were the highest. Density and water absorption decreased as density of circulating aggregates increased and water absorption increased. However, when the mixing ratio of the circulating aggregate exceeded 70%, the flexural strength and compressive strength decreased. Therefore, in order to obtain strengths meeting the KS standards, the mixing ratio of recycled aggregate was set to 70%, and artificial stone was manufactured using industrial by-products.

• Computers and Concrete
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• v.32 no.4
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• pp.373-381
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• 2023

Fly ash, granulated blast furnace slag, marble waste powder, etc. are just some of the by-products of other sectors that the construction industry is looking to include into the many types of concrete they produce. This research seeks to use surrogate machine learning methods to forecast the compressive strength of self-compacting concrete. The surrogate models were developed using Gradient Boosting Machine (GBM), Support Vector Machine (SVM), Random Forest (RF), and Gaussian Process Regression (GPR) techniques. Compressive strength is used as the output variable, with nano silica content, cement content, coarse aggregate content, fine aggregate content, superplasticizer, curing duration, and water-binder ratio as input variables. Of the four models, GBM had the highest accuracy in determining the compressive strength of SCC. The concrete's compressive strength is worst predicted by GPR. Compressive strength of SCC with nano silica is found to be most affected by curing time and least by fine aggregate.

• Journal of the Korean Recycled Construction Resources Institute
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• v.6 no.4
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• pp.127-133
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• 2012

In this paper, tests were carried out to monitor the effect of the curing temperature on autogenous shrinkage of the high strength cement mortar incorporating silica fume, blast furnace slag and fly ash ranged from 10%~30% by mass of cement. The curing temperatures were varied from $5^{\circ}C$ to $35^{\circ}C$, respectively. According to results, the setting time exhibited to delay with increase of admixture and drop of temperature. As for the effect of curing temperature on autogenous shrinkage, the increase of SF and BS resulted in an increase of autogenous shrinkage, while the use of FA decrease. The higher the curing temperature is, the greater the autogenous shrinkage is. This is due to the accelerated hydration rate of cement. It is found that the maturity does not consider the effect of curing temperature on autogenous shrinkage.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.6
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• pp.9-17
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• 2019

Cement hydrates and the related characteristics change with ages, and the behaviors are much related with chloride diffusion. In this work, 30% replacement ratio with FA(Fly Ash) and GGBFS(Ground Granulated Blast Furnace Slag) are considered for concrete with three levels of W/B (Water to Binder ratio) and 2 years of curing period. Chloride diffusion coefficients from accelerated condition are obtained at 5 measurement period (28days, 56days, 180days, 365days, and 730days), and the results are compared with porosity, binding capacity, and permeability from program-DUCOM. The similar changing pattern between chloride diffusion and permeability is observed since permeability is proportional to the square of porosity. Curing period is grouped into 4 periods and the changing ratios are investigated. Cement hydrate characteristics such as porosity, permeability, and diffusion coefficient are dominantly changed at the early ages (28~56 days), and diffusion coefficient in OPC concrete with low W/B continuously changes to 180days.

• Journal of Soil and Groundwater Environment
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• v.21 no.6
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• pp.135-145
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• 2016

MgO recently has been regarded as the alternative material for replacement of cement. The aim of this study is to investigate the effects of accelerated carbonation on the strength development of MgO-based binder which is binary mixtures of magnesium oxide (MgO) with portland cement (PC) or ground granulated blast furnace slag (GGBS) or fly ash (FA). The compressive strengths of all binders were higher in the 20% $CO_2$ condition and for longer curing time. The strength were generally higher as the following order: MgO/PC > MgO/GGBS > MgO/FA system. The binder composed of 20% MgO and 80% PC showed highest compressive strength (38.0MPa) which was higher than PC. The correlation analysis of the porosity and compressive strength showed that compressive strength was higher when porosity was lower. The hydration and carbonation products of MgO including brucite ($Ca(OH)_2$), magnesite ($MgCO_3$) and nesquehonite ($MgCO_3{\cdot}3H_2O$) presumably filled the pores and contributed to strength development. Thermogravimetric analyses elucidated that 0.34 kg of $CO_2$ could be stored the 50% MgO/50% PC binder which performed the maximum $CO_2$ uptake at 20% $CO_2$ condition.