• Journal of the Korean Society of Hazard Mitigation
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• v.3 no.4 s.11
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• pp.119-129
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• 2003

Concrete and steel are essential structural materials in the construction. But, concrete, different from steel, consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructors. Concrete have two kinds of properties, immediately knowing properties such as slump, air contents and time dependent one like strength. Therefore, concrete mixes depend on experiences of experts. However, at point of time using High Performance Concrete, new method is wanted because of more ingredients like mineral and chemical admixtures and lack of data. Artificial Neural Networks(ANN) are a mimic models of human brain to solve a complex nonlinear problem. They are powerful pattern recognizers and classifiers, also their computing abilities have been proven in the fields of prediction, estimation and pattern recognition. Here, among them, the back propagation network and radial basis function network ate used. Compositions of high-performance concrete mixes are eight components(water, cement, fine aggregate, coarse aggregate, fly ash, silica fume, superplasticizer and air-entrainer). Compressive strength, slump, and air contents are measured. The results show that neural networks are proper tools to minimize the uncertainties of the design of concrete mixtures.

• Journal of the Korea Institute of Building Construction
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• v.18 no.3
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• pp.211-218
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• 2018

This study examined the reliability and revision necessity of concrete standard specifications based on the comparisons with test data obtained by using domestic artificial lightweight aggregates and the contents specified in different foreign specifications including ACI 211.2, ACI 213, ACI 301, JASS 5 and CEB-FIP. To achieve the continuous particle distribution of domestic fine lightweight aggregates, the partial addition of natural sand with the maximum size of 2.5mm was required. To control the segregation and excessive bleeding in the fresh lightweight concrete, the current limitations on the water-to-binder ratio and unit water content need to be modified using lower values. In particular, a rational mixture proportion approach of lightweight concrete needs to be established for the targeted requirements of initial slump, 28-day compressive strength, air content and dry unit weight. Ultimately, significant revision of the concrete standard specifications is required considering the characteristics of domestic artificial lightweight aggregates.

• Journal of Korean Neurosurgical Society
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• v.30 no.sup2
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• pp.189-196
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• 2001

Objective : We tested the hypothesis that photodynamic therapy(PDT) with Photofrin inhibits tumor invasion of U87 human glioma cells using several in vitro assay to measure tumor invasiveness. The effects of PDT on cell growth, directional migration and cell invasion were investigated. Material and Method : Tumor cells were treated with Photofrin at various doses and at a fixed optical(632nm) dose of $100mJ/cm^2$. Cytotoxicity was tested using the MTT method. Invasion assays including the matrigelartificial basement membrane barrier migration and spheroid confrontation with confocal microscopic analysis were used to study the relationship between PDT and invasiveness. Result : U87 cells showed a dose dependent cytotoxic response to increasing Photofrin dose. Data from the matrigel artificial basement membrane assay indicate that PDT inhibits the U87 cell migration dose dependently. Low doses of subcytotoxic PDT treatment, such as 2.5ug/ml Photofrin dose, also appeared to significantly inhibit migration of U87 cells(p<0.05). In co-cultures between U87 cell spheroids and brain aggregates, progressive invasion with destruction of the brain aggregate occurs. The extent of tumor cell infiltration and proportion or intact brain aggregate remaining after 24h differs in Photofrin PDT treated versus Photofrin only control, with changes suggestive of a dose-response effect. Conclusion : our data indicate that PDT with Photofrin significantly inhibits the invasiveness of U87 cells, and this inhibition is dose dependent.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.22 no.4
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• pp.200-206
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• 2012

The artificial aggregate composing of coal bottom ash and waste catalyst slag (7 : 3, wt%) were fabricated using direct sintering method and, the bloating properties of aggregates were investigated as a function of raw material particle size and sintering temperature. Most of the artificial aggregates sintered at over $1150^{\circ}C$ showed the bloating phenomenon regardless of particle size of the raw materials. Consequently, the specific gravity of the aggregates was drastically decreased to below 1.4. The aggregates containing waste catalyst slag of $90{\mu}m$ under among the W-series specimens, however, did not show the noticeable bloating phenomenon. For the aggregates sintered at lower temperature as $1050{\sim}1150^{\circ}C$, the specific gravity increased with particle size of raw materials. Also, the water absorption of all aggregates decreased with the sintering temperature. The aggregates fabricated in this study met the lightweight aggregate standard showing the specific gravity 1.7~1.4 and water absorption 8~19 % and, therefore, can be applicable for the various fields.

