• Restorative Dentistry and Endodontics
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• v.37 no.3
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• pp.155-159
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• 2012

Objectives: To investigate the effect of dentin moisture degree and air-drying time on dentin-bond strength of two different one-step self-etching adhesive systems. Materials and Methods: Twenty-four human third molars were used for microtensile bond strength testing of G-Bond and Clearfil $S^3$ Bond. The dentin surface was either blot-dried or air-dried before applying these adhesive agents. After application of the adhesive agent, three different air drying times were evaluated: 1, 5, and 10 sec. Composite resin was build up to 4 mm thickness and light cured for 40 sec with 2 separate layers. Then the tooth was sectioned and trimmed to measure the microtensile bond strength using a universal testing machine. The measured bond strengths were analyzed with three-way ANOVA and regression analysis was done (p = 0.05). Results: All three factors, materials, dentin wetness and air drying time, showed significant effect on the microtensile bond strength. Clearfil $S^3$ Bond, dry dentin surface and 10 sec air drying time showed higher bond strength. Conclusions: Within the limitation of this experiment, air drying time after the application of the one-step self-etching adhesive agent was the most significant factor affecting the bond strength, followed by the material difference and dentin moisture before applying the adhesive agent.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05b
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• pp.85-88
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• 2006

This study describes the optimum mix proportion of the high strength and self-compacting concrete placed in main structures of LNG above tank. This concrete requires high strength level about $60{\sim}80MPa$, low hydration heat, balance between workability and consistency without vibrating in the actual work. For this purpose, low heat portland cement and fly ash are selected and design factors including water-binder ratio, replacement ratio of fly ash are tested. As experimental results, low heat portland cement shows lower the confined water ratio than another cement type and the optimum replacement ratio of fly ash in order to improve properties of the binder-paste shows 10% by cement weight considering test results of the confined water ratio$({\beta}p)$. Also, flowability of the high strength and self-compacting concrete by using fly ash about $10{\sim}20%$ is improved. The replacement ratio of fly ash 10% and water-binder ratio $25{\sim}27%$ are suitable to the design strength 80MPa and cost, In case of the design strength 60MPa, the replacement ratio of fly ash and water-binder ratio show 20% and $25{\sim}30%$ separately. Based on the results of this study, the optimum mix proportions of the high strength and self-compacting concrete will be applied to the construction of LNG above tank as a new type.

• Computers and Concrete
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• v.19 no.5
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• pp.555-566
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• 2017

Recently some efforts have been performed to combine the advantages of light-weight and self-compacting concrete in one package called Light-Weight Self-Compacting Concrete (LWSCC). Accurate prediction of hardened properties from fresh state characteristics is vital in design of concrete structures. Considering the lack of references in mixture design of LWSCC, investigating the proper mixture components and their effects on mechanical properties of LWSCC can lead to a reliable basis for its application in construction industry. This study utilizes wide range of existing data of LWSCC mixtures to study the individual and combined effects of the components on the compressive strength. From sensitivity of compressive strength to the proportions and interaction of the components, two equations are proposed to estimate the LWSCC compressive strength. Predicted values of the equations are in good agreement with the experimental data. Application of lightweight aggregate to reduce the density of LWSCC may bring some mixing problems like segregation. Reaching a higher strength by lowered density is a challenging problem that is investigated as well. The results show that, the compressive strength can be improved by increasing the of mixture density of LWSCC, especially in the range of density under $2000Kg/m^3$.

• Computers and Concrete
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• v.20 no.1
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• pp.31-38
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• 2017

In the present study an Artificial Neural Network (ANN) was used to predict the compressive strength of self-compacting concrete. The data developed experimentally for self-compacting concrete and the data sets of a total of 99 concrete samples were used in this work. ANN's are considered as nonlinear statistical data modeling tools where complex relationships between inputs and outputs are modeled or patterns are found. In the present ANN model, eight input parameters are used to predict the compressive strength of self-compacting of concrete. These include varying amounts of cement, coarse aggregate, fine aggregate, fly ash, fiber, water, super plasticizer (SP), viscosity modifying admixture (VMA) while the single output parameter is the compressive strength of concrete. The importance of different input parameters for predicting the strengths at various ages using neural network was discussed in the study. There is a perfect correlation between the experimental and prediction of the compressive strength of SCC based on ANN with very low root mean square errors. Also, the efficiency of ANN model is better compared to the multivariable regression analysis (MRA). Hence it can be concluded that the ANN model has more potential compared to MRA model in developing an optimum mix proportion for predicting the compressive strength of concrete without much loss of material and time.

