• 레미콘
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• no.7 s.72
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• pp.29-41
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• 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

• Journal of the Korea Academia-Industrial cooperation Society
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• v.1 no.1
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• pp.63-72
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• 2000

The Purpose of concrete mix design is to determine the most economical and practical combination of materials in order to produce a concrete that will satisfy the performance requirements at any particular conditions of use. Mix design is regarded as a very complicated work, because for fulfilling this purpose deep understanding about the mix design is required. Mix design procedure of concrete is discussed in this study and a computer program for mix design using visual basic as 1anguage was developed. Even though beginners about concrete engineering. they can determine concrete mix proportions easily with the program.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.04b
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• pp.719-724
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• 1998

It is proposed in this paper to develop the rational mix design system of High-strength concrete which is adjusted in the domestic circumstances. 1) Collect a lots of data in order to introduce the optimum mix design which has relation among material variables which compose High-strength concrete and run by using SAS (Statistical analysis system) which is one of multivariate statistical analysis method. 2) Select the important material variables for mix design of High-strength concrete by major component analysis and propose the standard range of each material variable along the target strengths. From the results of this study, it was proposed the range of proper material variables in domestic circumstance, which are W/C, S/A, air and admixture amounts, etc, at the target strengths for concrete kind. Also it was developed the optimum mix design program of High-strength concrete according to target strength and size of aggregate and made mix design ease in domestic construction site.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.108-113
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• 1996

Concrete mix degign and adjustments are somewhat complicated and time-consuming tasks in which various uncertainties and errors are involved and depend on the quality control test results. In this paper, as a tool to minimize the uncertainties and errors the neural network is applied to the concrete mix design. Input data to train and test the neural network are obtained from the results of design and adjustments following the concrete standard specifications of Korea. The results show that neural networks have a strong potential as a tool for concrete mix design.

• Steel and Composite Structures
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• v.29 no.1
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• pp.67-75
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• 2018

High performance concrete (HPC) depends on various parameters such as the type of cement, aggregate and water reducer amount. Generally, the ready concrete company in various regions according to the requirements and costs, mix design of concrete as well as type of cement, aggregates, and, amount of other components will vary as a result of moment decisions or dynamic optimization, though the ideal conditions will be more applicable for the design of mix proportion of concrete. This study aimed to apply dynamic optimization for mix design of HPC; consequently, the objective function, decision variables, input and output variables and constraints are defined and also the proposed dynamic optimization model is validated by experimental results. Results indicate that dynamic optimization objective function can be defined in such a way that the compressive strength or performance of all constraints is simultaneously examined, so changing any of the variables at each step of the process input and output data changes the dynamic of the process which makes concrete mix design formidable.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.223-224
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• 2021

Recently, the demand for high fluidity concrete has been increased due to skyscrapers. However, it has its own limits. First of all, high fluidity concrete has large variation and through trial & error it costs lots of money and time. Neural network model has repetitive learning process which can solve the problem while training the data. Therefore, the purpose of this study is to predict optimum mix design of 40MPa, 60MPa high fluidity concrete by using neural network model and verifying compressive strength by applying real data. As a result, comparing collective data and predicted compressive strength data using MATLAB, 40MPa mix design error rate was 1.2%~1.6% and 60MPa mix design error rate was 2%~3%. Overall 40MPa mix design error rate was less than 60MPa mix design error rate.

• Magazine of the Korea Concrete Institute
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• v.9 no.2
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• pp.145-151
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• 1997

In concrete mix design we need the informations of the codes, the specifications, and the experiences of experts. However we can't consider all factors regarding concrete mix design. The final acceptance depends on concrete quality control test results. In this process we meet the uncertainties of materials. temperature, site environmental situations, personal skillfulness. and errors in calculations and testing process. Then the mix design adjustments must be made. Concrete mix design and adjustments arc somewhat complicated, time-consuming. and uncertain tasks. In this paper, as a tool to minimize the uncertainties and errors the neural network is applied to the concrete mix design. Input data to train and test the neural network are obtained numerically from the results of design following the concrete standard specifications of Korea. The 28-days compressive strengths which are variate according to the uncertainties and errors are considered. The results show that neural networks have a strong potential as a tool for concrete mix design.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.133-142
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• 2006

The purpose of this study is to predict the fracture energy in accordance with the combination variables by applying the mix design nomogram in ready mixed concrete products. In terms of the experiment for drawing up Mix Design Nomogram, the beam is manufactured based on the mixture table described in the specifications of ready mixed concrete manufacturing company and a three-point bending test suggested in RILEM 50-FMC Committee is performed. As a result, this study makes sure the possibility to apply the mix design nomogram that is possible to predict the fracture energy in ready mixed concrete products and enables one to achieve the automation of the design of mixture for the production of ready mixed concrete products with the development of program using it.

• Journal of the Korean Society for Advanced Composite Structures
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• v.6 no.2
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• pp.1-7
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• 2015

As energy consumption of building and the reduction of carbon dioxide emissions have been emphasized, phase change materials(PCM) have been introduced as building materials due to its high heat storage performance. Using shape-stabilizing technique, octadecane/xGnP shape-stabilized PCM(SSPCM) can prevent leakage and improve heat storage performance. The objectives of this study are to propose mix design method of concrete mixed with SSPCM and to evaluate mechanical behaviors of the concrete mixed with SSPCM manufactured according to the proposed mix design. Based on the previously reported material test result, the existing mix design of plain concrete(Concrete standard specification, 2009) is modified to consider reduction of strength in concrete due to the addition of SSPCM. To verify the proposed mix design, specimens are fabricated according to the proposed mix design and axial strength tests and three-point loading tests are performed. Test results show that compressive strengths of the tested specimens reach the designed strength even when two different mix ratios of SSPCM are used. From three-point loading tests, flexural stresses decrease as mix ratio of SSPCM increases.

• Proceedings of the Korea Concrete Institute Conference
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• 2010.05a
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• pp.329-330
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• 2010

For the computerization of structural lightweight concrete mix design, mix design theories of ACI211.2-98(Standard Practice for Selecting Proportions for Structural Lightweight Concrete) are investigated and the mix design process is mathematized by Table Curve 2D and 3D software of Jandel company.