• Journal of Ocean Engineering and Technology
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• v.19 no.4 s.65
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• pp.28-34
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• 2005

In the study application of volcanic scoria concrete to artificial reefs is investigated. Volcanic scoria is a natural volcanic product that shows light weight, mil/i-porous, and far-infrared irradiation characteristics. The properties of volcanic scoria concrete using Jeju scoria aggregate are evaluated by conducting a comprehensive series of tests on strength and void ratio. It is concluded that the volcanic scoria concrete has the sufficient strength of 4MPa-13MPa and adequate void ratio of $12\%-35\%$ to be accepted as artificial reef concrete. The field experiments are performed through observation by scuba diver's at the Seogwipo coast. Porous specimen and plane concrete specimen are prepared for comparison purposes. Seasonal changes of soft coral on the two series of test specimens were have been observed from Apr. 9, 2004 to Mar. 18, 2005. The soft coral is well grown on the porous specimen however there are no significant changes on the conventional plain concrete specimen. Thus it is concluded that the volcanic scoria concrete is highly suitable as artificial reef concrete.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.2
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• pp.135-145
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• 2023

Aggregate is used to produce stable materials like concrete and asphalt and is fundamental to meet the social needs of housing, industry, road, energy and health. A total of 42.35 billion tons of aggregate were produced in 2021 worldwide, an increase of 0.91% compared to the previous year. Among them, 2 billion tons were produced in China, India, European Union and United States, making up to 71.75% of the share. South Korea has witnessed a constant increase in aggregate production, overtaking Mexico and Japan for seventh place with 390 million tons and 0.85% of the share. The industrial sand and gravel produced globally amounted to 352.66 million tons. The top seven countries with the highest production were China, United States, Netherlands, Italy, India, Turkey and France, and their production exceeded 10 million tons and held a share of 74.69%. Exports of natural rock recorded $21.68 billion in 2021, increased by $2.3 billion compared to the previous year, while exports of artificial rock increased by $2.66 billion to $13.59 billion. Exports of sand reached $1.71 billion with United States, Netherlands, Germany and Belgium being the four countries with the highest exports of sand. The four countries exported more than $100 million in sand and took up 57.70% of the total amount. Exports of gravel totaled $2.75 billion, with China, Norway, Germany, Belgium, France and Austria in the lead, making up to 48.30% of the total share. The aggregate quarry started to surge in the 1950s due to the change in people's lifestyle such as population growth, urbanization and infrastructure delvelopment. Demand for aggregate is also skyrocketing to prevent land reclamation and flood caused by sea-level rise. Demand for aggregate, which was around 24 gigatons in 2011, is expected to double to 55 gigatons in 2060. However, it is likely that aggregate extraction will heavily damage the ecosystem and the world will eventually face a shortage of aggregate followed by tense social conflict.

• Computers and Concrete
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• v.12 no.2
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• pp.151-167
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• 2013

Prediction of concrete properties is an important issue for structural engineers and different methods are developed for this purpose. Most of these methods are based on experimental data and use measured data for parameter estimation. Three typical methods of output estimation are Categorized Linear Regression (CLR), Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN). In this paper a statistical cleansing method based on CLR is introduced. Afterwards, MLR and ANN approaches are also employed to predict the compressive strength of structural lightweight aggregate concrete. The valid input domain is briefly discussed. Finally the results of three prediction methods are compared to determine the most efficient method. The results indicate that despite higher accuracy of ANN, there are some limitations for the method. These limitations include high sensitivity of method to its valid input domain and selection criteria for determining the most efficient network.

• 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.

• Journal of the Korea Institute of Building Construction
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• v.3 no.3
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• pp.107-112
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• 2003

This study is to investigate the properties of concrete with crushed sand on site and to propose a quality guideline for its use as artificial sand and concrete. From our experimental result in laboratory and site, we found that demand water of concrete with crushed sand for target slump increased by 18kg/m3 compared to mixed sand and l8kg/m3 compared to sea sand respectively. The compressive strength increased by around 3∼6% when compared to concrete with sea sand. Accordingly, our study showed that the combined sand mixed with sea sand would be desirable to obtain workability and strength of concrete including dry shrinkage and bleeding test. Furthermore, the optimal replacement percentage of crushed sand was 50% with sea sand. As such, crushed sand would be sufficient as fine aggregate for concrete in terms of economic efficiency and quality. Crushed sand, on the other hand can only be used as fine aggregate when VFS(Very Fine Sand) is below 3.5 percentage of weight of sand and particle shape is above 55 percentage. Also, the particle shape and microsand passing NO.200 sieve should continually be improved to increase workability of concrete on site.

• Computers and Concrete
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• v.24 no.2
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• pp.137-150
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• 2019

In this paper, surrogate models such as multivariate adaptive regression splines (MARS) and M5P model tree (M5P MT) methods have been investigated in order to propose a new formulation for the 28-days compressive strength of self-compacting concrete (SCC) incorporating metakaolin as a supplementary cementitious materials. A database comprising experimental data has been assembled from several published papers in the literature and the data have been used for training and testing. In particular, the data are arranged in a format of seven input parameters covering contents of cement, coarse aggregate to fine aggregate ratio, water, metakaolin, super plasticizer, largest maximum size and binder as well as one output parameter, which is the 28-days compressive strength. The efficiency of the proposed techniques has been demonstrated by means of certain statistical criteria. The findings have been compared to experimental results and their comparisons shows that the MARS and M5P MT approaches predict the compressive strength of SCC incorporating metakaolin with great precision. The performed sensitivity analysis to assign effective parameters on 28-days compressive strength indicates that cementitious binder content is the most effective variable in the mixture.