• 레미콘
• /
• no.7 s.72
• /
• pp.29-41
• /
• 2002

The purpose of this study is to investigarte the mix design method and the mechanical properties of High stength Lightweight Concrete (HSLC). In the experment, concrete mixing was conducted to select the optimum mix design for HSLC in laboratory. Also, concrete mixing in ready mix design. As a result, it is possible to establish the mix design of HSLC according to the using these experimental results ;the estimate equation for unit weight of HSLC. the relationship between W/C and compressive strength of HSLC and the fluidity of HSLC in the view of workability

• Resources Recycling
• /
• v.22 no.3
• /
• pp.18-27
• /
• 2013

In this study, it was developed eco-friendly mix design of mine sprayed concrete, which satisfies both the stability and economics by mixing the industrial in cement, for development of the mine sprayed concrete and recycling of industrial. From this research, it is found that mixing of mineral admixture is effective on strength enhancement. Also, it is considered that designed mixing ratio of sprayed concrete using industrial byproducts should be applied to the field through field test.

• Journal of the Korea Institute of Building Construction
• /
• v.22 no.6
• /
• pp.619-630
• /
• 2022

The concrete mix design and compressive strength evaluation are used as basic data for the durability of sustainable structures. However, the recent diversification of mixing factors has created difficulties in calculating the correct mixing factor or setting the reference value concrete mixing design. The purpose of this study is to design a predictive model of bidirectional analysis that calculates the mixing elements of ternary concrete using deep learning, one of the artificial intelligence techniques. For the DNN-based predictive model for calculating the concrete mixing factor, performance evaluation and comparison were performed using a total of 8 models with the number of layers and the number of hidden neurons as variables. The combination calculation result was output. As a result of the model's performance evaluation, an average error rate of about 1.423% for the concrete compressive strength factor was achieved. and an average MAPE error of 8.22% for the prediction of the ternary concrete mixing factor was satisfied. Through comparing the performance evaluation for each structure of the DNN model, the DNN5L-2048 model showed the highest performance for all compounding factors. Using the learned DNN model, the prediction of the ternary concrete formulation table with the required compressive strength of 30 and 50 MPa was carried out. The verification process through the expansion of the data set for learning and a comparison between the actual concrete mix table and the DNN model output concrete mix table is necessary.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2021.11a
• /
• pp.156-157
• /
• 2021

Since concrete is contaminated or radioactive during operation of nuclear power plants, it is the most important radioactive waste generated during the dismantling of a nuclear power plant. The amount of waste is different depending on the pollution state of each facility and the applied technology is different, so there is a big difference. We aim to reduce the amount of waste and increase the value of recyclability through technology to remove radionuclides attached to the surface. For this purpose, laser scabbling, which exfoliates the surface of concrete by irradiating a laser, and a facility system for controlling dust and dust are used in parallel. The purpose of this study is to evaluate the efficiency of laser scabbling by manufacturing simulated concrete for nuclear facilities, and to review the optimal mixing design conditions for nuclear facility structures.

• International Journal of Concrete Structures and Materials
• /
• v.2 no.2
• /
• pp.161-167
• /
• 2008

Optimization of concrete mixing system is very important for the production of quality mixture of concrete and requires very complicated, specialized knowledge as there are a variety of variables that influence the result. One of the methods of optimizing the concrete mixing system is to minimize the volume of cement paste which, in turn, means maximizing the volume of aggregate. The purpose of this study is to determine the minimum volume of cement paste used in the design of concrete mixture and to design the optimum concrete mixing system based on the fluidity of mortar and concrete. In determining the minimum volume of cement paste, experiments of mortar and concrete were performed based on their workability, material segregation and bleeding. Type of aggregate, granularity distribution and sand percentage were used as test parameters and measurements were taken of the distribution of granularity, usage of HRWRA, minimum volume of paste and drying shrinkage and compressive strength of concrete.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2022.11a
• /
• pp.57-58
• /
• 2022

