• Journal of the Korea Concrete Institute
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• v.16 no.5 s.83
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• pp.591-596
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• 2004

In order to evaluate the applicability of steel slag aggregates for tetrapod concrete, the properties of concrete as structural material were investigated. The biochemical research of marine concrete using steel slag aggregates was also carried out. The tested concrete properties are slump, ai content, compressive strength, splitting tensile strength, elastic modulus, carbonation, hydration heat, freezing and thawing, sulfate attack, drying shrinkage, etc. The biochemical experiments are carried to research the propagation and reproduction of seaweeds and survival of bottom dwelling species. According to this experiment results, the steel slag aggregate content did not have a significant effect on compressive strength, splitting tensile strength and elastic modulus. The durability of concrete was not influenced by the steel slag aggregate content. From the biochemical research, steel slag aggregate can be evaluated as the material that is ideally suited for promoting propagation and reproduction of seaweeds and sessile benthos.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.3
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• pp.109-113
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• 1999

The objective of this research was to develop growth media for artificial ground by blending calcined clay and coconut peat. To achieve this, aggregates of clay particles were mixed with disel oil and heated to high temperature(1150~120$0^{\circ}C$) to expand clays. The particle sizes of expanded clay were controlled to 2~5mm in diameter. Then expanded clayes were mixed with coconut peat and changes of soil physicochemical properties and their effect on plant growth of Hedera L. were determined. The infiltration rate of calcined clay was very high, but the water holding capacity, the cation exchange capacity(CEC), and the nutrient contents were low. The characteritics of coconut peat was vice verse to calcined clay. This indicates that the mixture of calcined clay and coconut peat have the better characteristics than each material. As compared to mineral soil, the infiltration rate, the water holding capacity, the CEC and the nutrient contents increased, but bulk density decreased to about 1/4. And, Hedera L. grown in the mixture of calcined clay and coconut peat(6:4, v/v) had higher plant height, longer leaf length, more total number of leaves per plant and fresh weight than that grown in mineral soil, but statistical differences were not observed between two treatments.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.4
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• pp.419-426
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• 2001

Concrete mix proportioning is a process of selecting the right combination of many materials such as cement, fine aggregates, coarse aggregates, water, and admixtures to make concrete satisfying for specification and cost. In determining proportioning of concrete mixes, code information, specification, and the experience of experts are needed. However, all factors regarding mix proportioning factor cannot be considered. Therefore, the final acceptance depends on concrete quality control test results. The proportioning of concrete mixes and the adjustments are somewhat complicated, time-consuming, and uncertain tasks. In this paper, as a tool to predict the factor of the proportioning of concrete mixes, an artificial neural network is used. To consider the varieties of material properties, the standard mixed table of two companies of ready mixed concrete are used. The results show that neural net works is successfully applied to the prediction of concrete mix proportioning factor.

• Steel and Composite Structures
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• v.49 no.6
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• pp.645-666
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• 2023

Due to the steadily declining supply of natural coarse aggregates, the concrete industry has shifted to substituting coarse aggregates generated from byproducts and industrial waste. Oil palm shell is a substantial waste product created during the production of palm oil (OPS). When considering the usage of OPSC, building engineers must consider its uniaxial compressive strength (UCS). Obtaining UCS is expensive and time-consuming, machine learning may help. This research established five innovative hybrid AI algorithms to predict UCS. Aquila optimizer (AO) is used with methods to discover optimum model parameters. Considered models are artificial neural network (AO - ANN), adaptive neuro-fuzzy inference system (AO - ANFIS), support vector regression (AO - SVR), random forest (AO - RF), and extreme gradient boosting (AO - XGB). To achieve this goal, a dataset of OPS-produced concrete specimens was compiled. The outputs depict that all five developed models have justifiable accuracy in UCS estimation process, showing the remarkable correlation between measured and estimated UCS and models' usefulness. All in all, findings depict that the proposed AO - XGB model performed more suitable than others in predicting UCS of OPSC (with R², RMSE, MAE, VAF and A_15-index at 0.9678, 1.4595, 1.1527, 97.6469, and 0.9077). The proposed model could be utilized in construction engineering to ensure enough mechanical workability of lightweight concrete and permit its safe usage for construction aims.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.21 no.3
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• pp.129-135
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• 2011

EAF dust from steel industry used as primary materials for the production of lightweight aggregates. Fe compounds in EAF dust plays an important role in the bloating reaction. This study was conducted to evaluate the feasibility of using bottom ash and dredged soil from coal power plant and EAF dust. The effect of different raw material compositions and sintering temperatures on the lightweight aggregate properties were evaluated. The characteristic of thermal bloating of bottom ash and dredged soil were mainly influenced by ferrous materials. The specific gravity of aggregate was decreased with the addition of EAF dust and kerosene was reduced sintering temperature on the bloating formation. Lightweight aggregate containing 10% EAF dust having apparent density under 1.0 g/$cm^3$ were produced at $1150{\sim}1200^{\circ}C$.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.135-140
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• 2021