• Journal of Families and Better Life
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• v.27 no.5
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• pp.123-135
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• 2009

The purpose of this study was to investigate the effects of family conflict and self-control on school maladjustments of early adolescents. Subjects of this study consisted 662 middle school students drawn from 4 middle schools in Cheong-ju city. The results of this study were as follows: First, younger students' maladjustment to teachers was influenced by variables such as school year, economic levels, conflict strength between parents, conflict settlement between parents, reliability between parents and children, communication between parents and children and self-control, etc. In other words, students' maladjustment to teachers was high at the students in the 2nd year rather than in the 1st year, low economic level, high conflict strength between parents that younger students perceived, low conflict settlement between parents, low reliability between parents and children, high hostility between parents and children and low self-control. Second, younger students' maladjustment to the class was influenced by variables such as gender, school year, economic levels, conflict strength between parents, reliability between parents and children, communication between parents and children, and self-control, etc. In other words, young students' maladjustment to the class was high at the 2nd year students rather than at the 1st year students, low economic level, high conflict strength between parents, low reliability between parents and children, poor communication between parents and children, and low self-control. Third, younger students' maladjustment to rules was influenced by variables such as school year, economic level, conflict level between parents, hostility between parents and children, and self-control, etc. In other words, younger students' maladjustment to rules was high at the 1st year students rather than the 2nd year students of middle school, low economic level, high conflict strength between parents, high hospitality between parents and children and low self-control, etc. Fourth, younger students' maladjustment to friends was influenced by variables such as conflict strength between parents, conflict settlement between parents, hospitality between parents and children, and self-control, etc. In other words, younger students' maladjustment to friends was high at high conflict strength between parents, low conflict settlement between parents, high hospitality between parents and children and low self-control, etc. In the study, self-control was found to be the most important variable at younger students' maladjustment to teachers, class and rules, etc, and conflict settlement between parents was found to be the most significant variable at younger students' maladjustment to friends.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.344-351
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• 2015

The purpose of this study was to evaluate the effect of the surface treatment of widely used in dental of silane coupling agent concentration on the shear bond strength of denture base resin and self curing resins. Denture base resin surface was treated with silane coupling agent concentration, after self curing resins were injected shear bond strength was measured. The results of silane coupling agent(MPS) concentration on the shear bond strength of Vertex self curing resin showed that the value of 5%, 7% groups were higher than that of other group(P<0.05). Silane coupling agent concentration on the shear bond strength of Kooliner resin showed that the value of 5% was highest(P<0.05). Therefore, we could conclude 5% MPS to strengthen effectively the shear bonding property of denture base resin and self curing resins of this study.

• Journal of the Korea Institute of Building Construction
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• v.2 no.4
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• pp.89-98
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• 2002

Self-leveling material(SLM) is one of the floor finishing materials which make flat surface like as water level by itself in a short time. So it is possible to increase construction speed and enhance economical efficiency In this study, author intended to develop SLM for the industrial warehouse and factory loading heavy weight machinery and vehicles. The demanded properties for this type of SLM are above 200mm of flow value and above 300kgf/$cm^2$ of 28-days compressive strength. To possess demended strength and fluidity, SLM have to be composed of many types of binders and chemical additives. So it is difficult to decide suitable mixing proportion of composition materials. In this study, author investigated the weight percentage effect of main composition materials for high-strength self-leveling material, by experimental design such as tables of orthogonal arrays and simplex design, and by statistical analysis such as analysis of variance and analysis of response surface. Variables of experiments were ordinary Portland cement(OPC), alumina cement(AC), anhydrous gypsum(AG), lime stone(LS) and sand, and properties of tests were fluidity of fresh state and strength of hardened state. Results of this study are showed that suitable mix proportions of binders for the high strength self-leveling materials are two groups. One is 78~85.5% OPC, 7.5~9.5% AC, 9~12.5% AG and the other is 72.5~78% OPC, 9~12.5% AC, 13~15% AG.