Concrete mix design is used as essential data for the quality of concrete, analysis of structures, and stable use of sustainable structures. However, since most of the formulation design is established based on the experience of experts, there is a lack of data to base it on. are suffering Accordingly, in this study, the purpose of this study is to build a predictive model to use the concrete mixing factor as basic data for calculation using the DNN technique. As for the data set for DNN model learning, OPC and ternary concrete data were collected according to the presence or absence of admixture, respectively, and the model was separated for OPC and ternary concrete, and training was carried out. In addition, by varying the number of hidden layers of the DNN model, the prediction performance was evaluated according to the model structure. The higher the number of hidden layers in the model, the higher the predictive performance for the prediction of the mixing elements except for the compressive strength factor set as the output value, and the ternary concrete model showed higher performance than the OPC. This is expected because the data set used when training the model also affected the training.

• Journal of the Korea Concrete Institute
• /
• v.21 no.6
• /
• pp.745-752
• /
• 2009

This paper presents the optimized mixing design of lightweight aerated concrete using hydrogen peroxide. Design of experiments in order to the optimized mixing design was applied and commercial program (MINITAB) was used. Statistical analysis was used to Box-Behnken (B-B) method in response surface analysis. The influencing factors of experimental are unit cement content, water ratio and hydrogen peroxide ratio. According to the analysis of variance, at the hardened state, water ratio and hydrogen peroxide ratio affects on dried density, compressive strength and bending strength of lightweight aerated concrete, but unit cement content affects on only dried density. In the results of response surface analysis, to obtain goal performance, the optimized mixing design for lightweight aerated concrete using hydrogen peroxide were unit cement content of 800 kg/$m^3$, water ratio of 44.33% and hydrogen peroxide ratio of 10%.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2017.11a
• /
• pp.11-12
• /
• 2017

The properties of concrete produced by ready mixed concrete company in Busan were tested. Because the concrete was mixed with blast furnace slag and fly ash, the compressive strength and chloride ion diffusion coefficient were lower than OPC concrete even though the specified concrete strength was same. If the durability about salt attack were satisfied, the concrete of lower specified concrete strength would be adopted to concrete mixing design.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2005.05b
• /
• pp.73-76
• /
• 2005

This study aims to suggest a simple and convenient design for a mix proportion method for high performance concrete by determining the optimum fine aggregate ratio and minimum binder content based on the maximum density theory. The mix design method introduced in this study adopted the optimum fine aggregate ratio with a minimum void and binder content higher than the minimum binder content level. The research results reveal that the method helps to reduce trial and error in the mixing process and is a convenient way of producing high performance concrete with self filler ability. In an experiment based on the mix proportion method, when aggregate with the fine aggregation ratio of 41$\%$ was used, the minimum binder content of high performance concrete was 470kg/$m^{3}$ and maximum aggregate capacity was $0.657m^{3}/m^{3}$. In addition, in mixing high performance concrete, the optimal slump flow to meet filler ability was 65$\pm$5cm, V load flow speed ranged from 0.5 to 1.5.

• Proceedings of the Korea Concrete Institute Conference
• /
• 1998.10a
• /
• pp.262-268
• /
• 1998

This research is to examine the selected method of optimal mixing proportion and cost analysis in the super flowing concrete. As confined water $ratio($\beta_p$)$ and K is introduced, itis to establish optimal mixing design of super flowing concrete according to the steps of paste, mortar and concrete. From paste and mortar test, it was led to $$\beta_p$$ and $K_p$satisfying the optimum condions depending on the kinds of binders. Then $$\beta_p$$ and $K_p$ is reflected to the mix condition of super flowing concrete. The result of test, the mix condition of super flowing concrete satisfied the quality performance of concrete with adjustment of additional rate of the superplasticizer. Besides, in case of design strength $350kg/\textrm{cm}^2$ of concrete, material cost in super flowing concrete is able to be reduced 5~16% in replacement of fly ash 30% in ordinary portland cement and slag cement.