In this study, the concrete aggregate shape features were extracted from the cross-section of a normal concrete strength cylinder, and the compressive strength of the cylinder was predicted using artificial neural networks and image processing technology. The distance-angle features of aggregates, along with general aggregate shape features such as area, perimeter, major/minor axis lengths, etc., were numerically expressed and utilized for the compressive strength prediction. The results showed that compressive strength can be predicted using only the aggregate shape features of the cross-section without using major variables. The artificial neural network algorithm was able to predict concrete compressive strength within a range of 4.43% relative error between the predicted strength and test results. This experimental study indicates that various material properties such as rheology, and tensile strength of concrete can be predicted by utilizing aggregate shape features.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.18 no.5
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• pp.211-216
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• 2008

The artificial lightweight aggregate (ALA) was manufactured in a rotary kiln at $1125^{\circ}C$ using green body formed by pelletizing the batch powder composing of coal bottom ash (CBA) produced from power plant, clay and dredged soil (DS). The TCLP (Toxicity characteristic leaching procedure) results showed that the dissolution concentration of heavy metal ions of ALA fabricated in this study was below the limitation defined by the enforcement regulations of wastes management law in Korea. The ALA containing 60$\sim$70 wt% CBA had a bulk density of 1.45$\sim$1.49 and a water absorption of 17.2$\sim$18.5 %. The impact values for oven-dry state and saturated-surface dry state of ALA were 27.4$\pm$1.3 and 23.4$\pm$2.6 % respectively. The 28-days compressive strength of concrete made with various ALA was $22.7\sim27.8 N/mm^2$. The slump of concrete with ALA containing CBA 60 and 70 wt% were 7.9 and 14.3 cm respectively. The unit weight of concrete made with any ALA fabricated in this study was satisfied with the standard specifications of lightweight concrete for the civil engineering and construction presented by Korea as below $1.84 ton/m^3$.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.4
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• pp.498-505
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• 2020

Aggregate occupies about 70-85% of the concrete volume and is an important factor in reducing the drying shrinkage of concrete. However, when constructing high-rise buildings, it acts as a problem due to the high load of natural aggregates. If the load becomes large during the construction of a high-rise building, creep may occur and the ground may be eroded. Material costs increase and there are financial problems. In order to reduce the load on concrete, we are working to reduce the weight of aggregates. However, artificial lightweight aggregates affect the interface between the aggregate and the paste due to its higher absorption rate and lower adhesion strength than natural aggregates, affecting the overall strength of concrete. Therefore, in this study, in order to grasp the interface between natural aggregate and lightweight aggregate by type, we adopted a method of measuring electrical resistance using an EIS measuring device, which is a non-destructive test, and lightweight bone. The change in the state of the interface was tested on the outside of the material through a blast furnace slag coating. As a result of the experiment, it was confirmed that the electric resistance was about 90% lower than that in the air-dried state through the electrolyte immersion, and the electric resistance differs depending on the type of aggregate and the presence or absence of coating. As a result of the experiment, the difference in compressive strength depending on the type of aggregate and the presence or absence of coating was shown, and the difference in impedance value and phase angle for each type of lightweight aggregate was shown.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1994.04a
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• pp.129-130
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• 1994

The science of toxicology is the understanding of the mechanisms by which exogenous agents produce deleterious effects in biological systems. The actions of chemicals such as drugs are ultimately exerted at the cellular and gene levels. Over the past decade. several in vitro alternative methods such as cultured cells for assessing the toxicity of various xenobiotics have been proposed to reduce the use of animals. In this workshop three advanced methods will be presented. These methods are novel important models for toxicologic studies. Dr. Tabuchis group has establishcd two immortalized gastric surface mucosa cell lines from the pminary cultore of gastric fundic mucosal cells of adult transgenic mice harboring a temperature sensitive simian virus 40 large T-anugen gene. As the immortalized cell lines of various tissues possess unique characteristics to maintain their normal functions for several months, these cell lines are extremely useful for not only toxicity testing but also pharmacological screening in new drug development. Professor Funatsu have studied the formation of spherical multicelluar aggregates of adult rat hepatocytes(spheroid) having tissue like structure. The sphcroid shown thre is a prototype module of an artificial liver support system. Thus, the urea synthesis activity of the artificial liver was maintained at least to days in 100％ rat blood plasma. Dr. Takezawa and his coworkers have developed a novel culture system of multicellular spheroids considered 〃organoids〃 by utilizing a thermo-responsive polymer as a substratum of anchorage dependent cells. His final goal is to reconstitute the organoids of various normal organs, e.g., liver, skin etc. and also abnormal deseased organs such as tumor.

• Computers and Concrete
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• v.17 no.5
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• pp.613-628
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• 2016

In this study, the influence of coarse aggregate size and type on chloride penetration of concrete was investigated, and the grey correlation analysis was applied to find the key influencing factor. Furthermore, the proposed 6-10-1 artificial neural network (ANN) model was constructed, and performed under the MATLAB program. Training, testing and validation of the model stages were performed using 81 experiment data sets. The results show that the aggregate type has less effect on the concrete permeability, compared with the size effect. For concrete with a lower w/b, the coarse aggregate with a larger particle size should be chose, however, for concrete with a higher w/c, the aggregate with a grading of 5-20 mm is preferred, too large or too small aggregates are adverse to concrete chloride diffusivity. A new idea for the optimum selection of aggregate to prepare concrete with a low penetration is provided. Moreover, the ANN model predicted values are compared with actual test results, and the average relative error of prediction is found to be 5.62%. ANN procedure provides guidelines to select appropriate coarse aggregate for required chloride penetration of concrete and will reduce number of trial and error, save cost and time.