• Advances in nano research
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• v.15 no.6
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• pp.495-511
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• 2023

In this research, the impact of micro-silica, nano-silica, and polypropylene fibers on the fracture energy of self-compacting concrete was thoroughly examined. Enhancing the fracture energy is very important to increase the crack propagation resistance. The study focused on evaluating the self-compacting properties of the concrete through various tests, including J-ring, V-funnel, slump flow, and T50 tests. Additionally, the mechanical properties of the concrete, such as compressive and tensile strengths, modulus of elasticity, and fracture parameters were investigated on hardened specimens after 28 days. The results demonstrated that the incorporation of micro-silica and nano-silica not only decreased the rheological aspects of self-compacting concrete but also significantly enhanced its mechanical properties, particularly the compressive strength. On the other hand, the inclusion of polypropylene fibers had a positive impact on fracture parameters, tensile strength, and flexural strength of the specimens. Utilizing the response surface method, the relationship between micro-silica, nano-silica, and fibers was established. The optimal combination for achieving the highest compressive strength was found to be 5% micro-silica, 0.75% nano-silica, and 0.1% fibers. Furthermore, for obtaining the best mixture with superior tensile strength, flexural strength, modulus of elasticity, and fracture energy, the ideal proportion was determined as 5% micro-silica, 0.75% nano-silica, and 0.15% fibers. Compared to the control mixture, the aforementioned parameters showed significant improvements of 26.3%, 30.3%, 34.3%, and 34.3%, respectively. In order to accurately model the tensile cracking of concrete, the authors used softening curves derived from an inverse algorithm proposed by them. This method allowed for a precise and detailed analysis of the concrete under tensile stress. This study explores the effects of micro-silica, nano-silica, and polypropylene fibers on self-compacting concrete and shows their influences on the fracture energy and various mechanical properties of the concrete. The results offer valuable insights for optimizing the concrete mix to achieve desired strength and performance characteristics.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05b
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• pp.513-516
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• 2006

Waste concrete powder(WCP) is a secondary by-product generated while processing waste concrete manufactured to coarse and fine aggregates for concrete. In order to assess the possibility of using WCP as admixture for self-compacting concrete, self-compactability, compressive strength and durability of self-compacting concrete containing waste concrete powder were investigated. Experimental results of this study appeared that in case of SCC mixed with WCP only, self-compactability and compressive strength decreased with increasing mixing ratio of WCP. When Blast-furnace slag(BFS) was added to SCC, self-compactability and compressive strength for a unit amount of cement increased. Also, SCC containing 15% BFS and 15%, 30% and 45% WCP, the dry shrinkage and carbonation depth appeared a tendency to decrease with increasing mixing ratio.

• Computers and Concrete
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• v.21 no.1
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• pp.47-54
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• 2018

Artificial neural network models can be successfully used to simulate the complex behavior of many problems in civil engineering. As compared to conventional computational methods, this popular modeling technique is powerful when the relationship between system parameters is intrinsically nonlinear, or cannot be explicitly identified, as in the case of concrete behavior. In this investigation, an artificial neural network model was developed to assess the residual compressive strength of self-compacted concrete at elevated temperatures ($20-900^{\circ}C$) and various relative humidity conditions (28-99%). A total of 332 experimental datasets, collected from available literature, were used for model calibration and verification. Data used in model development incorporated concrete ingredients, filler and fiber types, and environmental conditions. Based on the feed-forward back propagation algorithm, systematic analyses were performed to improve the accuracy of prediction and determine the most appropriate network topology. Training, testing, and validation results indicated that residual compressive strength of self-compacted concrete, exposed to high temperatures and relative humidity levels, could be estimated precisely with the suggested model. As illustrated by statistical indices, the reliability between experimental and predicted results was excellent. With new ingredients and different environmental conditions, the proposed model is an efficient approach to estimate the residual compressive strength of self-compacted concrete as a substitute for sophisticated laboratory procedures.