• Proceedings of the Korea Concrete Institute Conference
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• 2005.05b
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• pp.153-156
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• 2005

Surface dry condition examination method on the KS F 2504(Testing method for specific gravity and absorption of fine aggregate) has dim detail prescriptions which can cause different ways of understanding based on one's convinence, not on correct means of rule. So we investigate the problems about the inconsistency on decisioing surface dry condition at management examination in the lab and scene. In conclusion, free-falling method is easier and faster than self-weight method. And we also found that the most important face on decisioning surface dry is compacting factor of tamping rod.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.1
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• pp.111-116
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• 2022

Recently, building structures tend to be super high-rise and large-scale with the development of concrete technology. When high-rise building is constructed of reinforced concrete structure, it has a disadvantage that its own weight increases. Light weight aggregate(LWA) was developed to compensate for these shortcomings. Manufacturing concrete using these light weight aggregates has the advantage of reducing the self weight of the reinforced concrete structure, but has a disadvantage in that the strength of the concrete is reduced. In this study, an experimental study was conducted to investigate the strength characteristics of hardened cement according to the presence or absence of surface coating of lightweight aggregates. As a result, in terms of compressive strength, the surface-coated lightweight aggregate exhibited higher strength than the uncoated lightweight aggregate. Also, it was considered that this is because the interfacial voids of the surface coated lightweight aggregate mixed cement hardened body were filled with blast furnace slag fine powder particles.

• Advances in concrete construction
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• v.6 no.2
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• pp.123-143
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• 2018

Self compacting concrete (SCC) has good flowability, passability and segregation resistance because of voluminous cementitious material & high coarse aggregate to fine aggregate ratio, and high free water availability. But these factors make it highly susceptible to shrinkage. Fibers are known to reduce shrinkage in concrete mixes. Until now for conserving cement, only pozzolanic materials are admixed in concrete to yield a SCC. Hence, this study compares the use of wollastonite micro fiber (WMF), a cheap pozzolanic easily processed raw mineral fiber, and flyash in yielding economical SCC for rigid pavement. Microsilica was used as a complimentary material with both admixtures. Since WMF has large surface area ($827m^2/kg$), is acicular in nature; therefore its use in yielding SCC was dubious. Binary and ternary mixes were constituted for WMF and flyash, respectively. Paste mixes were tested for compatibility with superplasticizer and trials were performed on a normal concrete mix of flexural strength 4.5 MPa to yield SCC. Flexural strength test and restrained shrinkage test were performed on those mixes, which qualified self compacting criteria. Results revealed that WMF admixed pastes have high water demand, and comparable setting times to flyash mixes. Workability tests showed that 20% WMF with microsilica (5-7.5%) is efficient enough in achieving SCC and higher flexural strength than normal concrete at 90 days. Also, stress rate due to shrinkage was lesser and time duration for final strain was higher in WMF admixed SCC which encourages its use in yielding a SCC than pozzolanic materials.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.40-49
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• 2004

In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Self-Organizing Polynomial Neural Networks(SOPNN), discuss a comprehensive design methodology and carry out a series of numeric experiments. The conventional SOPNN is based on the extended Group Method of Data Handling(GMDH) method and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons (or nodes) located in each layer through a growth process of the network. Moreover it does not guarantee that the SOPNN generated through learning has the optimal network architecture. But the proposed GA-based SOPNN enable the architecture to be a structurally more optimized network, and to be much more flexible and preferable neural network than the conventional SOPNN. In order to generate the structurally optimized SOPNN, GA-based design procedure at each stage (layer) of SOPNN leads to the selection of preferred nodes (or PNs) with optimal parameters- such as the number of input variables, input variables, and the order of the polynomial-available within SOPNN. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. A detailed design procedure is discussed in detail. To evaluate the performance of the GA-based SOPNN, the model is experimented with using two time series data (gas furnace and NOx emission process data of gas turbine power plant). A comparative analysis shows that the proposed GA-based SOPNN is model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.365-368
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• 2008

In recent, the crushed sand as a fine aggregate has increasingly used for concrete industry due to the shortage of natural sand from river and the growing demand for protection of natural environments. Aggregates may have a significant influence on the properties of self-compacting concrete (SCC) including self-compacting mortar (SCM). The rheological properties of SCC and SCM using crushed sand as a fine aggregate has been compared to that of SCC and SCM using natural sand and mixed sand of both. Test results indicate that the yield stress of SCM containing 50% of mixed sand present higher than those prepared with natural sand and crushed sand according to SP content. the slump values of SCC with natural sand have approximately 5-15% higher than those of SCC with crushed sand. Also the L-box test values ($H_2/H_1$) of SCC with natural sand have approximately 20-30 higher than those of SCC with crushed sand under same water/cement ratio and viscosity enhancing admixture.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.341-344
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• 2008

Lightweight concrete is known for its advantage of reducing the self-weight of the structures, reducing the areas of sectional members as well as making the construction convenient. Thus the construction cost can be saved when applied to structures such as long-span bridge and high rise building. However, the lightweight concrete requires specific mix design method that is quite different from the typical concrete, since using the typical mix method would give rise the material segregation as well as lower the strength by the reduced weight of the aggregate. In order to avoid such problems, it is recommended to apply the mix design method of self-consolidating concrete for the lightweight concrete. Therefore experimental tests were performed as such mechanical properties(compressive strength, dry density and structural efficiency) of concrete and dry shrinkage according to ACI committee 209.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.423-434
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• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• Advances in concrete construction
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• v.13 no.5
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• pp.349-360
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• 2022

The rising prices of landfills and the lack of cement production are motivating researchers to be more interested in using wastes to produce concrete mixtures materials. The use of waste materials such as eggshell and matakoline waste not only reduces landfill costs and space, but also reduces the cost of cement production for the concrete mixture. However, recycling waste materials has become critical in order to effectively manage environmental sustainability. The purpose of this paper is to investigate the appropriate properties of self-compacting concrete (SCC) by incorporating waste materials such as crushed ceramics as coarse aggregate and nano egg shell (NES) and nanoclay (NC) as cement replacements. Fresh properties of SCC, such as segregation, flow time and diameter, V-funnel, H2/H1 ratio, and fresh unit weight of concrete mixtures, as well as hardened properties, such as 7, 14, and 28 days compressive strength and 28 and 90 days flexural strength, were measured for this purpose. The presence of NC in the SCC mixture enhanced the compressive strength of the concrete when 5% of NES was added or in the case without the addition of NES compared to the control mixture. The flexural strength enhanced with the incorporation of NC in the SCC increased the flexural strength of the concrete compared to the control mixture, but the incorporation of 5% of NES decreased the flexural strength compared to the mixtures with NC. These results prove the possibility of using crushed ceramics as the coarse aggregate, and NES and NC as substitutes for 5, 7, and 10% of the cement in SCC, because the properties of such SCC in hardened and fresh states are satisfactory.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.11a
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• pp.411-414
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• 2005

Concrete structure is recognized as the universal structuring material for its outstanding formability, economic efficiency, and strength development. However, as the ageing of field workers and the deficiency of skilled workers due to evasions from 3D business have recently become the major issues of the industry in Korea and as the materials are becoming more diversified and complicated for today's concrete structures are becoming higher, larger, and specialized, the need for practicality of construction work based on new technology and new method has greatly increased. In other words, the overall condition of today's construction business requires researches and developments on the self-compacting concrete for higher construction efficiency and quality improvements and the high-strength lightweight concrete for concrete weight reduction and reduction of area. Therefore experimental tests were performed as such compressive strength, dry shrinkage and carbonation of self-compacting concrete.

• Structural Engineering and Mechanics
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• v.67 no.1
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• pp.87-91
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• 2018

Concrete is the most widely used building material all over the world, because of its many technical and economic qualities. This pressure on the concrete resource causes an intensive exploitation of the quarries of aggregates, which results in a exhaustion of these and environmental problems. That is why recycling and valorization of materials are considered as future solutions, to fill the deficit between production and consumption and to protect the environment. This study is part of the valorization process of local materials, which aims to reuse marble waste as fine aggregate (excess loads of marble waste exposed to bad weather conditions) available in the marble quarry of Fil-fila (Skikda, East of Algeria) in the manufacture of self-compacting concretes. It consists of introducing the marble waste as sand into the self-compacting concrete formulation, with variable percentages (25%, 50%, 75% and 100%) and to study the development of its properties both in fresh state (air content, density, slump flow, V-funnel, L-box and sieve stability) as well as the hardened one (compressive strength and flexural strength). The results obtained showed us that marble wastes can be used as sand in the manufacture of self compacting concretes.